AGW Observer

Observations of anthropogenic global warming

Papers on tropical troposphere hotspot

Posted by Ari Jokimäki on September 6, 2009

This list contains papers on the tropical troposphere hotspot. The list is not complete, and will most likely be updated in the future in order to make it more thorough and more representative.

UPDATE (February 4, 2017): Seidel et al. (2012), Mitchell et al. (2013), Varotsos et al. (2013), and Po-Chedley et al. (2015) added. Thanks to Barry for pointing them out.
UPDATE (January 2, 2012): Fu et al. (2011) added.
UPDATE (September 21, 2010): McIntyre & McKitrick (2009) removed (it didn’t pass peer-review) and McKitrick et al. (2010) added.
UPDATE (January 4, 2009): Addendum for Douglass et al. (2008) added, thanks to kse for pointing this out, see the comment section below.
UPDATE (December 24, 2009): Fu et al. (2004) and Steiner et al. (2009) moved to global troposphere list. Some of the papers are still in both lists.
UPDATE (December 24, 2009): Sherwood et al. (2008) added and final publication links to Bengtsson & Hodges (2009) added.
UPDATE (September 23, 2009): Steiner et al. (2009) added, thanks for John Cook for pointing this out (see the comment section below). McCarthy et al. (2008) added.
UPDATE (September 13, 2009): Bengtsson & Hodges (2009?) added.

Removing Diurnal Cycle Contamination in Satellite-Derived Tropospheric Temperatures: Understanding Tropical Tropospheric Trend Discrepancies – Po-Chedley et al. (2015) “Independent research teams have constructed long-term tropical time series of the temperature of the middle troposphere (TMT) using satellite Microwave Sounding Unit (MSU) and Advanced MSU (AMSU) measurements. Despite careful efforts to homogenize the MSU/AMSU measurements, tropical TMT trends beginning in 1979 disagree by more than a factor of 3. Previous studies suggest that the discrepancy in tropical TMT trends is caused by differences in both the NOAA-9 warm target factor and diurnal drift corrections. This work introduces a new observationally based method for removing biases related to satellite diurnal drift. Over land, the derived diurnal correction is similar to a general circulation model (GCM) diurnal cycle. Over ocean, the diurnal corrections have a negligible effect on TMT trends, indicating that oceanic biases are small. It is demonstrated that this method is effective at removing biases between coorbiting satellites and biases between nodes of individual satellites. Using a homogenized TMT dataset, the ratio of tropical tropospheric temperature trends relative to surface temperature trends is in accord with the ratio from GCMs. It is shown that bias corrections for diurnal drift based on a GCM produce tropical trends very similar to those from the observationally based correction, with a trend difference smaller than 0.02 K decade−1. Differences between various TMT datasets are explored further. Large differences in tropical TMT trends between this work and that of the University of Alabama in Huntsville (UAH) are attributed to differences in the treatment of the NOAA-9 target factor and the diurnal cycle correction.” Stephen Po-Chedley, Tyler J. Thorsen, and Qiang Fu, Journal of Climate, 28, 6, DOI: http://dx.doi.org/10.1175/JCLI-D-13-00767.1. [Full text]

Plausible reasons for the inconsistencies between the modeled and observed temperatures in the tropical troposphere – Varotsos et al. (2013) “We hereby attempt to detect plausible reasons for the discrepancies between the measured and modeled tropospheric temperature anomalies in the tropics. For this purpose, we calculate the trends of the upper-minus-lower tropospheric temperature anomaly differences (TAD) for both the measured and modeled time series during 1979–2010. The modeled TAD trend is significantly higher than that of the measured ones, confirming that the vertical amplification of warming is exaggerated in models. To investigate the cause of this exaggeration, we compare the intrinsic properties of the measured and modeled TAD by employing detrended fluctuation analysis (DFA). The DFA exponent obtained for the measured values reveals white noise behavior, while the exponent for the modeled ones shows that they exhibit long-range power law correlations. We suggest that the vertical amplification of warming derived from modeled simulations is weighted with a persistent signal, which should be removed in order to achieve better agreement with observations.” Varotsos, C. A., M. N. Efstathiou, and A. P. Cracknell (2013), Plausible reasons for the inconsistencies between the modeled and observed temperatures in the tropical troposphere, Geophys. Res. Lett., 40, 4906–4910, doi:10.1002/grl.50646. [Full text]

Revisiting the controversial issue of tropical tropospheric temperature trends – Mitchell et al. (2013) “Controversy remains over a discrepancy between modeled and observed tropical upper tropospheric temperature trends. This discrepancy is reassessed using simulations from the Coupled Climate Model Inter-comparison Project phase 5 (CMIP 5) together with radiosonde and surface observations that provide multiple realizations of possible “observed” temperatures given various methods of homogenizing the data. Over the 1979–2008 period, tropical temperature trends are not consistent with observations throughout the depth of the troposphere, and this primarily stems from a poor simulation of the surface temperature trends. This discrepancy is substantially reduced when (1) atmosphere-only simulations are examined or (2) the trends are considered as an amplification of the surface temperature trend with height. Using these approaches, it is shown that within observational uncertainty, the 5–95 percentile range of temperature trends from both coupled-ocean and atmosphere-only models are consistent with the analyzed observations at all but the upper most tropospheric level (150 hPa), and models with ultra-high horizontal resolution (≤ 0.5° × 0.5°) perform particularly well. Other than model resolution, it is hypothesized that this remaining discrepancy could be due to a poor representation of stratospheric ozone or remaining observational uncertainty.” Mitchell, D. M., P. W. Thorne, P. A. Stott, and L. J. Gray (2013), Revisiting the controversial issue of tropical tropospheric temperature trends, Geophys. Res. Lett., 40, 2801–2806, doi:10.1002/grl.50465. [Full text]

Reexamining the warming in the tropical upper troposphere: Models versus radiosonde observations – Seidel et al. (2012) “A recent study of 1979–2010 tropical tropospheric temperature trends in climate model simulations and satellite microwave sounding unit (MSU) observations concluded that, although both showed greater warming in the upper than lower troposphere, the vertical amplification of warming was exaggerated in most models. We repeat that analysis of temperature trends, vertical difference trends, and trend ratios using five radiosonde datasets. Some, but not all, comparisons support the notion that vertical amplification in models exceeds that observed. However, larger ranges of radiosonde trends compared with those for MSU, and the sensitivity of results to the upper-tropospheric level analyzed, make it difficult to conclude unambiguously that models are inconsistent with radiosonde observations. The larger ranges are due to the availability of more radiosonde datasets with different approaches for adjusting measurement biases. Together these two studies highlight challenges of using imperfect observations of tropical tropospheric temperature over a few decades to assess climate model performance.” Seidel, D. J., M. Free, and J. S. Wang (2012), Reexamining the warming in the tropical upper troposphere: Models versus radiosonde observations, Geophys. Res. Lett., 39, L22701, doi:10.1029/2012GL053850. [Full text]

On the warming in the tropical upper troposphere: Models versus observations – Fu et al. (2011) “IPCC (Intergovernmental Panel on Climate Change) AR4 (Fourth Assessment Report) GCMs (General Circulation Models) predict a tropical tropospheric warming that increases with height, reaches its maximum at ~200 hPa, and decreases to zero near the tropical tropopause. This study examines the GCM-predicted maximum warming in the tropical upper troposphere using satellite MSU (microwave sounding unit)-derived deep-layer temperatures in the tropical upper- and lower-middle troposphere for 1979–2010. While satellite MSU/AMSU observations generally support GCM results with tropical deep-layer tropospheric warming faster than surface, it is evident that the AR4 GCMs exaggerate the increase in static stability between tropical middle and upper troposphere during the last three decades.” Fu, Q., S. Manabe, and C. M. Johanson (2011), On the warming in the tropical upper troposphere: Models versus observations, Geophys. Res. Lett., 38, L15704, doi:10.1029/2011GL048101. [Full text]

Panel and multivariate methods for tests of trend equivalence in climate data series – McKitrick et al. (2010) “We explain panel and multivariate regressions for comparing trends in climate data sets. They impose minimal restrictions on the covariance matrix and can embed multiple linear comparisons, which is a convenience in applied work. We present applications comparing post-1979 modeled and observed temperature trends in the tropical lower- and mid-troposphere. Results are sensitive to the sample length. In data spanning 1979–1999, observed trends are not significantly different from zero or from model projections. In data spanning 1979–2009, the observed trends are significant in some cases but tend to differ significantly from modeled trends.” Ross McKitrick, Stephen McIntyre, Chad Herman, Atmospheric Science Letters, Article first published online: 17 SEP 2010, DOI: 10.1002/asl.290. [Full text]

On the evaluation of temperature trends in the tropical troposphere – Bengtsson & Hodges (2009) “A series of model experiments with the coupled Max-Planck-Institute ECHAM5/OM climate model have been investigated and compared with microwave measurements from the Microwave Sounding Unit (MSU) and re-analysis data for the period 1979-2008. … When forced by analysed sea surface temperature the model reproduces accurately the time-evolution of the mean outgoing tropospheric microwave radiation especially over tropical oceans but with a minor bias towards higher temperatures in the upper troposphere. … We have also compared the trend of the vertical lapse rate over the tropical oceans assuming that the difference between TLT and TMT is an approximate measure of the lapse rate. The TLT–TMT trend is larger in both the measurements and in the JRA25 than in the model runs by 0.04–0.06 K/decade. Furthermore, a calculation of all 30 year TLT–TMT trends of the unforced 500-year integration vary between ±0.03 K/decade suggesting that the models have a minor systematic warm bias in the upper troposphere.” [Full text]

Robust Tropospheric Warming Revealed by Iteratively Homogenized Radiosonde Data – Sherwood et al. (2008) “Results are presented from a new homogenization of data since 1959 from 527 radiosonde stations. … The troposphere warms at least as strongly as the surface, with local warming maxima at 300 hPa in the tropics” [Full text]

Toward Elimination of the Warm Bias in Historic Radiosonde Temperature Records—Some New Results from a Comprehensive Intercomparison of Upper-Air Data – Haimberger et al. (2008) “Both of the new adjusted radiosonde time series are in better agreement with satellite data than comparable published radiosonde datasets, not only for zonal means but also at most single stations. A robust warming maximum of 0.2–0.3K (10 yr)−1 for the 1979–2006 period in the tropical upper troposphere could be found in both homogenized radiosonde datasets.” [Full text]

Consistency of modelled and observed temperature trends in the tropical troposphere – Santer et al. (2008) “Early versions of satellite and radiosonde datasets suggested that the tropical surface had warmed more than the troposphere, while climate models consistently showed tropospheric amplification of surface warming in response to human-caused increases in well-mixed greenhouse gases (GHGs). We revisit such comparisons here using new observational estimates of surface and tropospheric temperature changes. We find that there is no longer a serious discrepancy between modelled and observed trends in tropical lapse rates. … Our results contradict a recent claim that all simulated temperature trends in the tropical troposphere and in tropical lapse rates are inconsistent with observations. This claim was based on use of older radiosonde and satellite datasets, and on two methodological errors: the neglect of observational trend uncertainties introduced by interannual climate variability, and application of an inappropriate statistical consistency test.” [Full text]

Warming maximum in the tropical upper troposphere deduced from thermal winds – Allen & Sherwood (2008) “Climate models and theoretical expectations have predicted that the upper troposphere should be warming faster than the surface. Surprisingly, direct temperature observations from radiosonde and satellite data have often not shown this expected trend. However, non-climatic biases have been found in such measurements. Here we apply the thermal-wind equation to wind measurements from radiosonde data, which seem to be more stable than the temperature data. … Warming patterns are consistent with model predictions except for small discrepancies close to the tropopause.” [Full text]

Assessing Bias and Uncertainty in the HadAT-Adjusted Radiosonde Climate Record – McCarthy et al. (2008) “This paper presents an automated homogenization method designed to replicate the decisions made by manual judgment in the generation of an earlier radiosonde dataset [i.e., the Hadley Centre radiosonde temperature dataset (HadAT)]. … Using climate model data to simulate biased radiosonde data, the authors show that limitations in the homogenization method are sufficiently large to explain much of the tropical trend discrepancy between HadAT and estimates from satellite platforms and climate models. … Previous assessment of trends and uncertainty in HadAT is likely to have underestimated the systematic bias in tropical mean temperature trends.” [Full text]

A comparison of tropical temperature trends with model predictions – Douglass et al. (2008) “We examine tropospheric temperature trends of 67 runs from 22 Climate of the 20th Century model simulations and try to reconcile them with the best available updated observations (in the tropics during the satellite era). Model results and observed temperature trends are in disagreement in most of the tropical troposphere, being separated by more than twice the uncertainty of the model mean.” [However, they ignored the observation uncertainties, see Santer et al. above and this RealClimate article.] [Full text] [Addendum]

Utility of Radiosonde Wind Data in Representing Climatological Variations of Tropospheric Temperature and Baroclinicity in the Western Tropical Pacific – Allen & Sherwood (2007) “Wind data show a slowing of the midlatitude jets in the Maritime Continent region since 1979, indicating that tropical thicknesses and temperature have increased less than those poleward of 25°N/S. This pattern is consistent with Microwave Sounding Unit temperature trends in the region but is exaggerated south of the equator in trends obtained directly from the temperature data. … These results support the use of the wind field as a way of overcoming heterogeneities in the temperature records in the monitoring of climate change patterns.” Allen, Robert J., Steven C. Sherwood, 2007, J. Climate, 20, 5229–5243. [Full text]

Tropical vertical temperature trends: A real discrepancy? – Thorne et al. (2007) “The uncertainty of inter-satellite calibration implied by available MSU T2 (mid-troposphere) estimates (σ = 0.035K) is much greater than that required to adequately resolve the trend (σ < 0.01K), or the amplification behaviour (implied amplification range ±0.95)."

Ozone, water vapor, and temperature in the upper tropical troposphere: Variations over a decade of MOZAIC measurements – Bortz et al. (2006) Provides another dataset for the tropics (by in situ aircraft samples), including water vapor and ozone measurements. “The decade of MOZAIC in situ measurements now available provides unique insights into the composition and processes of the upper tropical troposphere. In this analysis of temperature, water vapor, and ozone at flight cruise levels in the tropics, we find greater seasonal variability for all three parameters in the South (0–20°S) than in the North (0–20°N) Tropics.” [Full text]

The Vertical Structure of Temperature in the Tropics: Different Flavors of El Niño – Trenberth & Smith (2006) Discusses the strong role of El Niño on tropical temperatures. [Full text]

Temperature Trends in the Lower Atmosphere: Steps for Understanding and Reconciling Differences – Karl et al. (2006) Report about temperature trends in stratosphere and in troposphere. [Full text of chapter 1]

Satellite-derived vertical dependence of tropical tropospheric temperature trends – Fu & Johanson (2005) “For the tropical troposphere’s response to greenhouse forcing, GCMs predict a positive temperature trend that is greater than that at the surface and increases with height [e.g., Hansen et al., 2002]. … Tropical atmospheric temperatures in different tropospheric layers are retrieved using satellite-borne Microwave Sounding Unit (MSU) observations. We find that tropospheric temperature trends in the tropics are greater than the surface warming and increase with height. Our analysis indicates that the near-zero trend from Spencer and Christy’s MSU channel-2 angular scanning retrieval for the tropical low-middle troposphere (T2LT) is inconsistent with tropical tropospheric warming derived from their MSU T2 and T4 data.” [Full text]

Amplification of Surface Temperature Trends and Variability in the Tropical Atmosphere – Santer et al. (2005) Highlights the problematics of the issue, and also notes the role of El Niño in tropical temperature variability. “On multidecadal time scales, tropospheric amplification of surface warming is a robust feature of model simulations, but it occurs in only one observational data set. Other observations show weak, or even negative, amplification.” [Full text]

Closely related

The Radiative Signature of Upper Tropospheric Moistening – Soden et al. (2005) “Climate models predict that the concentration of water vapor in the upper troposphere could double by the end of the century as a result of increases in greenhouse gases. Such moistening plays a key role in amplifying the rate at which the climate warms in response to anthropogenic activities, but has been difficult to detect because of deficiencies in conventional observing systems. We use satellite measurements to highlight a distinct radiative signature of upper tropospheric moistening over the period 1982 to 2004. The observed moistening is accurately captured by climate model simulations and lends further credence to model projections of future global warming.” [Full text]

There are a lot of papers discussing troposphere temperature trends from the global perspective. Those papers are not on the list above, but have their own list:

Papers on tropospheric temperatures

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28 Responses to “Papers on tropical troposphere hotspot”

  1. Curious said

    Great compilation, thanks a lot!

    I think an index would be very helpful (at least with the paperlists). It could be linked in the “Pages” section.

    Cheers!

  2. Ari Jokimäki said

    Thanks for the suggestion. An index page has been in my plans, but I thought first to post some posts to include to the index page. But I guess it’s about time to do it, so you can expect it in a few days.

  3. Curious said

    It’s already there! Thanks a lot again!
    Your compliations are really good, I added your site to my resources list on AGW. 🙂

  4. Ari Jokimäki said

    Well, when you suggested it, I decided to do it right away so I don’t forget. Besides, the index page is also helpful to me for browsing around here.

  5. John Cook said

    New paper: Atmospheric temperature change detection with GPS radio occultation 1995 to 2008 – Steiner (2009)
    Existing upper air records of radiosonde and operational satellite data recently showed a reconciliation of temperature trends but structural uncertainties remain. GPS radio occultation (RO) provides a new high-quality record, profiling the upper troposphere and lower stratosphere with stability and homogeneity. Here we show that climate trends are since recently detected by RO data, consistent with earliest detection times estimated by simulations. Based on a temperature change detection study using the RO record within 1995–2008 we found a significant cooling trend in the tropical lower stratosphere in February while in the upper troposphere an emerging warming trend is obscured by El Niño variability. The observed trends and warming/cooling contrast across the tropopause agree well with radiosonde data and basically with climate model simulations, the latter tentatively showing less contrast. The performance of the short RO record to date underpins its capability to become a climate benchmark record in the future.

  6. Ari Jokimäki said

    Thanks, John. I added it, and I also added McCarthy et al. (2008). Curiously, I was just yesterday browsing new papers in journals, including GRL, but I missed this one. It perhaps wasn’t in the list yet, but I don’t know if I had paid much attention to it anyway because the title doesn’t really say that they are studying the “hotspot”. 🙂

  7. Ari Jokimäki said

    I added Sherwood et al. (2008). It’s more about the whole tropophere, but I included it here as they do have nice tropical troposphere hotspot in their data (as witnessed by their figure 6).

  8. kse said

    I think that you should include the replay from Douglass to the critique about the version of ROABCORE:

    LINK TO PAPER

    and possibly link to a paper pointing out the problems with ERA-40 and its implications to reanalyses:

    LINK TO PAPER

  9. Ari Jokimäki said

    (In case you’re wondering, I fixed the link presentations in your post, they weren’t showing properly, because of missing HTML tags.)

    Thanks. Douglass et al. doesn’t seem to be published yet, but I added it anyway.

    Sakamoto & Christy don’t seem to be discussing the hot spot issue specifically (at least based on the abstract), so I didn’t add it.

  10. kse said

    (Eh… I hope that some day I’ll learn how to use these different tagging styles in each blog service…)

    It is true that Sakamoto & Christy do not discuss about the hot spot issue. However, their paper supports Douglass et. al. doubts about ERA-40 and thus ROABCORE 1.3-4. Furthermore, that paper nullifies (at least partially) some of the critique expressed in Santer et. al. (2008).

    So, if we combine Sakamoto & Christy and McIntyre & McKitrick (2009) (bad data + poor analysis), is there anything concrete left in Santer et. al (2008)?

  11. Ari Jokimäki said

    I removed McIntyre & McKitrick (2009) because it didn’t pass peer-review, and I added McKitrick et al. (2010).

  12. Ari Jokimäki said

    I updated this list (checked links, etc.). Soden et al. (2005) now has full text link.

  13. New paper:
    Tropospheric temperature trends: history of an ongoing controversy (Thorne et al 2010)
    Changes in atmospheric temperature have a particular importance in climate research because climate models consistently predict a distinctive vertical profile of trends. With increasing greenhouse gas concentrations, the surface and troposphere are consistently projected to warm, with an enhancement of that warming in the tropical upper troposphere. Hence, attempts to detect this distinct ‘fingerprint’ have been a focus for observational studies. The topic acquired heightened importance following the 1990 publication of an analysis of satellite data which challenged the reality of the projected tropospheric warming. This review documents the evolution over the last four decades of understanding of tropospheric temperature trends and their likely causes. Particular focus is given to the difficulty of producing homogenized datasets, with which to derive trends, from both radiosonde and satellite observing systems, because of the many systematic changes over time. The value of multiple independent analyses is demonstrated. Paralleling developments in observational datasets, increased computer power and improved understanding of climate forcing mechanisms have led to refined estimates of temperature trends from a wide range of climate models and a better understanding of internal variability. It is concluded that there is no reasonable evidence of a fundamental disagreement between tropospheric temperature trends from models and observations when uncertainties in both are treated comprehensively.

  14. Ari Jokimäki said

    Thanks Jesús! As this is more general paper on tropospheric temperatures, I added it to the list of tropospheric temperatures. I actually did a Finnish news article on this paper, but I have been lazy in adding the new papers to these lists.

  15. Ari Jokimäki said

    I added. Fu et al. (2011).

  16. barry said

    Ari, did you move all these papers to the list on tropospheric temps? A note to that effect, with a link, would be good. Unless there is something wrong with my browser, I only see two papers here.

  17. Ari Jokimäki said

    All papers are still here, and I also see them with my browser. I checked the file and there shouldn’t be any special characters that would cut the list after two papers. If you still have the problem, it would be good if you could pinpoint the exact point where the list ends for you.

  18. barry said

    I see the updates at the top, Fu et al 2011 and Mckitrick et al 2010, indluding the abstracts, and that’s where the list stops. Below is a screenshot.

    I’m using firefox browser on Windows 7 Ultimate

  19. Ari Jokimäki said

    Ok, thanks. It should work now, I changed the URL to McKitrick et al. full text. For some reason the original link made the page cut there with Firefox, but not with IE.

  20. barry said

    Yep, fixed. 🙂

  21. barry said

    2015 paper on the hotspot:

    http://iopscience.iop.org/article/10.1088/1748-9326/10/5/054007/meta

    “We present an updated version of the radiosonde dataset homogenized by Iterative Universal Kriging (IUKv2), now extended through February 2013, following the method used in the original version (Sherwood et al 2008 Robust tropospheric warming revealed by iteratively homogenized radiosonde data J. Clim. 21 5336–52). This method, in effect, performs a multiple linear regression of the data onto a structural model that includes both natural variability, trends, and time-changing instrument biases, thereby avoiding estimation biases inherent in traditional homogenization methods. One modification now enables homogenized winds to be provided for the first time. This, and several other small modifications made to the original method sometimes affect results at individual stations, but do not strongly affect broad-scale temperature trends. Temperature trends in the updated data show three noteworthy features. First, tropical warming is equally strong over both the 1959–2012 and 1979–2012 periods, increasing smoothly and almost moist-adiabatically from the surface (where it is roughly 0.14 K/decade) to 300 hPa (where it is about 0.25 K/decade over both periods), a pattern very close to that in climate model predictions. This contradicts suggestions that atmospheric warming has slowed in recent decades or that it has not kept up with that at the surface. Second, as shown in previous studies, tropospheric warming does not reach quite as high in the tropics and subtropics as predicted in typical models. Third, cooling has slackened in the stratosphere such that linear trends since 1979 are about half as strong as reported earlier for shorter periods. Wind trends over the period 1979–2012 confirm a strengthening, lifting and poleward shift of both subtropical westerly jets; the Northern one shows more displacement and the southern more intensification, but these details appear sensitive to the time period analysed. There is also a trend toward more easterly winds in the middle and upper troposphere of the deep tropics.”

  22. barry said

    Reexamining the warming in the tropical upper troposphere: Models versus radiosonde observations

    Seidel, D. J., M. Free, and J. S. Wang (2012)

    http://onlinelibrary.wiley.com/doi/10.1029/2012GL053850/full

    “A recent study of 1979–2010 tropical tropospheric temperature trends in climate model simulations and satellite microwave sounding unit (MSU) observations concluded that, although both showed greater warming in the upper than lower troposphere, the vertical amplification of warming was exaggerated in most models. We repeat that analysis of temperature trends, vertical difference trends, and trend ratios using five radiosonde datasets. Some, but not all, comparisons support the notion that vertical amplification in models exceeds that observed. However, larger ranges of radiosonde trends compared with those for MSU, and the sensitivity of results to the upper-tropospheric level analyzed, make it difficult to conclude unambiguously that models are inconsistent with radiosonde observations. The larger ranges are due to the availability of more radiosonde datasets with different approaches for adjusting measurement biases. Together these two studies highlight challenges of using imperfect observations of tropical tropospheric temperature over a few decades to assess climate model performance.”

  23. barry said

    Plausible reasons for the inconsistencies between the modeled and observed temperatures in the tropical troposphere

    Varotsos, C. A., M. N. Efstathiou, and A. P. Cracknell (2013)

    “We hereby attempt to detect plausible reasons for the discrepancies between the measured and modeled tropospheric temperature anomalies in the tropics. For this purpose, we calculate the trends of the upper-minus-lower tropospheric temperature anomaly differences (TAD) for both the measured and modeled time series during 1979–2010. The modeled TAD trend is significantly higher than that of the measured ones, confirming that the vertical amplification of warming is exaggerated in models. To investigate the cause of this exaggeration, we compare the intrinsic properties of the measured and modeled TAD by employing detrended fluctuation analysis (DFA). The DFA exponent obtained for the measured values reveals white noise behavior, while the exponent for the modeled ones shows that they exhibit long-range power law correlations. We suggest that the vertical amplification of warming derived from modeled simulations is weighted with a persistent signal, which should be removed in order to achieve better agreement with observations.”

  24. barry said

    Link for the last:

    http://onlinelibrary.wiley.com/doi/10.1002/grl.50646/full

  25. barry said

    Revisiting the controversial issue of tropical tropospheric temperature trends

    Mitchell, D. M., P. W. Thorne, P. A. Stott, and L. J. Gray (2013)

    “Controversy remains over a discrepancy between modeled and observed tropical upper tropospheric temperature trends. This discrepancy is reassessed using simulations from the Coupled Climate Model Inter-comparison Project phase 5 (CMIP 5) together with radiosonde and surface observations that provide multiple realizations of possible “observed” temperatures given various methods of homogenizing the data. Over the 1979–2008 period, tropical temperature trends are not consistent with observations throughout the depth of the troposphere, and this primarily stems from a poor simulation of the surface temperature trends. This discrepancy is substantially reduced when (1) atmosphere-only simulations are examined or (2) the trends are considered as an amplification of the surface temperature trend with height. Using these approaches, it is shown that within observational uncertainty, the 5–95 percentile range of temperature trends from both coupled-ocean and atmosphere-only models are consistent with the analyzed observations at all but the upper most tropospheric level (150 hPa), and models with ultra-high horizontal resolution (≤ 0.5° × 0.5°) perform particularly well. Other than model resolution, it is hypothesized that this remaining discrepancy could be due to a poor representation of stratospheric ozone or remaining observational uncertainty.”

    http://onlinelibrary.wiley.com/doi/10.1002/grl.50465/full

  26. barry said

    Removing Diurnal Cycle Contamination in Satellite-Derived Tropospheric Temperatures: Understanding Tropical Tropospheric Trend Discrepancies

    Stephen Po-Chedley, Tyler J. Thorsen, and Qiang Fu (2015)

    “Independent research teams have constructed long-term tropical time series of the temperature of the middle troposphere (TMT) using satellite Microwave Sounding Unit (MSU) and Advanced MSU (AMSU) measurements. Despite careful efforts to homogenize the MSU/AMSU measurements, tropical TMT trends beginning in 1979 disagree by more than a factor of 3. Previous studies suggest that the discrepancy in tropical TMT trends is caused by differences in both the NOAA-9 warm target factor and diurnal drift corrections. This work introduces a new observationally based method for removing biases related to satellite diurnal drift. Over land, the derived diurnal correction is similar to a general circulation model (GCM) diurnal cycle. Over ocean, the diurnal corrections have a negligible effect on TMT trends, indicating that oceanic biases are small. It is demonstrated that this method is effective at removing biases between coorbiting satellites and biases between nodes of individual satellites. Using a homogenized TMT dataset, the ratio of tropical tropospheric temperature trends relative to surface temperature trends is in accord with the ratio from GCMs. It is shown that bias corrections for diurnal drift based on a GCM produce tropical trends very similar to those from the observationally based correction, with a trend difference smaller than 0.02 K decade−1. Differences between various TMT datasets are explored further. Large differences in tropical TMT trends between this work and that of the University of Alabama in Huntsville (UAH) are attributed to differences in the treatment of the NOAA-9 target factor and the diurnal cycle correction.”

    http://journals.ametsoc.org/doi/abs/10.1175/JCLI-D-13-00767.1

    [Full paper] – http://www.atmos.washington.edu/~qfu/Publications/jtech.pochedley.2015.pdf

  27. Ari Jokimäki said

    Thanks once again, Barry. 🙂 I added the first paper (Sherwood) to the tropospheric temperature list and all the others to this list. I also added the temperature reconstruction paper you suggested in the other thread to the reconstruction list.

  28. Atomsks Sanakan said

    Papers:

    “Comparing Tropospheric Warming in Climate Models and Satellite Data”
    http://journals.ametsoc.org/doi/pdf/10.1175/JCLI-D-16-0333.1

    “Homogenization of the Global Radiosonde Temperature Dataset through Combined Comparison with Reanalysis Background Series and Neighboring Stations”
    http://journals.ametsoc.org/doi/full/10.1175/JCLI-D-11-00668.1

    “New estimates of tropical mean temperature trend profiles from zonal mean historical radiosonde and pilot
balloon wind shear observations”
    https://www.researchgate.net/profile/L_Haimberger/publication/274645707_New_estimates_of_tropical_mean_temperature_trend_profiles_from_zonal_mean_historical_radiosonde_and_pilot_balloon_wind_shear_observations_TROPICAL_TEMP_TREND_FROM_UPPER_AIR_WIND/links/577e5f6808aed807ae7b1558.pdf

    “Atmospheric changes through 2012 as shown by iteratively homogenized radiosonde temperature and wind data (IUKv2)”
    http://iopscience.iop.org/article/10.1088/1748-9326/10/5/054007

    “Estimating low-frequency variability and trends in atmospheric temperature using ERA-Interim”
    http://onlinelibrary.wiley.com/doi/10.1002/qj.2317/full

    “Radiosonde bias adjustments – ERA-CLIM2 Project; Bias adjustments for radiosonde temperature, wind and humidity from existing reanalysis feedback; Deliverable 4.1 of EU 7FP project ERA-CLIM2 (Grant No. 607029)”
    http://www.era-clim.eu/ERA-CLIM2/Products/ERA-CLIM2_D4.1.pdf

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