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Observations of anthropogenic global warming

Archive for October, 2009

Papers on anthropogenic carbon dioxide observations

Posted by Ari Jokimäki on October 31, 2009

This is a list of papers on carbon dioxide sources of atmospheric carbon dioxide concentration. Emphasis is on the papers that study the cause for the decadal increasing trend of carbon dioxide concentration in the atmosphere. The list is not complete, and will most likely be updated in the future in order to make it more thorough and more representative.

UPDATES October 15, 2021: Levin et al. (1995) added. September 22, 2014: Lopez et al. (2013) and Lehman et al. (2013) added. April 26, 2012: Miller et al. (2012) and two papers of Graven et al. (2012) added. December 31, 2011: Turnbull et al. (2011) added. April 1, 2011: Schmidt et al. (1996), Zondervan & Meijer (1996) and Levin (1987) added. March 14, 2011: Freyer (1979) added. August 9, 2010: van der Laan et al. (2010) added. June 1, 2010: Levin et al. (2003) added. February 26, 2010: Ghosh & Brand (2003) and Revelle & Suess (1957) added. January 28, 2010: Francey & Farquhar (1982), Keeling & Shertz (1992), Bender et al. (1995), Suess (1955), Stuiver & Quay (1981), and Levin & Hesshaimer (2000) added. January 23, 2010: Damon et al. (1978) and Tans et al. (1979) added.

Allocation of Terrestrial Carbon Sources Using 14CO2: Methods, Measurement, and Modeling – Lehman et al. (2013) “The radiocarbon content of whole air provides a theoretically ideal and now observationally proven tracer for recently added fossil-fuel-derived CO2 in the atmosphere (Cff). Over large industrialized land areas, determination of Cff also constrains the change in CO2 due to uptake and release by the terrestrial biosphere. Here, we review the development of a Δ14CO2 measurement program and its implementation within the US portion of the NOAA Global Monitoring Division’s air sampling network. The Δ14CO2 measurement repeatability is evaluated based on surveillance cylinders of whole air and equates to a Cff detection limit of ≤0.9 ppm from measurement uncertainties alone. We also attempt to quantify additional sources of uncertainty arising from non-fossil terms in the atmospheric 14CO2 budget and from uncertainties in the composition of “background” air against which Cff enhancements occur. As an example of how we apply the measurements, we present estimates of the boundary layer enhancements of Cff and Cbio using observations obtained from vertical airborne sampling profiles off of the northeastern US. We also present an updated time series of measurements from NOAA GMD’s Niwot Ridge site at 3475 m asl in Colorado in order to characterize recent Δ14CO2 variability in the well-mixed free troposphere.” Scott J Lehman, John B Miller, Chad Wolak, John Southon, Pieter P Tans, Stephen A Montzka, Colm Sweeney, Arlyn Andrews, Brian LaFranchi, Thomas P Guilderson, Jocelyn C Turnbull, Radiocarbon, Vol 55, No 2–3 (2013), DOI: 10.2458/azu_js_rc.55.16392. [Full text]

CO, NOx and 13CO2 as tracers for fossil fuel CO2: results from a pilot study in Paris during winter 2010 – Lopez et al. (2013) “Measurements of the mole fraction of the CO2 and its isotopes were performed in Paris during the MEGAPOLI winter campaign (January–February 2010). Radiocarbon (14CO2) measurements were used to identify the relative contributions of 77% CO2 from fossil fuel consumption (CO2ff from liquid and gas combustion) and 23% from biospheric CO2 (CO2 from the use of biofuels and from human and plant respiration: CO2bio). These percentages correspond to average mole fractions of 26.4 ppm and 8.2 ppm for CO2ff and CO2bio, respectively. The 13CO2 analysis indicated that gas and liquid fuel contributed 70% and 30%, respectively, of the CO2 emission from fossil fuel use. Continuous measurements of CO and NOx and the ratios CO/CO2ff and NOx/CO2ff derived from radiocarbon measurements during four days make it possible to estimate the fossil fuel CO2 contribution over the entire campaign. The ratios CO/CO2ff and NOx/CO2ff are functions of air mass origin and exhibited daily ranges of 7.9 to 14.5 ppb ppm-1 and 1.1 to 4.3 ppb ppm-1, respectively. These ratios are consistent with different emission inventories given the uncertainties of the different approaches. By using both tracers to derive the fossil fuel CO2, we observed similar diurnal cycles with two maxima during rush hour traffic.” Lopez, M., Schmidt, M., Delmotte, M., Colomb, A., Gros, V., Janssen, C., Lehman, S. J., Mondelain, D., Perrussel, O., Ramonet, M., Xueref-Remy, I., and Bousquet, P.: CO, NOx and 13CO2 as tracers for fossil fuel CO2: results from a pilot study in Paris during winter 2010, Atmos. Chem. Phys., 13, 7343-7358, doi:10.5194/acp-13-7343-2013, 2013. [Full text]

Linking emissions of fossil fuel CO2 and other anthropogenic trace gases using atmospheric 14CO2 – Miller et al. (2012) “Atmospheric CO2 gradients are usually dominated by the signal from net terrestrial biological fluxes, despite the fact that fossil fuel combustion fluxes are larger in the annual mean. Here, we use a six year long series of 14CO2 and CO2 measurements obtained from vertical profiles at two northeast U.S. aircraft sampling sites to partition lower troposphere CO2 enhancements (and depletions) into terrestrial biological and fossil fuel components (Cbio and Cff). Mean Cff is 1.5 ppm, and 2.4 ppm when we consider only planetary boundary layer samples. However, we find that the contribution of Cbio to CO2 enhancements is large throughout the year, and averages 60% in winter. Paired observations of Cff and the lower troposphere enhancements (Δgas) of 22 other anthropogenic gases (CH4, CO, halo- and hydrocarbons and others) measured in the same samples are used to determine apparent emission ratios for each gas. We then scale these ratios by the well known U.S. fossil fuel CO2 emissions to provide observationally based estimates of national emissions for each gas and compare these to “bottom up” estimates from inventories. Correlations of Δgas with Cff for almost all gases are statistically significant with median r2 for winter, summer and the entire year of 0.59, 0.45, and 0.42, respectively. Many gases exhibit statistically significant winter:summer differences in ratios that indicate seasonality of emissions or chemical destruction. The variability of ratios in a given season is not readily attributable to meteorological or geographic variables and instead most likely reflects real, short-term spatiotemporal variability of emissions.” Miller, J. B., et al. (2012), Linking emissions of fossil fuel CO2 and other anthropogenic trace gases using atmospheric 14CO2, J. Geophys. Res., 117, D08302, doi:10.1029/2011JD017048.

Observations of radiocarbon in CO2 at La Jolla, California, USA 1992–2007: Analysis of the long-term trend – Graven et al. (2012) “High precision measurements of Δ14C were performed on CO2 sampled at La Jolla, California, USA over 1992–2007. A decreasing trend in Δ14C was observed, which averaged −5.5 ‰ yr−1 yet showed significant interannual variability. Contributions to the trend in global tropospheric Δ14C by exchanges with the ocean, terrestrial biosphere and stratosphere, by natural and anthropogenic 14C production and by 14C-free fossil fuel CO2 emissions were estimated using simple models. Dilution by fossil fuel emissions made the strongest contribution to the Δ14C trend while oceanic 14C uptake showed the most significant change between 1992 and 2007, weakening by 70%. Relatively steady positive influences from the stratosphere, terrestrial biosphere and 14C production moderated the decreasing trend. The most prominent excursion from the average trend occurred when Δ14C decreased rapidly in 2000. The rapid decline in Δ14C was concurrent with a rapid decline in atmospheric O2, suggesting a possible cause may be the anomalous ventilation of deep 14C-poor water in the North Pacific Ocean. We additionally find the presence of a 28-month period of oscillation in the Δ14C record at La Jolla.” Graven, H. D., T. P. Guilderson, and R. F. Keeling (2012), Observations of radiocarbon in CO2 at La Jolla, California, USA 1992–2007: Analysis of the long-term trend, J. Geophys. Res., 117, D02302, doi:10.1029/2011JD016533.

Observations of radiocarbon in CO2 at seven global sampling sites in the Scripps flask network: Analysis of spatial gradients and seasonal cycles – Graven et al. (2012) “High precision measurements of Δ14C were conducted for monthly samples of CO2 from seven global stations over 2- to 16-year periods ending in 2007. Mean Δ14C over 2005–07 in the Northern Hemisphere was 5 ‰ lower than Δ14C in the Southern Hemisphere, similar to recent observations from I. Levin. This is a significant shift from 1988–89 when Δ14C in the Northern Hemisphere was slightly higher than the South. The influence of fossil fuel CO2 emission and transport was simulated for each of the observation sites by the TM3 atmospheric transport model and compared to other models that participated in the Transcom 3 Experiment. The simulated interhemispheric gradient caused by fossil fuel CO2 emissions was nearly the same in both 1988–89 and 2005–07, due to compensating effects from rising emissions and decreasing sensitivity of Δ14C to fossil fuel CO2. The observed 5 ‰ shift must therefore have been caused by non-fossil influences, most likely due to changes in the air-sea 14C flux in the Southern Ocean. Seasonal cycles with higher Δ14C in summer or fall were evident at most stations, with largest amplitudes observed at Point Barrow (71°N) and La Jolla (32°N). Fossil fuel emissions do not account for the seasonal cycles of Δ14C in either hemisphere, indicating strong contributions from non-fossil influences, most likely from stratosphere-troposphere exchange.” Graven, H. D., T. P. Guilderson, and R. F. Keeling (2012), Observations of radiocarbon in CO2 at seven global sampling sites in the Scripps flask network: Analysis of spatial gradients and seasonal cycles, J. Geophys. Res., 117, D02303, doi:10.1029/2011JD016535.

Atmospheric observations of carbon monoxide and fossil fuel CO2 emissions from East Asia – Turnbull et al. (2011) “Flask samples from two sites in East Asia, Tae-Ahn Peninsula, Korea (TAP), and Shangdianzi, China (SDZ), were measured for trace gases including CO2, CO and fossil fuel CO2 (CO2ff, derived from Δ14CO2 observations). The five-year TAP record shows high CO2ff when local air comes from the Korean Peninsula. Most samples, however, reflect air masses from Northeastern China with lower CO2ff. Our small set of SDZ samples from winter 2009/2010 have strongly elevated CO2ff. Biospheric CO2 contributes substantially to total CO2 variability at both sites, even in winter when non-fossil CO2 sources (including photosynthesis, respiration, biomass burning and biofuel use) contribute 20–30% of the total CO2 enhancement. Carbon monoxide (CO) correlates strongly with CO2ff. The SDZ and TAP far-field (China influenced) samples have CO: CO2ff ratios (RCO:CO2ff) of 47 ± 2 and 44 ± 3 ppb/ppm respectively, consistent with recent bottom-up inventory estimates and other observational studies. Locally influenced TAP samples fall into two distinct data sets, ascribed to air sourced from South Korea and North Korea. The South Korea samples have low RCO:CO2ff of 13 ± 3 ppb/ppm, slightly higher than bottom-up inventories, but consistent with emission ratios for other developed nations. We compare our CO2ff observations with modeled CO2ff using the FLEXPART Lagrangian particle dispersion model convolved with a bottom-up CO2ff emission inventories. The modeled annual mean CO2ff mole fractions are consistent with our observations when the model inventory includes the reported 63% increase in Chinese emissions from 2004 to 2010, whereas a model version which holds Chinese emissions flat is unable to replicate the observations.” Turnbull, J. C., P. P. Tans, S. J. Lehman, D. Baker, T. J. Conway, Y. S. Chung, J. Gregg, J. B. Miller, J. R. Southon, and L.-X. Zhou (2011), J. Geophys. Res., 116, D24306, doi:10.1029/2011JD016691.

Observation-based estimates of fossil fuel-derived CO2 emissions in the Netherlands using Δ14C, CO and 222Radon – van der Laan et al. (2010) “Surface emissions of CO2 from fossil fuel combustion (ΦFFCO2) are estimated for the Netherlands for the period of May 2006-June 2009 using ambient atmospheric observations taken at station Lutjewad in the Netherlands (6° 21′ E, 53° 24′ N, 1 m. a.s.l.). Measurements of Δ14C on two-weekly integrations of CO2 and CO mixing ratios are combined to construct a quasi-continuous proxy record (FFCO2*) from which surface fluxes (ΦFFCO2*) are determined using the 222Rn flux method. The trajectories of the air masses are analysed to determine emissions which are representative for the Netherlands. We compared our observationally based estimates to the national inventories and we evaluated our methodology using the regional atmospheric transport model REMO. Based on three years of observations we find annual mean ΦFFCO2* emissions of (4.7 ± 1.6) kt km−2 a−1 which is in very good agreement with the Dutch inventories of (4.5 ± 0.2) kt km−2 a−1 (average of 2006–2008).” S. Van Der Laan, U. Karstens, R.E.M. Neubert, I.T. Van Der Laan-Luijkx, H.A.J. Meijer, Tellus B, Volume 62, Issue 5, pages 389–402, November 2010, DOI: 10.1111/j.1600-0889.2010.00493.x. [Full text]

Variations of anthropogenic CO2 in urban area deduced by radiocarbon concentration in modern tree rings – Rakowski et al. (2008) “Radiocarbon concentration in the atmosphere is significantly lower in areas where man-made emissions of carbon dioxide occur. This phenomenon is known as Suess effect, and is caused by the contamination of clean air with non-radioactive carbon from fossil fuel combustion. The effect is more strongly observed in industrial and densely populated urban areas. Measurements of carbon isotope concentrations in a study area can be compared to those from areas of clear air in order to estimate the amount of carbon dioxide emission from fossil fuel combustion by using a simple mathematical model. This can be calculated using the simple mathematical model. The result of the mathematical model followed in this study suggests that the use of annual rings of trees to obtain the secular variations of 14C concentration of atmospheric CO2 can be useful and efficient for environmental monitoring and modeling of the carbon distribution in local scale.”

High resolution atmospheric monitoring of urban carbon dioxide sources – Pataki et al. (2006) “We used a tunable diode laser absorption spectrometer (TDL) to measure CO2 mixing ratios and carbon isotope composition of CO2 in order to estimate the contribution of gasoline versus natural gas combustion to atmospheric CO2 in Salt Lake City. The results showed a pronounced diurnal pattern: the proportional contribution of natural gas combustion varied from 30–40% of total anthropogenic CO2 during evening rush hour to 60–70% at pre-dawn. In addition, over a warming period of several days, the proportional contribution of natural gas combustion decreased with air temperature, likely related to decreased residential heating. These results show for the first time that atmospheric measurements may be used to infer patterns of energy and fuel usage on hourly to daily time scales.” [Full text]

Controlling for anthropogenically induced atmospheric variation in stable carbon isotope studies – Long et al. (2005) “Recent elevation of atmospheric CO2 concentration, related primarily to fossil fuel combustion, has reduced atmospheric CO2 δ13C (13C/12C), and this change in isotopic baseline has, in turn, reduced plant and animal tissue δ13C of terrestrial and aquatic organisms. Such depletion in CO2 δ13C and its effects on tissue δ13C may introduce bias into δ13C investigations, and if this variation is not controlled, may confound interpretation of results obtained from tissue samples collected over a temporal span. … …we estimated a correction factor that controls for atmospheric change…”

Diurnal variability of δ13C and δ18O of atmospheric CO2 in the urban atmosphere of Kraków, Poland – Zimnoch et al. (2004) “This article presents the results of measurements of the isotopic composition and concentration of atmospheric carbon dioxide, performed on air samples from Kraków (Southern Poland) in different seasons of the year. … The calculations show that during the summer and early autumn the dominant contribution to local CO2 peaks is the biosphere, making up to 20% of atmospheric CO2 during the nocturnal temperature inversion in the lower troposphere. During early spring and winter, anthropogenic emissions are the main local source.” [Full text]

Stable isotope ratio mass spectrometry in global climate change research – Ghosh & Brand (2003) “Stable isotope ratios of the life science elements carbon, hydrogen, oxygen and nitrogen vary slightly, but significantly in major compartments of the earth. Owing mainly to antropogenic activities including land use change and fossil fuel burning, the 13C/12C ratio of CO2 in the atmosphere has changed over the last 200 years by 1.5 parts per thousand (from about 0.0111073 to 0.0110906). In between interglacial warm periods and glacial maxima, the 18O/16O ratio of precipitation in Greenland has changed by as much as 5 parts per thousand (0.001935–0.001925). While seeming small, such changes are detectable reliably with specialised mass spectrometric techniques. The small changes reflect natural fractionation processes that have left their signature in natural archives.” [Full text]

A novel approach for independent budgeting of fossil fuel CO2 over Europe by 14CO2 observations – Levin et al. (2003) “Long-term atmospheric 14CO2 observations are used to quantify fossil fuel-derived CO2 concentrations at a regional polluted site, and at a continental mountain station in southwest Germany. Fossil fuel CO2 emission rates for the relevant catchment areas are obtained by applying the Radon-Tracer-Method. They compare well with statistical emissions inventories but reveal a larger seasonality than earlier assumed, thus contributing significantly to the observed CO2 seasonal cycle over Europe. Based on the present approach, emissions reductions on the order of 5–10% are detectable for catchment areas of several hundred kilometres radius, as anticipated within a five-years commitment period of the Kyoto Protocol. Still, no significant change of fossil fuel CO2 emissions is observed at the two sites over the last 16 years.” [Full text]

Seasonal cycle of carbon dioxide and its isotopic composition in an urban atmosphere: Anthropogenic and biogenic effects – Pataki et al. (2003) “Atmospheric CO2 mixing ratios and carbon and oxygen isotope composition were measured at 18 m above the ground in Salt Lake City, Utah, United States, for a one-year period. … The isotope-tracer technique used shows promise for quantifying the impacts of urban processes on the isotopic composition of the atmosphere and partitioning urban CO2 sources into their component parts.” [Full text]

Stable carbon isotope constraints on mixing and mass balance of CO2 in an urban atmosphere: Dallas metropolitan area, Texas, USA – Clark-Thorne & Yapp (2003) “The concentrations and δ13C values of atmospheric CO2 were measured in 150 air samples collected at 8 sites in the Dallas metropolitan area over the period August 1998 to December 1999. … …but the overall pattern suggests that, as temperature decreases, the proportion of anthropogenic CO2 derived from combustion of natural gas increases. This increase appears to reflect increased use of natural gas for home heating, etc., in cooler weather. Therefore, seasonally changing patterns of fossil fuel use are detectable in the atmospheric CO2 of this urban environment.”

Evidence for preindustrial variations in the marine surface water carbonate system from coralline sponges – Böhm et al. (2002) “Carbon isotope records from coralline sponges clearly reflect the industrial 12C increase in atmospheric CO2 with a precision that permits quantitative interpretations. … All δ13C records (appendix A) show the full extent of the industrial decline (Figure 3) caused by the anthropogenic addition of 12C-enriched CO2 to the atmosphere. … The industrial decline in δ13C started in the first half of the 19th century after a short period of stable values around 1800 A.D.” [Full text]

Radiocarbon – a unique tracer of global carbon cycle dynamics – Levin & Hesshaimer (2000) “Radiocarbon observations have played a crucial role as an experimental tool enlightening the spatial and temporal variability of carbon sources and sinks. Studies of the “undisturbed” natural carbon cycle profit from the radioactive decay of 14C in using it as a dating tracer, e.g. to determine the turnover time of soil organic matter or to study internal mixing rates of the global oceans. Moreover, the anthropogenic disturbance of 14C through atmospheric bomb tests has served as an invaluable tracer to get insight into the global carbon cycle on the decadal time scale. … It has been erroneously argued that the observed atmospheric CO2 increase since the middle of the 19th century may be due to an ongoing natural perturbation of gross fluxes between the atmosphere, biosphere, and oceans. That the increase is in fact a predominantly anthropogenic disturbance, caused by accelerated release of CO2 from burning of fossil fuels, has been elegantly demonstrated through 14C analyses of tree rings from the last two centuries (Stuiver and Quay 1981; Suess 1955; Tans et al. 1979).” [Full text]

A 1000-year high precision record of δ13C in atmospheric CO2 – Francey et al. (1999) “We present measurements of the stable carbon isotope ratio in air extracted from Antarctic ice core and firn samples. … Here, we start by confirming the trend in the Cape Grim in situ δ13C record from 1982 to 1996, and extend it back to 1978 using the Cape Grim Air Archive. … An almost continuous atmospheric history of δ13C over 1000 years results, exhibiting significant decadal-to-century scale variability unlike that from earlier proxy records. The decrease in δ13C from 1860 to 1960 involves a series of steps confirming enhanced sensitivity of δ13C to decadal timescale-forcing, compared to the CO2 record.”

Isotopic characterisation of CO2 sources during regional pollution events using isotopic and radiocarbon analysis – Zondervan & Meijer (1996) “At the station Kollumerwaard (The Netherlands), for monitoring tracers in the troposphere, air is sampled in 16 containers for off-line 13C, 18O and 14C isotopic analysis of CO2. The timing of the sampling is chosen such that CO2 variations correlating with pollutants like CO and CH4 are optimally covered. The 14C measurements enable us to discriminate between biospheric and fossil fuel contributions to atmospheric CO2. The analysis of one series sampled on 23 November 1994 resolves the increased CO2 mixing ratio into a purely biospheric component with a δ13C of (− 22.2 ± 1.5)‰, and a fossil component of up to 35 ppm with a δ13C of (− 34.1 ± 1.6)‰. Another series, recorded on 2 and 3 February 1995, shows a nearby emission of fossil CO2, methane and carbon monoxide, most likely due to the flaring of natural gas. Both events clearly indicate the importance of natural gas consumption in or in the vicinity of Holland. These experimental values can be compared with estimates of CO2 emissions from combustion of fossil fuels and the corresponding δ13C values. The results for 18O show the pronounced difference in behaviour between the O and C isotopes in atmospheric CO2, due to the fast isotopic exchange processes with (plant, soil or ocean) water. As a side result, the method produces the ratio CO: fossil CO2, a direct measure for combustion quality on a regional scale.” Albert Zondervan, Harro A. J. Meijer, Tellus B, Volume 48, Issue 4, pages 601–612, September 1996, DOI: 10.1034/j.1600-0889.1996.00013.x. [Full text]

Isotopic characterisation of anthropogenic CO2 emissions using isotopic and radiocarbon analysis – Meijer et al. (1996) “At the station Kollumerwaard (Netherlands), for monitoring tracers in the troposphere, air is sampled in sixteen containers for off-line 13C, 18O and 14C isotopic analysis of CO2. The timing of the sampling is chosen such that CO2 variations correlating with pollutants like CO and CH4 are optimally covered. The 14C measurements enable us to discriminate between biospheric and fossil fuel contributions to background atmosphere CO2. Results during the first year of operation show that the δ13C values for the anthropogenic CO2 are significantly more negative than generally assumed (values ranging from -30 to -58 ‰ VPDB), which clearly indicates the importance of natural gas consumption in the Netherlands. We compare these experimental values with results from a detailed study of CO2 emission estimates from combustion of fossil fuels and the corresponding δ13C values. As an important side result, the method produces reliable values for the regionally averaged ratio CO : fossil CO2 (results ranging from 0.5 to 1%), a direct measure for combustion quality.” H. A. J. Meijer, H. M. Smid, E. Perez and M. G. Keizer, Physics and Chemistry of The Earth, Volume 21, Issues 5-6, October-December 1996, Pages 483-487, doi:10.1016/S0079-1946(97)81146-9. [Full text]

The 13C Suess Effect in the World Surface Oceans and Its Implications for Oceanic Uptake of CO2: Analysis of Observations at Bermuda – Bacastow et al. (1996) “Surface ocean water δ13C measurements near Bermuda are examined in an attempt to find the annual decrease caused by the addition of anthropogenic CO2 to the atmosphere. … Results are, in general, consistent with the low side of the Intergovernmental Panel on Climate Control estimation of 2.0 ± 0.8 GtC yr−1.” [Full text]

Carbon dioxide and methane in continental Europe: a climatology, and 222Radon-based emission estimates – Schmidt et al. (1996) “4-year records of gas chromatographic carbon dioxide and methane observations from the continental mountain station Schauinsland in the Black Forest (Germany) are presented. These data are supplemented by continuous atmospheric 222Radon observations. The raw data of CO2 concentration show a large seasonal cycle of about 16 ppm with monthly mean wintertime enhancements up to 10 ppm higher and summer minima up to 5 ppm lower than the maritime background level in this latitude. These offsets are caused by regional and continental scale CO2 sources and sinks. The mean CH4 concentration at Schauinsland is 31 ppb higher than over the Atlantic ocean, due to the European continent acting as a net source of atmospheric CH4 throughout the year. No significant seasonal cycle of methane has been observed. The long term CO2 and CH4 increase rates at Schauinsland are found to be similar to background stations in the northern hemisphere, namely 1.5 ppm CO2 yr-1 and 8 ppb CH4 yr-1. On the time scale of hours and days, the wintertime concentrations of all three trace gases are highly correlated, the mean ratio of CH4/CO2 is 7.8 ± 1.0 ppb/ ppm. The wintertime monthly mean concentration offsets relative to the maritime background level show a CH4/CO2 ratio of 6.5 ± 1.1 ppb/ ppm, thus, not significantly different from the short term ratio. Using the wintertime regressions of CO2 and 222Radon respectively CH4 and 222Radon we estimate winter time CO2 flux densities of 10.4 ± 4.3 mmol CO2 m-2 h-1 (from monthly mean offsets) and 6.4 ± 2.5 mmol CO2 m-2 h-1 (from short term fluctuations) and winter time methane flux densities of 0.066 ± 0.034 mmol CH4 m-2 h-1 (from monthly mean offsets) and 0.057 ± 0.022 mmole CH4 m-2 h-1 (from short-term fluctuations). These flux estimates are in close agreement to CO2 respectively CH4 emission inventories reported for Germany from statistical data.” Martina Schmidt, Rolf Graul, Hartmut Sartorius, Ingeborg Levin, Tellus B, Volume 48, Issue 4, pages 457–473, September 1996, DOI: 10.1034/j.1600-0889.1994.t01-2-00002.x-i1.

Interannual extremes in the rate of rise of atmospheric carbon dioxide since 1980 – Keeling et al. (1995) “Observations of atmospheric CO2 concentrations at Mauna Loa, Hawaii, and at the South Pole over the past four decades show an approximate proportionality between the rising atmospheric concentrations and industrial CO2 emissions. This proportionality, which is most apparent during the first 20 years of the records, was disturbed in the 1980s by a disproportionately high rate of rise of atmospheric CO2, followed after 1988 by a pronounced slowing down of the growth rate. To probe the causes of these changes, we examine here the changes expected from the variations in the rates of industrial CO2 emissions over this time, and also from influences of climate such as El Niño events. We use the 13C/12C ratio of atmospheric CO2 to distinguish the effects of interannual variations in biospheric and oceanic sources and sinks of carbon. We propose that the recent disproportionate rise and fall in CO13 growth rate were caused mainly by interannual variations in global air temperature (which altered both the terrestrial biospheric and the oceanic carbon sinks), and possibly also by precipitation. We suggest that the anomalous climate-induced rise in CO13 was partially masked by a slowing down in the growth rate of fossil-fuel combustion, and that the latter then exaggerated the subsequent climate-induced fall.” [Full text]

Variability in The O2/N2 Ratio of Southern Hemisphere Air, 1991-1994: Implications for the Carbon Cycle – Bender et al. (1995) “We present a record of variations in the O2/N2 ratio of air at 41° S latitude from 1991–1994 based on the mass spectrometric analysis of flask samples from Cape Grim, Tasmania, and Baring Head, New Zealand. Results for Cape Grim for the period from June 1991 to February 1992 are in good agreement with previously published data of Keeling and Shertz [1992]. … The O2/N2 ratio of air decreased at the rate of 12±4 per meg/yr (0.012 ‰/yr) between winter 1991 and winter 1993. This value is considerably less than the O2 consumption rate associated with fossil fuel burning (about 20 per meg/yr), suggesting that the land biosphere was an O2 source and an important CO2 sink during this period. Alternatively, the oceans may have been a transient O2 sink during 1991–1993, most likely caused by an enhanced rate of thermocline ventilation with respect to the steady-state value.”

Long-term observations of atmospheric CO2 and carbon isotopes at continental sites in Germany – Levin et al. (1995) “The long-term mean CO2 increase rate in the last 20 years at Westerland and Schauinsland is 1.49 and 1.48 ppmv yr-1, respectively. The mean d13C of the seasonal source CO2 at Schauinsland is calculated from unselected d13C and CO2 data to be -25.1‰. From the 14C observations in unselected CO2, we derive yearly mean fossil fuel contributions at Westerland of 4 ppmv, and at Schauinsland of only 2.5 ppmv. Based on the seasonality of the fossil fuel CO2 component at Schauinsland and on concurrently observed atmospheric 222Radon activities, we derive a seasonal amplitude of the fossil fuel CO2 source which is higher by a factor of 3 compared to emission estimates for Europe.”

Seasonal and interannual variations in atmospheric oxygen and implications for the global carbon cycle – Keeling & Shertz (1992) “Measurements of changes in atmospheric molecular oxygen using a new interferometric technique show that the O2 content of air varies seasonally in both the Northern and Southern Hemispheres and is decreasing from year to year. The seasonal variations provide a new basis for estimating global rates of biological organic carbon production in the ocean, and the interannual decrease constrains estimates of the rate of anthropogenic CO2 uptake by the oceans.” [Full text]

Oceanic Uptake of Fossil Fuel CO2: Carbon-13 Evidence – Quay et al. (1992) “The δ13C value of the dissolved inorganic carbon in the surface waters of the Pacific Ocean has decreased by about 0.4 per mil between 1970 and 1990. This decrease has resulted from the uptake of atmospheric CO2 derived from fossil fuel combustion and deforestation. The net amounts of CO2 taken up by the oceans and released from the biosphere between 1970 and 1990 have been determined from the changes in three measured values: the concentration of atmospheric CO2, the δ13C of atmospheric CO2 and the δ13C value of dissolved inorganic carbon in the ocean. The calculated average net oceanic CO2 uptake is 2.1 gigatons of carbon per year. This amount implies that the ocean is the dominant net sink for anthropogenically produced CO2 and that there has been no significant net CO2 released from the biosphere during the last 20 years.” [Full text]

Atmospheric CO2 in continental Europe—an alternative approach to clean air CO2 data – Levin (1987) “A 5-year record of continuous atmospheric CO2 concentration data from the Schauinsland mountain top station (48°N, 8°E, 1205 m a.s.l.) is analysed for contributions from different continental sources, e.g., fossil fuels and by the natural biosphere. The fossil fuel contribution is determined from monthly averages of parallel carbon isotope data (14C, (13C)) collected from 1977 to 1984. The observed short-term fluctuations are identified as “local contamination” with help of continuous atmospheric 222Radon data from the same location. The combination of all tracer data, carbon isotopes and 222Radon activity, in addition to CO2 concentration makes it possible to evaluate a CO2 concentration record representative for “continental clean air” not influenced locally by natural and anthropogenic sources. Comparison of the processed record with CO2 data from a marine station (Ocean Weather Station P, 50°N, 145° W) (Wong et al., 1984) shows a significant phase shift at the continental compared to the marine site. This is attributed to the continental biosphere acting as a net sink in early summer (April to June) and as a net source in autumn and winter (October to January).” Ingeborg Levin, Tellus B, Volume 39B, Issue 1-2, pages 21–28, February-April 1987, DOI: 10.1111/j.1600-0889.1987.tb00267.x.

Input of excess CO2 to the surface ocean based on 13C/12C ratios in a banded Jamaican sclerosponge – Druffel & Benavides (1986) “Here we present surface ocean 13C and 18O records measured in the skeleton of a living sclerosponge (Ceratoporella nicholsoni), which accretes aragonite in isotopic equilibrium with the surrounding sea water/dissolved inorganic carbon (DIC) system. The 13C record reveals a decrease of 0.50 [promille] from 1820 to 1972.”

Ice core record of the 13C/12C ratio of atmospheric CO2 in the past two centuries – Friedli et al. (1986) “The release of carbon into the atmosphere due to the activities of humans has caused an increase in concentration as well as a change in the isotopic composition of atmospheric carbon dioxide. CO2 derived from fossil fuel combustion and from biomass destruction have δ13C values of ~-25 [promille] (compared to the atmospheric value of ~-7 [promille]) and are thus depleted in 13C. We have measured δ13C of CO2 separated from air trapped in bubbles in ice samples from an ice core taken at Siple Station in Antarctica, in which it has been possible to demonstrate the atmospheric increase of CO2 (ref. 1) and methane2 with high time resolution. The isotopic results, together with the CO2 record from the same ice core, yield information on the sources of excess carbon dioxide and provide a data base for testing the consistency of global carbon cycle models.”

An explanation of 13C/12C variations in tree rings – Francey & Farquhar (1982) “Variations in the 13C/12C ratio in trees are examined in the light of a simple expression relating the relative isotope composition of plant material, δp13 to δa13, the atmospheric isotope value, ca, the atmospheric CO2 concentration and ci, the internal concentration of CO2 in leaves. The expression gives good agreement with δp13 measurements where independent information on ci exists, such as seasonal growth, growth low in the canopy and in conditions of low humidity. The expression provides possible explanations for two previously unexplained phenomena: the absence of anticipated changes due to fossil fuel-induced changes in δa13, and regional differences in δp13 trends.”

Atmospheric 14C changes resulting from fossil fuel CO2 release and cosmic ray flux variability – Stuiver & Quay (1981) “A high-precision tree-ring record of the atmospheric 14C levels between 1820 and 1954 is presented. Good agreement is obtained between measured and model calculated 19th and 20th century atmospheric Δ14C levels when both fossil fuel CO2 release and predicted natural variations in 14C production are taken into account.”

Natural atmospheric 14C variation and the Suess effect – Tans et al. (1979) “THE dilution of the atmospheric 14CO2 concentration by large amounts of fossil-fuel derived CO2 which do not contain any 14C is commonly called the Suess effect. Its magnitude can be calculated with the same geochemical models as the global carbon cycle that also predict the future rise of atmospheric CO2 to be caused by the combustion of fossil fuels. Validation of a CO2 predictive model with the Suess effect 14C data is important because these two phenomena have a common cause, and therefore register model responses at roughly the same frequencies. Measurements of the Suess effect yield values between -15, and -25 in 14C (in 1950), while different model predictions also cover about this range. The requirement that a model correctly reproduces the Suess effect becomes a strong constraint when the accuracy of the measurement is improved to better than 2. 14C measurements in tree rings to an accuracy of 1.2 are reported here. The results indicate that the natural fluctuations of atmospheric 14C as yet preclude determination of the Suess effect to the accuracy required by the models.”

On the 13C record in tree rings. Part I. 13C Variations in northern hemispheric trees during the last 150 years – Freyer (1979) 13C data from 26 trees of different northern hemispheric locations are presented covering the time interval of the last 150 years. It has been found that the mean 13C data of these trees during the 1850–1920, 1920–1940 and 1960–1975 time intervals decrease with an almost linear slope, while the data in the 1940–1960 time interval are increasing. The total δ13C shift since industrialization found from our trees amounts to nearly −29% which is higher than the linear δ13C decrease of −1%/100 years due to the biogenic and fossil CO2 input into the atmosphere, as assumed previously in model calculations of Siegenthaler et al. (1978). The mean data within the given error-probability correspond to those of other authors with the exception of the data for the 1920–1940 time interval. The disturbances in 13C data for recording of increasing atmospheric CO2 levels have been pointed out.” H. D. Freyer, Tellus, Volume 31, Issue 2, pages 124–137, April 1979, DOI: 10.1111/j.2153-3490.1979.tb00889.x.

Recent trends in the 13C/12C ratio of atmospheric carbon dioxide – Keeling et al. (1979) “The 13C/12C ratio of atmospheric carbon dioxide has decreased by approximately 0.6 [promille] over 22 yr according to new direct measurements reported here.”

Temporal Fluctuations of Atmospheric 14C: Causal Factors and Implications – Damon et al. (1978) A review article. “In this review we consider the time variations of the atmospheric concentration of 14C, a radioisotope induced by cosmic rays and also known as radiocarbon.” [Full text, click PDF-link]

Carbon dioxide exchange between atmosphere and ocean and the – Revelle & Suess (1957) “From a comparison of C14/C12 and C13/C12 ratios in wood and in marine material and from a slight decrease of the C14 concentration in terrestrial plants over the past 50 years it can be concluded that the average lifetime of a CO2 molecule in the atmosphere before it is dissolved into the sea is of the order of 10 years. This means that most of the CO2 released by artificial fuel combustion since the beginning of the industrial revolution must have been absorbed by the oceans. The increase of atmospheric CO2 from this cause is at present small but may become significant during future decades if industrial fuel combustion continues to rise exponentially.” [Full text]

Radiocarbon Concentration in Modern Wood – Suess (1955)


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Papers on sea ice amount observations

Posted by Ari Jokimäki on October 28, 2009

This is a list of papers on the amount of sea ice globally and in Arctic and Antarctic regions. The list is not complete, and will most likely be updated in the future in order to make it more thorough and more representative.

UPDATE (August 1, 2019): Walsh et al. (2016) added. Thanks to Barry for pointing it out.
UPDATE (August 27, 2012): Thomsen (1948), Sanderson (1975), Kelly (1979), Walsh & Johnson (1979), Walsh & Johnson (1979), Carsey (1982), Mysak & Manak (1989), Serreze et al. (1995), Serreze et al. (2003), and Rigor & Wallace (2004) added.
UPDATE (April 14, 2012): Tareghian & Rasmussen (2012) added.
UPDATE (October 10, 2010): Polyak et al. (2010) added. Thanks to Barry for pointing it out, see the comment section below.
UPDATE (December 9, 2009): Kwok et al. (2009) added.

Global sea ice papers

Analysis of Arctic and Antarctic sea ice extent using quantile regression – Tareghian & Rasmussen (2012) “A number of recent studies have examined trends in sea ice cover using ordinary least squares regression. In this study, quantile regression is applied to analyse other aspects of the distribution of sea ice extent. More specifically, trends in the mean, maximum, and minimum sea ice extent in the Arctic and Antarctic are investigated. While there is a significant decreasing trend in mean Arctic sea ice extent of − 4.5% per decade from 1979 through 2010, the Antarctic results show a small positive trend of 2.3% per decade. In some cases such as the Antarctic minimum ice cover, selected quantile regressions yield slope estimates that differ from trends in the mean. It was also found that the variability in Antarctic sea ice extent is higher than that in the Arctic.” Reza Tareghian, Peter Rasmussen, International Journal of Climatology, DOI: 10.1002/joc.3491.

Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century – Rayner et al. (2003) “We present the Met Office Hadley Centre’s sea ice and sea surface temperature (SST) data set, HadISST1, and the nighttime marine air temperature (NMAT) data set, HadMAT1. HadISST1 replaces the global sea ice and sea surface temperature (GISST) data sets and is a unique combination of monthly globally complete fields of SST and sea ice concentration on a 1° latitude-longitude grid from 1871. … The sea ice fields are made more homogeneous by compensating satellite microwave-based sea ice concentrations for the impact of surface melt effects on retrievals in the Arctic and for algorithm deficiencies in the Antarctic and by making the historical in situ concentrations consistent with the satellite data.”

Analysis of merged SMMR‐SSMI time series of Arctic and Antarctic sea ice parameters 1978–1995 – Bjørgo et al. (1997) “The Nimbus 7 Scanning Multichannel Microwave Radiometer (SMMR) and the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave Imager (SSMI) provide information on the global sea ice cover from 1978 to present. … Statistical analysis on the time series estimates the decreases in Arctic ice extent and ice area to be 4.5% and 5.7%, respectively, during the 16.8‐year observation period.” [Full text]

Observed Hemispheric Asymmetry in Global Sea Ice Changes – Cavalieri et al. (1997) “From November 1978 through December 1996, the areal extent of sea ice decreased by 2.9 ± 0.4 percent per decade in the Arctic and increased by 1.3 ± 0.2 percent per decade in the Antarctic. The observed hemispheric asymmetry in these trends is consistent with a modeled response to a carbon dioxide-induced climate warming. The interannual variations, which are 2.3 percent of the annual mean in the Arctic, with a predominant period of about 5 years, and 3.4 percent of the annual mean in the Antarctic, with a predominant period of about 3 years, are uncorrelated.”

Arctic and antarctic sea ice, 1978-1987: Satellite passive-microwave observations and analysis – Gloersen et al. (1992) “This book contains a description and analysis of the spatial and temporal variations in the Arctic and Antarctic sea ice covers from October 26, 1978 througb August 20, 1987. It is based on data collected by tbe Scanning Multichannel Microwave Radiometer (SMMR) onboard the NASA Nimbus 7 satellite. … The interannual variability of the ice extent areas is much larger for the perimeter seas than for the Arctic as a whole; some regions exhibit decreasing trends, while others exhibit increasing trends. … As in the Arctic, the individual sectors have larger interannual differences than in the Antarctic as a whole, implying compensating relationships in the various regions.”

Arctic sea ice papers

A database for depicting Arctic sea ice variations back to 1850 – Walsh et al. (2016)
Abstract: Arctic sea ice data from a variety of historical sources have been synthesized into a database extending back to 1850 with monthly time‐resolution. The synthesis procedure includes interpolation to a uniform grid and an analog‐based estimation of ice concentrations in areas of no data. The consolidated database shows that there is no precedent as far back as 1850 for the 21st century’s minimum ice extent of sea ice on the pan‐Arctic scale. A regional‐scale exception to this statement is the Bering Sea. The rate of retreat since the 1990s is also unprecedented and especially large in the Beaufort and Chukchi Seas. Decadal and multidecadal variations have occurred in some regions, but their magnitudes are smaller than that of the recent ice loss. Interannual variability is prominent in all regions and will pose a challenge to sea ice prediction efforts.
Citation: Walsh, J. E., Fetterer, F. , Scott Stewart, J. and Chapman, W. L. (2017), A database for depicting Arctic sea ice variations back to 1850. Geogr Rev, 107: 89-107. doi:10.1111/j.1931-0846.2016.12195.x

History of sea ice in the Arctic – Polyak et al. (2010) “Arctic sea-ice extent and volume are declining rapidly. Several studies project that the Arctic Ocean may become seasonally ice-free by the year 2040 or even earlier. Putting this into perspective requires information on the history of Arctic sea-ice conditions through the geologic past. This information can be provided by proxy records from the Arctic Ocean floor and from the surrounding coasts. Although existing records are far from complete, they indicate that sea ice became a feature of the Arctic by 47 Ma, following a pronounced decline in atmospheric pCO2 after the Paleocene–Eocene Thermal Optimum, and consistently covered at least part of the Arctic Ocean for no less than the last 13–14 million years. Ice was apparently most widespread during the last 2–3 million years, in accordance with Earth’s overall cooler climate. Nevertheless, episodes of considerably reduced sea ice or even seasonally ice-free conditions occurred during warmer periods linked to orbital variations. The last low-ice event related to orbital forcing (high insolation) was in the early Holocene, after which the northern high latitudes cooled overall, with some superimposed shorter-term (multidecadal to millennial-scale) and lower-magnitude variability. The current reduction in Arctic ice cover started in the late 19th century, consistent with the rapidly warming climate, and became very pronounced over the last three decades. This ice loss appears to be unmatched over at least the last few thousand years and unexplainable by any of the known natural variabilities.” Leonid Polyak, Richard B. Alley, John T. Andrews, Julie Brigham-Grette, Thomas M. Cronin, Dennis A. Darby, Arthur S. Dyke, Joan J. Fitzpatrick, Svend Funder, Marika Holland, Anne E. Jennings, Gifford H. Miller, Matt O’Regan, James Savelle, Mark Serreze, Kristen St. John, James W.C. White and Eric Wolff, Quaternary Science Reviews, Volume 29, Issues 15-16, July 2010, Pages 1757-1778,doi:10.1016/j.quascirev.2010.02.010. [Full text]

Thinning and volume loss of the Arctic Ocean sea ice cover: 2003–2008 – Kwok et al. (2009) “We present our best estimate of the thickness and volume of the Arctic Ocean ice cover from 10 Ice, Cloud, and land Elevation Satellite (ICESat) campaigns that span a 5-year period between 2003 and 2008. … Along with a more than 42% decrease in multiyear (MY) ice coverage since 2005, there was a remarkable thinning of ∼0.6 m in MY ice thickness over 4 years. In contrast, the average thickness of the seasonal ice in midwinter (∼2 m), which covered more than two-thirds of the Arctic Ocean in 2007, exhibited a negligible trend.”

Circumpolar thinning of Arctic sea ice following the 2007 record ice extent minimum – Giles et al. (2008) “Using satellite radar altimetry data, covering the Arctic Ocean up to 81.5° North, we show that the average winter sea ice thickness anomaly, after the melt season of 2007, was 0.26 m below the 2002/2003 to 2007/2008 average. More strikingly, the Western Arctic anomaly was 0.49 m below the six-year mean in the winter of 2007/2008. These results show no evidence of short-term preconditioning through ice thinning between 2002 and 2007 but show that, after the record minimum ice extent in 2007, the average ice thickness was reduced, particularly in the Western Arctic.”

Accelerated decline in the Arctic sea ice cover – Comiso et al. (2008) “Satellite data reveal unusually low Arctic sea ice coverage during the summer of 2007, caused in part by anomalously high temperatures and southerly winds. The extent and area of the ice cover reached minima on 14 September 2007 at 4.1 × 106 km2 and 3.6 × 106 km2, respectively. These are 24% and 27% lower than the previous record lows, both reached on 21 September 2005, and 37% and 38% less than the climatological averages. Acceleration in the decline is evident as the extent and area trends of the entire ice cover (seasonal and perennial ice) have shifted from about −2.2 and −3.0% per decade in 1979–1996 to about −10.1 and −10.7% per decade in the last 10 years.” [Full text]

Recent trend reversals in arctic sea ice extents: possible connections to the north Atlantic oscillation – Parkinson (2008) “This paper reports the results of regression analysis performed on the yearly averaged ice extents for the two time periods 1979-1990 and 1990-1999, and reveals two important findings: (1) for the Arctic as a whole, the decade of the 1990s witnessed a deceleration of the trend toward lesser ice extents; and (2) the sign of the trend reversed from the 1979-1990 period to the 1990-1999 period in seven of the nine regions into which the Arctic ice cover is divided for analysis. The paper explores the possible connection between the spatial patterns of the sea ice trends and their reversals and the North Atlantic Oscillation (NAO), which reached a peak in its annual index in 1990.”

Arctic sea ice decline: Faster than forecast – Stroeve et al. (2007) “From 1953 to 2006, Arctic sea ice extent at the end of the melt season in September has declined sharply. All models participating in the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) show declining Arctic ice cover over this period. However, depending on the time window for analysis, none or very few individual model simulations show trends comparable to observations. If the multi-model ensemble mean time series provides a true representation of forced change by greenhouse gas (GHG) loading, 33–38% of the observed September trend from 1953–2006 is externally forced, growing to 47–57% from 1979–2006.” [Full text]

Rapid reduction of Arctic perennial sea ice – Nghiem et al. (2007) “The extent of Arctic perennial sea ice, the year-round ice cover, was significantly reduced between March 2005 and March 2007 by 1.08 × 106 km2, a 23% loss from 4.69 × 106 km2 to 3.61 × 106 km2, as observed by the QuikSCAT/SeaWinds satellite scatterometer (QSCAT). … QSCAT data also revealed mechanisms contributing to the perennial-ice extent loss: ice compression toward the western Arctic, ice loading into the Transpolar Drift (TD) together with an acceleration of the TD carrying excessive ice out of Fram Strait, and ice export to Baffin Bay.” [Full text]

Variations in the age of Arctic sea-ice and summer sea-ice extent – Rigor & Wallace (2004) “Three of the past six summers have exhibited record low sea-ice extent on the Arctic Ocean. These minima may have been dynamically induced by changes in the surface winds. Based on results of a simple model that keeps track of the age of ice as it moves about on the Arctic Ocean, we show that the areal coverage of thick multi-year ice decreased precipitously during 1989–1990 when the Arctic Oscillation was in an extreme “high index” state, and has remained low since that time. Under these conditions, younger, thinner ice anomalies recirculate back to the Alaskan coast more quickly, decreasing the time that new ice has to ridge and thicken before returning for another melt season. During the 2002 and 2003 summers this anomalously younger, thinner ice was advected into Alaskan coastal waters where extensive melting was observed, even though temperatures were locally colder than normal. The age of sea-ice explains more than half of the variance in summer sea-ice extent.” Rigor, I. G. and J. M. Wallace (2004), Variations in the age of Arctic sea-ice and summer sea-ice extent, Geophys. Res. Lett., 31, L09401, doi:10.1029/2004GL019492. [Full text]

A record minimum arctic sea ice extent and area in 2002 – Serreze et al. (2003) “Arctic sea ice extent and area in September 2002 reached their lowest levels recorded since 1978. These conditions likely resulted from (1) anomalous warm southerly winds in spring, advecting ice poleward from the Siberian coast (2) persistent low pressure and high temperatures over the Arctic Ocean in summer, promoting ice divergence and rapid melt.” Serreze, M. C., J. A. Maslanik, T. A. Scambos, F. Fetterer, J. Stroeve, K. Knowles, C. Fowler, S. Drobot, R. G. Barry, and T. M. Haran (2003), A record minimum arctic sea ice extent and area in 2002, Geophys. Res. Lett., 30(3), 1110, doi:10.1029/2002GL016406. [Full text]

Thinning of the Arctic sea‐ice cover – Rothrock et al. (1999) “Comparison of sea‐ice draft data acquired on submarine cruises between 1993 and 1997 with similar data acquired between 1958 and 1976 indicates that the mean ice draft at the end of the melt season has decreased by about 1.3 m in most of the deep water portion of the Arctic Ocean, from 3.1 m in 1958–1976 to 1.8 m in the 1990s.” [Full text]

Arctic sea ice extents, areas, and trends, 1978–1996 – Parkinson et al. (1999) “Satellite passive-microwave data for November 1978 through December 1996 reveal marked seasonal, regional, and interannual variabilities, with an overall decreasing trend of −34,300 ± 3700 km2/yr (−2.8%/decade) in Arctic sea ice extents over the 18.2-year period.”

Satellite Evidence for an Arctic Sea Ice Cover in Transformation – Johannessen et al. (1999) “Recent research using microwave satellite remote sensing data has established that there has been a reduction of about 3 percent per decade in the areal extent of the Arctic sea ice cover since 1978, although it is unknown whether the nature of the perennial ice pack has changed. These data were used to quantify changes in the ice cover’s composition, revealing a substantial reduction of about 14 percent in the area of multiyear ice in winter during the period from 1978 to 1998. There also appears to be a strong correlation between the area of multiyear ice and the spatially averaged thickness of the perennial ice pack, which suggests that the satellite-derived areal decreases represent substantial rather than only peripheral changes.” [Full text]

Diagnosis of the record minimum in Arctic sea ice area during 1990 and associated snow cover extremes – Serreze et al. (1995) “The Arctic sea ice cover exhibited its record minimum area during 1990, characterized by extensive ice‐free conditions during August along the Siberian coast. These reductions are consistent with warm, windy conditions in May and continued warmth in June promoting early melt and reductions in ice concentration, followed in August by strong coastal winds forcing a final breakup and retreat of the pack ice. The unusually warm Arctic conditions in 1990 are part of a larger‐scale temperature anomaly pattern, linking the sea ice anomaly to accompanying record minima in Eurasian snow cover.” Serreze, M. C., J. A. Maslanik, J. R. Key, R. F. Kokaly, and D. A. Robinson (1995), Diagnosis of the record minimum in Arctic sea ice area during 1990 and associated snow cover extremes, Geophys. Res. Lett., 22(16), 2183–2186, doi:10.1029/95GL02068.

Arctic Sea‐Ice extent and anomalies, 1953–1984 – Mysak & Manak (1989) “A study is presented of the seasonal and interannual variability of Arctic sea‐ice extent over the 32‐year period 1953–84. The data set used consists of monthly sea‐ice concentration values given on a 1°‐latitude grid and represents a 7‐year extension of the 25‐year data set analysed by Walsh and Johnson (1979). By focussing attention on the variability in seven distinct subregions that circumscribe the polar region, a number of interesting spatial patterns emerge in the regional seasonal cycles and anomalies of ice coverage. For example, the time‐scale of the smoothed anomaly fluctuations varies from a 4–6 year cycle in the western Arctic (e.g. the Beaufort Sea) to a decadal one in the eastern Arctic (e.g. the Barents Sea). Also, in agreement with earlier studies, a significant out‐of‐phase relationship was found between the 25‐month smoothed anomalies in the Beaufort and Chukchi Sea region and the Greenland Sea. It is proposed that this behaviour is related to atmospheric pressure anomalies associated with the see‐saw in winter air temperature between northern Europe and western Greenland. Finally, a particularly large 9‐year ice anomaly in the Greenland Sea that was centred on 1968 appears to have evolved into a substantial 4‐year Labrador Sea anomaly that peaked in 1972. Both of these anomalies coincided with the passage of the “ Great Salinity Anomaly”, which traversed cyclonically around the subpolar gyre in the northern North Atlantic during the period 1968–82.” Lawrence A. Mysak & Davinder K. Manak, Atmosphere-Ocean, Volume 27, Issue 2, 1989, 376-405, DOI:10.1080/07055900.1989.9649342. [Full text]

Arctic Sea Ice Distribution at End of Summer 1973–1976 From Satellite Microwave Data – Carsey (1982) “Passive microwave data at 1.55 cm collected by the Nimbus 5 Electrically Scanning Microwave Radiometer are analyzed to determine the areal extent and distribution of Arctic sea ice at the time of transition from summer melt to fall freeze up of years 1973–1976. While regional variations are great, the total areal coverage of ice-laden sea changes interannually only about 2% from 7 × 106 km2. Ice surviving the summer melt has a mean concentration of 0.74 and a volume of 15.8 × 103 km3, both somewhat lower than earlier estimates. Multiyear ice concentrations were measured by examining on grid cells of 200 km dimension of brightness changes associated with freezing of leads. A significant spatial variation in multiyear ice emissivity was observed which brought about spatial brightness variation comparable to that caused by typical mixtures with open water and first-year ice. Measurement errors made the detail of interannual changes in emissivity suspect.” Carsey, F. D. (1982), Arctic Sea Ice Distribution at End of Summer 1973–1976 From Satellite Microwave Data, J. Geophys. Res., 87(C8), 5809–5835, doi:10.1029/JC087iC08p05809.

An Analysis of Arctic Sea Ice Fluctuations, 1953–77 – Walsh & Johnson (1979) “Arctic sea ice data from the 1953–77 period are digitized onto a set of 300 monthly grids covering the polar cap. Each grid contains 1648 ice concentration points at a spacing of 1° latitude (60 n mi). The synthesis of the regional ice data sets is described. The digitized data are used to evaluate quantitatively the normal seasonal cycle of ice extent, the 25 year extremes for winter and summer, and the longitudinal dependence of the variance and trend of ice extent. Interannual variations of ice extent exceeding 5° latitude are found at most longitudes. The time series of total Arctic ice extent shows a statistically significant positive trend and correlates negatively with recent high-latitude temperature fluctuations. Empirical orthogonal functions of longitude are used to identify the major spatial and temporal scales of ice fluctuations within the 25-year period. The dominant spatial mode is an asymmetric mode in which the North Atlantic anomaly is opposite in sign to the anomaly over the remainder of the polar cap. A tendency for ice anomalies to persist for several months is apparent in the lagged autocorrelations of the amplitudes of the dominant ice eigenvectors. The month-to-month persistence of the ice anomalies is considerably greater than the persistence of the high-latitude meteorological anomaly fields of sea level pressure, surface temperature and 700 mb height.” Walsh, John E., Claudia M. Johnson, 1979: An Analysis of Arctic Sea Ice Fluctuations, 1953–77. J. Phys. Oceanogr., 9, 580–591. doi:;2. [Full text]

Interannual Atmospheric Variability and Associated Fluctuations in Arctic Sea Ice Extent – Walsh & Johnson (1979) “Observational data are used to evaluate quantitatively the relationships between arctic sea ice extent and the high-latitude atmospheric circulation on the seasonal time scale. The sea ice data set contains 300 monthly grids of observed sea ice concentrations. The atmospheric variables include sea level pressure, surface temperature, 700-mbar height, and 700-mbar temperature. Statistically significant correlations between the dominant modes of atmospheric and sea ice variability are found at atmospheric lags of up to 2 months and ice lags of up to 4 months. The surface temperature field generally shows the strongest relationship to the sea ice fluctuations. The strongest correlations between ice anomalies and subsequent atmospheric fluctuations are found in the autumn months of increasing ice extent. Evidence of ice-atmosphere coupling is also found in the mid-latitude fields of the North Atlantic. The meteorological difference fields derived from years of extreme ice extent contain statistically significant pressure differences of up to 10–15 mbar, surface temperature differences of up to 8°–9°K, and 700-mbar height differences of up to 16–18 decameters. The anomaly centers tend to migrate seasonally with the ice edge. The statistical predictability of large-scale sea ice fluctuations decays to the level of no skill at a forecast interval of 5–6 months.” Walsh, J. E., and C. M. Johnson (1979), Interannual Atmospheric Variability and Associated Fluctuations in Arctic Sea Ice Extent, J. Geophys. Res., 84(C11), 6915–6928, doi:10.1029/JC084iC11p06915.

An Arctic Sea Ice Data Set, 1901-1956 – Kelly (1979) “The Climatic Research Unit, University of East Anglia, is engaged in a feasibility study of the potential for Arctic sea ice prediction on climatic time scales. The main stages in this research were summarized in an appendix. The program includes the collection of sea ice data for the Arctic covering the 20th century; the statistical analysis of these data to identify the major fluctuations in sea ice extent, both spatially and temporally; correlation with climatic and atmospheric circulation data to determine the immediate causes of these sea ice variations, not excluding the possibility of feedback; and research, both theoretical and empirical, aimed at achieving the degree of understanding of the causes of these variations in climate and sea ice which is a necessary prerequisite to any predictive effort. This paper dealt with the first stage in this research: the collection of Arctic sea ice data for the 20th century. (See also W80-00566) (Humphreys-ISWS)” Kelly, PM, Glaciological Data: Workshop on Snow Cover and Sea Ice Data; Workshop held in Boulder, Colorado November 2-3, 1978. p 101-106, May 1979. 1 fig, 1 tab, 25 ref, 1 append. ONR N00014-77-G-0074.

Changes in the area of Arctic sea ice 1966 to 1974 – Sanderson (1975) Doesn’t seem to be available online. Sanderson, R. M., 1975: Changes in the area of Arctic sea ice, 1966 to 1974. Meteor. Mag., 104, 313–323.

The annual reports on the Arctic sea-ice issued by the Danish Meteorological Institute – Thomsen (1948) No abstract or full text available online. Thomsen, Helge, 1948, Journal of Glaciology, vol.1, Issue 3, pp.140-141.

Antarctic sea ice papers

Non‐annular atmospheric circulation change induced by stratospheric ozone depletion and its role in the recent increase of Antarctic sea ice extent – Turner et al. (2009) “Based on a new analysis of passive microwave satellite data, we demonstrate that the annual mean extent of Antarctic sea ice has increased at a statistically significant rate of 0.97% dec-1 since the late 1970s.”

Thickness distribution of Antarctic sea ice – Worby et al. (2008) “Ship-based observations are used to describe regional and seasonal changes in the thickness distribution and characteristics of sea ice and snow cover thickness around Antarctica. The data set comprises 23,373 observations collected over more than 2 decades of activity and has been compiled as part of the Scientific Committee on Antarctic Research (SCAR) Antarctic Sea Ice Processes and Climate (ASPeCt) program. The results show the seasonal progression of the ice thickness distribution for six regions around the continent together with statistics on the mean thickness, surface ridging, snow cover, and local variability for each region and season. … The long-term mean and standard deviation of total sea ice thickness (including ridges) is reported as 0.87 ± 0.91 m, which is 40% greater than the mean level ice thickness of 0.62 m.” [Full text]

Antarctic sea ice variability and trends, 1979–2006 – Cavalieri & Parkinson (2008) “Analyses of 28 years (1979–2006) of Antarctic sea ice extents and areas derived from satellite passive microwave radiometers are presented and placed in the context of results obtained previously for the 20-year period 1979–1998. … The total Antarctic sea ice extent trend increased slightly, from 0.96 ± 0.61% decade-1 to 1.0 ± 0.4% decade-1, from the 20- to 28-year period, reflecting contrasting changes in the sector trends.”

Increasing Antarctic Sea Ice under Warming Atmospheric and Oceanic Conditions – Zhang et al. (2007) A model study, but important for the explanation of the sea ice increase in Antarctic. “Estimates of sea ice extent based on satellite observations show an increasing Antarctic sea ice cover from 1979 to 2004 even though in situ observations show a prevailing warming trend in both the atmosphere and the ocean. This riddle is explored here using a global multicategory thickness and enthalpy distribution sea ice model coupled to an ocean model. … The model shows that an increase in surface air temperature and downward longwave radiation results in an increase in the upper-ocean temperature and a decrease in sea ice growth, leading to a decrease in salt rejection from ice, in the upper-ocean salinity, and in the upper-ocean density. The reduced salt rejection and upper-ocean density and the enhanced thermohaline stratification tend to suppress convective overturning, leading to a decrease in the upward ocean heat transport and the ocean heat flux available to melt sea ice. The ice melting from ocean heat flux decreases faster than the ice growth does in the weakly stratified Southern Ocean, leading to an increase in the net ice production and hence an increase in ice mass. This mechanism is the main reason why the Antarctic sea ice has increased in spite of warming conditions both above and below during the period 1979–2004 and the extended period 1948–2004.” [Full text]

Variability of Antarctic sea ice 1979–1998 – Zwally et al. (2002) “The principal characteristics of the variability of Antarctic sea ice cover as previously described from satellite passive microwave observations are also evident in a systematically calibrated and analyzed data set for 20.2 years (1979–1998). The total Antarctic sea ice extent (concentration >15%) increased by 11,180 ± 4190 km2 yr-1 (0.98 ± 0.37% (decade)-1). The increase in the area of sea ice within the extent boundary is similar (10,860 ± 3720 km2 yr-1 and 1.26 ± 0.43% (decade)-1).”

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Papers on cloud feedback observations

Posted by Ari Jokimäki on October 26, 2009

This is a list of papers on cloud feedback observations. Note that most papers listed are local analyses. The list is not complete, and will most likely be updated in the future in order to make it more thorough and more representative.

UPDATES: (August 16, 2021) Ceppi & Nowack (2021) added – thanks to climafuturo for pointing it out. (September 12, 2016): Norris et al. (2016) added. (April 3, 2012): Zelinka & Hartmann (2010) and Gehlot & Quaas (2012) added – thanks to Barry for pointing them out. (December 10, 2010): Dessler (2010) added. (December 6, 2010): Palm et al. (2010) added.

Observational evidence that cloud feedback amplifies global warming – Ceppi & Nowack (2021) “Global warming drives changes in Earth’s cloud cover, which, in turn, may amplify or dampen climate change. This “cloud feedback” is the single most important cause of uncertainty in Equilibrium Climate Sensitivity (ECS)—the equilibrium global warming following a doubling of atmospheric carbon dioxide. Using data from Earth observations and climate model simulations, we here develop a statistical learning analysis of how clouds respond to changes in the environment. We show that global cloud feedback is dominated by the sensitivity of clouds to surface temperature and tropospheric stability. Considering changes in just these two factors, we are able to constrain global cloud feedback to 0.43 ± 0.35 W⋅m−2⋅K−1 (90% confidence), implying a robustly amplifying effect of clouds on global warming and only a 0.5% chance of ECS below 2 K. We thus anticipate that our approach will enable tighter constraints on climate change projections, including its manifold socioeconomic and ecological impacts.” Paulo Ceppi, Peer Nowack, PNAS July 27, 2021 118 (30) e2026290118;

Evidence for climate change in the satellite cloud record – Norris et al. (2016) “Clouds substantially affect Earth’s energy budget by reflecting solar radiation back to space and by restricting emission of thermal radiation to space. They are perhaps the largest uncertainty in our understanding of climate change, owing to disagreement among climate models and observational datasets over what cloud changes have occurred during recent decades and will occur in response to global warming. This is because observational systems originally designed for monitoring weather have lacked sufficient stability to detect cloud changes reliably over decades unless they have been corrected to remove artefacts. Here we show that several independent, empirically corrected satellite records exhibit large-scale patterns of cloud change between the 1980s and the 2000s that are similar to those produced by model simulations of climate with recent historical external radiative forcing. Observed and simulated cloud change patterns are consistent with poleward retreat of mid-latitude storm tracks, expansion of subtropical dry zones, and increasing height of the highest cloud tops at all latitudes. The primary drivers of these cloud changes appear to be increasing greenhouse gas concentrations and a recovery from volcanic radiative cooling. These results indicate that the cloud changes most consistently predicted by global climate models are currently occurring in nature.” Joel R. Norris, Robert J. Allen, Amato T. Evan, Mark D. Zelinka, Christopher W. O’Dell & Stephen A. Klein, Nature 536, 72–75 (04 August 2016) doi:10.1038/nature18273.

Convection-climate feedbacks in the ECHAM5 general circulation model: Evaluation of cirrus cloud life cycles with ISCCP satellite data from a Lagrangian trajectory perspective – Gehlot & Quaas (2012) “A process-oriented climate model evaluation is presented, applying the International Satellite Cloud Climatology Project (ISCCP) simulator to pinpoint deficiencies related to the cloud processes in the ECHAM5 general circulation model. A Lagrangian trajectory analysis is performed to track the transitions of anvil cirrus originating from deep-convective detrainment to cirrostratus and thin cirrus, comparing ISCCP observations and the ECHAM5 model. Trajectories of cloudy air parcels originating from deep convection are computed for both, the ISCCP observations and the model, over which the ISCCP joint histograms are used for analyzing the cirrus life cycle over 5 days. The clouds originating from detrainment from deep-convection decay and gradually thin-out after the convective event over 3 to 4 days. The effect of the convection-cirrus transitions in a warmer climate is analyzed, in order to understand the climate feedbacks due to deep-convective cloud transitions. An idealized climate change simulation is performed using a +2K Sea Surface Temperature (SST) perturbation. The Lagrangian trajectory analysis over perturbed climate suggests that more and thicker cirrostratus and cirrus clouds occur in the warmer climate compared to the present day climate. Stronger convection is noticed in the perturbed climate which leads to an increased precipitation, especially on day-2 and -3 after the individual convective events. The shortwave and the longwave cloud forcings both increase in the warmer climate, with an increase of net cloud radiative forcing (NCRF), leading to an overall positive feedback of the increased cirrostratus and cirrus clouds from a Lagrangian transition perspective.” Swati Gehlot and Johannes Quaas, Journal of Climate 2012.

Why is longwave cloud feedback positive? – Zelinka & Hartmann (2010) “Longwave cloud feedback is systematically positive and nearly the same magnitude across all global climate models used in the Intergovernmental Panel on Climate Change Fourth Assessment Report (AR4). Here it is shown that this robust positive longwave cloud feedback is caused in large part by the tendency for tropical high clouds to rise in such a way as to remain at nearly the same temperature as the climate warms. Furthermore, it is shown that such a cloud response to a warming climate is consistent with well-known physics, specifically the requirement that, in equilibrium, tropospheric heating by convection can only be large in the altitude range where radiative cooling is efficient, following the fixed anvil temperature hypothesis of Hartmann and Larson (2002). Longwave cloud feedback computed assuming that high-cloud temperature follows upper tropospheric convergence-weighted temperature, which we refer to as proportionately higher anvil temperature, gives an excellent prediction of the longwave cloud feedback in the AR4 models. The ensemble-mean feedback of 0.5 W m−2 K−1 is much larger than that calculated assuming clouds remain at fixed pressure, highlighting the large contribution from rising cloud tops to the robustly positive feedback. An important result of this study is that the convergence profile computed from clear-sky energy and mass balance warms slightly as the climate warms, in proportion to the increase in stability, which results in a longwave cloud feedback that is slightly smaller than that calculated assuming clouds remain at fixed temperature.” Zelinka, M. D., and D. L. Hartmann (2010), Why is longwave cloud feedback positive?, J. Geophys. Res., 115, D16117, doi:10.1029/2010JD013817. [Full text]

A Determination of the Cloud Feedback from Climate Variations over the Past Decade – Dessler (2010) “Estimates of Earth’s climate sensitivity are uncertain, largely because of uncertainty in the long-term cloud feedback. I estimated the magnitude of the cloud feedback in response to short-term climate variations by analyzing the top-of-atmosphere radiation budget from March 2000 to February 2010. Over this period, the short-term cloud feedback had a magnitude of 0.54 ± 0.74 (2σ) watts per square meter per kelvin, meaning that it is likely positive. A small negative feedback is possible, but one large enough to cancel the climate’s positive feedbacks is not supported by these observations. Both long- and short-wave components of short-term cloud feedback are also likely positive. Calculations of short-term cloud feedback in climate models yield a similar feedback. I find no correlation in the models between the short- and long-term cloud feedbacks.” A. E. Dessler, Science 10 December 2010, Vol. 330 no. 6010 pp. 1523-1527, DOI: 10.1126/science.1192546.

Influence of Arctic sea ice extent on polar cloud fraction and vertical structure and implications for regional climate – Palm et al. (2010) “Recent satellite lidar measurements of cloud properties spanning a period of 5 years are used to examine a possible connection between Arctic sea ice amount and polar cloud fraction and vertical distribution. We find an anticorrelation between sea ice extent and cloud fraction with maximum cloudiness occurring over areas with little or no sea ice. We also find that over ice-free regions, there is greater low cloud frequency and average optical depth. Most of the optical depth increase is due to the presence of geometrically thicker clouds over water. In addition, our analysis indicates that over the last 5 years, October and March average polar cloud fraction has increased by about 7% and 10%, respectively, as year average sea ice extent has decreased by 5%–7%. The observed cloud changes are likely due to a number of effects including, but not limited to, the observed decrease in sea ice extent and thickness. Increasing cloud amount and changes in vertical distribution and optical properties have the potential to affect the radiative balance of the Arctic region by decreasing both the upwelling terrestrial longwave radiation and the downward shortwave solar radiation. Because longwave radiation dominates in the long polar winter, the overall effect of increasing low cloud cover is likely a warming of the Arctic and thus a positive climate feedback, possibly accelerating the melting of Arctic sea ice.” [Conference article (use the “extended abstract” link)]

Observational and Model Evidence for Positive Low-Level Cloud Feedback – Clement et al. (2009) “Feedbacks involving low-level clouds remain a primary cause of uncertainty in global climate model projections. This issue was addressed by examining changes in low-level clouds over the Northeast Pacific in observations and climate models. Decadal fluctuations were identified in multiple, independent cloud data sets, and changes in cloud cover appeared to be linked to changes in both local temperature structure and large-scale circulation. This observational analysis further indicated that clouds act as a positive feedback in this region on decadal time scales. … The only model that passed this test simulated a reduction in cloud cover over much of the Pacific when greenhouse gases were increased, providing modeling evidence for a positive low-level cloud feedback.” [Full text]

Cloud forcing and feedback during recent Arctic sea ice loss – Kay et al. (2009) “Recent impressive declines in Arctic sea ice extent provide new opportunities to assess the influence of cloud forcing and feedbacks on sea ice loss in observations and models. … Our results indicate large-scale atmospheric circulation patterns and sea surface temperatures primarily controlled Arctic cloud forcing. Cloud feedback on sea ice extent loss is important because it can amplify or dampen ice loss processes. … We find that the observed cloud feedbacks are not well represented in either assimilation system. We explore reasons for incorrect model cloud feedbacks and the implications for the radiative forcing on projected sea ice loss.” [Presentation material]

Evaluation of Cloud Feedback at Local Scale: Warming or Cooling? – Malek (2009) A conference paper. “To evaluate cloudiness and its feedback at local scale, a radiation station was set up, which used two CM21 Kipp & Zonen pyranometers (one inverted), and two CGI Kipp & Zonen pyrgeometers (one inverted) in Logan, Utah, USA. … As shown, due to cloudiness at the experimental site, the net radiation loss was 2791−3707 = −916 MJ m−2 y−1, which indicates cooler temperature and a negative feedback due to cloudiness.”

Cloud radiative forcing of subtropical low level clouds in global models – Karlsson et al. (2008) “Simulations of subtropical marine low clouds and their radiative properties by nine coupled ocean-atmosphere climate models participating in the fourth assesment report (AR4) of the intergovernmental panel on climate change (IPCC) are analyzed. Satellite observations of cloudiness and radiative fluxes at the top of the atmosphere (TOA) are utilized for comparison. … As a consequence of the combination of these two biases, this study suggests that all investigated models are likely to overestimate the radiative response to changes in low level subtropical cloudiness.”

Cloud Feedbacks in the Climate System: A Critical Review – Stephens (2005) A review article. “This paper offers a critical review of the topic of cloud–climate feedbacks and exposes some of the underlying reasons for the inherent lack of understanding of these feedbacks and why progress might be expected on this important climate problem in the coming decade. … Models provide the tool for diagnosing processes and quantifying feedbacks while observations provide the essential test of the model’s credibility in representing these processes. … Aspects of these parameterizations remain worrisome, containing levels of empiricism and assumptions that are hard to evaluate with current global observations. Clearly observationally based methods for evaluating cloud parameterizations are an important element in the road map to progress.” [Full text]

The Iris Hypothesis: A Negative or Positive Cloud Feedback? – Lin et al. (2002) “Using the Tropical Rainfall Measuring Mission (TRMM) satellite measurements over tropical oceans, this study evaluates the iris hypothesis recently proposed by Lindzen et al. that tropical upper-tropospheric anvils act as a strong negative feedback in the global climate system. The modeled radiative fluxes of Lindzen et al. are replaced by the Clouds and the Earth’s Radiant Energy System (CERES) directly observed broadband radiation fields. The observations show that the clouds have much higher albedos and moderately larger longwave fluxes than those assumed by Lindzen et al. As a result, decreases in these clouds would cause a significant but weak positive feedback to the climate system, instead of providing a strong negative feedback.” [Full text]

Influence of cloud feedback on annual variation of global mean surface temperature – Tsushima & Manabe (2001) “The goal of this study is to estimate the cloud radiative feedback effect on the annual variation of the global mean surface temperature using radiative flux data from the Earth Radiation Budget Experiment. We found that the influence of the cloud feedback upon the change of the global mean surface temperature is quite small, though the increase of the temperature is as much as 3.3 K from January to July. On a global scale, we found no significant relationship between either solar reflectivity of clouds or effective cloud top height and the annual cycle of surface temperature.” [Full text]

Cloud Feedbacks – Randall et al. (2000) A symposium paper. “The observational literature contains some evidence of cloud feedbacks on decadal time scales. Recent work shows that global atmospheric circulation models (AGCMs) are capable of simulating many observed fluctuations of cloudiness.” [Full text]

Interannual Variability in Stratiform Cloudiness and Sea Surface Temperature – Norris & Leovy (1994) “Long-term datasets of cloudiness and sea surface temperature (SST) from surface observations from 1952 to 1981 are used to examine interannual variations in MSC and SST. Linear correlations of anomalies in seasonal MSC amount with seasonal SST anomalies are negative and significant in midlatitude and eastern subtropical oceans, especially during summer. Significant negative correlations between SST and nimbostratus and nonprecipitating midlevel cloudiness are also observed at midlatitudes during summer, suggesting that summer storm tracks shift from year to year following year-to-year meridional shifts in the SST gradient. Over the 30-yr period, there are significant upward trends in MSC amount over the northern midlatitude oceans and a significant downward trend off the coast of California. The highest correlations and trends occur where gradients in MSC and SST are strongest.” [Full text]

Cirrus-cloud thermostat for tropical sea surface temperatures tested using satellite data – Fu et al. (1992) “Ramanathan and Collins have suggested cirrus clouds associated with tropical convection might act as a ‘thermostat’ to limit tropical sea surface temperatures (SSTs) to less than 305 K by shielding the ocean from sunlight. Here we use satellite radiance data to test this hypothesis. We find that changes in the properties of cirrus clouds do not seem to be related to changes in SSTs. During the 1987 El Niño event, large-scale perturbations to the radiative effects of cirrus clouds were controlled by changes in large-scale atmospheric circulation rather than directly by SSTs. If they are averaged over the entire tropical Pacific, increases in surface evaporative cooling are stronger than decreases in solar heating owing to cirrus cloud variations. Thus we conclude that there is no ‘cirrus cloud thermostat’ to tropical SSTs.” [Full text]

Thermodynamic regulation of ocean warming by cirrus clouds deduced from observations of the 1987 El Niño – Ramanathan & Collins (1991) “Observations made during the 1987 El Niño show that in the upper range of sea surface temperatures, the greenhouse effect increases with surface temperature at a rate which exceeds the rate at which radiation is being emitted from the surface. In response to this ‘super greenhouse effect’, highly reflective cirrus clouds are produced which act like a thermostat shielding the ocean from solar radiation. The regulatory effect of these cirrus clouds may limit sea surface temperatures to less than 305 K.” [Full text]

Closely related

Papers on global cloud cover trends
Papers on the albedo of the Earth

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Papers on models vs. observations

Posted by Ari Jokimäki on October 23, 2009

This is a list of papers that compare climate model simulations to real world observations. Emphasis is on the global climate studies. The list is not complete, and will most likely be updated in the future in order to make it more thorough and more representative.

UPDATE (November 19, 2015): Ramanathan & Coakley (1978) added, thanks to Barry for pointing it out, in the Earth’s radiation budget list
UPDATE (July 24, 2013): Rahmstorf et al. (2012) added.
UPDATE (October 25, 2009): Hansen et al. (1988) and Hansen et al. (2006) added, thanks to PeterPan for pointing it out, see the discussion section below.
UPDATE (October 23, 2009): Rahmstorf et al. (2007) added, thanks to PeterPan for pointing it out, see the discussion section below.

Comparing climate projections to observations up to 2011 – Rahmstorf et al. (2012) “We analyse global temperature and sea-level data for the past few decades and compare them to projections published in the third and fourth assessment reports of the Intergovernmental Panel on Climate Change (IPCC). The results show that global temperature continues to increase in good agreement with the best estimates of the IPCC, especially if we account for the effects of short-term variability due to the El Niño/Southern Oscillation, volcanic activity and solar variability. The rate of sea-level rise of the past few decades, on the other hand, is greater than projected by the IPCC models. This suggests that IPCC sea-level projections for the future may also be biased low.” Stefan Rahmstorf et al 2012 Environ. Res. Lett. 7 044035 doi:10.1088/1748-9326/7/4/044035. [Full text]

How natural and anthropogenic influences alter global and regional surface temperatures: 1889 to 2006 – Lean & Rind (2008) “To distinguish between simultaneous natural and anthropogenic impacts on surface temperature, regionally as well as globally, we perform a robust multivariate analysis using the best available estimates of each together with the observed surface temperature record from 1889 to 2006. The results enable us to compare, for the first time from observations, the geographical distributions of responses to individual influences consistent with their global impacts.” [Full text]

Climate simulations for 1880-2003 with GISS modelE – Hansen et al. (2007) “We compare side-by-side simulated climate change for each forcing, all forcings, observations, unforced variability among model ensemble members, and, if available, observed variability. Discrepancies between observations and simulations with all forcings are due to model deficiencies, inaccurate or incomplete forcings, and imperfect observations. Although there are notable discrepancies between model and observations, the fidelity is sufficient to encourage use of the model for simulations of future climate change.” [Full text, size of the file is over 20 MB]

Recent Climate Observations Compared to Projections – Rahmstorf et al. (2007) “We present recent observed climate trends for carbon dioxide concentration, global mean air temperature, and global sea level, and we compare these trends to previous model projections as summarized in the 2001 assessment report of the Intergovernmental Panel on Climate Change (IPCC). … The data available for the period since 1990 raise concerns that the climate system, in particular sea level, may be responding more quickly to climate change than our current generation of models indicates.” [Full text]

Present-Day Atmospheric Simulations Using GISS ModelE: Comparison to In Situ, Satellite, and Reanalysis Data – Schmidt et al. (2006) “The performance of the model using three configurations with different horizontal and vertical resolutions is compared to quality-controlled in situ data, remotely sensed and reanalysis products. Overall, significant improvements over previous models are seen, particularly in upper-atmosphere temperatures and winds, cloud heights, precipitation, and sea level pressure.” [Full text]

Global temperature change – Hansen et al. (2006) Compares the model projections of Hansen et al. (1988) to observations. “Global surface temperature has increased ≈0.2°C per decade in the past 30 years, similar to the warming rate predicted in the 1980s in initial global climate model simulations with transient greenhouse gas changes.” [Full text]

Assessment of Twentieth-Century Regional Surface Temperature Trends Using the GFDL CM2 Coupled Models – Knutson et al. (2006) “Historical climate simulations of the period 1861–2000 using two new Geophysical Fluid Dynamics Laboratory (GFDL) global climate models (CM2.0 and CM2.1) are compared with observed surface temperatures. … Observed warming trends on the global scale and in many regions are simulated more realistically in the all-forcing and anthropogenic-only forcing runs than in experiments using natural-only forcing or no external forcing.” [Full text]

Transient Climate Simulations with the HadGEM1 Climate Model: Causes of Past Warming and Future Climate Change – Stott et al. (2006) “The ability of climate models to simulate large-scale temperature changes during the twentieth century when they include both anthropogenic and natural forcings and their inability to account for warming over the last 50 yr when they exclude increasing greenhouse gas concentrations has been used as evidence for an anthropogenic influence on global warming. One criticism of the models used in many of these studies is that they exclude some forcings of potential importance, notably from fossil fuel black carbon, biomass smoke, and land use changes. Herein transient simulations with a new model, the Hadley Centre Global Environmental Model version 1 (HadGEM1), are described, which include these forcings in addition to other anthropogenic and natural forcings, and a fully interactive treatment of atmospheric sulfur and its effects on clouds. These new simulations support previous work by showing that there was a significant anthropogenic influence on near-surface temperature change over the last century. They demonstrate that black carbon and land use changes are relatively unimportant for explaining global mean near-surface temperature changes.” [Full text]

Combinations of Natural and Anthropogenic Forcings in Twentieth-Century Climate – Meehl et al. (2004) “The late-twentieth-century warming can only be reproduced in the model with anthropogenic forcing (mainly GHGs), while the early twentieth-century warming is mainly caused by natural forcing in the model (mainly solar).” [Full text]

Forty years of numerical climate modelling – McGuffie & Henderson-Sellers (2001) A review article. “This paper discusses some of the important developments during the first 40 years of climate modelling from the first models of the global atmosphere to today’s models, which typically consist of integrated multi-component representations of the full climate system.” [Full text]

Causes of Climate Change Over the Past 1000 Years – Crowley (2000) “Recent reconstructions of Northern Hemisphere temperatures and climate forcing over the past 1000 years allow the warming of the 20th century to be placed within a historical context and various mechanisms of climate change to be tested. Comparisons of observations with simulations from an energy balance climate model indicate that as much as 41 to 64% of preanthropogenic (pre-1850) decadal-scale temperature variations was due to changes in solar irradiance and volcanism. … Removal of all forcing except greenhouse gases from the ~1000-year time series results in a residual with a very large late-20th-century warming that closely agrees with the response predicted from greenhouse gas forcing.” [Full text]

The impact of new physical parametrizations in the Hadley Centre climate model: HadAM3 – Pope et al. (2000) “The work covers three aspects of model performance: (1) it shows the improvements in the mean climate in changing from HadAM2b to HadAM3; (2) it demonstrates that the model now compares well with observations and (3) it isolates the impacts of new physical parametrizations.” [Full text]

Climate simulations with the global coupled atmosphere-ocean model ECHAM2/OPYC Part I: present-day climate and ENSO events – Lunkeit et al. (1996) “In this study the global coupled atmosphere-ocean general circulation model ECHAM2/OPYC and its performance in simulating the present-day climate is presented. … The coupled model simulates a realistic mean climate state, which is close to the observations.” [Full text]

Global Climate Changes as Forecast by Goddard Institute for Space Studies Three-Dimensional Model – Hansen et al. (1988) The classic paper that made very accurate global temperature projections by model runs but they also compared the runs with the existing observations. Comparison with existing observations is in a siderole in this paper, though, but there is a reasonable match with observations and model runs (obviously there are some differences as all model runs had at that time). “We use a three-dimensional climate model, the Goddard Institute for Space Studies (GISS) model II with 8° by 10° horizontal resolution, to simulate the global climate effects of time-dependent variations of atmospheric trace gases and aerosols.” [Full text]

Sensitivity of a Global Climate Model to an Increase of CO2 Concentration in the Atmosphere – Manabe & Stouffer (1980) “This study investigates the response of a global model of the climate to the quadrupling of the CO2 concentration in the atmosphere. … It is found that with some exceptions, the model succeeds in reproducing the large-scale characteristics of seasonal and geographical variation of the observed atmospheric temperature.” [Full text]

Climate modeling through radiative-convective models – Ramanathan & Coakley (1978)
Abstract: “We present a review of the radiative-convective models that have been used in studies pertaining to the earth’s climate. After familiarizing the reader with the theoretical background, modeling methodology, and techniques for solving the radiative transfer equation the review focuses on the published model studies concerning global climate and global climate change. Radiative-convective models compute the globally and seasonally averaged surface and atmospheric temperatures. The computed temperatures are in good agreement with the observed temperatures. The models include the important climatic feedback mechanism between surface temperature and H2O amount in the atmosphere. The principal weakness of the current models is their inability to simulate the feedback mechanism between surface temperature and cloud cover. It is shown that the value of the critical lapse rate adopted in radiative-convective models for convective adjustment is significantly larger than the observed globally averaged tropospheric lapse rate. The review also summarizes radiative-convective model results for the sensitivity of surface temperature to perturbations in (1) the concentrations of the major and minor optically active trace constituents, (2) aerosols, and (3) cloud amount. A simple analytical model is presented to demonstrate how the surface temperature in a radiative-convective model responds to perturbations.”
Ramanathan, V., and J. A. Coakley Jr. (1978), Climate modeling through radiative-convective models, Rev. Geophys., 16(4), 465–489, doi:10.1029/RG016i004p00465. [Full text}

Climate Calculations with a Combined Ocean-Atmosphere Model – Manabe & Bryan (1969) The first combined atmosphere-ocean model. “It is hoped that the experience gained in this preliminary study will be useful in planning and carrying out more extensive climatic calculations in the near future.” [Full text]

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Papers on aerosol forcing observations

Posted by Ari Jokimäki on October 20, 2009

This is a list of papers about aerosol forcing observations with an emphasis to global estimates. The list is not complete, and will most likely be updated in the future in order to make it more thorough and more representative.

Consistency Between Satellite-Derived and Modeled Estimates of the Direct Aerosol Effect – Myhre (2009) “This study demonstrates consistency between a global aerosol model and adjustment to an observation-based method, producing a global and annual mean radiative forcing that is weaker than –0.5 W m-2, with a best estimate of –0.3 W m-2. The physical explanation for the earlier discrepancy is that the relative increase in anthropogenic black carbon (absorbing aerosols) is much larger than the overall increase in the anthropogenic abundance of aerosols.” [Full text]

Global aerosol climatology from the MODIS satellite sensors – Remer et al. (2008) “The recently released Collection 5 Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol products provide a consistent record of the Earth’s aerosol system. Comparing with ground-based AERONET observations of aerosol optical depth (AOD) we find that Collection 5 MODIS aerosol products estimate AOD to within expected accuracy more than 60% of the time over ocean and more than 72% of the time over land. … However, the new collection introduces a 0.015 offset between the Terra and Aqua global mean AOD over ocean, where none existed previously. Aqua conforms to previous values and expectations while Terra is higher than what had been expected. The cause of the offset is unknown, but changes to calibration are a possible explanation.” [Full text]

Satellite-based estimate of the direct and indirect aerosol climate forcing – Quaas et al. (2008) “We develop a new methodology to derive a measurement-based estimate using almost exclusively information from an Earth radiation budget instrument (CERES) and a radiometer (MODIS). We derive a statistical relationship between planetary albedo and cloud properties, and, further, between the cloud properties and column aerosol concentration. Combining these relationships with a data set of satellite-derived anthropogenic aerosol fraction, we estimate an anthropogenic radiative forcing of −0.9 ± 0.4 Wm-2 for the aerosol direct effect and of −0.2 ± 0.1 Wm-2 for the cloud albedo effect.” [Full text]

Satellite-based assessment of top of atmosphere anthropogenic aerosol radiative forcing over cloud-free oceans – Christopher et al. (2006) “Here, by combining MODIS narrowband measurements with broadband radiative flux data sets from the Clouds and the Earth’s Radiant Energy System (CERES), we provide a measurement-based assessment of the global direct climate forcing (DCF) of anthropogenic aerosols at the top of atmosphere (TOA) only for cloud free oceans. The mean TOA DCF of anthropogenic aerosols over cloud-free oceans [60N–60S] is −1.4 ± 0.9 Wm-2, which is in excellent agreement (mean value of −1.4 Wm-2) with a recent observational study by Kaufman et al. [2005].” [Full text]

A review of measurement-based assessment of aerosol direct radiative effect and forcing – Yu et al. (2006) “In recent years, a great deal of effort has gone into improving measurements and datasets. It is thus feasible to shift the estimates of aerosol forcing from largely model-based to increasingly measurement-based. Here we assess the aerosol optical depth, direct radiative effect (DRE) by natural and anthropogenic aerosols, and direct climate forcing (DCF) by anthropogenic aerosols, focusing on satellite and ground-based measurements supplemented by global chemical transport model (CTM) simulations. … Despite these achievements, a number of issues remain open and more efforts are required to address them. Current estimates of the aerosol direct effect over land are poorly constrained.” [Full text]

Aerosol anthropogenic component estimated from satellite data – Kaufman et al. (2005) “Satellite instruments do not measure the aerosol chemical composition needed to discriminate anthropogenic from natural aerosol components. However the ability of new satellite instruments to distinguish fine (submicron) from coarse (supermicron) aerosols over the oceans, serves as a signature of the anthropogenic component and can be used to estimate the fraction of anthropogenic aerosols with an uncertainty of ±30%. Application to two years of global MODIS data shows that 21 ± 7% of the aerosol optical thickness over the oceans has an anthropogenic origin. We found that three chemical transport models, used for global estimates of the aerosol forcing of climate, calculate a global average anthropogenic optical thickness over the ocean between 0.030 and 0.036, in line with the present MODIS assessment of 0.033. This increases our confidence in model assessments of the aerosol direct forcing of climate. The MODIS estimated aerosol forcing over cloud free oceans is therefore −1.4 ± 0.4 W/m2.” [Full text]

Global anthropogenic aerosol direct forcing derived from satellite and ground-based observations – Chung et al. (2005) “A global estimate of the direct effects of anthropogenic aerosols on solar radiation in cloudy skies is obtained by integrating satellite and ground-based observations with models of aerosol chemistry, transport, and radiative transfer. The models adopt global distribution of aerosol optical depths (from MODIS), clouds, water vapor, ozone, and surface albedo from various satellite climatology. … The global annual mean direct forcing is −0.35 Wm-2 (range of −0.6 to −0.1 Wm-2) at the top-of-the atmosphere (TOA), +3.0 Wm-2 (range of +2.7 to +3.3Wm-2) in the atmosphere, and −3.4 Wm-2 (range of −3.5 to −3.3 Wm-2) at the surface. … Another major finding of this study is that the reduction in the surface solar radiation is a factor of 10 larger than the reduction in net solar (down minus up) radiation at TOA.” [Full text]

Global estimate of aerosol direct radiative forcing from satellite measurements – Bellouin et al. (2005) “Here we use state-of-the-art satellite-based measurements of aerosols and surface wind speed to estimate the clear-sky direct radiative forcing for 2002, incorporating measurements over land and ocean. … Probability density functions obtained for the direct radiative forcing at the top of the atmosphere give a clear-sky, global, annual average of -1.9 W m-2 with standard deviation, ± 0.3 W m-2. These results suggest that present-day direct radiative forcing is stronger than present model estimates, implying future atmospheric warming greater than is presently predicted, as aerosol emissions continue to decline10.” [Full text]

Climate Forcing by Aerosols–a Hazy Picture – Anderson et al. (2003) “Anthropogenic aerosol emissions are believed to have counteracted the global-warming effect of greenhouse gases over the past century. However, the magnitude of this cooling effect is highly uncertain. In their Perspective, Anderson et al. argue that the magnitude and uncertainty of aerosol forcing may be larger than is usually considered in models.” [Full text]

Large differences in tropical aerosol forcing at the top of the atmosphere and Earth’s surface – Satheesh & Ramanathan (2000) “Here we present an observational method for quantifying aerosol forcing to within ± 5 per cent. We use calibrated satellite radiation measurements and five independent surface radiometers to quantify the aerosol forcing simultaneously at the Earth’s surface and the top of the atmosphere over the tropical northern Indian Ocean. … Accordingly, mean clear-sky solar radiative heating for the winters of 1998 and 1999 decreased at the ocean surface by 12 to 30 W m-2, but only by 4 to 10 W m-2 at the top of the atmosphere. This threefold difference (due largely to solar absorption by soot) and the large magnitude of the observed surface forcing both imply that tropical aerosols might slow down the hydrological cycle.”

Direct radiative forcing by anthropogenic airborne mineral aerosols – Sokolik & Toon (1996) “The effects of mineral aerosols on the radiation budget are important relative to those of other types of aerosols—such as sulphate and smoke particles—due to the widespread distribution and large optical depth of mineral dust. … Here we use estimates of anthropogenic dust inputs and observations of dust optical properties to show that although the key quantities contributing to the evaluation of the direct solar radiative forcing by dust generated through human activities have a wide range of uncertainty, the forcing by anthropogenically generated mineral aerosols may be comparable to the forcing by other anthropogenic aerosols.”

Atmospheric transmission at Davos, Switzerland 1909–1979 – Hoyt & Fröhlich (1983) “Pyrheliometric measurements at Davos, Switzerland from 1909 to 1979 are used to reconstruct the time history of atmospheric transmission. Measurements were numerous enough to allow yearly and seasonal values of atmospheric transmission to be determined. Other than the eruptions of Katmai in 1912 and Agung in 1963, there are no significant long-term changes in atmospheric transmission observed at this central European site.”

Posted in AGW evidence | 2 Comments »

Timing of carbon dioxide and temperature in Vostok ice core

Posted by Ari Jokimäki on October 17, 2009

It is well known that carbon dioxide (CO2) concentration generally lags temperature in Vostok ice core records, see for example papers listed here. Some time ago I was writing another post that used Vostok ice core records and I decided to check how was the timing of the peaks seen there (data for CO2 is here and for temperature here). I also checked the timing of the “valleys”. Figure 1 shows the peaks I checked marked with letters and valleys marked with numbers. I checked pretty much all the peaks that are seen, but in the case of valleys there were lot of difficulty to find corresponding minimums so I ended up checking only ten most obvious ones. In my analysis, in order to avoid cherry picking accusations, I have generally favoured temperature leading, so that when there’s uncertainty about exact peak/valley timing, I have selected the one that favours the earlier peaking of temperature. See the appendix for notes on individual peaks and valleys.

Figure 1. The Vostok ice core records for carbon dioxide concentration and temperature with peaks and valleys marked as explained in text. Data for temperature is from here and for carbon dioxide from here. Temperature values has been scaled (T’ = T * 10 + 200) to show up more clearly in combined view of the two. It makes no difference because it is the timing we are interested here and the timing is not affected by the scaling.

Timing of the peaks and valleys

Table 1 presents the timing of the peaks in CO2 and temperature, and their difference (in years so that present = 0):

    Name CO2 (earliest...latest)      T (earliest...latest)        Difference (Min...Max)
    A    -415434 (-417160...-414085)  -410483 (-417969...-409995)  4951 (-3884...7165)
    B    -384909 (-386579...-383504)  -383641 (-384159...-383134)  1268 (-655...3445)
    D    -342998 (-344735...-340165)  -341930 (-342401...-341462)  1068 (-2236...3273)
    E    -323485 (-324189...-322827)  -322638 (-323695...-322426)  847 (-868...1763)
    F    -303953 (-304590...-303334)  -303316 (-303558...-303077)  637 (-224...1513)
    G    -292474 (-293002...-291769)  -292732 (-292976...-292490)  -258 (-1207...512)
    H    -277298 (-277925...-275218)  -276830 (-277036...-276622)  468 (-1818...1303)
    J    -255233 (-256053...-253880)  -254767 (-254972...-254560)  466 (-1092...1493)
    K    -238199 (-238935...-237831)  -237975 (-238084...-237866)  224 (-253...1069)
    L    -212281 (-217271...-211929)  -217244 (-217356...-217131)  -4963 (-5427...140)
    M    -202212 (-203191...-199025)  -202169 (-202275...-202065)  43 (-3250...1126)
    N    -191057 (-191592...-189335)  -190934 (-191043...-190822)  123 (-1708...770)
    O    -181617 (-182447...-180779)  -181382 (-181502...-181259)  235 (-723...1188)
    P    -169870 (-175440...-166299)  -169531 (-169638...-169425)  339 (-3339...6015)
    Q    -160494 (-161037...-155707)  -159548 (-159651...-159444)  946 (-3944...1593)
    R    -149157 (-150303...-145435)  -150972 (-151076...-150868)  -1815 (-5641...-565)
    S    -128399 (-128652...-128300)  -128357 (-128405...-128309)  42 (-105...343)
    U    -84929 (-85727...-82858)     -84576 (-84638...-84515)     353 (-1780...1212)
    V    -57068 (-57799...-51174)     -57289 (-57362...-57215)     -221 (-6188...584)
    W    -49414 (-51174...-48229)     -51159 (-51230...-51086)     -1745 (-3001..88)
    X    -39880 (-44766...-27062)     -42225 (-42298...-42152)     -2345 (-15236...2614)

Positive difference means that CO2 leads. 15 peaks out of 21 have positive nominal difference, so 71 ± 10 % of the peaks seem to be lead by CO2. However, note that none of the peaks have positive minimum difference, so in strict interpretation we can not claim for sure any of the individual peaks to show CO2 leading. Note also that this is only very rough analysis, for example the uncertainties in age determinations have not been included here. However, uncertainties are expected to make the minimum-maximum difference bigger, so they would not change the nominal values.

What about valleys then? Table 2 presents the timing of the valleys in CO2 and temperature, and their difference (in years so that present = 0):

    Name CO2 (earliest...latest)      T (earliest...latest)        Difference (Min...Max)
    1    -354372 (-356838...-352412)  -353838 (-354400...-353273)  534 (-1988...3565)
    2    -333627 (-335290...-332293)  -333602 (-334101...-333106)  25 (-1808...2184)
    3    -280361 (-281200...-279543)  -281602 (-281875...-281332)  -1241 (-2332...-132)
    4    -257792 (-258477...-257247)  -262131 (-261865...-261865)  -4339 (-4618...-3388)
    5    -246090 (-247447...-245483)  -246917 (-247135...-246700)  -827 (-1652...747)
    6    -222958 (-223446...-221612)  -224351 (-224536...-224164)  -1393 (-2924...-718)
    7    -138226 (-139445...-137986)  -138193 (-138308...-138078)  33 (-322...1367)
    8    -89363 (-91691...-88051)     -90128 (-90209...-90048)     -765 (-2158...1643)
    9    -65701 (-66883...-63687)     -65756 (-65855...-65655)     -55 (-2168...1228)
    10   -17695 (-19988...-13989)     -19610 (-19696...-19525)     -1915 (-5707...463)

Valleys seem to be leaning towards temperature leading. 7 out of 10 valleys have negative difference, three of them even so that the maximum difference is also negative. 70 ± 15 % of the valleys seem therefore to be lead by temperature. However, even in valleys some minimums show CO2 leading in nominal values, although only one of them (valley 1) has substantial positive difference.

There is an interesting string of events, where CO2 seems to lead all the time: 354372 years ago, CO2 concentration started to increase (valley 1). Then, 534 years later (353838 years ago), temperature started to increase. Following that, 10840 years later (342998 years ago), CO2 concentration started to decrease (peak D), and 1068 years later (341930 years ago), temperature started to decrease. CO2 concentration started to increase again (valley 2) 8303 years later (333627 years ago), and 25 years later (333602 years ago), temperature started to increase. 10117 years later (323485 years ago), CO2 concentration started to decrease (peak E), and 847 years later (322638 years ago), temperature started to decrease.

Another, shorter string of events also shows CO2 leading whole time; in valley 7 CO2 leads by 33 years, and in the subsequent peak S, CO2 leads by 42 years. It needs to be noted, that these are of course very small time differences. However, another interesting thing here is that two largest climate changes seen in Vostok ice core, the change from valley 2 to peak E and the change from valley 7 to peak S both seem to have CO2 leading through the whole climate change.

Mean for the timing differences are 32 years in peaks and -994 years in valleys, but for three largest climate changes (peaks E, K, S and valleys 2, 5, 7) the mean is 371 years for peaks and -256 years for valleys. General picture seems to be that temperature starts the warming events, but CO2 then takes the lead and only when CO2 has started to decrease, temperature starts to cool.

Although all of this is very uncertain, at least next time when someone claims that CO2 always lags temperature in Vostok ice core records, you can wave this in front of them and ask: “are you sure?”

Appendix. Some notes on individual peaks and valleys


A – There is some uncertainty about where the corresponding peak of temperature is. Highest peak has been selected, but there is another, slightly earlier peak (max. at -417419) which would lead CO2 peak. Value for earliest peaking has been selected from this earlier peak.

B – Temperature is double-peaked. Earlier and higher peak has been selected.

C – It is very unclear what is the CO2 peak here. There are two minor peaks. Earlier one matches temporally much better (and leads temperature by about 700 years). Later peak is so much later (peaks almost 10000 years later than temperature peak) than temperature peak that it wouldn’t make sense as a matching peak. However, earlier peak is so small that it really isn’t much of a peak at all, so this whole entry has been rejected.

D – Both peaks are quite round.

E – Temperature peak is quite difficult. It first reaches a peak only 3 years later than CO2 peak but it then drops a bit and soon reaches even higher. Highest peak has been selected, but the value for earliest peaking has been selected from the earlier peak.

H – CO2 peak is quite wide but there doesn’t seem to be much question about the time of the maximum peak.

J – Temperature is double-peaked, earlier has been selected.

L – CO2 is double-peaked, higher and later has been selected. However, considering timing of other peaks, it would seem that the earlier peak would really be more correct here, so the value for earliest peaking has been taken from the earlier peak.

M – Temperature is double-peaked, earlier has been selected. Later peak would be about 900 years later than the CO2 peak.

O – Temperature is double-peaked, earlier has been selected. Later peak would be about 700 years later than the CO2 peak.

P – Temperature is double-peaked by quite wide margin, earlier has been selected. CO2 peak is very wide, possibly corresponding to both peaks of temperature. Whole width of the CO2 peak has been used in calculation.

Q – Temperature is double-peaked by quite wide margin, earlier has been selected.

R – Very minor peak. CO2 is double-peaked, higher and later has been selected.

T – No obvious CO2 peak is evident, so this entry has been rejected.

X – Temperature is double-peaked by quite wide margin, earlier has been selected. CO2 peak is very wide, possibly corresponding to both peaks of temperature. Whole width of the CO2 peak has been used in calculation.

Y – Temperature seems to peak here without corresponding peak in CO2, so this entry has been rejected.


1 – Temperature peak is quite wide.

4 – Both temperature and CO2 are double-peaked, later has been selected for both.

5 – Temperature is double-peaked. Later has been selected, because that’s when temperature really starts rising.

6 – Temperature is double-peaked. Later has been selected, because that’s when temperature really starts rising.

7 – CO2 is double-peaked. Later has been selected, because that’s when CO2 really starts rising.

10 – Temparture peak is wide and the lowest peak is much earlier than when the temperature actually starts to rise. The point where temperature starts to rise has been selected.

Posted in Climate claims | 4 Comments »

Papers on Earth’s radiation budget

Posted by Ari Jokimäki on October 16, 2009

This is a list of papers about Earth’s radiation budget as a whole. The list is not complete, and will most likely be updated in the future in order to make it more thorough and more representative.

UPDATE (July 7, 2021): Kramer et al. (2021) added.

UPDATE (November 1, 2009): Murphy et al. (2009) added, thanks to “qwerty” for pointing it out, see the discussion section below.

Observational Evidence of Increasing Global Radiative Forcing (Kramer et al. 2021). “We apply radiative kernels to satellite observations to disentangle these components and find all-sky instantaneous radiative forcing has increased 0.53 ± 0.11 W/m2 from 2003 to 2018, accounting for positive trends in the total planetary radiative imbalance. This increase has been due to a combination of rising concentrations of well-mixed greenhouse gases and recent reductions in aerosol emissions. These results highlight distinct fingerprints of anthropogenic activity in Earth’s changing energy budget, which we find observations can detect within 4 years.

An observationally based energy balance for the Earth since 1950 – Murphy et al. (2009) “We examine the Earth’s energy balance since 1950, identifying results that can be obtained without using global climate models. Important terms that can be constrained using only measurements and radiative transfer models are ocean heat content, radiative forcing by long-lived trace gases, and radiative forcing from volcanic eruptions. We explicitly consider the emission of energy by a warming Earth by using correlations between surface temperature and satellite radiant flux data and show that this term is already quite significant. About 20% of the integrated positive forcing by greenhouse gases and solar radiation since 1950 has been radiated to space. Only about 10% of the positive forcing (about 1/3 of the net forcing) has gone into heating the Earth, almost all into the oceans. About 20% of the positive forcing has been balanced by volcanic aerosols, and the remaining 50% is mainly attributable to tropospheric aerosols.”

Changes in the flow of energy through the Earth’s climate system – Trenberth & Fasullo (2009) “A review is given of the trends, variability, mean and annual cycle of energy flowing through the climate system, and its storage, release, and transport in the atmosphere, ocean, and land surface as estimated with recent observations, with some new updates using the latest datasets. The current imbalance in radiation at the top-of-atmosphere owing to human-induced increases in greenhouse gases means that the atmosphere, land and ocean are warming up, and ice is melting, leading to a rise in sea level. A discussion is given of our ability to track these changes with current observations and analyses.” [Link to PDF]

Toward Optimal Closure of the Earth’s Top-of-Atmosphere Radiation Budget – Loeb et al. (2009) “Despite recent improvements in satellite instrument calibration and the algorithms used to determine reflected solar (SW) and emitted thermal (LW) top-of-atmosphere (TOA) radiative fluxes, a sizeable imbalance persists in the average global net radiation at the TOA from satellite observations. … This study provides a detailed error analysis of TOA fluxes based on the latest generation of Clouds and the Earth’s Radiant Energy System (CERES) gridded monthly mean data products [the monthly TOA/surface averages geostationary (SRBAVG-GEO)] and uses an objective constrainment algorithm to adjust SW and LW TOA fluxes within their range of uncertainty to remove the inconsistency between average global net TOA flux and heat storage in the earth–atmosphere system.”

Earth’s Global Energy Budget – Trenberth et al. (2009) “An update is provided on the Earth’s global annual mean energy budget in the light of new observations and analyses.” [Link to PDF]

Reexamination of the Observed Decadal Variability of the Earth Radiation Budget Using Altitude-Corrected ERBE/ERBS Nonscanner WFOV Data – Wong et al. (2006) “With this final correction, the ERBS Nonscanner-observed decadal changes in tropical mean LW, SW, and net radiation between the 1980s and the 1990s now stand at 0.7, −2.1, and 1.4 W m−2, respectively, which are similar to the observed decadal changes in the High-Resolution Infrared Radiometer Sounder (HIRS) Pathfinder OLR and the International Satellite Cloud Climatology Project (ISCCP) version FD record but disagree with the Advanced Very High Resolution Radiometer (AVHRR) Pathfinder ERB record.” [Link to PDF]

The Geostationary Earth Radiation Budget Project – Harries et al. (2005) “GERB is designed to make the first measurements of the Earth’s radiation budget from geostationary orbit. Measurements at high absolute accuracy of the reflected sunlight from the Earth, and the thermal radiation emitted by the Earth are made every 15 min, with a spatial resolution at the subsatellite point of 44.6 km (north–south) by 39.3 km (east–west). With knowledge of the incoming solar constant, this gives the primary forcing and response components of the top-of-atmosphere radiation.” [Link to PDF]

Physics of the Earth’s radiative energy balance – Harries (2000) “Following an introduction to the basic physics of the energy balance and the greenhouse effect, a discussion is given of how the spectrum of outgoing thermal radiation (by which the planet cools to space) depends on internal parameters such as surface temperature and atmospheric humidity. This includes a discussion of the sign and magnitude of the water vapour-climate feedback, and the ‘super greenhouse effect’. It is shown that the role of cloud in the energy balance is extremely important, although poorly understood. Recent work to exploit the information contained in the resolved spectrum of outgoing longwave radiation (OLR) is described, including a new technique to search for the ‘signal’ of climate change within the ‘noise’ of natural climate fluctuations.”

Earth’s Annual Global Mean Energy Budget – Kiehl & Trenberth (1997) “The purpose of this paper is to put forward a new estimate, in the context of previous assessments, of the annual global mean energy budget. A description is provided of the source of each component to this budget. The top-of-atmosphere shortwave and longwave flux of energy is constrained by satellite observations. … The authors find that for the clear sky case the contribution due to water vapor to the total longwave radiative forcing is 75 W m-2, while for carbon dioxide it is 32 W m-2.” [Link to PDF]

The Nimbus Earth Radiation Budget (ERB) Experiment: 1975 to 1992 – Kyle et al. (1993) “Three spectrally broadband measurement sets are presently being used for earth radiation budget (ERB) studies. These are the Nimbus-6 ERB (July 1975 to June 1978), the Nimbus-7 ERB (November 1978 to the present), and the Earth Radiation Budget Experiment (ERBE) (November 1984 to present). … This report describes some successes and lessons learned during the Nimbus ERB program and the compatibility of the Nimbus and ERBE products.”

The Role of Earth Radiation Budget Studies in Climate and General Circulation Research – Ramanathan (1987) “Two decades of near-continuous measurements of earth radiation budget data from satellites have made significant contributions to our understanding of the global mean climate, the greenhouse effect, the meridional radiative heating that drives the general circulation, the influence of radiative heating on regional climate, and climate feedback processes. The remaining outstanding problems largely concern the role of clouds in governing climate, in influencing the general circulation, and in determining the sensitivity of climate to external perturbations, i.e., the so-called cloud feedback problem. In this paper a remarkably simple and effective approach is proposed to address these problems, with the aid of the comprehensive radiation budget data collected by the Earth Radiation Budget Experiment (ERBE).”

Satellite observations of the earth’s radiation budget components and the problem of the energetically active zones of the world ocean (EAZO) – Kondrat’ev & Kozoderov (1986) “The numerical models developed by Lappo et al. (1984) to describe the role of energy-active zones of the ocean (EAZOs) in short-term climatic changes are refined on the basis of satellite data on the earth radiation budget (ERB), with a focus on four North Atlantic EAZOs. The data are presented in graphs and maps, and consideration is given to annual changes in the mean-square deviation of the ERB, teleconnections between tropical and midlatitude ERB anomalies, and the effects of cloud cover on ERB. The data are found to confirm the importance of EAZOs for ERB changes, and global regions with major teleconnections to the tropical central Pacific region are shown to be closely related to EAZOs.”

The Earth Radiation Budget Experiment (ERBE) – Barkstrom (1984) “The Earth Radiation Budget Experiment (ERBE) is the first multi-satellite system designed to measure the Earth’s radiation budget. It will fly on a low-inclination NASA satellite and two Sun-synchronous NOAA satellites during the mid-1980s.”

The Earth Radiation Budget Derived From the NIMBUS 7 ERB Experiment – Jacobowitz & Tighe (1984) “The earth radiation budget as determined from the ERB experiment aboard the NIMBUS 7 polar-orbiting satellite is presented in the form of time-latitude cross sections, hemispherically and globally averaged time plots, and annual global averages for the time period spanning November 1978 through October 1979.”

The Earth Radiation Budget (ERB) Experiment: An Overview – Jacobowitz et al. (1984) “The development of ERB observational systems is traced from its beginnings in the late 1950’s through to the current ERB on the NIMBUS 7 satellite. The instruments comprising the current 22-channel ERB experiment are described in some detail.”

Measurements of the Earth’s Radiation Budget from Satellites During a Five-Year Period. Part I: Extended Time and Space Means – Vonder Haar & Suomi (1970) “This paper summarizes an extended time series of measurements of the earth’s radiation budget from the first and second generation United States meteorological satellites. Values of planetary albedo, infrared radiant emittance, and the resulting net radiation budget are now available for 39 months during the period 1962–66. These measurements show a mean global albedo of 30%, and net radiation balance within measurement accuracy.”

Satellite Observations of the Earth’s Radiation Budget – Vonder Haar & Suomi (1969) “Meteorological satellites have provided the first complete data on energy exchange between earth and space. The planetary albedo is 29 percent for the mean annual case, and the entire earth-atmosphere system is in near radiative equilibrium. More energy is absorbed in tropical regions than previously believed, and major energy source and sink regions exist within latitude belts.”

Posted in AGW evidence | 7 Comments »

Papers on water vapor feedback observations

Posted by Ari Jokimäki on October 13, 2009

This is a list of papers about the observations of the water vapor feedback. The list is not complete, and will most likely be updated in the future in order to make it more thorough and more representative.

UPDATE (February 14, 2018): Serreze et al. (2012) and Gordon et al. (2013) added and some dead links corrected.
UPDATE (March 29, 2012): Raval & Ramanathan (1989) and Yang & Tung (1998) added.
UPDATE (June 4, 2011): Paltridge et al. (2009) and Dessler & Davis (2010) added.
UPDATE (March 20, 2010): Held & Soden (2000) added.
UPDATE (December 9, 2009): Dessler & Wong (2009) added.
UPDATE (November 23, 2009): Wentz & Schabel (2000) and Wentz et al. (2007) added, and a broken link fixed. Thanks to PeterPan for pointing these out, see the comment section below.
UPDATE (November 6, 2009): Soden et al. (2002) and Soden et al. (2005) added. Thanks to PeterPan for pointing these out, see the comment section below.
UPDATE (October 30, 2009): Huang & Ramaswamy (2008) added.

An observationally based constraint on the water-vapor feedback – Gordon et al. (2013)
Abstract: The increase in atmospheric concentrations of water vapor with global warming is a large positive feedback in the climate system. Thus, even relatively small errors in its magnitude can lead to large uncertainties in predicting climate response to anthropogenic forcing. This study incorporates observed variability of water vapor over 2002–2009 from the Atmospheric Infrared Sounder instrument into a radiative transfer scheme to provide constraints on this feedback. We derive a short-term water vapor feedback of 2.2 ± 0.4 Wm−2K−1. Based on the relationship between feedback derived over short and long timescales in twentieth century simulations of 14 climate models, we estimate a range of likely values for the long-term twentieth century water vapor feedback of 1.9 to 2.8 Wm−2K−1. We use the twentieth century simulations to determine the record length necessary for the short-term feedback to approach the long-term value. In most of the climate models we analyze, the short-term feedback converges to within 15% of its long-term value after 25 years, implying that a longer observational record is necessary to accurately estimate the water vapor feedback.
Citation: Gordon, N. D., A. K. Jonko, P. M. Forster, and K. M. Shell (2013), An observationally based constraint on the water-vapor feedback, J. Geophys. Res. Atmos., 118, 12,435–12,443, doi:10.1002/2013JD020184. [Full text]

Recent changes in tropospheric water vapor over the Arctic as assessed from radiosondes and atmospheric reanalyses – Serreze et al. (2012)
Abstract: Changes in tropospheric water vapor over the Arctic are examined for the period 1979 to 2010 using humidity and temperature data from nine high latitude radiosonde stations north of 70°N with nearly complete records, and from six atmospheric reanalyses, emphasizing the three most modern efforts, MERRA, CFSR and ERA-Interim. Based on comparisons with the radiosonde profiles, the reanalyses as a group have positive cold-season humidity and temperature biases below the 850 hPa level and consequently do not capture observed low-level humidity and temperature inversions. MERRA has the smallest biases. Trends in column-integrated (surface to 500 hPa) water vapor (precipitable water) computed using data from the radiosondes and from the three modern reanalyses at the radiosonde locations are mostly positive, but magnitudes and statistical significance vary widely between sites and seasons. Positive trends in precipitable water from MERRA, CFSR and ERA-Interim, largest in summer and early autumn, dominate the northern North Atlantic, including the Greenland, Norwegian and Barents seas, the Canadian Arctic Archipelago and (on the Pacific side) the Beaufort and Chukchi seas. This pattern is linked to positive anomalies in air and sea surface temperature and negative anomalies in end-of-summer sea ice extent. Trends from ERA-Interim are weaker than those from either MERRA or CFSR. As assessed for polar cap averages (the region north of 70°N), MERRA, CFSR and ERA-Interim all show increasing surface-500 hPa precipitable over the analysis period encompassing most months, consistent with increases in 850 hPa air temperature and 850 hPa specific humidity. Data from all of the reanalyses point to strong interannual and decadal variability. The MERRA record in particular shows evidence of artifacts likely introduced by changes in assimilation data streams. A focus on the most recent decade (2001–2010) reveals large differences between the three reanalyses in the vertical structure of specific humidity and temperature anomalies.
Citation: Serreze, M. C., A. P. Barrett, and J. Stroeve (2012), Recent changes in tropospheric water vapor over the Arctic as assessed from radiosondes and atmospheric reanalyses, J. Geophys. Res., 117, D10104, doi:10.1029/2011JD017421. [Full text]

Trends in tropospheric humidity from reanalysis systems – Dessler & Davis (2010) “A recent paper (Paltridge et al., 2009) found that specific humidity in the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis declined between 1973 and 2007, particularly in the tropical mid and upper troposphere, the region that plays the key role in the water vapor feedback. If borne out, this result suggests potential problems in the consensus view of a positive water vapor feedback. Here we consider whether this result holds in other reanalyses and what time scale of climate fluctuation is associated with the negative specific humidity trends. The five reanalyses analyzed here (the older NCEP/NCAR and ERA40 reanalyses and the more modern Japanese Reanalysis (JRA), Modern Era Retrospective-Analysis for Research and Applications (MERRA), and European Centre for Medium-Range Weather Forecasts (ECMWF)-interim reanalyses) unanimously agree that specific humidity generally increases in response to short-term climate variations (e.g., El Niño). In response to decadal climate fluctuations, the NCEP/NCAR reanalysis is unique in showing decreases in tropical mid and upper tropospheric specific humidity as the climate warms. All of the other reanalyses show that decadal warming is accompanied by increases in mid and upper tropospheric specific humidity. We conclude from this that it is doubtful that these negative long-term specific humidity trends in the NCEP/NCAR reanalysis are realistic for several reasons. First, the newer reanalyses include improvements specifically designed to increase the fidelity of long-term trends in their parameters, so the positive trends found there should be more reliable than in the older reanalyses. Second, all of the reanalyses except the NCEP/NCAR assimilate satellite radiances rather than being solely dependent on radiosonde humidity measurements to constrain upper tropospheric humidity. Third, the NCEP/NCAR reanalysis exhibits a large bias in tropical upper tropospheric specific humidity. And finally, we point out that there exists no theoretical support for having a positive short-term water vapor feedback and a negative long-term one.” Dessler, A. E., and S. M. Davis (2010), J. Geophys. Res., 115, D19127, doi:10.1029/2010JD014192. [Full text]

Trends in middle- and upper-level tropospheric humidity from NCEP reanalysis data – Paltridge et al. (2009) “The National Centers for Environmental Prediction (NCEP) reanalysis data on tropospheric humidity are examined for the period 1973 to 2007. It is accepted that radiosonde-derived humidity data must be treated with great caution, particularly at altitudes above the 500 hPa pressure level. With that caveat, the face-value 35-year trend in zonal-average annual-average specific humidity q is significantly negative at all altitudes above 850 hPa (roughly the top of the convective boundary layer) in the tropics and southern midlatitudes and at altitudes above 600 hPa in the northern midlatitudes. It is significantly positive below 850 hPa in all three zones, as might be expected in a mixed layer with rising temperatures over a moist surface. The results are qualitatively consistent with trends in NCEP atmospheric temperatures (which must also be treated with great caution) that show an increase in the stability of the convective boundary layer as the global temperature has risen over the period. The upper-level negative trends in q are inconsistent with climate-model calculations and are largely (but not completely) inconsistent with satellite data. Water vapor feedback in climate models is positive mainly because of their roughly constant relative humidity (i.e., increasing q) in the mid-to-upper troposphere as the planet warms. Negative trends in q as found in the NCEP data would imply that long-term water vapor feedback is negative—that it would reduce rather than amplify the response of the climate system to external forcing such as that from increasing atmospheric CO2. In this context, it is important to establish what (if any) aspects of the observed trends survive detailed examination of the impact of past changes of radiosonde instrumentation and protocol within the various international networks.” Garth Paltridge, Albert Arking and Michael Pook, Theoretical and Applied Climatology, Volume 98, Numbers 3-4, 351-359, DOI: 10.1007/s00704-009-0117-x. [Full text]

Estimates of the Water Vapor Climate Feedback during El Niño–Southern Oscillation – Dessler & Wong (2009) “The strength of the water vapor feedback has been estimated by analyzing the changes in tropospheric specific humidity during El Niño–Southern Oscillation (ENSO) cycles. This analysis is done in climate models driven by observed sea surface temperatures [Atmospheric Model Intercomparison Project (AMIP) runs], preindustrial runs of fully coupled climate models, and in two reanalysis products, the 40-yr European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-40) and the NASA Modern Era Retrospective-Analysis for Research and Applications (MERRA). The water vapor feedback during ENSO-driven climate variations in the AMIP models ranges from 1.9 to 3.7 W m−2 K−1, in the control runs it ranges from 1.4 to 3.9 W m−2 K−1, and in the ERA-40 and MERRA it is 3.7 and 4.7 W m−2 K−1, respectively.”

Water-vapor climate feedback inferred from climate fluctuations, 2003–2008 – Dessler et al. (2008) “Between 2003 and 2008, the global-average surface temperature of the Earth varied by 0.6°C. We analyze here the response of tropospheric water vapor to these variations. Height-resolved measurements of specific humidity (q) and relative humidity (RH) are obtained from NASA’s satelliteborne Atmospheric Infrared Sounder (AIRS). … The water-vapor feedback implied by these observations is strongly positive, with an average magnitude of [lambda]q = 2.04 W/m2/K, similar to that simulated by climate models.” [Full text]

Observed and simulated seasonal co-variations of outgoing longwave radiation spectrum and surface temperature – Huang & Ramaswamy (2008) “We analyze the seasonal variations of Outgoing Longwave Radiation (OLR) accompanying the variations in sea surface temperature (SST) from satellite observations and model simulations, focusing on the tropical oceans where the two quantities are strikingly anti-correlated. A spectral perspective of this “super-greenhouse effect” is provided, which demonstrates the roles of water vapor line and continuum absorptions at different altitudes and the influences due to clouds.” [Full text]

Observed and Simulated Upper-Tropospheric Water Vapor Feedback – Gettelman & Fu (2008) “Satellite measurements from the Atmospheric Infrared Sounder (AIRS) in the upper troposphere over 4.5 yr are used to assess the covariation of upper-tropospheric humidity and temperature with surface temperatures, which can be used to constrain the upper-tropospheric moistening due to the water vapor feedback. … Results indicate that the upper troposphere maintains nearly constant relative humidity for observed perturbations to ocean surface temperatures over the observed period, with increases in temperature ~ 1.5 times the changes at the surface, and corresponding increases in water vapor (specific humidity) of 10%–25% °C−1. Increases in water vapor are largest at pressures below 400 hPa, but they have a double peak structure. Simulations reproduce these changes quantitatively and qualitatively.” [Full text]

Identification of human-induced changes in atmospheric moisture content – Santer et al. (2007) “Data from the satellite-based Special Sensor Microwave Imager (SSM/I) show that the total atmospheric moisture content over oceans has increased by 0.41 kg/m2 per decade since 1988. … In a formal detection and attribution analysis using the pooled results from 22 different climate models, the simulated “fingerprint” pattern of anthropogenically caused changes in water vapor is identifiable with high statistical confidence in the SSM/I data. Experiments in which forcing factors are varied individually suggest that this fingerprint “match” is primarily due to human-caused increases in greenhouse gases and not to solar forcing or recovery from the eruption of Mount Pinatubo.” [Full text] [Supporting information]

How Much More Rain Will Global Warming Bring? – Wentz et al. (2007) “Climate models and satellite observations both indicate that the total amount of water in the atmosphere will increase at a rate of 7% per kelvin of surface warming. … Rather, the observations suggest that precipitation and total atmospheric water have increased at about the same rate over the past two decades.” [Full text]

Enhanced positive water vapor feedback associated with tropical deep convection: New evidence from Aura MLS – Su et al. (2006) “Recent simultaneous observations of upper tropospheric (UT) water vapor and cloud ice from the Microwave Limb Sounder (MLS) on the Aura satellite provide new evidence for tropical convective influence on UT water vapor and its associated greenhouse effect. … The moistening of the upper troposphere by deep convection leads to an enhanced positive water vapor feedback, about 3 times that implied solely by thermodynamics. Over tropical oceans when SST greater than ∼300 K, the ‘convective UT water vapor feedback’ inferred from the MLS observations contributes approximately 65% of the sensitivity of the clear-sky greenhouse parameter to SST.” [Full text]

The Radiative Signature of Upper Tropospheric Moistening – Soden et al. (2005) “Climate models predict that the concentration of water vapor in the upper troposphere could double by the end of the century as a result of increases in greenhouse gases. … We use satellite measurements to highlight a distinct radiative signature of upper tropospheric moistening over the period 1982 to 2004. The observed moistening is accurately captured by climate model simulations and lends further credence to model projections of future global warming.” [Full text]

Anthropogenic greenhouse forcing and strong water vapor feedback increase temperature in Europe – Philipona et al. (2005) “Surface radiation measurements in central Europe manifest anthropogenic greenhouse forcing and strong water vapor feedback, enhancing the forcing and temperature rise by about a factor of three.”

Trends and variability in column-integrated atmospheric water vapor – Trenberth et al. (2005) “An analysis and evaluation has been performed of global datasets on column-integrated water vapor (precipitable water). … The evidence from SSM/I for the global ocean suggests that recent trends in precipitable water are generally positive and, for 1988 through 2003, average 0.40±0.09 mm per decade or 1.3±0.3% per decade for the ocean as a whole, where the error bars are 95% confidence intervals. Over the oceans, the precipitable water variability relates very strongly to changes in SSTs, both in terms of spatial structure of trends and temporal variability (with a regression coefficient for 30°N–30°S of 7.8% K−1) and is consistent with the assumption of fairly constant relative humidity.” [Full text]

Quantifying the water vapour feedback associated with post-Pinatubo global cooling – Forster & Collins (2004) “In this work we employ observations of water vapour changes, together with detailed radiative calculations to estimate the water vapour feedback for the case of the Mt. Pinatubo eruption. … The observed estimates are consistent with that found in the climate model,… Variability, both in the observed value and in the climate model’s feedback parameter, between different ensemble members, suggests that the long-term water vapour feedback associated with global climate change could still be a factor of 2 or 3 different than the mean observed value found here and the model water vapour feedback could be quite different from this value; although a small water vapour feedback appears unlikely.” [Full text]

Water Vapor Feedback in the Tropical Upper Troposphere: Model Results and Observations – Minschwaner & Dessler (2004) “These changes in upper-tropospheric humidity with respect to surface temperature are consistent with observed interannual variations in relative humidity and water vapor mixing ratio near 215 mb as measured by the Microwave Limb Sounder and the Halogen Occultation Experiment. The analysis suggests that models that maintain a fixed relative humidity above 250 mb are likely overestimating the contribution made by these levels to the water vapor feedback.” [Full text]

Global Cooling After the Eruption of Mount Pinatubo: A Test of Climate Feedback by Water Vapor – Soden et al. (2002) “We use the global cooling and drying of the atmosphere that was observed after the eruption of Mount Pinatubo to test model predictions of the climate feedback from water vapor. …. Then, by comparing model simulations with and without water vapor feedback, we demonstrate the importance of the atmospheric drying in amplifying the temperature change and show that, without the strong positive feedback from water vapor, the model is unable to reproduce the observed cooling. These results provide quantitative evidence of the reliability of water vapor feedback in current climate models, which is crucial to their use for global warming projections.” [Full text]

Precise climate monitoring using complementary satellite data sets – Wentz & Schabel (2000) “We find a strong association between sea surface temperature, lower-tropospheric air temperature and total column water-vapour content over large oceanic regions on both time scales. This lends observational support to the idea of a constant relative humidity model having a moist adiabatic lapse rate. On the decadal timescale, the combination of data sets shows a consistent warming and moistening trend of the marine atmosphere for 1987–1998.” [Full text]

Water vapor feedback and global warming – Held & Soden (2000) A review paper. “In this review, we describe the background behind the prevailing view on water vapor feedback and some of the arguments raised by its critics, and attempt to explain why these arguments have not modified the consensus within the climate research community.” [Full text]

Water Vapor, Surface Temperature, and the Greenhouse Effect—A Statistical Analysis of Tropical-Mean Data – Yang & Tung (1998) “Water vapor feedback is one of the important factors that determine the response of the atmosphere to surface warming. To take into account the compensating drying effects in downdraft regions, averaging over the whole Tropics is necessary. However, this operation drastically reduces the number of degrees of freedom and raises questions concerning the statistical significance of any correlative results obtained using observational data. A more involved statistical analysis is performed here, using multiple datasets, including the global water vapor datasets of Special Sensor for Microwave/Imaging (column water), upper-tropospheric relative humidity, the Television Infrared Observational Satellite Operational Vertical Sounder retrieved upper-tropospheric specific humidity, and the surface temperature data from the National Centers for Environmental Prediction–National Center for Atmospheric Research Reanalysis dataset. The tropical-mean correlations between relative humidity and surface temperature cannot be established, but those between specific humidity and the surface temperature are found to be positive and shown to be statistically significant. This conclusion holds even when the averaging is done on the natural logarithm of the upper-tropospheric water vapor content. The effect on the tropical-mean outgoing longwave radiation is also discussed.” Yang, Hu, Ka Kit Tung, 1998: Water Vapor, Surface Temperature, and the Greenhouse Effect—A Statistical Analysis of Tropical-Mean Data. J. Climate, 11, 2686–2697. doi:;2. [Full text]

Water vapor feedback over the Arctic Ocean – Curry et al. (1995) “Results of this study indicate that water vapor feedback over the Arctic Ocean is substantially more complex than in other regions because of the relative lack of convective coupling between the surface and the atmosphere and the different thermodynamic and radiative environment in the Arctic. In particular, the effect of water vapor on the net flux of radiation is complicated by low temperatures, low amounts of water vapor, and the presence of temperature and humidity inversions. During winter a “hyper” water vapor feedback arises from the control of ice saturation on the lower tropospheric humidity and a water vapor “window” in the rotation band at low atmospheric humidities.” Curry, J. A., J. L. Schramm, M. C. Serreze, and E. E. Ebert (1995), Water vapor feedback over the Arctic Ocean, J. Geophys. Res., 100(D7), 14,223–14,229, doi:10.1029/95JD00824. [Full text]

Observed dependence of the water vapor and clear-sky greenhouse effect on sea surface temperature: comparison with climate warming experiments – Bony et al. (1995) “One part of the coupling between the surface temperature, the water vapor and the clear-sky greenhouse effect is explained by the dependence of the saturation water vapor pressure on the atmospheric temperature. However, the analysis of observed and simulated fields shows that the coupling is very different according to the type of region under consideration and the type of climate forcing that is applied to the Earth-atmosphere system. This difference, due to the variability of the vertical structure of the atmosphere, is analyzed in detail by considering the temperature lapse rate and the vertical profile of relative humidity. Our results suggest that extrapolating the feedbacks inferred from seasonal and short-term interannual climate variability to longer-term climate changes requires great caution.” Sandrine Bony, Jean-Philippe Duvel and Hervé Trent, Climate Dynamics, Volume 11, Number 5, 307-320, DOI: 10.1007/BF00211682.

Positive water vapour feedback in climate models confirmed by satellite data – Rind et al. (1991) “CHIEFamong the mechanisms thought to amplify the global climate response to increased concentrations of trace gases is the atmospheric water vapour feedback. As the oceans and atmosphere warm, there is increased evaporation, and it has been generally thought that the additional moisture then adds to the greenhouse effect by trapping more infrared radiation. Recently, it has been suggested that general circulation models used for evaluating climate change overestimate this response, and that increased convection in a warmer climate would actually dry the middle and upper troposphere by means of associated compensatory subsidence. We use some new satellite-generated water vapour data to investigate this question. From a comparison of summer and winter moisture values in regions of the middle and upper troposphere that have previously been difficult to observe with confidence, we find that, as the hemispheres warm, increased convection leads to increased water vapour above 500 mbar in approximate quantitative agreement with the results from current climate models. The same conclusion is reached by comparing the tropical western and eastern Pacific regions. Thus, we conclude that the water vapour feedback is not overestimated in models and should amplify the climate response to increased trace-gas concentrations.” D. Rind, E.-W. Chiou, W. Chu, J. Larsen, S. Oltmans, J. Lerner, M. P. McCormkk & L. McMaster, Nature 349, 500 – 503 (07 February 1991); doi:10.1038/349500a0.

Observational determination of the greenhouse effect – Raval & Ramanathan (1989) “Satellite measurements are used to quantify the atmospheric greenhouse effect, defined here as the infrared radiation energy trapped by atmospheric gases and clouds. The greenhouse effect is found to increase significantly with sea surface temperature. The rate of increase gives compelling evidence for the positive feedback between surface temperature, water vapour and the green-house effect; the magnitude of the feedback is consistent with that predicted by climate models. This study demonstrates an effective method for directly monitoring, from space, future changes in the greenhouse effect.” A. Raval & V. Ramanathan, Nature 342, 758 – 761 (14 December 1989); doi:10.1038/342758a0.

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Papers on global sea level

Posted by Ari Jokimäki on October 12, 2009

This is a list of papers about sea level with an emphasis on global long time trends. The list is not complete, and will most likely be updated in the future in order to make it more thorough and more representative. This list has three sections: Modern sea level changes, historical sea level changes, and future sea level projections. Also the list of ocean temperature papers has relevant papers for this issue.

UPDATE (March 5, 2018): Fasullo et al. (2016) and Nerem et al. (2018) added.
UPDATE (September 24, 2012): Jevrejeva et al. (2006), Ray & Douglas (2011), Church & White (2011), and Church et al. (2011) added. Thanks to Barry for pointing them out.
UPDATE (April 18, 2012): Raymo & Mitrovica (2012). Thanks to Barry for pointing it out.
UPDATE (April 2, 2012): Kemp et al. (2011) added. Thanks to Barry for pointing it out.
UPDATE (March 31, 2010): Cazenave & Llovel (2010) added, thanks to Skagedal for pointing it out, see the comment section below.
UPDATE (February 27, 2010): Future sea level projections added and some papers to it that were suggested by PeterPan and Kit Stolz (see the comment section below), thanks to them.
UPDATE (February 25, 2010): Domingues et al. (2008) and Ablain et al. (2009) added, thanks to Barry for pointing them out, see the comment section below.
UPDATE (December 9, 2009): Jevrejeva et al. (2009) added.

Modern sea level changes

Climate-change–driven accelerated sea-level rise detected in the altimeter era – Nerem et al. (2018) [Full text]
Significance: Satellite altimetry has shown that global mean sea level has been rising at a rate of ∼3 ± 0.4 mm/y since 1993. Using the altimeter record coupled with careful consideration of interannual and decadal variability as well as potential instrument errors, we show that this rate is accelerating at 0.084 ± 0.025 mm/y2, which agrees well with climate model projections. If sea level continues to change at this rate and acceleration, sea-level rise by 2100 (∼65 cm) will be more than double the amount if the rate was constant at 3 mm/y.
Citation: R. S. Nerem, B. D. Beckley, J. T. Fasullo, B. D. Hamlington, D. Masters and G. T. Mitchum (2018). PNAS; published ahead of print February 12, 2018,

Is the detection of accelerated sea level rise imminent? – Fasullo et al. (2016) [Full text]
Abstract: Global mean sea level rise estimated from satellite altimetry provides a strong constraint on climate variability and change and is expected to accelerate as the rates of both ocean warming and cryospheric mass loss increase over time. In stark contrast to this expectation however, current altimeter products show the rate of sea level rise to have decreased from the first to second decades of the altimeter era. Here, a combined analysis of altimeter data and specially designed climate model simulations shows the 1991 eruption of Mt Pinatubo to likely have masked the acceleration that would have otherwise occurred. This masking arose largely from a recovery in ocean heat content through the mid to late 1990 s subsequent to major heat content reductions in the years following the eruption. A consequence of this finding is that barring another major volcanic eruption, a detectable acceleration is likely to emerge from the noise of internal climate variability in the coming decade.
Citation: J. T. Fasullo, R. S. Nerem, B. Hamlington (2016). Is the detection of accelerated sea level rise imminent? Scientific Reports 6: 31245. doi:10.1038/srep31245.

Revisiting the Earth’s sea-level and energy budgets from 1961 to 2008 – Church et al. (2011) “We review the sea-level and energy budgets together from 1961, using recent and updated estimates of all terms. From 1972 to 2008, the observed sea-level rise (1.8 ± 0.2 mm yr−1 from tide gauges alone and 2.1 ± 0.2 mm yr−1 from a combination of tide gauges and altimeter observations) agrees well with the sum of contributions (1.8 ± 0.4 mm yr−1) in magnitude and with both having similar increases in the rate of rise during the period. The largest contributions come from ocean thermal expansion (0.8 mm yr−1) and the melting of glaciers and ice caps (0.7 mm yr−1), with Greenland and Antarctica contributing about 0.4 mm yr−1. The cryospheric contributions increase through the period (particularly in the 1990s) but the thermosteric contribution increases less rapidly. We include an improved estimate of aquifer depletion (0.3 mm yr−1), partially offsetting the retention of water in dams and giving a total terrestrial storage contribution of −0.1 mm yr−1. Ocean warming (90% of the total of the Earth’s energy increase) continues through to the end of the record, in agreement with continued greenhouse gas forcing. The aerosol forcing, inferred as a residual in the atmospheric energy balance, is estimated as −0.8 ± 0.4 W m−2 for the 1980s and early 1990s. It increases in the late 1990s, as is required for consistency with little surface warming over the last decade. This increase is likely at least partially related to substantial increases in aerosol emissions from developing nations and moderate volcanic activity.” Church, J. A., N. J. White, L. F. Konikow, C. M. Domingues, J. G. Cogley, E. Rignot, J. M. Gregory, M. R. van den Broeke, A. J. Monaghan, and I. Velicogna (2011), Revisiting the Earth’s sea-level and energy budgets from 1961 to 2008, Geophys. Res. Lett., 38, L18601, doi:10.1029/2011GL048794. [Full text]

Sea-Level Rise from the Late 19th to the Early 21st Century – Church & White (2011) “We estimate the rise in global average sea level from satellite altimeter data for 1993–2009 and from coastal and island sea-level measurements from 1880 to 2009. For 1993–2009 and after correcting for glacial isostatic adjustment, the estimated rate of rise is 3.2 ± 0.4 mm year−1 from the satellite data and 2.8 ± 0.8 mm year−1 from the in situ data. The global average sea-level rise from 1880 to 2009 is about 210 mm. The linear trend from 1900 to 2009 is 1.7 ± 0.2 mm year−1 and since 1961 is 1.9 ± 0.4 mm year−1. There is considerable variability in the rate of rise during the twentieth century but there has been a statistically significant acceleration since 1880 and 1900 of 0.009 ± 0.003 mm year−2 and 0.009 ± 0.004 mm year−2, respectively. Since the start of the altimeter record in 1993, global average sea level rose at a rate near the upper end of the sea level projections of the Intergovernmental Panel on Climate Change’s Third and Fourth Assessment Reports. However, the reconstruction indicates there was little net change in sea level from 1990 to 1993, most likely as a result of the volcanic eruption of Mount Pinatubo in 1991.” John A. Church and Neil J. White, Surveys in Geophysics, 2011, Volume 32, Numbers 4-5, Pages 585-602, DOI: 10.1007/s10712-011-9119-1. [Full text]

Experiments in reconstructing twentieth-century sea levels – Ray & Douglas (2011) “One approach to reconstructing historical sea level from the relatively sparse tide-gauge network is to employ Empirical Orthogonal Functions (EOFs) as interpolatory spatial basis functions. The EOFs are determined from independent global data, generally sea-surface heights from either satellite altimetry or a numerical ocean model. The problem is revisited here for sea level since 1900. A new approach to handling the tide-gauge datum problem by direct solution offers possible advantages over the method of integrating sea-level differences, with the potential of eventually adjusting datums into the global terrestrial reference frame. The resulting time series of global mean sea levels appears fairly insensitive to the adopted set of EOFs. In contrast, charts of regional sea level anomalies and trends are very sensitive to the adopted set of EOFs, especially for the sparser network of gauges in the early 20th century. The reconstructions appear especially suspect before 1950 in the tropical Pacific. While this limits some applications of the sea-level reconstructions, the sensitivity does appear adequately captured by formal uncertainties. All our solutions show regional trends over the past five decades to be fairly uniform throughout the global ocean, in contrast to trends observed over the shorter altimeter era. Consistent with several previous estimates, the global sea-level rise since 1900 is 1.70 ± 0.26 mm yr−1. The global trend since 1995 exceeds 3 mm yr−1 which is consistent with altimeter measurements, but this large trend was possibly also reached between 1935 and 1950.” Richard D. Ray, Bruce C. Douglas, Progress In Oceanography, Volume 91, Issue 4, December 2011, Pages 496–515,

Climate related sea-level variations over the past two millennia – Kemp et al. (2011) “We present new sea-level reconstructions for the past 2100 y based on salt-marsh sedimentary sequences from the US Atlantic coast. The data from North Carolina reveal four phases of persistent sea-level change after correction for glacial isostatic adjustment. Sea level was stable from at least BC 100 until AD 950. Sea level then increased for 400 y at a rate of 0.6 mm/y, followed by a further period of stable, or slightly falling, sea level that persisted until the late 19th century. Since then, sea level has risen at an average rate of 2.1 mm/y, representing the steepest century-scale increase of the past two millennia. This rate was initiated between AD 1865 and 1892. Using an extended semiempirical modeling approach, we show that these sea-level changes are consistent with global temperature for at least the past millennium.” Andrew C. Kemp, Benjamin P. Horton, Jeffrey P. Donnelly, Michael E. Mann, Martin Vermeer, and Stefan Rahmstorf, PNAS July 5, 2011 vol. 108 no. 27 11017-11022, doi: 10.1073/pnas.1015619108. [Full text]

Contemporary Sea Level Rise – Cazenave & Llovel (2010) A review article. “Here we report on most recent results on contemporary sea level rise. We first present sea level observations from tide gauges over the twentieth century and from satellite altimetry since the early 1990s. We next discuss the most recent progress made in quantifying the processes causing sea level change on timescales ranging from years to decades, i.e., thermal expansion of the oceans, land ice mass loss, and land water–storage change. We show that for the 1993–2007 time span, the sum of climate-related contributions (2.85 ± 0.35 mm year−1) is only slightly less than altimetry-based sea level rise (3.3 ± 0.4 mm year−1): 30% of the observed rate of rise is due to ocean thermal expansion and 55% results from land ice melt. Recent acceleration in glacier melting and ice mass loss from the ice sheets increases the latter contribution up to 80% for the past five years.” Anny Cazenave and William Llovel, Annual Review of Marine Science, Vol. 2: 145-173 (Volume publication date January 2010), DOI: 10.1146/annurev-marine-120308-081105. [Full text]

A new assessment of the error budget of global mean sea level rate estimated by satellite altimetry over 1993–2008 – Ablain et al. (2009) “A new error budget assessment of the global Mean Sea Level (MSL) determined by TOPEX/Poseidon and Jason-1 altimeter satellites between January 1993 and June 2008 is presented using last altimeter standards. We discuss all potential errors affecting the calculation of the global MSL rate. … These new calculations highlight a reduction in the rate of sea level rise since 2005, by ~2 mm/yr. This represents a 60% reduction compared to the 3.3 mm/yr sea level rise (glacial isostatic adjustment correction applied) measured between 1993 and 2005. Since November 2005, MSL is accurately measured by a single satellite, Jason-1. However the error analysis performed here indicates that the recent reduction in MSL rate is real.” [Full text]

Anthropogenic forcing dominates sea level rise since 1850 – Jevrejeva et al. (2009) “Here we use a delayed response statistical model to attribute the past 1000 years of sea level variability to various natural (volcanic and solar radiative) and anthropogenic (greenhouse gases and aerosols) forcings. We show that until 1800 the main drivers of sea level change are volcanic and solar radiative forcings. For the past 200 years sea level rise is mostly associated with anthropogenic factors. Only 4 ± 1.5 cm (25% of total sea level rise) during the 20th century is attributed to natural forcings, the remaining 14 ± 1.5 cm are due to a rapid increase in CO2 and other greenhouse gases.” [Full text]

An anomalous recent acceleration of global sea level rise – Merrifield et al. (2009) “The average global sea level trend for the time segments centered on 1962 through 1990 is 1.5 ± 0.5 mm yr−1 (standard error), in agreement with previous estimates of late 20th century sea level rise. After 1990, the global trend increases to the most recent rate of 3.2 ± 0.4 mm yr−1, matching estimates obtained from satellite altimetry. The acceleration is distinct from decadal variations in global sea level that have been reported in previous studies. Increased rates in the tropical and southern oceans primarily account for the acceleration. The timing of the global acceleration corresponds to similar sea level trend changes associated with upper ocean heat content and ice melt.”

Improved estimates of upper-ocean warming and multi-decadal sea-level rise – Domingues et al. (2008) “Our ocean warming and thermal expansion trends for 1961–2003 are about 50 per cent larger than earlier estimates but about 40 per cent smaller for 1993–2003, which is consistent with the recognition that previously estimated rates for the 1990s had a positive bias as a result of instrumental errors. … We add our observational estimate of upper-ocean thermal expansion to other contributions to sea-level rise and find that the sum of contributions from 1961 to 2003 is about 1.560.4mm yr-1, in good agreement with our updated estimate of near-global mean sea-level rise (using techniques established in earlier studies) of 1.660.2mm yr-1.” [Full text]

Understanding global sea levels: past, present and future – Church et al. (2008) “While sea levels have varied by over 120 m during glacial/interglacial cycles, there has been little net rise over the past several millennia until the 19th century and early 20th century, when geological and tide-gauge data indicate an increase in the rate of sea-level rise. Recent satellite-altimeter data and tide-gauge data have indicated that sea levels are now rising at over 3 mm year−1. The major contributions to 20th and 21st century sea-level rise are thought to be a result of ocean thermal expansion and the melting of glaciers and ice caps.” [Full text]

Recent global sea level acceleration started over 200 years ago? – Jevrejeva et al. (2008) “We present a reconstruction of global sea level (GSL) since 1700 calculated from tide gauge records and analyse the evolution of global sea level acceleration during the past 300 years. We provide observational evidence that sea level acceleration up to the present has been about 0.01 mm/yr2 and appears to have started at the end of the 18th century. Sea level rose by 6 cm during the 19th century and 19 cm in the 20th century. Superimposed on the long-term acceleration are quasi-periodic fluctuations with a period of about 60 years. If the conditions that established the acceleration continue, then sea level will rise 34 cm over the 21st century. Long time constants in oceanic heat content and increased ice sheet melting imply that the latest Intergovernmental Panel on Climate Change (IPCC) estimates of sea level are probably too low.” [Full text]

A 20th century acceleration in global sea-level rise – Church & White (2006) “Multi-century sea-level records and climate models indicate an acceleration of sea-level rise, but no 20th century acceleration has previously been detected. … Here, we extend the reconstruction of global mean sea level back to 1870 and find a sea-level rise from January 1870 to December 2004 of 195 mm, a 20th century rate of sea-level rise of 1.7 ± 0.3 mm yr−1 and a significant acceleration of sea-level rise of 0.013 ± 0.006 mm yr−2. This acceleration is an important confirmation of climate change simulations which show an acceleration not previously observed.” [Full text]

Nonlinear trends and multiyear cycles in sea level records – Jevrejeva et al. (2006) “We analyze the Permanent Service for Mean Sea Level (PSMSL) database of sea level time series using a method based on Monte Carlo Singular Spectrum Analysis (MC-SSA). We remove 2–30 year quasi-periodic oscillations and determine the nonlinear long-term trends for 12 large ocean regions. Our global sea level trend estimate of 2.4 ± 1.0 mm/yr for the period from 1993 to 2000 is comparable with the 2.6 ± 0.7 mm/yr sea level rise calculated from TOPEX/Poseidon altimeter measurements. However, we show that over the last 100 years the rate of 2.5 ± 1.0 mm/yr occurred between 1920 and 1945, is likely to be as large as the 1990s, and resulted in a mean sea level rise of 48 mm. We evaluate errors in sea level using two independent approaches, the robust bi-weight mean and variance, and a novel “virtual station” approach that utilizes geographic locations of stations. Results suggest that a region cannot be adequately represented by a simple mean curve with standard error, assuming all stations are independent, as multiyear cycles within regions are very significant. Additionally, much of the between-region mismatch errors are due to multiyear cycles in the global sea level that limit the ability of simple means to capture sea level accurately. We demonstrate that variability in sea level records over periods 2–30 years has increased during the past 50 years in most ocean basins.” Jevrejeva, S., A. Grinsted, J. C. Moore, and S. Holgate (2006), Nonlinear trends and multiyear cycles in sea level records, J. Geophys. Res., 111, C09012, doi:10.1029/2005JC003229. [Full text]

Rapid sea-level rise in the North Atlantic Ocean since the first half of the nineteenth century – Gehrels et al. (2006) “A high-resolution late-Holocene sea-level record is produced from salt-marsh deposits at Vioarhólmi in Snæfellsnes, western Iceland. … Our reconstruction indicates that relative sea level along the coast of western Iceland has risen by about 1.3 m since c. AD 100. The detrended sea-level record shows a slow rise between AD 100 and 500, followed by a slow downward trend reaching a lowstand in the first half of the nineteenth century. This falling trend is consistent with a steric change estimated from reconstructions of sea-surface and sea-bottom temperatures from shelf sediments off Northern Iceland. The sea-level record shows a marked recent rise of about 0.4 m that commenced AD 1820±20 as dated by palaeomagnetism and Pb produced by European coal burning. This rapid sea-level rise is interpreted to be related to global temperature rise. The rise has continued up to the present day and has also been measured, since 1957, by the Reykjavik tide gauge.”

Coupling instrumental and geological records of sea-level change: Evidence from southern New England of an increase in the rate of sea-level rise in the late 19th century – Donnelly et al. (2004) “We construct a high-resolution relative sea-level record for the past 700 years by dating basal salt-marsh peat samples above a glacial erratic in an eastern Connecticut salt marsh, to test whether or not the apparent recent acceleration in the rate of sea-level rise (SLR) is coeval with climate warming. The data reveal an average SLR rate of 1.0 ± 0.2 mm/year from about 1300 to 1850 A.D. Coupling of the regional tide-gauge data (1856 to present) with this marsh-based record indicates that the nearly three-fold increase in the regional rate of SLR to modern levels likely occurred in the later half of the 19th century. Thus the timing of the observed SLR rate increase is coincident with the onset of climate warming, indicating a possible link between historic SLR increases and recent temperature increases.” [Full text]

Mass and volume contributions to twentieth-century global sea level rise – Miller & Douglas (2004) “We find that gauge-determined rates of sea level rise, which encompass both mass and volume changes, are two to three times higher than the rates due to volume change derived from temperature and salinity data. Our analysis supports earlier studies that put the twentieth-century rate in the 1.5–2.0 mm yr-1 range, but more importantly it suggests that mass increase plays a larger role than ocean warming in twentieth-century global sea level rise.” [Full text]

The Puzzle of Global Sea-Level Rise – Douglas & Peltier (2002) “Global sea level (GSL) embodies many aspects of the global hydrological cycle and reflects the heat content of the oceans because the density of sea water depends on temperature. GSL is therefore a potent indicator of climate change and a key observational constraint on climate models.” [Full text]

Global Sea Level Acceleration – Douglas (1992) “Greenhouse warming scenarios commonly forecast an acceleration of sea level rise in the next 5 or 6+ decades in the range 0.1–0.2 mm/yr2. … Thus there is no evidence for an apparent acceleration in the past 100+ years that is significant either statistically, or in comparison to values associated with global warming. … This means that tide gauges alone cannot serve as a leading indicator of climate change in less than at least several decades.”

Global Sea Level Rise – Douglas (1990) “The value for mean sea level rise obtained from a global set of 21 such stations in nine oceanic regions with an average record length of 76 years during the period 1880–1980 is 1.8 mm/yr ± 0.1. This result provides confidence that carefully selected long tide gauge records measure the same underlying trend of sea level and that many old tide gauge records are of very high quality.”

Global sea level rise and the greenhouse effect – Might they be connected? – Peltier & Tushingham (1989) “When the tide gauge data are filtered so as to remove the contribution of ongoing glacial isostatic adjustment to the local sea level trend at each location, then the individual tide gauge records reveal sharply reduced geographic scatter and suggest that there is a globally coherent signal of strength 2.4 + or – 0.90 millimeters per year that is active in the system. This signal could constitute an indication of global climate warming.”

Contribution of Small Glaciers to Global Sea Level – Meier (1984) “Observed long-term changes in glacier volume and hydrometeorological mass balance models yield data on the transfer of water from glaciers, excluding those in Greenland and Antarctica, to the oceans. The average observed volume change for the period 1900 to 1961 is scaled to a global average by use of the seasonal amplitude of the mass balance. These data are used to calibrate the models to estimate the changing contribution of glaciers to sea level for the period 1884 to 1975. Although the error band is large, these glaciers appear to account for a third to half of observed rise in sea level, approximately that fraction not explained by thermal expansion of the ocean.”

The estimation of ‘‘global’’ sea level change: A problem of uniqueness – Barnett (1984) “The study results suggest that it is not possible to uniquely determine either a global rate of change of SL or even the average rate of change associated with the existing (inadequate) data set. Indeed, different analysis methods, by themselves, can cause 50% variations in the estimates of SL trend in the existing data set. A signal/noise analysis suggests it should be easy to detect small, future changes in the SL trends estimated for the period 1930–1980. However, detection of theoretically predicted low-frequency signals (e.g., caused by CO2 warming) will be difficult in view of the huge, low-frequency, natural variability associated with glacial/tectonic processes.”

Global Sea Level Trend in the Past Century – Gornitz et al. (1982) “Data derived from tide-gauge stations throughout the world indicate that the mean sea level rose by about 12 centimeters in the past century. The sea level change has a high correlation with the trend of global surface air temperature. A large part of the sea level rise can be accounted for in terms of the thermal expansion of the upper layers of the ocean. The results also represent weak indirect evidence for a net melting of the continental ice sheets.” [Full text]

Historical sea level changes

Collapse of polar ice sheets during the stage 11 interglacial – Raymo & Mitrovica (2012) “Contentious observations of Pleistocene shoreline features on the tectonically stable islands of Bermuda and the Bahamas have suggested that sea level about 400,000 years ago was more than 20 metres higher than it is today. Geochronologic and geomorphic evidence indicates that these features formed during interglacial marine isotope stage (MIS) 11, an unusually long interval of warmth during the ice age. Previous work has advanced two divergent hypotheses for these shoreline features: first, significant melting of the East Antarctic Ice Sheet, in addition to the collapse of the West Antarctic Ice Sheet and the Greenland Ice Sheet; or second, emplacement by a mega-tsunami during MIS 11 (ref. 4, 5). Here we show that the elevations of these features are corrected downwards by ~10 metres when we account for post-glacial crustal subsidence of these sites over the course of the anomalously long interglacial. On the basis of this correction, we estimate that eustatic sea level rose to ~6–13 m above the present-day value in the second half of MIS 11. This suggests that both the Greenland Ice Sheet and the West Antarctic Ice Sheet collapsed during the protracted warm period while changes in the volume of the East Antarctic Ice Sheet were relatively minor, thereby resolving the long-standing controversy over the stability of the East Antarctic Ice Sheet during MIS 11.” Maureen E. Raymo & Jerry X. Mitrovica, Nature, 483, 453–456, (22 March 2012), doi:10.1038/nature10891. [Full text]

The Phanerozoic Record of Global Sea-Level Change – Miller et al. (2005) “We review Phanerozoic sea-level changes [543 million years ago (Ma) to the present] on various time scales and present a new sea-level record for the past 100 million years (My). Long-term sea level peaked at 100 ± 50 meters during the Cretaceous, implying that ocean-crust production rates were much lower than previously inferred.” [Full text]

Cenozoic Global Sea Level, Sequences, and the New Jersey Transect: Results From Coastal Plain and Continental Slope Drilling – Miller et al. (1998) “The New Jersey Sea Level Transect was designed to evaluate the relationships among global sea level (eustatic) change, unconformity-bounded sequences, and variations in subsidence, sediment supply, and climate on a passive continental margin. By sampling and dating Cenozoic strata from coastal plain and continental slope locations, we show that sequence boundaries correlate (within ±0.5 myr) regionally (onshore-offshore) and interregionally (New Jersey-Alabama-Bahamas), implicating a global cause. … We conclude that the New Jersey margin provides a natural laboratory for unraveling complex interactions of eustasy, tectonics, changes in sediment supply, and climate change.” [Full text]

Deglacial sea-level record from Tahiti corals and the timing of global meltwater discharge – Bard et al. (1996) “Here we date fossil corals from Tahiti, which is far from plate boundaries (and thus is likely to be tectonically relatively stable) and remote from the locations of large former ice sheets. The resulting record indicates a large sea-level jump shortly before 13,800 calendar years BP, which corresponds to meltwater pulse 1A in the Barbados coral records. The timing of this event is more accurately constrained in the Tahiti record, revealing that the meltwater pulse coincides with a short and intense climate cooling event that followed the initiation of the Bølling–Allerød warm period, but preceded the Younger Dryas cold event by about 1,000 years.”

Chronology of Fluctuating Sea Levels Since the Triassic – Haq et al. (1987) “An effort has been made to develop a realistic and accurate time scale and widely applicable chronostratigraphy and to integrate depositional sequences documented in public domain outcrop sections from various basins with this chronostratigraphic framework. A description of this approach and an account of the results, illustrated by sea level cycle charts of the Cenozoic, Cretaceous, Jurassic, and Triassic intervals, are presented.” [Full text]

Future sea level projections

Global sea level linked to global temperature – Vermeer & Rahmstorf (2009) “We propose a simple relationship linking global sea-level variations on time scales of decades to centuries to global mean temperature. This relationship is tested on synthetic data from a global climate model for the past millennium and the next century. When applied to observed data of sea level and temperature for 1880–2000, and taking into account known anthropogenic hydrologic contributions to sea level, the correlation is >0.99, explaining 98% of the variance. For future global temperature scenarios of the Intergovernmental Panel on Climate Change’s Fourth Assessment Report, the relationship projects a sea-level rise ranging from 75 to 190 cm for the period 1990–2100.” [Full text]

Reconstructing sea level from paleo and projected temperatures 200 to 2100 ad – Grinsted et al. (2009) “We use a physically plausible four parameter linear response equation to relate 2,000 years of global temperatures and sea level. … Over the last 2,000 years minimum sea level (−19 to −26 cm) occurred around 1730 ad, maximum sea level (12–21 cm) around 1150 ad. Sea level 2090–2099 is projected to be 0.9 to 1.3 m for the A1B scenario, with low probability of the rise being within IPCC confidence limits.” [Full text]

Reassessment of the Potential Sea-Level Rise from a Collapse of the West Antarctic Ice Sheet – Bamber et al. (2009) “We reassess the potential contribution to eustatic and regional sea level from a rapid collapse of the ice sheet and find that previous assessments have substantially overestimated its likely primary contribution. We obtain a value for the global, eustatic sea-level rise contribution of about 3.3 meters, with important regional variations.”

Kinematic Constraints on Glacier Contributions to 21st-Century Sea-Level Rise – Pfeffer et al. (2008) “We consider glaciological conditions required for large sea-level rise to occur by 2100 and conclude that increases in excess of 2 meters are physically untenable. We find that a total sea-level rise of about 2 meters by 2100 could occur under physically possible glaciological conditions but only if all variables are quickly accelerated to extremely high limits. More plausible but still accelerated conditions lead to total sea-level rise by 2100 of about 0.8 meter.”

A Semi-Empirical Approach to Projecting Future Sea-Level Rise – Rahmstorf (2006) “A semi-empirical relation is presented that connects global sea-level rise to global mean surface temperature. It is proposed that, for time scales relevant to anthropogenic warming, the rate of sea-level rise is roughly proportional to the magnitude of warming above the temperatures of the pre–Industrial Age. This holds to good approximation for temperature and sea-level changes during the 20th century, with a proportionality constant of 3.4 millimeters/year per °C. When applied to future warming scenarios of the Intergovernmental Panel on Climate Change, this relationship results in a projected sea-level rise in 2100 of 0.5 to 1.4 meters above the 1990 level.” [Full text], [comment, Holgate et al. (2007)], [comment, Schmith et al. (2007)], [Rahmstorf response (2007)]

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Papers on carbon dioxide absorption properties in atmosphere

Posted by Ari Jokimäki on October 8, 2009

This list of papers contains observations of carbon dioxide absorption properties measured from Earth’s atmosphere. Some of the papers discuss CO2 concentration measurements, but they are about CO2 retrievals from infrared spectrum, so they are also about CO2 absorption properties in that sense. The list is not complete, and will most likely be updated in the future in order to make it more thorough and more representative.

Satellite remote sounding of mid-tropospheric CO2 – Chahine et al. (2008) “Mid-tropospheric CO2 retrieved by the Atmospheric Infrared Sounder shows a substantial spatiotemporal variability that is supported by in situ aircraft measurements.” [Link to PDF]

Development of remote sensing techniques for detecting variations of atmospheric carbon dioxide concentrations from high-resolution infrared sounders – Uspensky et al. (2007) Conference paper. “The paper describes the approach developed for the retrieval of CO2 columns from clear-sky or cloud-cleared AIRS measurements in the dedicated channels subset (LW band), based on the physical inversion algorithm. The results of validation exercise, that has been carried out with actual AIRS data for two areas in Western Siberia and 10 months of year 2003, demonstrate the ability of retrievals to capture seasonal cycle of CO2 columns, derived from collocated air-borne observations.” [Link to PDF]

Direct retrieval of stratospheric CO2 infrared cooling rate profiles from AIRS data – Feldman et al. (2006) No need to guess if CO2 cools stratosphere when we can just measure it. “Specifically, we infer lower- and mid-stratospheric cooling rates from the CO2 ν2 band on the basis of selected spectral channels and available data from the Atmospheric Infrared Sounder (AIRS). In order to establish the validity of our results, we compare our retrievals to those calculated from a forward radiative transfer program using retrieved temperature data from spectra taken by the Scanning High-Resolution Interferometer Sounder (S-HIS) on two aircraft campaigns: the Mixed-Phase Arctic Cloud Experiment (MPACE) and the Aura Validation Experiment (AVE) both in Fall, 2004. Reasonable and consistent comparisons are illustrated, revealing that spectral radiance data taken by high-resolution infrared sounders can be used to determine the vertical distribution of radiative cooling due to CO2.” [Link to PDF]

On the determination of atmospheric minor gases by the method of vanishing partial derivatives with application to CO2 – Chahine et al. (2005) “We present a general method for the determination of minor gases in the troposphere from high spectral resolution observations. In this method, we make use of a general property of the total differential of multi-variable functions to separate the contributions of each individual minor gas. We have applied this method to derive the mixing ratio of carbon dioxide in the mid-troposphere using data from the Atmospheric Infrared Sounder (AIRS) currently flying on the NASA Aqua Mission. We compare our results to the aircraft flask CO2 measurements obtained by H. Matsueda et al. over the western Pacific and demonstrate skill in tracking the measured 5 ppmv seasonal variation with an accuracy of 0.43 ± 1.20 ppmv.” [Link to PDF] [Presentation material]

Estimating atmospheric CO2 from advanced infrared satellite radiances within an operational four-dimensional variational (4D-Var) data assimilation system: Results and validation – Engelen et al. (2005) “More than a year of Atmospheric Infrared Sounder (AIRS) radiance observations have been assimilated in the European Centre for Medium-Range Weather Forecasts four-dimensional variational (4D-Var) data assimilation system to estimate tropospheric CO2. … Comparisons with independent flight data from Japanese Airlines and National Oceanic and Atmospheric Administration Climate Monitoring and Diagnostics Laboratory are favorable.” [Link to PDF]

Spectra calculations in central and wing regions of CO2 IR bands between 10 and 20 μm. III: atmospheric emission spectra – Niro et al. (2005) Compare figures 1 and 3 for a simple demonstration of CO2 effect in the atmosphere (CO2 frequency is 667 cm-1). “The present work completes these studies by now considering atmospheric emission in the 10–20 μm range. Comparisons are made between computed atmospheric radiances and measurements obtained using four different Fourier transform experiments collecting spectra for nadir, up-looking, as well as limb (from balloon and satellite) geometries. Our results confirm that using a Voigt model can lead to very large errors that affect the spectrum more than 300 cm−1 away from the center of the CO2 ν2 band. They also demonstrate the capability of our model to represent accurately the radiances in the entire region for a variety of atmospheric paths.” [Link to PDF]

Spectra calculations in central and wing regions of CO2 IR bands between 10 and 20 μm. II. Atmospheric solar occultation spectra – Niro et al. (2004) “Comparisons are made between forward calculations of atmospheric transmission spectra and values measured using two different solar occultation experiments based on high resolution Fourier transform instruments. The results demonstrate that neglecting line-mixing and using a Voigt model can lead to a very large overestimation of absorption that may extend over more than 300 cm−1 in the wing of the CO2 ν2 band. They also demonstrate the capability of our model to represent accurately the absorption in the entire region for a variety of atmospheric paths.”

Estimating atmospheric CO2 from advanced infrared satellite radiances within an operational 4D-Var data assimilation system: Methodology and first results – Engelen et al. (2004) “Atmospheric CO2 concentrations have been obtained from the Atmospheric Infrared Sounder (AIRS) radiance data within the European Centre for Medium-Range Weather Forecasts data assimilation system. … First results for February and August 2003 show considerable geographical variability compared to the background with values ranging between 371 and 380 ppmv.” [Link to PDF]

The feasibility of monitoring CO2 from high-resolution infrared sounders – Chédin et al. (2003) “Satellite instruments specifically designed to monitor atmospheric carbon dioxide concentrations have not been flown to date but, high-resolution infrared sounders, being launched in the next few years, may offer the possibility of at least a basic carbon dioxide monitoring capability. … We also show results of an information content study for the Atmospheric InfraRed Sounder, AIRS, data, which suggests 50 channels are adequate for inferring the tropospheric carbon dioxide amounts but that they are not sensitive to CO2 changes in the boundary layer.” [Link to PDF]

Closely related

Papers on atmospheric measurements of GHGs
Papers on atmospheric carbon dioxide concentration measurements
Papers on changes in OLR due to GHG’s
Papers on changes in DLR
Papers on laboratory measurements of CO2 absorption properties

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