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Archive for June, 2010


Posted by Ari Jokimäki on June 28, 2010

Note (September 8, 2016): The article below contains some false statements. I have overlined the false parts. See the discussion below for further information.

Arthur Smith wrote about the Mann/Tiljander issue. For months I have had a draft about this issue waiting for me to finish and publish it. As Arthur Smith asks comments on this issue and as I do seem to have something relevant to say on this issue, it is time for me to finish this thing.

Mann et al. (2008, from hereafter I will call this paper “MEA”, proper references with links are given at the end of this article) used Lake Korttajärvi dataseries from Tiljander et al. (2003, from hereafter “TEA”) as temperature proxies in their reconstruction. There has been lot of different claims about Tiljander series being upside-down in MEA. McIntyre & McKitrick (2009, from hereafter “M&M”) wrote a comment to PNAS on MEA and on the Tiljander issue they said:

Their non-dendro network uses some data with the axes upside down, e.g., Korttajarvi sediments, which are also compromised by agricultural impact (M. Tiljander, personal communication),…

To this, Mann et al. (2009) responded:

The claim that “upside down” data were used is bizarre. Multivariate regression methods are insensitive to the sign of predictors. Screening, when used, employed one-sided tests only when a definite sign could be a priori reasoned on physical grounds. Potential nonclimatic influences on the Tiljander and other proxies were discussed in the SI, which showed that none of our central conclusions relied on their use.

McIntyre has also presented some claims relating to this before in his website. Here’s to my knowledge the first of his posts on the issue, saying:

By flipping the data opposite to the interpretation of Tiljander et al, Mann shows the Little Ice Age in Finland as being warmer than the MWP, 100% opposite to the interpretation of the authors and the paleoclimate evidence. The flipping is done because the increase in varve thickness due to construction and agricultural activities is interpreted by Mann et al as a “nonlocal statistical relationship” or “teleconnection” to world climate.

Is the TEA data upside-down in MEA?

One of the four dataseries in TEA is the relative X-ray density. This dataseries is presented in TEA Figure 5. MEA presents it (among some other proxies) in their Supporting Information Figure S9. Mann website has the data and the codes for their reconstruction available. The relative X-ray density dataseries is there in the “data” section as tiljander_2003_xraydenseave.ppd. I have made a graph out of this data presented in Figure 1. It is easy to see by comparing the values in X-axis and Y-axis to those in TEA Figure 5 that the data is in the ppd-file exactly same way as it is presented in TEA.

Figure 1. The relative X-ray density series in TEA.

Now that it is established that the data in MEA input (in the ppd-file) is in same way as in TEA, I shall now look at the reconstruction codes a little. The ppd-file is read among other proxy files and written to a data-matrix. TEA data is not handled in any special way compared to other proxies before it is entered to the matrix, so TEA data is not turned upside-down at this stage.

Data is then read from the data-matrix to perform the reconstruction (there are several steps involved in this but it is not important here). There’s nothing special done on TEA data at this point either compared to other proxies, so the data seems to stay the same way throughout the reconstruction. So, the Tiljander data clearly is not flipped upside-down there. That doesn’t mean the Tiljander data is handled correctly there. Tiljander data is actually handled upside-down there. It is because the data is given in TEA so that higher values of relative X-ray density correspond to lower temperature values, so MEA should have turned the data upside-down before using it in their analysis.

Seeing the real situation with this issue, it seems that MEA did an honest mistake, which of course should be corrected. There has been some claims that MEA would have done this deliberately, and/or that they have refused to correct the mistake. I don’t see any proof here that they would have done it deliberately. The thing about correcting the mistake has more to do with M&M description of the situation than MEA attitude, in my opinion. The way M&M descibed this problem is bizarre, just like Mann et al. (2009) put it. M&M comment to me seems so misleading that I don’t see how it could be considered as informing the situation to MEA.

Are McIntyre’s claims about the issue correct?

Looking at McIntyre’s claims on this and the real situation descibed above shows that McIntyre’s claims are false. Just look at the graphs McIntyre presented. In all graphs there the values in X- and Y-axes give matching values, and yet McIntyre shows them as they would show the mistake. The graphs he presents just show how the data is in the TEA and in the input of the MEA reconstruction so basically those graphs just show that MEA have not flipped the data upside-down before feeding it to their analysis, which is exactly the opposite that McIntyre claims to be the case. He claims that MEA have flipped the data, while in real world the problem is that they haven’t flipped the data.

McIntyre’s role in this is very strange. Even when the basic claim is correct, i.e. the claim that the data is used upside-down in MEA, McIntyre still cannot make correct claims about it. It makes one wonder. If a person is aware of this problem, then why make false claims about it?

Bizarre, indeed.


Mann, Michael E., Zhihua Zhang, Malcolm K. Hughes, Raymond S. Bradley, Sonya K. Miller, Scott Rutherford, and Fenbiao Ni, PNAS September 9, 2008 vol. 105 no. 36 13252-13257, doi: 10.1073/pnas.0805721105. [abstract, full text, supporting information]

Mann, Michael E., Raymond S. Bradley and Malcolm K. Hughes, Reply to McIntyre and McKitrick: Proxy-based temperature reconstructions are robust, PNAS February 10, 2009 vol. 106 no. 6 E11, doi: 10.1073/pnas.0812936106. [Full text]

McIntyre, Stephen, and Ross McKitrick, PNAS February 10, 2009 vol. 106 no. 6 E10, doi: 10.1073/pnas.0812509106. [Full text]

Tiljander, Mia, Matti Saarnisto, Antti Ojala, Timo Saarinen, A 3000-year palaeoenvironmental record from annually laminated sediment of Lake Korttajärvi, central Finland, Boreas, Volume 32, Number 4, December 2003 , pp. 566-577(12). [abstract, full text]

Appendix – Tiljander relative X-ray density against local temperature

UPDATE (June 29, 2010): I decided to add this section as there’s a question relating to this by AMac in the comment section.

I have also looked at the relative X-ray density series of TEA against the local temperature record. The closest temperature measurement site in GISS database is Jyväskylä (which is quite close to the Lake Korttajärvi – about 10 km). Here’s the link to the GISS-data of the Jyväskylä temperature measurements. Jyväskylä temperature series start only from 1950, so there’s not much overlap between the two series. I inverted the Tiljander series and plotted the two in the same graph. Here’s the result:

The linear correlation between the two series is only about -0.12, so the relative X-ray density is not very good temperature proxy. It is, however, interesting to see that this series (when inverted) tracks temperature somewhat even if there were strong human influence to 20th century part of the series (according to TEA).


Posted in Climate claims | 39 Comments »

The summer

Posted by Ari Jokimäki on June 23, 2010

Ok, it’s time to start enjoying the summer and spend less time building paperlists. I will not promise that I won’t post anything during the summer but most likely there will be very little going on in here for the next couple of months.

I will, however, correct the mess I have made with the atmospheric GHG measurement lists. I just posted the water vapor list. The list has its own section for stratospheric water vapor. When I had posted the list and was adding it to the index-page I noticed that I already had a list on stratospheric water vapor. Then I also noticed that there already are some water vapor papers in the atmospheric measurements of GHGs -list. It seems that the time has arrived for me to start checking what I already have before I make a new list. 🙂 I’ll check all these lists and try to make it less messy.

I hope you all will have a nice summer!

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Papers on atmospheric water vapor

Posted by Ari Jokimäki on June 23, 2010

This is a list of papers on atmospheric water vapor with an emphasis on the observations. Note that there is a separate list on water vapor feedback and all the papers there are relevant for this also. Some papers in this list also include some discussion on water vapor feedback. Stratospheric water vapor has its own list. 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 3, 2013): Vonder Haar et al. (2012) added.
UPDATE (June 17, 2011): Dai et al. (2011) added.
UPDATE (June 4, 2011): Gaffen et al. (1992), Gaffen & Elliott (1993), Elliott (1995), Ross & Elliott (1996), Soden & Lanzante (1996), Ross & Elliott (2001), Soden et al. (2005), and Trenberth et al. (2005) added.

Weather and climate analyses using improved global water vapor observations – Vonder Haar et al. (2012) “The NASA Water Vapor Project (NVAP) dataset is a global (land and ocean) water vapor dataset created by merging multiple sources of atmospheric water vapor to form a global data base of total and layered precipitable water vapor. Under the NASA Making Earth Science Data Records for Research Environments (MEaSUREs) program, NVAP is being reprocessed and extended, increasing its 14-year coverage to include 22 years of data. The NVAP-MEaSUREs (NVAP-M) dataset is geared towards varied user needs, and biases in the original dataset caused by algorithm and input changes were removed. This is accomplished by relying on peer reviewed algorithms and producing the data in multiple “streams” to create products geared towards studies of both climate and weather. We briefly discuss the need for reprocessing and extension, steps taken to improve the product, and provide some early science results highlighting the improvements and potential scientific uses of NVAP-M.” Thomas H. Vonder Haar, Janice L. Bytheway, John M. Forsythe, Geophysical Research Letters, Volume 39, Issue 15, August 2012, DOI: 10.1029/2012GL052094.

A New Approach to Homogenize Daily Radiosonde Humidity Data – Dai et al. (2011) “Radiosonde humidity records represent the only in situ observations of tropospheric water vapor content with multidecadal length and quasi-global coverage. However, their use has been hampered by ubiquitous and large discontinuities resulting from changes to instrumentation and observing practices. Here a new approach is developed to homogenize historical records of tropospheric (up to 100 hPa) dewpoint depression (DPD), the archived radiosonde humidity parameter. Two statistical tests are used to detect changepoints, which are most apparent in histograms and occurrence frequencies of the daily DPD: a variant of the Kolmogorov–Smirnov (K–S) test for changes in distributions and the penalized maximal F test (PMFred) for mean shifts in the occurrence frequency for different bins of DPD. These tests capture most of the apparent discontinuities in the daily DPD data, with an average of 8.6 changepoints (1 changepoint per 5 yr) in each of the analyzed radiosonde records, which begin as early as the 1950s and ended in March 2009. Before applying breakpoint adjustments, artificial sampling effects are first adjusted by estimating missing DPD reports for cold (T < −30°C) and dry (DPD artificially set to 30°C) conditions using empirical relationships at each station between the anomalies of air temperature and vapor pressure derived from recent observations when DPD reports are available under these conditions. Next, the sampling-adjusted DPD is detrended separately for each of the 4–10 quantile categories and then adjusted using a quantile-matching algorithm so that the earlier segments have histograms comparable to that of the latest segment. Neither the changepoint detection nor the adjustment uses a reference series given the stability of the DPD series. Using this new approach, a homogenized global, twice-daily DPD dataset (available online at is created for climate and other applications based on the Integrated Global Radiosonde Archive (IGRA) and two other data sources. The adjusted-daily DPD has much smaller and spatially more coherent trends during 1973–2008 than the raw data. It implies only small changes in relative humidity in the lower and middle troposphere. When combined with homogenized radiosonde temperature, other atmospheric humidity variables can be calculated, and these exhibit spatially more coherent trends than without the DPD homogenization. The DPD adjustment yields a different pattern of change in humidity parameters compared to the apparent trends from the raw data. The adjusted estimates show an increase in tropospheric water vapor globally." Dai, Aiguo, Junhong Wang, Peter W. Thorne, David E. Parker, Leopold Haimberger, Xiaolan L. Wang, 2011, J. Climate, 24, 965–991, doi: 10.1175/2010JCLI3816.1

An analysis of the dependence of clear-sky top-of-atmosphere outgoing longwave radiation on atmospheric temperature and water vapor – Dessler et al. (2008) “We have analyzed observations of clear-sky top-of-atmosphere outgoing longwave radiation (OLR) measured by the Clouds and the Earth’s Radiant Energy System (CERES). … First, we compare the OLR measurements to OLR calculated from two radiative transfer models. The models use as input simultaneous and collocated measurements of atmospheric temperature and atmospheric water vapor made by the Atmospheric Infrared Sounder (AIRS). We find excellent agreement between the models’ predictions of OLR and observations, well within the uncertainty of the measurements.” [Full text]

Measurement of the water vapour vertical profile and of the Earth’s outgoing far infrared flux – Palchetti et al. (2008) “An assessment is shown of the atmospheric outgoing flux obtained from a balloon-borne platform with wideband spectrally-resolved nadir measurements at the top of the atmosphere over the full spectral range, from 100 to 1400 cm-1, made by a Fourier transform spectrometer with uncooled detectors. From these measurements, we retrieved 15 pieces of information regarding water vapour and temperature profiles and surface temperature, with a major improvement in our knowledge of water vapour in the upper troposphere.” [Full text]

REFIR/BB initial observations in the water vapour rotational band: Results from a field campaign – Esposito et al. (2007) “The spectral and radiometric performance of the instrument and initial observations are shown in this paper. Comparisons to both (1) BOMEM MR100 Fourier Transform spectrometer observations and (2) line-by-line radiative transfer calculations for selected clear sky are presented and discussed. These comparisons (1) show a very nice agreement between radiance measured by REFIR/BB and by BOMEM MR100 and (2) demonstrate that REFIR/BB accurately observes the very fine spectral structure in the water vapour rotational band.” [Full text]

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). For years before 1996, the Ross and Elliott radiosonde dataset is used for validation of European Centre for Medium-range Weather Forecasts (ECMWF) reanalyses ERA-40. Only the special sensor microwave imager (SSM/I) dataset from remote sensing systems (RSS) has credible means, variability and trends for the oceans, but it is available only for the post-1988 period. Major problems are found in the means, variability and trends from 1988 to 2001 for both reanalyses from National Centers for Environmental Prediction (NCEP) and the ERA-40 reanalysis over the oceans, and for the NASA water vapor project (NVAP) dataset more generally. NCEP and ERA-40 values are reasonable over land where constrained by radiosondes. Accordingly, users of these data should take great care in accepting results as real. The problems highlight the need for reprocessing of data, as has been done by RSS, and reanalyses that adequately take account of the changing observing system. Precipitable water variability for 1988–2001 is dominated by the evolution of ENSO and especially the structures that occurred during and following the 1997–98 El Niño event. 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. In the tropics, the trends are also influenced by changes in rainfall which, in turn, are closely associated with the mean flow and convergence of moisture by the trade winds. The main region where positive trends are not very evident is over Europe, in spite of large and positive trends over the North Atlantic since 1988. A much longer time series is probably required to obtain stable patterns of trends over the oceans, although the main variability could probably be deduced from past SST and associated precipitation variations.” Kevin E. Trenberth, John Fasullo and Lesley Smith, Climate Dynamics, Volume 24, Numbers 7-8, 741-758, DOI: 10.1007/s00382-005-0017-4. [Full text]

An analysis of satellite, radiosonde, and lidar observations of upper tropospheric water vapor from the Atmospheric Radiation Measurement Program – Soden et al. (2005) “To improve our understanding of the distribution and radiative effects of water vapor, the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Program has conducted a series of coordinated water vapor Intensive Observation Periods (IOPs). This study uses observations collected from four ARM IOPs to accomplish two goals: First we compare radiosonde and Raman lidar observations of upper tropospheric water vapor with colocated geostationary satellite radiances at 6.7 μm. During all four IOPs we find excellent agreement between the satellite and Raman lidar observations of upper tropospheric humidity with systematic differences of ∼10%. In contrast, radiosondes equipped with Vaisala sensors are shown to be systematically drier in the upper troposphere by ∼40% relative to both the lidar and satellite measurements. Second, we assess the performance of various “correction” strategies designed to rectify known deficiencies in the radiosonde measurements. It is shown that existing methods for correcting the radiosonde dry bias, while effective in the lower troposphere, offer little improvement in the upper troposphere. An alternative method based on variational assimilation of satellite radiances is presented and, when applied to the radiosonde measurements, is shown to significantly improve their agreement with coincident Raman lidar observations. It is suggested that a similar strategy could be used to improve the quality of the global historical record of radiosonde water vapor observations during the satellite era.” Soden, B. J., D. D. Turner, B. M. Lesht, and L. M. Miloshevich (2004), J. Geophys. Res., 109, D04105, doi:10.1029/2003JD003828. [Full text]

Observed Interannual Variability of Tropical Troposphere Relative Humidity – McCarthy & Toumi (2003) “Relative humidity fields from the High-Resolution Infrared Radiation Sounder (HIRS) flown on NOAA series satellites since 1979 have been used to study the seasonal aspects of the interannual variability of relative humidity in the tropical troposphere. The El Niño–Southern Oscillation (ENSO) is the only statistically identifiable physical mechanism of such variability. … The authors argue that observed linear trends in regional and tropical mean relative humidity are unlikely to be due solely to ENSO or a simple intensification of the hydrological cycle.” [Full text]

A new METEOSAT “water vapor” archive for climate studies – Picon et al. (2003) “Since 1977, the METEOSAT satellites are equipped with a radiometer dedicated to the measurements of upper tropospheric humidity (UTH) which covers a relevant range of scales for a better understanding of the water vapor role in the climate. Due to the changes of the satellites and the calibration techniques over the last 20 years, this water vapor METEOSAT archive is not homogeneous and cannot be directly used for climatic studies. Hence the authors present in this paper a newly homogenized METEOSAT water vapor channel archive.” [Full text]

Recent climate changes in precipitable water in the global tropics as revealed in National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis – Zveryaev & Chu (2003) “For the first time, long-term climate changes in the atmospheric moisture over the global tropics are investigated using precipitable water (PW) from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis data sets for two different periods: 1979–1998 and 1948–1998. … The second EOF has a spatial pattern, which is characterized by the zonal dipole structure. This mode is associated with the major climatic signal in the region, El Niño-Southern Oscillation.” [Full text]

Analysis of moisture variability in the European Centre for Medium-Range Weather Forecasts 15-year reanalysis over the tropical oceans – Allan et al. (2002) “We compare European Centre for Medium-Range Weather Forecasts 15-year reanalysis (ERA-15) moisture over the tropical oceans with satellite observations and the U.S. National Centers for Environmental Prediction (NCEP) National Center for Atmospheric Research 40-year reanalysis. … The moisture variability provided by ERA-15 is not deemed of sufficient quality for use in the validation of climate models.” [Full text]

Water Vapor Variability in the Tropical Western Pacific from 20-year Radiosonde Data – Wang et al. (2001) “The 20-year (1976-1995) daily radiosonde data at 17 stations in the tropical western Pacific was ana lyzed. The analysis shows that the atmosphere is more humid in a warmer climate on seasonal, inter-annual and long-term (20-year) time scales, implying a positive water vapor feedback. The vertical structure of the long-term trends in relative humidity (RH) is distinct from that on short-term (seasonal and inter-annual) time scales, suggesting that observed water vapor changes on short time scales could not be considered as a surrogate of long-term climate change. The increasing trend of RH (3%-5%/decade) in the upper troposphere is stronger than that in the lower troposphere (1%-2% / decade). Such vertical structure would amplify positive water vapor feedback in comparison to the common assumption of constant RH changes vertically.” [Full text]

Trends in upper‐tropospheric humidity – Bates & Jackson (2001) “Satellite radiance observations from the past 20 years, which are sensitive to the water vapor and temperature of the upper troposphere, provide the first global observations of trends in upper‐tropospheric humidity. These decadal trends are strongly positive in the deep tropics, negative in the Southern Hemisphere subtropics and midlatitudes, and of mixed sign in the Northern Hemisphere subtropics and midlatitudes. The trends are shown to be consistent with atmospheric circulation changes observed in the past 20 years, including a tendency toward more El Niño‐Southern Oscillation warm events and changes in transient eddy activity in the subtropics.”

Radiosonde-Based Northern Hemisphere Tropospheric Water Vapor Trends – Ross & Elliott (2001) “Trends in tropospheric water vapor at Northern Hemisphere radiosonde stations are presented for two periods;1973–95 and 1958–95. Stations with incomplete or inhomogeneous temporal records were identified and excluded from the analysis. For the 1973–95 period, trends in surface–500-mb precipitable water and in specific humidity, dewpoint, and temperature at the 850-mb level are shown. At most stations in this analysis, precipitable water, specific humidity, and dewpoint temperature have increased along with temperature over the period. An exception is Europe, over which temperature increased but humidity slightly decreased. Water vapor increases are larger, more uniform, and more significant over North America than over Eurasia, and the differences in trend magnitude and sign between the two regions may be attributable to changes in the late 1970s that affected North America more than Eurasia. Seasonal and annual correlations of surface–500-mb precipitable water with temperature, dewpoint temperature, and specific and relative humidity at the surface, 850, and 700 mb indicate a strong and relatively geographically invariant relationship between 850-mb specific humidity and surface–500-mb precipitable water. Specific humidity at 850 mb is then used as a surrogate for the surface–500-mb precipitable water over the 1958–95 period to avoid data quality problems in the pre-1973 precipitable water time series. Generally, 850-mb specific humidity trends at a small set of stations for 1958–95 show that only small increases occurred and that most of the overall increase probably occurred since 1973.” Ross, Rebecca J., William P. Elliott, 2001, J. Climate, 14, 1602–1612, doi: 10.1175/1520-0442(2001)0142.0.CO;2. [Full text]

Decadal Variations in Tropical Water Vapor: A Comparison of Observations and a Model Simulation – Soden & Schroeder et al. (2000) “Multiple satellite records of tropical-mean water vapor are compared with a general circulation model (GCM) simulation to assess the ability to monitor and to predict low-frequency changes in total precipitable water. Particular attention is focused on the drying between 1979 and 1995 recorded by a TOVS statistical retrieval that is calibrated to radiosondes. Both a GCM integrated with observed SSTs and microwave and TOVS physical retrievals that overlap the drying period show no sustained drying. This discrepancy is consistent with the suggestion by Ross and Gaffen that the TOVS statistical algorithm is vulnerable to radiosonde instrumentation changes over this period that introduce an artificial drying trend into the retrieval.” [Full text]

Water vapor measurements by lidar: Raman and DIAL campaigns – Di Girolamo (2000) “Ground-based water vapor measurements by lidar have been performed in Potenza, Southern Italy, by the application of the Raman and the DIAL techniques. Raman measurements have been accomplished through the simultaneous detection of the backscattered radiation in the vibrational Raman bands of water vapor and molecular nitrogen as stimulated by a 355 nm beam, while DIAL measurements at 720 nm have been accomplished by means of a dye laser transmitter. Water vapor measurements in the troposphere up to approximately 10 km above station level have been obtained through the simultaneous application of the Raman and DIAL techniques.”

In Situ Measurements of H2O From a Stratospheric Balloon by Diode Laser Direct-Differential Absorption Spectroscopy at 1.39 um – Durry & Megie (2000) “A distributed-feedback InGaAs laser diode emitting near 1.393 um is used in conjunction with an optical multipass cell that is open to the atmosphere to yield ambient water-vapor measurements by infrared absorption spectroscopy.”

Temporal trends in United States dew point temperatures – Robinson (2000) “In this study, hourly data for the 1951-1990 period for 178 stations in the coterminous United States were used to establish temporal trends in dew point temperature. … Nevertheless, seasonally averaged results indicated an increase over much of the area, of slightly over 1°C/100 years in spring and autumn, slightly less than this in summer. Winter displayed a drying of over 1°C/100 years. When only the 1961-1990 period was considered, the patterns were similar and trends increased by approximately 1-2°C/100 years, except in autumn, which displayed a slight drying.”

Spatial Patterns of Climate Variability in Upper-Tropospheric Water Vapor Radiances from Satellite Data and Climate Model Simulations – Geer et al. (1999) “However, the large body of radiance data from satellite-borne instruments includes contiguous datasets of up to 17 yr in length and in future years will present the most well-calibrated and large-scale data archive available for climate change studies. Here the authors give an example of the spatial correlation technique used to analyze satellite radiance data. They examine yearly mean brightness temperatures from High Resolution Infrared Spectrometer (HIRS) channel 12, sensitive to upper-tropospheric water vapor and temperature.”

Validation of a new prototype water vapor retrieval for the UARS Microwave Limb Sounder – Pumphrey (1999) “The UARS Microwave Limb Sounder (MLS) measured water vapor in the middle atmosphere between September 1991 and April 1993. … As part of the process of developing the next version of UARS MLS data, a new prototype retrieval for the stratosphere/mesosphere water vapor product was developed at the University of Edinburgh. The main improvements made were (1) corrections for systematic errors and (2) doubling of the vertical resolution of the retrieval grid.” [Full text]

Water vapor of the polar middle atmosphere: Annual variation and summer mesosphere Conditions as observed by ground‐based microwave spectroscopy – Seele & Hartogh (1999) “We have been operating a ground‐based microwave radiometer for the 22.235GHz water vapor line at the ALOMAR observatory, Norway, in 1995/96 and continuously since July 1997. Its high latitude location (69°N, 16°E) provides a new and unique dataset of stratospheric and mesospheric water vapor observations. … The water vapor mixing ratio shows a pronounced annual cycle that is stronger than what has been reported for mid‐latitudes. … This investigation indicates that water vapor is already present near mesopause heights when the PMSE/NLC season starts and is still present long after it has declined.”

Atmospheric radiation and atmospheric humidity – Harries (1997) Shows how scientists are well aware of the importance of water vapor. “Results from two satellite experiments which provide data on the concentration of water vapour in the upper and middle troposphere are presented. … Sensitivity studies are presented of the effect on the outgoing-radiation spectrum of varying the amount of water vapour throughout the troposphere. It is shown that uncertainties of only a few percent in knowledge of the humidity distribution in the atmosphere could produce changes to the outgoing spectrum of similar magnitude to that caused by doubling carbon dioxide in the atmosphere. Errors in the water vapour amounts generated in model simulations of the climate could, therefore, be significant in climate change calculations.”

A New Global Water Vapor Dataset – Randel et al. (1996) “A comprehensive and accurate global water vapor dataset is critical to the adequate understanding of water vapor’s role in the earth’s climate system. To begin to satisfy this need, the authors have produced a blended dataset made up of global, 5-yr (1988–92), 1° × 1° spatial resolution, atmospheric water vapor (WV) and liquid water path products. These new products consist of both the daily total column-integrated composites and a multilayered WV product at three layers (1000–700, 700–500, 500–300 mb). The analyses combine WV retrievals from the Television and Infrared Operational Satellite (TIROS) Operational Vertical Sounder (TOVS), the Special Sensor Microwave/Imager, and radiosonde observations. … A distinct global annual cycle is shown to be dominated by the Northern Hemisphere observations. Planetary-scale variations are found to relate well to recent independent estimates of tropospheric temperature variations. Maps of regional interannual variability in the 5-yr period show the effect of the 1992 ENSO and other features.” [Full text]

An Assessment of Satellite and Radiosonde Climatologies of Upper-Tropospheric Water Vapor – Soden & Lanzante (1996) “This study compares radiosonde and satellite climatologies of upper-tropospheric water vapor for the period 1979–1991. Comparison of the two climatologies reveals significant differences in the regional distribution of upper-tropospheric relative humidity. These discrepancies exhibit a distinct geopolitical dependence that is demonstrated to result from international differences in radiosonde instrumentation. Specifically, radiosondes equipped with goldbeater’s skin humidity sensors (found primarily in the former Soviet Union, China, and eastern Europe) report a systematically moister upper troposphere relative to the satellite observations, whereas radiosondes equipped with capacitive or carbon hygristor sensors (found at most other locations) report a systematically drier upper troposphere. The bias between humidity sensors is roughly 15%–20% in terms of the relative humidity, being slightly greater during summer than during winter and greater in the upper troposphere than in the midtroposphere. However, once the instrumentation bias is accounted for, regional variations of satellite and radiosonde upper-tropospheric relative humidity are shown to be in good agreement. Additionally, temporal variations in radiosonde upper-tropospheric humidity agree reasonably well with the satellite observations and exhibit much less dependence upon instrumentation. The impact that the limited spatial coverage of the radiosonde network has upon the moisture climatology is also examined and found to introduce systematic errors of 10%–20% relative humidity over data-sparse regions of the Tropics. It is further suggested that the present radiosonde network lacks sufficient coverage in the eastern tropical Pacific to adequately capture ENSO-related variations in upper-tropospheric moisture. Finally, we investigate the impact of the clear-sky sampling restriction upon the satellite moisture climatology. Comparison of clear-sky and total-sky radiosonde observations suggests the clear-sky sampling limitation introduces a modest dry bias (<10% relative humidity) in the satellite climatology." Soden, Brian J., John R. Lanzante, 1996, J. Climate, 9, 1235–1250, doi: 10.1175/1520-0442(1996)0092.0.CO;2. [Full text]

Tropospheric Water Vapor Climatology and Trends over North America: 1973–93 – Ross & Elliott (1996) “Here 21 years of radiosonde observations from stations in the Western Hemisphere north of the equator were analyzed for trends in tropospheric water vapor. Mean fields of precipitable water and relative humidity at several levels we shown. Annual trends of surface-500 mb precipitable water were generally increasing over this region except over northeastern Canada. When trends were expressed as a percentage of the climatological mean at each station, the trends south of 45°N represent a linear rate of increase of 3%–7% decade−1. Trends in the upper portion of this layer, 700–500 mb, were as large or larger than those of the middle (850–700 mb) or lower layer and were consistent in sign. Annual trends in dewpoint generally agree in sign with trends in temperature. However, the dewpoint trends tended to be larger than those of temperature. This was consistent with the annual increases found in relative humidity over this period. Relative humidity increased except in Canada, Alaska, and a few stations in western mountainous areas. Largest percentage increases of relative humidity were in the Tropics. Seasonal trends of precipitable water varied spatially more than the annual trends and fewer were statistically significant. More stations had significant trends in summer than in other seasons and these were located over the central and eastern United States and the Tropics. Spring trends were largest over the western United States, while the largest winter trends were along the Gulf Coast. The one area where significant water vapor increases were found in all four seasons was the Caribbean.” Ross, Rebecca J., William P. Elliott, 1996, J. Climate, 9, 3561–3574, doi: 10.1175/1520-0442(1996)0092.0.CO;2. [Full text]

Ground-based measurements of water vapor in the middle atmosphere – Nedoluha et al. (1995) “We present measurements of the middle atmospheric water vapor mixing ratio profile obtained using the ground-based Naval Research Laboratory water vapor millimeter-wave spectrometer (WVMS) instrument at the Jet Propulsion Laboratory Table Mountain Observatory. The measurements cover a period of 262 days from January 23, 1992, to October 13, 1992. During this campaign it was possible to retrieve useful daily mixing ratio profiles for 186 days. We thus have a nearly continuous record of water vapor mixing ratios for altitudes from ≈35 to 75 km. … The high-altitude (≳65 km) data show a sharp rise prior to the expected maximum near the summer solstice and a gradual decline in the following months. The mixing ratios generally peak between 55 and 65 km, at which point the mixing ratios are 6–7 parts per million by volume. The highest peaks occur in January, May, and October.”

On detecting long-term changes in atmospheric moisture – Elliott (1995) “Long-term temperature changes are expected to give rise to changes in the water vapor content of the atmosphere, which in turn would accentuate the temperature change. It is thus important to monitor water vapor in the troposphere and lower stratosphere. This paper reviews existing data for such an endeavor and the prospects for improvement in monitoring. In general, radiosondes provide the longest record but the data are fraught with problems, some arising from the distribution of stations and some from data continuity questions arising from the use of different measuring devices over both time at one place and over space at any one time. Satellite records are now of limited duration but they will soon be useful in detecting changes. Satellite water vapor observations have their own limitations; there is no one system capable of measuring water vapor over all surfaces in all varieties of weather. Among the needs are careful analysis of existing records, the collection of metadata about the measuring systems, the development of a transfer standard radiosonde system, and the commitment to maintaining an observing system dedicated to describing any climate changes worldwide.” William P. Elliott, Climatic Change, Volume 31, Numbers 2-4, 349-367, DOI: 10.1007/BF01095152. [Full text]

Column Water Vapor Content in Clear and Cloudy Skies – Gaffen & Elliott (1993) “With radiosonde data from 15 Northern Hemisphere stations, surface-to-400-mb column water vapor is computed from daytime soundings for 1988–1990. On the basis of simultaneous surface visual cloud observations, the data are categorized according to sky-cover amount. Climatological column water vapor content in clear skies is shown to be significantly lower than in cloudy skies. Column water vapor content in tropical regions varies only slightly with cloud cover, but at midlatitude stations, particularly in winter, clear-sky values are much lower. The variation in column water content with cloud cover is not simply due to variations in atmospheric temperature, since the increase in water vapor with cloud cover is generally associated with a decrease in daytime temperature. Biases in radiosonde instruments associated with cloudiness do not explain the station-to-station variations in the magnitude of the increase of column water vapor with cloud cover. Statistics are presented that can be used as guidance in estimating the bias in water vapor climatologies based on clear-sky or partly cloudy-sky measurements. These may be helpful in distinguishing the clear- and cloudy-sky greenhouse effects of water vapor.” Gaffen, Dian J., William P. Elliott, 1993, J. Climate, 6, 2278–2287, doi: 10.1175/1520-0442(1993)0062.0.CO;2. [Full text]

Relationships between tropospheric water vapor and surface temperature as observed by radiosondes – Gaffen et al. (1992) “Using radiosonde data from 50 stations for 1973–1990, we quantify relationships between surface air temperature (Ts) and precipitable water vapor (W) for different time scales. Monthly mean observations are fairly well described by an equation of the form ln W = A + B Ts, but the coefficients A and B depend on the Ts range considered. At high Ts, the relationship is poor. This relationship and relationships between sea surface temperature (SST) and W based on satellite microwave observations over oceans are in remarkably good agreement over restricted SST ranges. Monthly and annual anomalies of W and Ts are well correlated only outside the tropics, but on longer time scales, there is some evidence of positive trends in both W and Ts at most of the stations studied. Thus the relationship between W and Ts depends on the time scales and geographic region considered.” Gaffen, D. J., W. P. Elliott, and A. Robock (1992), Geophys. Res. Lett., 19(18), 1839–1842, doi:10.1029/92GL02001. [Full text]

Infrared Continuum Absorption by Atmospheric Water Vapor in the 8-12- Micrometer Window – Roberts et al. (1976) “We have carried out a detailed analysis of several long-path-length transmission measurements in the 8 to 12 micrometer atmospheric window in order to determine the extinction coefficient due to the water vapor continuum. Our results indicate that three modifications to the current LOWTRAN atmospheric transmission model are required. The first two corrections are an improved fit to the pure water vapor continuum absorption coefficient and the elimination of the atmospheric broadened continuum term. Finally, and most critically, a strong measured temperature dependence must be included in the water vapor continuum absorption coefficient. For path lengths ranging from 10 to 50 km, failure to incorporate these corrections can lead to errors in the computed transmission ranging from factors of 2 to more than 10,000.” [Full text]

Atmospheric Absorption of Infrared Solar Radiation at the Lowell Observatory. II. The Spectral Interval: 5.5-8μ – Adel & Lampland (1940) “The intensity variations in the telluric spectrum between the limits 5.5 and 8 μ are great. They are here empirically specified as functions of the atmospheric water vapor content.” [Full text is available in the abstract page]

Atmospheric Absorption of Infrared Solar Radiation at the Lowell Observatory. I. – Adel (1940) “In the present paper it is experimentally demonstrated that the influence of the rotation spectrum of water vapor extends down to [lambda] < 8 μ." [Full text is available in the abstract page]

The Importance of Water Vapour in the Atmosphere – Patterson (1926) Discusses some of the basics of the issue. [Full text available in the abstract page]

Spectra of Water-Vapor in the Earth’s Atmosphere – Gilchrist (1909) Presents water vapor measurements. [Full text available in the abstract page]

Dr. Arendt’s Spectroscopic Investigation of the Variation of Aqueous Vapor in the Atmosphere – Jewell (1897) Jewell discusses his observations further. [Full text available in the abstract page]

Die Schwankungen im Wasserdampfgehalte Der Atmosphare auf Grund Spectroskopischer Untersuchungen; Th. Arendt – Frost (1897) Despite the title, the paper is in English. “In this paper the author, a member of the staff of the Prussian Meteorological Observatory at Potsdam, gives an account of his spectroscopic investigation of the variations in the amount of aqueous vapor in the atmosphere during the latter part of the summer of 1895.” [Full text available in the abstract page]

The Determination of the Relative Quantities of Aqueous Vapor in the Atmosphere BV Means of the Absorption Lines of the Spectrum – Jewell (1896) . [Full text available in the abstract page]

A Review of the Spectroscopic Observations of Mars – Campbell (1895) Water vapor in the Earth’s atmosphere is involved in the discussion. [Full text available in the abstract page]

The Spectrum of Mars – Jewell (1895) Presents measurements of water vapor in the Earth’s atmosphere in different seasons. [Full text available in the abstract page]

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Papers on stalagmite reconstructions

Posted by Ari Jokimäki on June 15, 2010

This is a list of papers on the climate reconstructions from stalagmites. The list is not complete, and will most likely be updated in the future in order to make it more thorough and more representative.

High-resolution isotope records of early Holocene rapid climate change from two coeval stalagmites of Katerloch Cave, Austria – Boch et al. (2009) “Two coeval stalagmites from Katerloch Cave show pronounced intervals of low δ18O values around 8.2, 9.1, and 10.0 kyr (all ages are reported before the year 2000 AD) and represent an inorganic U–Th dated climate archive from the southeast of the European Alps, a region where only very few well-dated climate records exist. The O isotope curves, providing near-annual resolution, allow a direct comparison to the Greenland ice core records, as temperature was the primary factor controlling the O isotopic composition of Katerloch speleothems.” [Full text]

Modern stalagmite δ18O: Instrumental calibration and forward modelling – Baker & Bradley (2009) “Here, two approaches that can quantify the climate signal contained with stalagmite δ18O are discussed. Firstly, linear regression based approaches are reviewed, which correlate stalagmite δ18O with instrumental climate parameters such as temperature and rainfall. The advantages and disadvantages of complex linear regression approaches that attempt to account for groundwater mixing within the karst aquifer are discussed. Secondly, a forward modelling approach is introduced, where stalagmite δ18O is modelled from rainfall δ18O, surface climate parameters and a simple karst hydrology model. Using a case study from Gibraltar, this latter approach demonstrates that between stalagmite variability in δ18O of the order of 1‰ can be explained solely by differences in karst hydrology. Forward modelling suggests that a similar variability in δ18O might be observed between stalagmites within a cave, or between caves within a homogenous climate region, and highlights the difficulty in attempting to use δ18O as a paleo-thermometer.”

Analysis of the climate signal contained within δ18O and growth rate parameters in two Ethiopian stalagmites – Baker et al. (2007) “We combine surface and cave climate monitoring with multiple stalagmite parameters to help understand and calibrate the climate records contained within stalagmites from a region with strong rainfall seasonality. Two actively growing stalagmites from Ethiopia were analysed in order to investigate the climate signal contained within δ18O and growth rate parameters. The δ18O and growth rate of the two stalagmites give different responses to surface climate due to variations in the climate signal transfer. Both stalagmites (Merc-1 and Asfa-3) have a climate response that is seasonal; however this signal is subsequently smoothed by the mixing of event and storage water within the aquifer. Merc-1 responds more to high frequency (‘event’) climate, due to a greater ratio of event to storage water in this sample, whereas Asfa-3 responds more to low frequency (‘storage’) climate. In addition, different parameters respond to different seasons.” [Full text]

A precisely dated climate record for the last 9 kyr from three high alpine stalagmites, Spannagel Cave, Austria – Vollweiler et al. (2006) “Here we use the δ18O time-series of three stalagmites from the high alpine Spannagel cave (Austria) which grew in small distance from each other to construct a precisely dated, continuous δ18O curve for the last 9 kyr (COMNISPA). This speleothem record is not influenced by effects of kinetic isotope fractionation due to the low temperatures in the cave. Thus, the variations in δ18O can be interpreted in terms of past climate change. COMNISPA exhibits several oscillations within the Holocene, and their timing and duration is in agreement with that documented by other alpine archives.” [Full text]

Climate variability in the SE Alps of Italy over the past 17 000 years reconstructed from a stalagmite record – Frisia et al. (2005) “Stalagmite SV1 from Grotta Savi, located at the SE margin of the European Alps (Italy), is the first Alpine speleothem that continuously spans the past c. 17kyr. Extension rate and δ18Oc record for the Lateglacial probably reflect a combination of temperature and rainfall, with rainfall exerting the dominant effect. Low speleothem calcite δ18Oc values were recorded from c. 14.5 and 12.35 kyr, during GI-1 (Bølling— Allerød) interstadial, which in our interpretation, was warm and wet. The GS-1 (Younger Dryas) was characterized by a shift to heavier δ18Oc, coinciding with δ13Cc enrichment and extremely low extension rate (<8 μm/year). These characteristics indicate that GS-1 climate was cool and dry in the SE Alps." [Full text]

Reconstruction of temperature in the Central Alps during the past 2000 yr from a δ18O stalagmite record – Mangini et al. (2005) “The precisely dated isotopic composition of a stalagmite from Spannagel Cave in the Central Alps is translated into a highly resolved record of temperature at high elevation during the past 2000 yr. Temperature maxima during the Medieval Warm Period between 800 and 1300 AD are in average about 1.7 °C higher than the minima in the Little Ice Age and similar to present-day values. The high correlation of this record to Δ14C suggests that solar variability was a major driver of climate in Central Europe during the past 2 millennia.” [Full text]

Stalagmite growth and palaeo-climate: an inverse approach – Kaufmann & Dreybrodt (2005) “We describe the complicated growth of a stalagmite with a simple mathematical model, in which both the growth rate and the equilibrium diameter of stalagmites are functions of palaeo-climate variables. Hence, inverting a given stalagmite stratigraphy in terms of growth rate and equilibrium diameter can in principle recover the palaeo-climate signal. The strongly nonlinear dependence of these two geometrical parameters, however, limits the success of a formal inversion of stratigraphical data. In this paper, we explore the resolving power of both growth rate and equilibrium diameter data for the palaeo-climate signals temperature, carbon-dioxide concentration, and precipitation. We use numerically generated stalagmite stratigraphies as observational data, thus we know beforehand the palaeo-climate signal contained in the stratigraphic record. Our results indicate that both variations in carbon-dioxide concentrations (as a proxy of soil cover) and drip interval (as a proxy of precipitation) can be recovered from the stratigraphy. However, temperature variations are poorly resolved.” [Full text]

Stalagmite growth and palaeo-climate: the numerical perspective – Kaufmann (2003) “The growth of stalagmites can be approximated by a simple mathematical model, which depends on growth rate and equilibrium radius. These two parameters are controlled by the climate. Temperature variations derived from ice and deep-sea core data, together with models for changes in precipitation and soil cover, are used to derive stalagmite stratigraphies, which reflect the palaeo-climate variations imposed. In general, stalagmite growth is strongly correlated to temperature and the amount of carbon dioxide available in the soil. Furthermore, precipitation is correlated to the stalagmite diameter. However, several assumptions need to be made: (i) A functional relationship between temperature on the one hand and precipitation and soil cover on the other needs to be established. (ii) The kinetics of calcite dissolution and precipitation needs to be assigned, either under soil and epikarst conditions open to the atmosphere or under fractured rock conditions closed from the atmosphere. These assumptions are difficult to access from field data, and therefore a stalagmite stratigraphy can be ambiguous and not easily converted back into an unknown palaeo-climate signal.” [Full text]

Indian Ocean Climate and an Absolute Chronology over Dansgaard/Oeschger Events 9 to 13 – Burns et al. (2003) “Oxygen-isotope ratios of a stalagmite from Socotra Island in the Indian Ocean provide a record of changes in monsoon precipitation and climate for the time period from 42 to 55 thousand years before the present. The pattern of precipitation bears a striking resemblance to the oxygen-isotope record from Greenland ice cores, with increased tropical precipitation associated with warm periods in the high northern latitudes. The largest change, at the onset of interstadial 12, occurred very rapidly, in about 25 years. The chronology of the events found in our record requires a reevaluation of previously published time scales for climate events during this period.” [Full text]

Climate variability in central China over the last 1270 years revealed by high-resolution stalagmite records – Paulsen et al. (2003) “Oxygen and carbon isotopic variations in the upper section of a stalagmite (SF-1) from Buddha Cave (33°40′N 109°05′E) dated by 230Th/234U 210Pb and lamination counting to a time resolution as fine as 1–3 years have recorded climate changes in central China for the last 1270 years. The changes include those corresponding to the Medieval Warm Period Little Ice Age and 20th-century warming lending support to the global extent of these events. The isotopic records also show cycles of 33, 22, 11, 9.6, and 7.2 years. The 33-year cycle could well represent the ~35-year periodicity of climate fluctuations previously recognized in China and Europe. Cycles of 22, 11, and 9.6 years have often been associated with the Sunspot or lunar-orbit variations. The 7.2-year cycle was recently identified also in tree-ring records from an area close to Buddha Cave. These cycles suggest that external forcing (e.g. solar irradiance) may affect the summer monsoon over eastern China. The general consistency between the climate characteristics inferred from the stable isotope records of SF-1 and those from other proxy records underscores the value of stalagmites as recorders of paleoclimate.” [Full text]

Precise dating of Dansgaard–Oeschger climate oscillations in western Europe from stalagmite data – Genty et al. (2003) “Here we present carbon and oxygen isotope records from a stalagmite collected in southwest France which have been precisely dated using 234U/230Th ratios. We find rapid climate oscillations coincident with the established Dansgaard–Oeschger events between 83,000 and 32,000 years ago in both isotope records. The oxygen isotope signature is similar to a record from Soreq cave, Israel4, and deep-sea records5, 6, indicating the large spatial scale of the climate oscillations. The signal in the carbon isotopes gives evidence of drastic and rapid vegetation changes in western Europe, an important site in human cultural evolution. We also find evidence for a long phase of extremely cold climate in southwest France between 61.2 ± 0.6 and 67.4 ± 0.9 kyr ago.”

Holocene Forcing of the Indian Monsoon Recorded in a Stalagmite from Southern Oman – Fleitmann et al. (2003) “A high-resolution oxygen-isotope record from a thorium-uranium–dated stalagmite from southern Oman reflects variations in the amount of monsoon precipitation for the periods from 10.3 to 2.7 and 1.4to 0.4thousand years before the present (ky B.P.). Between 10.3 and 8 ky B.P., decadal to centennial variations in monsoon precipitation are in phase with temperature fluctuations recorded in Greenland ice cores, indicating that early Holocene monsoon intensity is largely controlled by glacial boundary conditions. After ~8 ky B.P., monsoon precipitation decreases gradually in response to changing Northern Hemisphere summer solar insolation, with decadal to multidecadal variations in monsoon precipitation being linked to solar activity.” [Full text]

Cyclic rapid warming on centennial-scale revealed by a 2650-year stalagmite record of warm season temperature – Tan et al. (2003) “A 2650-year (BC665-AD1985) warm season (MJJA: May, June, July, August) temperature reconstruction is derived from a correlation between thickness variations in annual layers of a stalagmite from Shihua Cave, Beijing, China and instrumental meteorological records. Observations of soil CO2 and drip water suggest that the temperature signal is amplified by the soil-organism-CO2 system and recorded by the annual layer series. Our reconstruction reveals that centennial-scale rapid warming occurred repeatedly following multicentenial cooling trends during the last millennia. These results correlate with different records from the Northern Hemisphere, indicating that the periodic alternation between cool and warm periods on a sub-millennial scale had a sub-hemispherical influence.” [Full text]

Late Holocene annual growth in three Alpine stalagmites records the influence of solar activity and the North Atlantic Oscillation on winter climate – Frisia et al. (2003) “Annual growth rates and the ratio of dark to light-colored calcite within single annual laminae in three contemporaneously deposited Holocene speleothems from Grotta di Ernesto, an Alpine cave in northern Italy, respond to changes in surface temperature rather than precipitation. Based on monitoring of present-day calcite growth, and correlation with instrumental data for surface climatic conditions, we interpret a higher ratio of dark to light-colored calcite and the simultaneous thinning of annual laminae as indicative of colder-than-present winters. Such dark and thin laminae occur in those parts of the three stalagmites deposited from AD 1650 to 1713 and from AD 1798 to 1840, as reconstructed through lamina counting. These periods correspond to the well-known Maunder and Dalton Minima of solar activity. An 11-yr cyclicity in growth rate, coupled with reduced calcite deposition during the historic minima of solar activity, is indicative of a solar influence on lamina thickness. Spectral analysis of the lamina thickness data also suggests that the North Atlantic Oscillation variability influenced winter temperatures. Based on the present-day controls on cave calcite formation, we infer that high-frequency changes in solar activity modulated the seasonal duration of soil CO2 production.”

A three thousand year record of North Atlantic climate – Proctor et al. (2002) “Annual band counting on three radiometrically dated stalagmites from NW Scotland, provides a record of growth rate variations for the last 3000 years. Over the period of instrumental meteorological records we have a good historical calibration with local climate (mean annual temperature/mean annual precipitation), regional climate (North Atlantic Oscillation) and sea surface temperature (SST; strongest at 65-70°N, 15-20°W), although the correlation with the latter breaks down prior to the instrumental record. This suggests that the climatic factors that force NW Scottish climate and therefore our stalagmite growth varied through time, and include winter NAO strength, the strength of the thermohaline circulation and possibly solar output. Spectral analysis was performed on the stalagmite growth rate time series. A spectral frequency of 50-70 years is predominant in two stalagmites that were deposited from 1000 to 3000 BP; a slightly longer frequency of 72-94 years is dominant from 1000 BP to present. These are the same as that observed in ocean GCM output for the North Atlantic region SSTs. Our stalagmites provide high resolution, precisely dated evidence of a similar periodicity predominating over the last 3000 years in a climate proxy record known to be sensitive to changes in forcing functions relevant to the North Atlantic sector.”

Correlation between high-resolution climate records from a Nanjing stalagmite and GRIP ice core during the last glaciation – Wang et al. (2001) “A 400-mm-long stalagmite from Tangshan Cave, Nanjing has been analyzed by a high-precision TIMS-U series dating method and also determined for oxygen and carbon stable isotopic compositions. The results provided a high-resolution paleoclimate record for eastern China during a time interval (from 54 000 to 19 000 aBP) of the last glaciation. The continuous record of oxygen-18 variations in the stalagmite, indicating a precipitation history of the East Asian monsoon, shows not only signals of the Heinrich events, but also the Dansgaard-Oeschger cycles which are first found in the last glacial climate record of the East Asian monsoon area. Although the stalagmite-based climatic signals match well with the GRIP ice core record, some differences between the two records can be recognized: (1) The last glacial climate changes in eastern China exhibited a long-term remarkably cooling trend, superimposed on which were four successive Bond’s cycles illustrated by the δ18O curve. This strong cooling tendency may be an effect of the strong summer monsoon event during the MIS 3 over the Tibetan Plateau. (2) There exist some phase differences of 1000–2000 years between the cooling events in the stalagmite-based climate signal and the GRIP ice core record. Such differences should be further verified by calibrations of multiple dating methods.”

Late Holocene Climate and Cultural Changes in the Southwestern United States – Polyak & Asmerom (2001) “Columnar stalagmites in caves of the Guadalupe Mountains during the late Holocene record a 4000-year annually resolved climate history for the southwestern United States. Annual banding, hiatuses, and high-precision uranium-series dating show a present day-like climate from 4000 to 3000 years ago, following a drier middle Holocene. A distinctly wetter and cooler period from 3000 to 800 years ago was followed by a period of present day-like conditions, with the exception of a slightly wetter interval from 440 to 290 years before the present. The stalagmite record correlates well with the archaeological record of changes in cultural activities of indigenous people. Such climate change may help to explain evidence of dwelling abandonment and population redistribution.”

A thousand year speleothem proxy record of North Atlantic climate from Scotland – Proctor et al. (2000) “Luminescent organic matter in stalagmites may form annual bands, allowing growth rate to be precisely determined. Stalagmite growth rate is controlled by precipitation, so annual bands can be used to derive long precipitation records. A continuously banded stalagmite from a cave in NW Scotland was used to provide a 1100 year high-resolution record of precipitation. The location of the cave means that precipitation is closely linked to the North Atlantic Oscillation, for which a record is also derived. This suggests that changes in the North Atlantic Oscillation state was an important control on European climate over the past millennium.” [Full text]

Climate and Vegetation History of the Midcontinent from 75 to 25 ka: A Speleothem Record from Crevice Cave, Missouri, USA – Dorale et al. (1998) “Four Missouri stalagmites yield consistent overlapping records of oxygen and carbon isotopic changes and provide a climate and vegetation history with submillennial resolution from 75 to 25 thousand years ago (ka). The thorium-230-dated records reveal that between 75 and 55 ka, the midcontinental climate oscillated on millennial time scales between cold and warm, and vegetation alternated among forest, savanna, and prairie. Temperatures were highest and prairie vegetation peaked between 59 and 55 ka. Climate cooled and forest replaced grassland at 55 ka, when global ice sheets began to build during the early part of Marine Oxygen Isotope Stage 3.”

A High-Resolution Record of Holocene Climate Change in Speleothem Calcite from Cold Water Cave, Northeast Iowa – Dorale et al. (1992) “High-precision uranium-thorium mass spectrometric chronology and 18O-13C isotopic analysis of speleothem calcite from Cold Water Cave in northeast Iowa have been used to chart mid-Holocene climate change. Significant shifts in 18O and 13C isotopic values coincide with well-documented Holocene vegetation changes. Temperature estimates based on 18O/16O ratios suggest that the climate warmed rapidly by about 3°C at 5900 years before present and then cooled by 4°C at 3600 years before present. Initiation of a gradual increase in 13C at 5900 years before present suggests that turnover of the forest soil biomass was slow and that equilibrium with prairie vegetation was not attained by 3600 years before present.”

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Thomas Karl – a lecture on NOAA surface temperature analysis

Posted by Ari Jokimäki on June 10, 2010

This was originally written in Finnish for Ilmastotieto-blog. This is just a summary of Karl’s lecture so English speaking audience would be better off just watching the lecture (link is given below), but I’ll put this summary out anyway just to emphasize some of the things Karl said.

Recently, AMS Policy Program lecturer was Thomas Karl who talked about NOAA surface temperature analysis. Specifically the subject was the global and the U.S. surface temperature, its analysis and the problems with their solutions.

Global surface temperature anomaly in NOAA analysis (monthly values in grey and 1-year running mean in black).

NOAA is the National Oceanic and Atmospheric Administration. Thomas Karl is the director of NOAA’s National Climatic Data Centerin (NCDC). NOAA’s NCDC is one of the few providers of global surface temperature analysis. David Easterling and Thomas Peterson have been doing the NOAA’s surface temperature analysis with Thomas Karl. NOAA’s data and methods are available for anyone to see and evaluate.

Three global surface temperature analyses have been made (sometimes also a fourth is mentioned – a russian analysis which is only an analysis of land-based records and additionally there’s also a japanese analysis but Karl didn’t mention that one). The differences between these three are the greatest in the oldest data. Oldest data has the biggest uncertainties so finding greatest differences there is not a surprise. All three analyses have different adjustments and the analysis differs also in other aspects, but still all three produce quite similar end result.

When studying global surface temperature analysis and especially the land and ocean temperatures separately, it becomes evident that land temperatures have more short-term changes. Ocean temperature is increasing more steadily and ocean temperature is lagging the land temperature by couple of tenths of a degree per century. This is most likely due to larger heat capacity of the oceans.

The geographical distribution of the temperature anomalies reveals that in the north there are areas of strong warming but there also still are some areas showing some cooling. An example of an area showing cooling is the southeast USA. The situation in the southeast USA has been suggested to be caused by the cooling effect of aerosols, especially sulfur-based aerosols. However, at any case, most of the Earth is warming.

Yet there has been some claims that warming has stopped. According to Karl that isn’t true. There is a long-term warming trend evident. Two last decades have been warmer than previous decades and the last decade has been warmer than its preceding decade. All the annual means in the 2000’s have been higher than the decadal mean of 1990’s and all the annual means in 1990’s were also higher than the decadal mean of 1980’s (Karl doesn’t mention it, but his graph shows that also all annual means of 1980’s were higher than the decadal mean of 1970’s).

Annual means (black dots) and decadal means (red lines) in NOAA analysis. After 1979 all annual means are higher than the decadal mean of the preceding decade (red dashed lines). In the lower right corner are the numerical values of the decadal means (middle column) and their difference from the mean of their preceding decade (right column).

Temperature measurements in the USA have been assembled to USHCN (United States Historical Climatology Network), where 1200 measurement stations has been selected based on the availability of long-term measurements. In the past the stations have experienced lot of changes. Some stations have had their measuring equipment changed. Some stations have changed location. Urban heat island has affected some stations. Some stations have been handled better than others and the environment has changed for some stations. Because of these changes all the stations are no longer ideal for measuring climate change. Stations like that have to be evaluated carefully and some adjustments has to be made to their data where possible, so that the stations can be used in the analysis. Karl shows an example where certain station location has changed several times in the past. He shows the original measurements and how the data has changed after the adjustments.

In the global analysis (GHCN, Global Historical Climatology Network) there is 7280 stations of which 4400 (all stations with 25 years or more data) are being used in the actual analysis. There is a new GHCN version (version 3) coming out soon. The new version has for the first time exactly the same analysis globally as the analysis in the USHCN. According to Karl, the methods used in the new version have been independently tested. In the new version the areas without measurement stations are being filled by an algorithm that uses the known relationships of nearby stations during comparable temperature changes. The Earth is warming a little bit more in the new version than in the current version.

Results of the temperature analysis are given as temperature anomalies (deviations from a reference value – usually a mean of certain time period) instead of absolute temperature values. There are some problems with the usage of absolute temperature values. For example the measurement stations are located at different heights compared to the sea level and the height of the station affects considerably the measured temperature. When stations are removed from the network, the height distribution of the stations in the network changes which may cause bias to the end result of the analysis. But when anomalies are being used, the removal of the stations doesn’t affect the end result so much.

Also the location of stations in the north-south direction causes an effect which shows in the absolute temperature values but doesn’t affect the anomalies that much. For example if many stations located in northern cold areas are removed from the network the average temperature rises due to number of “cold stations” decreasing. This kind of thing doesn’t affect the anomalies. Temperature anomalies are additionally area-averaged instead of calculating simple mean of all stations. The removal of northern stations actually causes a cooling bias when anomalies are being used, because there has been most warming in the northern areas so the removal of northern stations actually removes stations that have warmed the most.

The number of measurement stations has been decreasing strongly in last decades. Some have claimed that it distorts the analysis. When the stations still measuring today (there are about 2300 of them) are being compared to the whole network, the results are almost the same. This means that the removal of the stations haven’t affected the end result of the analysis. This is due to usage of anomalies and area-averaging. One doesn’t actually need much stations for global analysis. We want lot of stations because we also want to know how things work at smaller scales (they become handy for example when determining station adjustments).

The time of the observation also causes a problem for the analysis. Early in the morning temperature usually is lower than in the afternoon. If the observation time of some station changes for example from morning to afternoon, it causes a warming bias to the data of the station in question. This has caused a false urban heat effect. There is practically no time of observation bias in urban-based stations which have taken their measurements punctually always at the same time, while in the rural stations the times of observation have changed. The change has usually happened from the afternoon to the morning. This causes a cooling bias in the data of the rural stations. Therefore one must correct for the time of observation bias before one tries to determine the effect of the urban heat island. Karl shows a comparison between urban and rural stations after the time of observation bias has been corrected, and there’s hardly no difference when the situation of the USA is considered. In the global analysis the rural stations even seem to show slightly more warming than the urban stations. Stations are being classified as urban or rural with assistance of satellite measurements where the amount of light pollution is measured in different areas. Also some other information are being used, such as maps, population statistics, etc.

Karl says that the situation with the handling of the measurement stations (for their location and environment) – i.e. the “siting” – is not very good at the moment. NOAA is working on the problem. In the studies of NOAA only 70 out of 1200 stations in USA turned out to have good siting. Fortunately it seems that this doesn’t affect the analysis much because the result from the mentioned 70 stations is almost the same as the result from the rest of the stations. There’s also the Climate Reference Network, which has 114 well sited measurement stations that are being monitored closely. Climate Reference Network has been operational only for some time but during that time the USHCN and Climate Reference Network differ from each other only very little.

Above it was mentioned that there’s a new GHCN version coming soon and how in that version the Earth warms a little bit more than in current version. One reason for it is that the new version corrects the data for a new “anti-urban heat effect”. For a long time there has been a migration going on among the measurement stations from cities to airports. Most of the airports are located outside the cities so the stations are moving out of urban heat islands. Karl shows the difference between the airport measurement stations and other stations. It shows that the stations located in airports show less warming than other stations. It is due to many stations moving from cities to airports and it has been corrected in the new GHCN version.

Some of the graphs Karl showed. Upper left is the change in the time of observation in the US measurement stations. Upper right is the comparison between urban and rural stations in the USA after the time of observation bias has been corrected. Lower right are the 1979-2008 trends from different analyses. Lower center is the effect of the airport correction. Lower right is the effect of station removal.

In the sea surface temperature measurements the amount of samples taken has changed a lot in the past. When mapping the old measurement sites the common shipping routes show up clearly and the ocean areas outside the routes have not been measured much. In the present the ocean areas have been covered well starting from the middle of 20th century. The problem of sampling amount has been well-studied and its effect has been found to be much smaller than the global warming signal. In smaller regions the sampling is bigger problem. Much of the modern measurements are being done from measurement buoys with which the oceans have been covered rather well.

It has been observed that the buoy measurements are systematically cooler than the ship-based measurements. The buoys have been used only in recent times and the earlier measurements were made from ships. This causes a cooling bias to the analysis. Originally the measurements were taken with buckets – first with wooden ones (good thermal insulator), then with canves buckets (bad thermal insulator), and the modern buckets are insulated with rubber. Today the ship measurements are commonly done from the intake of the engine cooling water. Measurement is done in the engine room so the heat from the engines has already warmed the intake water a little before measurement. According to current best estimate the too warm measurements from the ships quite accurately cancel the too cool measurements from the buoys. The issue is currently under investigation.

The uncertainty of sea surface temperature measurements is larger in oldest measurements and then decreases but grows again in recent times due to above mentioned problems. The combined analysis from land and ocean measurements has lot of uncertainties which makes it difficult to say anything certain about individual years but the overall trend is statistically significant.

Karl shows briefly also a few other indicators of global warming. Today lakes and rivers are freezing later and the ice breaks up from them earlier. The volume of glaciers is decreasing all over the world. Arctic sea ice is steadily decreasing over long period. Heat content of the oceans has increased. Global sea level is rising. Plants start blooming 1-3 days earlier per decade. Ranges of many species are moving towards the poles.

In the end Karl returns to the surface temperature analysis and compares different analyses from surface measurements and from satellite measurements and from radiosonde measurements. Three surface temperature analyses (NOAA, GISS, and HadCRUT) give almost the same result for the temperature trend of 1979-2008. They are using same data, though, but their analyses differ from each other. There are also three satellite analyses (RSS, UAH, and NOAA has its own “Star”), but for them the 1979-2008 trend differs clearly from each other. The weather balloon radiosondes (4 analyses) also gives quite large spread for the trends. So the satellite and radiosonde analyses have large spread while all three surface temperature analyses give almost the same result. This suggests that the surface temperature analyses are currently more reliable.

There are large short term differences for example due to El Niños which warm the troposphere more than the surface. However, there’s no systematic difference between satellite and surface temperature analyses. In July, NOAA is going to publish a new report “State of the Climate Report 2009”, which gives some fresh information of the state of our climate. Report has been peer-reviewed and it has 275 authors from 45 different countries. Karl gives a brief review of the contents of the report by showing a few graphs from the report.

Source: AMS Policy Program, AMS Climate Briefing Series, Thomas Karl: The Temperature Fingerprint of Climate Change (page loads a 59 minute video). There’s also the PDF of the presentation material(>11MB file).

Additional information:
Smith, Thomas M., Richard W. Reynolds, Thomas C. Peterson, and Jay Lawrimore, Improvements to NOAA’s Historical Merged Land–Ocean Surface Temperature Analysis (1880–2006), Journal of Climate 2008; 21: 2283-2296, [abstract, full article]

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Papers on climate and size variations of birds

Posted by Ari Jokimäki on June 7, 2010

This is a list of papers on the climate related size variations of birds. The list is not complete, and will most likely be updated in the future in order to make it more thorough and more representative.

Wintering French Mallard and Teal Are Heavier and in Better Body Condition than 30 Years Ago: Effects of a Changing Environment? – Guillemain et al. (2010) “The aim of this study was to assess whether there have been morphometric changes in Mallard (Anas platyrhynchos) and Teal (Anas crecca) over the last 30 years at a major wintering site. Body mass and condition increased from the 1950s–1960s to the 2000s in both species. The increase in body mass amounted to as much as 11.7%, with no corresponding change in body size. Improved body condition was maintained from early to mid-winter, but then converged with historical values for late winter. Our interpretation is that increasingly benign ambient winter conditions permit ducks to maintain better energetic “safety margins” throughout winter, and that converging spring departure values may be related to evolutionary flight energetic optima. The observed changes are consistent with large-scale climate amelioration and local/regional habitat improvement (both anthropogenic).”

Declining body sizes in North American birds associated with climate change – Van Buskirk et al. (2010) “We report that migrating birds captured at a banding station in western Pennsylvania, USA, have exhibited steadily decreasing fat-free mass and wing chord since 1961, consistent with a response to a warmer climate. This confirms that phenotypic responses to climate change are currently underway in entire avian assemblages. Declines in body size were not explained by an index of habitat condition within the breeding or wintering distributions. Instead, size was negatively correlated with temperature in the previous year, and long-term trends were associated with the direction of natural selection acting on size over the winter: species undergoing the strongest selection favoring small wing chord showed the most rapid long-term declines in wing. Phenotypic changes are therefore in line with the prevailing selection regime.”

Differential migration of the sexes cannot be explained by the body size hypothesis in Teal – Guillemain et al. (2009) “The “body size hypothesis” predicts that if individuals of a population migrate different distances from the breeding to the wintering grounds, the distance should be related to the differential ability to cope with adverse conditions, with larger individuals wintering further north. Data collected over a 40-year period in Essex, UK and the Camargue, southern France, revealed that the average body mass of Teal ringed in Essex during these years was actually not greater than that of Teal ringed in the Camargue. A higher proportion of males were included in the UK ringing catch than in the French catch, but we found no support for the body size hypothesis to explain such differential migration of the sexes.”

Recent changes in body weight and wing length among some British passerine birds – Yom-Tov et al. (2006) “We tested the prediction that global warming has caused recent decreases in body weight (Bergmann’s rule) and increases in wing length (Allen’s rule) in 14 species of passerine birds at two localities in England: Wicken Fen (1968–2003) and Treswell Wood (1973–2003). Predicted long-term linear decreases in residual body weight occurred in four species: dunnocks (Wicken Fen), and great tits, blue tits and bullfinches (Treswell Wood). Non-linear decreases also occurred in reed warblers and blackcaps at Wicken Fen, which also had a surprising linear increase in residual body weight in blackbirds. Residual wing lengths increased linearly, as predicted, in six of seven species at Wicken Fen. Whereas there were non-linear long-term increases in wrens, dunnocks and blackbirds in Treswell Wood. Unexpected linear decreases also occurred in residual wing lengths in willow warblers (Wicken Fen), and blue tits, great tits and chaffinches (Treswell Wood). The most parsimonious explanation for such long-term changes in body weight is global warming, as predicted by Bergmann’s rule. Greater site and species-specific effects on wing length (e.g. non-linear changes plus shorter wings in the woodland habitat) suggest a less straightforward conclusion concerning Allen’s rule, probably because wing length involved variation in both bone and feather growth. Changes in residual body weights and wing lengths often differed between species and were sometimes non-linear, perhaps reflecting short-term modifications in selection pressures. Human-induced influences are discussed, such as avian predator population densities and land-use change. Short-term variation in temperature had little effect, but rainfall did explain the unusual increase in blackbird body weight, possibly as a result of improving food (earthworm) availability.” [Full text]

Long-term climatic trend and body size variation in teal Anas crecca – Guillemain et al. (2005) “We analysed ringing data from more than 38,000 teal Anas crecca caught at the Station Biologique de la Tour du Valat in the Camargue, Southern France, between September 1954 and April 1971. … The clearest pattern we observed was a positive relationship between temperature and wing length of the individuals: in all sex and age classes, birds tended to get smaller as temperature decreased. It is unlikely that this pattern was related to harsh climate affecting teal feather growth. Rather, we hypothesise that climate affected the distribution of the individuals in Europe: as temperature got colder, small birds found it still more difficult to remain in northern areas and increasingly used the Camargue as a refuge.” [Full text]

Does climate at different scales influence the phenology and phenotype of the River Warbler Locustella fluviatilis? – Kaňuščák et al. (2004) “We examined the North Atlantic Oscillation (NAO), precipitation in the Sahel zone, temperatures in the wintering grounds, on the migration route, and in the breeding area in relation to arrival dates and six morphological measures (wing, tarsus, bill, and tail lengths, body mass, body condition) in a Slovak population of the River Warbler Locustella fluviatilis. Arrival dates did not change significantly over the study period, but were significantly positively correlated with NAO, although not with temperatures in wintering areas, migration route or breeding area, nor with Sahel precipitation. Four of the six morphological traits changed during the study period and part of the change in condition index can be attributed to climatic variables. We suggest changes in birds phenotype vary with food availability, which fluctuate according to climate events.”

Should avian egg size increase as a result of global warming? A case study using the red-backed shrike ( Lanius collurio) – Tryjanowski et al. (2004) “In this paper, we present and discuss the potential effect of mean temperature in the breeding season on egg size of the red-backed shrike (Lanius collurio). During the 1971–2002 study period, egg volume of the red-backed shrike decreased significantly, birds arrived at the breeding site significantly earlier, and arrival date was correlated with the earliest first egg date. To our knowledge, we present the first evidence that avian egg size decreased significantly in a long-term study. However, we do not have experimental manipulations in support of our data and we can only conclude that the decrease in egg volume in the studied population might result as a consequence of a number of factors, including changes in temperature, as well as in food supply. Therefore climate change effects on a birds life-history traits can be more complex than just the simple direct effect of temperature.”

Strategy and Constraint in the Winter Fattening Response to Temperature in the Great Tit Parus major – Gosler (2002) “This paper uses observations of fat from a wild great tit population, studied over 17 years, to address these two areas. First, it demonstrates that temperature acts as a proximate factor influencing fat reserve levels. Secondly, by relating the time of observation more precisely than previously to temperatures prevailing at particular times during the previous 24 h, it is shown that while past temperature (e.g. 5 + h previously) is used to optimize fat reserves (strategic fattening), more immediate temperature may constrain the bird’s ability to achieve the optimum. 4. This constraint is demonstrated by a positive correlation between fat reserves and current temperature; probably the first demonstration of such a relationship. However, this constraining effect of temperature has diminished over the last 17 years, presumably because of climate amelioration.”

Global warming, Bergmann’s rule and body mass – are they related? The chukar partridge (Alectoris chukar) case – Yom-Tov et al. (2002) “Using museum specimens collected in Israel during the second half of the 20th century, no support was found for the hypothesis that body mass and tarsus length of chukar partridges Alectoris chukar has changed as a result of global warming. Body mass showed fluctuations during the year, reaching a maximum in late winter and spring and a minimum in summer. Bergmann’s rule predicts that in warm-blooded animals, races from warm regions will be smaller than races from colder regions, and a wider explanation states that body size is positively related to latitude. Because of its topography and varied climate, Israel provides a unique opportunity to separate partly the effect of latitude from that of ambient temperature, thus testing if Bergmann’s rule is related to latitude or to climatic variables. We found that body mass (and marginally also tarsus length) declined significantly with decreasing latitude in accordance with the wider explanation of Bergmann’s rule, but ambient temperature explained a much smaller fraction of the variation in body mass than latitude. These results weaken the traditional explanation to Bergmann’s rule that a heat conservation mechanism causes the latitudinal size variation.”

Global warming and body mass decline in Israeli passerine birds – Yom-Tov (2001) “Using museum specimens, I tested the prediction that the body mass and tarsus length of five resident passerine species in Israel declined between 1950 and 1999. The body mass of four species (the graceful warbler Prinia gracilis, the house sparrow Passer domesticus, the yellow-vented bulbul Pycnonotus xanthopygos and the Sardinian warbler Sylvia melanocephala, but not of the crested lark Galerida cristata) declined significantly during this period. Tarsus length also declined significantly during this period for two species (the graceful warbler and the house sparrow). Body condition (body mass–to–tarsus length ratio) decreased in the Sardinian warbler, the yellow–vented bulbul and the crested lark. It is suggested that the above declines in body mass and tarsus length are due to global warming and also in accordance with Bergmann’s rule. The above explanation does not exclude the possibility that other factors, such as a decrease in food availability, contributed to the decline in body mass.These declines may have serious implications for community structure and competition among bird species and may affect the survival of small passerines.” [Full text]

Global Warming and Egg Size of Birds – Järvinen (1994) “Global warming or climate change is known to have many effects on plants, but there has been relatively little research on global warming and animals, partly because too few long-term studies have been carried out. In northern areas, mean temperature is believed to be rising, and indeed during the last decades mean spring temperatures in Finnish Lapland have increased. In 1975-1993, mean air temperature during the main egg-laying period of a pied flycatcher Ficedula hypoleuca population correlated positively and significantly with mean egg volume of that population. Since larger eggs enjoy improved hatching success, global warming may alter birds’ reproductive strategies, because warmer weather may allow females to invest more resources in reproduction. This in turn may help birds rapidly conquer new areas when they become available and compensate for rising mortality rates to be expected elsewhere where warming means desiccation.”

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Papers on anthropogenic CO2 emissions

Posted by Ari Jokimäki on June 3, 2010

This is a list of papers on carbon dioxide emissions from anthropogenic sources with emphasis on the global estimates. Note that also some direct observations (although regional) have been done relating to this issue. The list is not complete, and will most likely be updated in the future in order to make it more thorough and more representative.

Consumption-based accounting of CO2 emissions – Davis & Caldeira (2010) “Much attention has been focused on the CO2 directly emitted by each country, but relatively little attention has been paid to the amount of emissions associated with the consumption of goods and services in each country. … Here, using the latest available data, we present a global consumption-based CO2 emissions inventory and calculations of associated consumption-based energy and carbon intensities. We find that, in 2004, 23% of global CO2 emissions, or 6.2 gigatonnes CO2, were traded internationally, primarily as exports from China and other emerging markets to consumers in developed countries. In some wealthy countries, including Switzerland, Sweden, Austria, the United Kingdom, and France, >30% of consumption-based emissions were imported, with net imports to many Europeans of >4 tons CO2 per person in 2004″

Global and regional drivers of accelerating CO2 emissions – Raupach et al. (2007) “CO2 emissions from fossil-fuel burning and industrial processes have been accelerating at a global scale, with their growth rate increasing from 1.1% y−1 for 1990–1999 to >3% y−1 for 2000–2004. The emissions growth rate since 2000 was greater than for the most fossil-fuel intensive of the Intergovernmental Panel on Climate Change emissions scenarios developed in the late 1990s. Global emissions growth since 2000 was driven by a cessation or reversal of earlier declining trends in the energy intensity of gross domestic product (GDP) (energy/GDP) and the carbon intensity of energy (emissions/energy), coupled with continuing increases in population and per-capita GDP.” [Full text]

World Carbon Dioxide Emissions: 1950–2050 – Schmalensee et al. (2006) “Emissions of carbon dioxide from the combustion of fossil fuels, which may contribute to long-term climate change, are projected through 2050 using reduced-form models estimated with national-level panel data for the period of 1950–1990. Using the same set of income and population growth assumptions as the Intergovernmental Panel on Climate Change (IPCC), we find that the IPCC’s widely used emissions growth projections exhibit significant and substantial departures from the implications of historical experience.” [Full text]

Historical CO2 emission and concentrations due to land use change of croplands and pastures by country – de Campos et al. (2005) “This work is aimed at estimating the historical land use change emission and concentrations of CO2 by country. Calculating the area differences of each biome (associated to carbon factors) converted to cropland (including urban areas) and pastures by country we calculated the land use change CO2 emission over the past 300 years using a new dataset, which is a well known one in the literature: the HYDE land use database. According to IPCC-SR-LULUCF (2000) the net cumulative global CO2 emission from land use change (1850–1990) is estimated to have been 499±205 Tg CO2, our result is 360 Tg CO2 for the same period, and Houghton’s (Houghton, RA, 2003a. Revised estimates of the annual net flux of carbon to the atmosphere from changes in land use and land management 1850–2000. Tellus 55B, 378–390) result is 492 Tg CO2.”

Carbon dioxide emissions from fossil-fuel use, 1751–1950 – Andres et al. (1999) “Newly compiled energy statistics allow for an estimation of the complete time series of carbon dioxide (CO2) emissions from fossil-fuel use for the years 1751 to the present. The time series begins with 3 × 106 metric tonnes carbon (C). This initial flux represents the early stages of the fossil-fuel era. The CO2 flux increased exponentially until World War I. The time series derived here seamlessly joins the modern 1950 to present time series. Total cumulative CO2 emissions through 1949 were 61.0 × 109 tonnes C from fossil-fuel use, virtually all since the beginning of the Industrial Revolution around 1860. The rate of growth continues to grow during present times, generating debate on the probability of enhanced greenhouse warming. In addition to global totals, national totals and 1° global distributions of the data have been calculated.”

Estimates of seasonal variation in fossil fuel CO2 emissions – Rotty (1987) “Seasonal variations are evident in the atmospheric CO2 concentration, and attempts to understand the causes of the variations require an estimate of the seasonal pattern of the fossil fuel CO2 source term. Estimates were made of CO2 emissions resulting from fossil fuel combustion on a month-to-month basis for a recent typical year (1982). Twenty-one countries account for over 86% of the fossil fuel emissions. Monthly fuel consumption was used directly for those countries where such fuel data were available, and for the others (e.g., USSR and China) fuel use data were deduced from other factors. Results indicate that CO2 emissions from gas fuel use show the largest seasonal variation, from 6.2% of the annual total in July or August to over 11.8% of the annual total in January. Liquid and solid fuel use shows less variation, with summer fractions about 7.8% of annual and winter about 9.2% of annual. Seasonal patterns are consistent throughout the Northern Hemisphere which dominates the global totals. Based on data for 87% of the world’s fossil fuel CO2 emissions, the highest release rate is 389.1 million tons of carbon in January and the lowest is 307.8 million tons of carbon in August.”

CO2 from fossil fuel burning: global distribution of emissions – Marland et al. (1985) “This paper describes an estimate of the areal distribution of CO2 emissions from energy sources. … Fuel consumption data by country, by state within the US, and by province in Canada are used to calculate CO2 emissions. … The final tabulation shows that 90% of total emissions are from the latitude band 20°–60° N, with the highest individual numbers from the grid spaces containing Frankfurt, London, and Tokyo.”

Carbon dioxide emissions from fossil fuels: a procedure for estimation and results for 1950–1982 – Marland & Rotty (1984) “Results of the calculations for 1980 through 1982 show decreases from 1979 CO2 emissions. This is the first time since the end of World War II that the emissions have decreased 3 years in succession. During the period following the 1973 escalation of fuel prices, the growth rate of emissions has been less than half what it was during the 1950s and 1960s (1.5%/year since 1973 as opposed to 4.5%/year through the 1950s and 1960s). Most of the change is a result of decreased growth in the use of oil.”

Closely related

Global, Regional, and National Fossil-Fuel CO2 Emissions – Carbon Dioxide Information Analysis Center

A Response to Climate Change: Cumulative Emissions of CO2

Estimates of Global, Regional, and National Annual CO2 Emissions from Fossil-Fuel Burning, Hydraulic Cement Production, and Gas Flaring: 1950-1992 – Boden et al. (1995) Apparently a non-peer-reviewed document. “This document describes the compilation, content, and format of the most comprehensive CO2-emissions database currently available. The database includes global, regional, and national annual estimates of CO2 emissions resulting from fossil-fuel burning, cement manufacturing, and gas flaring in oil fields for 1950-92 as well as the energy production, consumption, and trade data used for these estimates.”

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