Papers on tropospheric temperatures
Posted by Ari Jokimäki on December 24, 2009
This is a list of papers on the temperature of the troposphere. 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): Sherwood & Nishant (2015) added. Thanks to Barry for pointing it out.
UPDATE (August 26, 2013): Gaffen et al. (2000) and Seidel et al. (2004) added, thanks to Barry for pointing them out.
UPDATE (February 8, 2011): Thorne et al. (2010) added, thanks to Jesús Rosino for pointing it out in the discussion of tropospheric hot spot list.
UPDATE (November 11, 2010): Hurrell & Trenberth (1998), Wentz & Schabel (1998), Christy et al. (1997), Hurrell & Trenberth (1997), Hansen et al. (1995), and Jones (1994) added.
Atmospheric changes through 2012 as shown by iteratively homogenized radiosonde temperature and wind data (IUKv2) – Sherwood & Nishant (2015) “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.” Steven C Sherwood and Nidhi Nishant 2015 Environ. Res. Lett. 10 054007, DOI: https://doi.org/10.1088/1748-9326/10/5/054007. [Full text]
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.” Peter W. Thorne, John R. Lanzante, Thomas C. Peterson, Dian J. Seidel, Keith P. Shine, Wiley Interdisciplinary Reviews: Climate Change, Volume 2, Issue 1, pages 66–88, January/February 2011, DOI: 10.1002/wcc.80. [Full text]
Critically Reassessing Tropospheric Temperature Trends from Radiosondes Using Realistic Validation Experiments – Titchner et al. (2009) “Biases and uncertainties in large-scale radiosonde temperature trends in the troposphere are critically reassessed. … The homogenization system consistently reduces the bias in the daytime tropical, global, and Northern Hemisphere (NH) extratropical trends but underestimates the full magnitude of the bias. … The implications are that tropical tropospheric trends in the unadjusted daytime radiosonde observations, and in many current upper-air datasets, are biased cold, but the degree of this bias cannot be robustly quantified. Therefore, remaining biases in the radiosonde temperature record may account for the apparent tropical lapse rate discrepancy between radiosonde data and climate models. Furthermore, the authors find that the unadjusted global and NH extratropical tropospheric trends are biased cold in the daytime radiosonde observations.” [Full text]
Atmospheric temperature change detection with GPS radio occultation 1995 to 2008 – Steiner et al. (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. … 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.” [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. … Relatively few artifacts were detected in wind shear, and associated adjustments were indistinguishable from random adjustments. Temperature artifacts were detected most often in the late 1980s–early 1990s. … The troposphere warms at least as strongly as the surface, with local warming maxima at 300 hPa in the tropics and in the boundary layer of the extratropical Northern Hemisphere (ENH). Tropospheric warming since 1959 is almost hemispherically symmetric, but since 1979 it is significantly stronger in ENH and weaker in the extratropical Southern Hemisphere (ESH). ESH trends are relatively uncertain because of poor sampling. Stratospheric cooling also remains stronger than indicated by MSU and likely excessive.” [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]
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. This objective assessment of radiosonde homogenization supports the conclusions of the synthesis report of the U.S. Climate Change Science Program (CCSP), and associated research, regarding potential bias in tropospheric temperature records from radiosondes.” [Full text]
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.” [Full text]
Tropospheric temperature change since 1979 from tropical radiosonde and satellite measurements – Christy et al. (2007) “Temperature change of the lower troposphere (LT) in the tropics (20°S–20°N) during the period 1979–2004 is examined using 58 radiosonde (sonde) stations and the microwave-based satellite data sets of the University of Alabama in Huntsville (UAH v5.2) and Remote Sensing Systems (RSS v2.1). … When the largest discontinuities in the sondes are detected and removed through comparison with UAH data, the trend of day and night releases combined becomes +0.09, and using RSS data, +0.12. Relative to several data sets, the RSS data show a warming shift, broadly occurring in 1992, of between +0.07 K and +0.13 K. Because the shift occurs at the time NOAA-12 readings began to be merged into the satellite data stream and large NOAA-11 adjustments were applied, the discrepancy appears to be due to bias adjustment procedures. Several comparisons are consistent with a 26-year trend and error estimate for the UAH LT product for the full tropics of +0.05 ± 0.07, which is very likely less than the tropical surface trend of +0.13 K decade−1.” [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]
Biases in Stratospheric and Tropospheric Temperature Trends Derived from Historical Radiosonde Data – Randel & Wu (2006) “Detailed comparisons of one radiosonde dataset with collocated satellite measurements from the Microwave Sounding Unit reveal time series differences that occur as step functions or jumps at many stations. These jumps occur at different times for different stations, suggesting that the differences are primarily related to problems in the radiosonde data, rather than in the satellite record. As a result of these jumps, the radiosondes exhibit systematic cooling biases relative to the satellites. A large number of the radiosonde stations in the Tropics are influenced by these biases, suggesting that cooling in the tropical lower stratosphere is substantially overestimated in these radiosonde data. Comparison of trends from stations with larger and smaller biases suggests the cooling bias extends into the tropical upper troposphere. Significant biases are observed in both daytime and nighttime radiosonde measurements.” [Full text]
Radiosonde Daytime Biases and Late-20th Century Warming – Sherwood et al. (2005) “The temperature difference between adjacent 0000 and 1200 UTC weather balloon (radiosonde) reports shows a pervasive tendency toward cooler daytime compared to nighttime observations since the 1970s, especially at tropical stations. Several characteristics of this trend indicate that it is an artifact of systematic reductions over time in the uncorrected error due to daytime solar heating of the instrument and should be absent from accurate climate records. Although other problems may exist, this effect alone is of sufficient magnitude to reconcile radiosonde tropospheric temperature trends and surface trends during the late 20th century.” [Full text]
The Effect of Diurnal Correction on Satellite-Derived Lower Tropospheric Temperature – Mears & Wentz (2005) “Satellite-based measurements of decadal-scale temperature change in the lower troposphere have indicated cooling relative to Earth’s surface in the tropics. Such measurements need a diurnal correction to prevent drifts in the satellites’ measurement time from causing spurious trends. We have derived a diurnal correction that, in the tropics, is of the opposite sign from that previously applied. When we use this correction in the calculation of lower tropospheric temperature from satellite microwave measurements, we find tropical warming consistent with that found at the surface and in our satellite-derived version of middle/upper tropospheric temperature.” [Full text]
Uncertainty in Signals of Large-Scale Climate Variations in Radiosonde and Satellite Upper-Air Temperature Datasets – Seidel et al. (2004) “There is no single reference dataset of long-term global upper-air temperature observations, although several groups have developed datasets from radiosonde and satellite observations for climate-monitoring purposes. The existence of multiple data products allows for exploration of the uncertainty in signals of climate variations and change. This paper examines eight upper-air temperature datasets and quantifies the magnitude and uncertainty of various climate signals, including stratospheric quasi-biennial oscillation (QBO) and tropospheric ENSO signals, stratospheric warming following three major volcanic eruptions, the abrupt tropospheric warming of 1976–77, and multidecadal temperature trends. Uncertainty estimates are based both on the spread of signal estimates from the different observational datasets and on the inherent statistical uncertainties of the signal in any individual dataset. The large spread among trend estimates suggests that using multiple datasets to characterize large-scale upper- air temperature trends gives a more complete characterization of their uncertainty than reliance on a single dataset. For other climate signals, there is value in using more than one dataset, because signal strengths vary. However, the purely statistical uncertainty of the signal in individual datasets is large enough to effectively encompass the spread among datasets. This result supports the notion of an 11th climate-monitoring principle, augmenting the 10 principles that have now been generally accepted (although not generally implemented) by the climate community. This 11th principle calls for monitoring key climate variables with multiple, independent observing systems for measuring the variable, and multiple, independent groups analyzing the data.” Seidel, D. J., and Coauthors, 2004: Uncertainty in Signals of Large-Scale Climate Variations in Radiosonde and Satellite Upper-Air Temperature Datasets. J. Climate, 17, 2225–2240. doi: http://dx.doi.org/10.1175/1520-0442(2004)0172.0.CO;2. [Full text]
Stratospheric cooling and the troposphere – Gillett et al. (2004) “Here we apply the method of Fu et al. to output from a state-of-the-art coupled climate model and show that simulated tropospheric temperature trends are consistent with those observed and that their method is robust.”
Stratospheric Influences on MSU-Derived Tropospheric Temperature Trends: A Direct Error Analysis – Fu & Johanson (2004) “Retrievals of tropospheric temperature trends from data of the Microwave Sounding Unit (MSU) are subject to biases related to the strong cooling of the stratosphere during the past few decades. The magnitude of this stratospheric contamination in various retrievals is estimated using stratospheric temperature trend profiles based on observations. It is found that from 1979 to 2001 the stratospheric contribution to the trend of MSU channel-2 brightness temperature is about −0.08 K decade−1, which is consistent with the findings of Fu et al. In the retrieval method developed by Fu et al. based on a linear combination of MSU channels 2 and 4, the stratospheric influence is largely removed, leaving a residual influence of less than ±0.01 K decade−1. This method is also found to be more accurate than the angular scanning retrieval technique of Spencer and Christy to remove the stratospheric contamination.” [Full text]
Contribution of stratospheric cooling to satellite-inferred tropospheric temperature trends – Fu et al. (2004) “Here we show that trends in MSU channel 2 temperatures are weak because the instrument partly records stratospheric temperatures whose large cooling trend offsets the contributions of tropospheric warming. We quantify the stratospheric contribution to MSU channel 2 temperatures using MSU channel 4, which records only stratospheric temperatures. The resulting trend of reconstructed tropospheric temperatures from satellite data is physically consistent with the observed surface temperature trend. For the tropics, the tropospheric warming is ~ 1.6 times the surface warming, as expected for a moist adiabatic lapse rate.” [Full text]
Global Warming Trend of Mean Tropospheric Temperature Observed by Satellites – Vinnikov & Grody (2003) “We have analyzed the global tropospheric temperature for 1978 to 2002 with the use of passive microwave sounding data from the NOAA series of polar orbiters and the Earth Observing System Aqua satellite. To accurately retrieve the climatic trend, we combined the satellite data with an analytic model of temperature that contains three different time scales: a linear trend and functions that define the seasonal and diurnal cycles. Our analysis shows a trend of +0.22° to 0.26°C per 10 years, consistent with the global warming trend derived from surface meteorological stations.”
A Reanalysis of the MSU Channel 2 Tropospheric Temperature Record – Mears et al. (2003) “Results presented herein show a global trend of 0.097 ± 0.020 K decade−1, generally agreeing with the work of Prabhakara et al. but in disagreement with the MSU analysis of Christy and Spencer, which shows significantly less (0.09 K decade−1) warming. Differences in the various methodologies are discussed and it is demonstrated that the principal source of these discrepancies is in the treatment of errors due to variations in the temperature of the MSU hot calibration target.” [Full text]
Error Estimates of Version 5.0 of MSU–AMSU Bulk Atmospheric Temperatures – Christy et al. (2003) “Deep-layer temperatures derived from satellite-borne microwave sensors since 1979 are revised (version 5.0) to account for 1) a change from microwave sounding units (MSUs) to the advanced MSUs (AMSUs) and 2) an improved diurnal drift adjustment for tropospheric products. … Error estimates for TLS temperatures are less well characterized due to significant heterogeneities in the radiosonde data at high altitudes, though evidence is presented to suggest that since 1979 the trend is −0.51° ± 0.10°C decade–1.” [Full text]
Multidecadal Changes in the Vertical Temperature Structure of the Tropical Troposphere – Gaffen et al. (2000) “Trends in global lower tropospheric temperature derived from satellite observations since 1979 show less warming than trends based on surface meteorological observations. Independent radiosonde observations of surface and tropospheric temperatures confirm that, since 1979, there has been greater warming at the surface than aloft in the tropics. Associated lapse-rate changes show a decrease in the static stability of the atmosphere, which exceeds unforced static stability variations in climate simulations with state-of-the-art coupled ocean-atmosphere models. The differential temperature trends and lapse-rate changes seen during the satellite era are not sustained back to 1960.” Dian J. Gaffen, Benjamin D. Santer, James S. Boyle, John R. Christy, Nicholas E. Graham, Rebecca J. Ross, Science 18 February 2000: Vol. 287 no. 5456 pp. 1242-1245, DOI: 10.1126/science.287.5456.1242. [Full text]
Effects of orbital decay on satellite-derived lower-tropospheric temperature trends – Wentz & Schabel (1998) “The 17-year lower-tropospheric temperature record derived from the satellite Microwave Sounding Unit (MSU) shows a global cooling trend, from 1979 to 1995, of -0.05 K per decade at an altitude of about 3.5 km (refs 4, 5). Air temperatures measured at the Earth’s surface, in contrast, have risen by approximately +0.13 K per decade over the same period. The two temperature records are derived from measurements of different physical parameters, and thus are not directly comparable. In fact, the lower stratosphere is cooling substantially (by about -0.5 K per decade), so the warming trend seen at the surface is expected to diminish with altitude and change into a cooling trend at some point in the troposphere. Even so, it has been suggested that the cooling trend seen in the satellite data is excessive. The difficulty in reconciling the information from these different sources has sparked a debate in the climate community about possible instrumental problems and the existence of global warming. Here we identify an artificial cooling trend in the satellite-derived temperature series caused by previously neglected orbital-decay effects. We find a new, corrected estimate of +0.07 K per decade for the MSU-based temperature trend, which is in closer agreement with surface temperatures. We also find that the reported7 cooling of the lower troposphere, relative to the middle troposphere, is another artefact caused by uncorrected orbital-decay effects.” [Full text]
Difficulties in Obtaining Reliable Temperature Trends: Reconciling the Surface and Satellite Microwave Sounding Unit Records – Hurrell & Trenberth (1998) “A chronic difficulty in obtaining reliable climate records from satellites has been changes in instruments, platforms, equator-crossing times, and algorithms. The microwave sounding unit (MSU) tropospheric temperature record has overcome some of these problems, but evidence is presented that it too contains unreliable trends over a 17-yr period (1979–95) because of transitions involving different satellites and complications arising from nonatmospheric signals associated with the surface. The two primary MSU measures of tropospheric temperature contain different error characteristics and trends. The MSU channel 2 record exhibits a slight warming trend since 1979. Its broad vertical weighting function means that the temperature signal originates from throughout the troposphere and part of the lower stratosphere; intersatellite comparisons reveal low noise levels. Off-nadir channel 2 data are combined to provide an adjusted weighting function (called MSU 2R) without the stratospheric signal, but at a cost of an increased influence of surface emissions. Land surface microwave emissions, which account for about 20% of the total signal, depend on ground temperature and soil moisture and are subject to large variations associated with the diurnal cycle. The result is that MSU 2R noise levels are a factor of 3 larger than for MSU 2 and are sufficient to corrupt trends when several satellite records are merged. After allowing for physical differences between the satellite and surface records, large differences remain in temperature trends over the Tropics where there is a strong and deterministic coupling with the surface. The authors use linear regression with observed sea surface temperatures (SSTs) and an atmospheric general circulation model to relate the tropical MSU and surface datasets. These and alternative analyses of the MSU data, radiosonde data, and comparisons between the MSU 2R and channel 2 records, with estimates of their noise, are used to show that the downward trend in tropical MSU 2R temperatures is very likely spurious. Tropical radiosonde records are of limited use in resolving the discrepancies because of artificial trends arising from changes in instruments or sensors;however, comparisons with Australian radiosondes show a spurious downward jump in MSU 2R in mid-1991, which is not evident in MSU 2. Evaluation of reanalyzed tropical temperatures from the National Centers for Environmental Prediction and the European Centre for Medium-Range Weather Forecasts shows that they contain very different and false trends, as the analyses are only as good as the input database. Statistical analysis of the MSU 2R record objectively identifies two stepwise downward discontinuities that coincide with satellite transitions. The first is in mid-1981, prior to which only one satellite was in operation for much of the time so the diurnal cycle was not well sampled. Tropical SST anomalies over these years were small, in agreement with the Southern Oscillation index, yet the MSU 2R values were anomalously warm by 0.25°C. The second transition from NOAA-10 to NOAA-12 in mid-1991 did not involve an overlap except with NOAA-11, which suffered from a large drift in its equator-crossing times. MSU 2R anomalies have remained anomalously cold since mid-1991 by 0.1°C. Adding the two stepwise discontinuities to the tropical MSU 2R record allows it to be completely reconciled with the SST record within expected noise levels. The statistical results also make physical sense as the tropical satellite anomalies are magnified relative to SST anomalies by a factor of 1.3, which is the amplification expected following the saturated adiabatic lapse rate to the level of the peak weighting function of MSU 2R.” [Full text]
How accurate are satellite ‘thermometers’? – Christy et al. (1997) “We believe that lower-tropospheric temperatures measured directly by satellites have excellent long-term accuracy, as seen by comparisons with independent atmospheric measurements from weather balloons. Our results contradict indirect measurements by Hurrell and Trenberth1 who claimed that the satellite data have significant discontinuities.” Nature 389, 342 (25 September 1997) | doi:10.1038/38640.
Spurious trends in satellite MSU temperatures from merging different satellite records – Hurrell & Trenberth (1997) “Analysis of global surface air temperature records has indicated that recent years have been among the warmest since the late nineteenth century1, with 1995 being the warmest year on record2. But the rate of global annual mean surface warming of 0.13 °C per decade during the period 1979–95 differs substantially from the global lower-tropospheric cooling trend of – 0.05 °C per decade3 Inferred from the record (MSU-2R) of radiance measurements by the satellite Microwave Sounder Unit (MSU)4,5. Accordingly, the satellite record has been widely cited by sceptics as evidence against global warming6–10. However, a substantial fraction of the measured radiance originates not from the atmosphere but from the Earth’s surface11, and gives rise to high noise levels. This noise can lead to errors when merging temperature time series obtained from different satellites. Here we present comparisons among different MSU retrievals, sea surface temperatures (SSTs), and equivalent MSU temperatures derived from an atmospheric general circulation model forced with observed SSTs. The comparisons, focused on the tropics where atmospheric temperatures are closely tied to SSTs, strongly suggest that two spurious downward jumps occur in the MSU-2R record coinciding with changes in satellites, and that the real trend in MSU temperatures is likely to be positive, albeit small.” Nature 386, 164 – 167 (13 March 1997); doi:10.1038/386164a0.
Satellite and surface temperature data at odds? Reply to John R. Christy and Roy W. Spencer – Hansen et al. (1995) “Reply to comments by Christy and Spencer regarding Hansen and Wilson (1993), “Commentary on the Significance of Global Temperature Records”, Climatic Change, 25, 896-910.” [Full text]
Recent warming in global temperature series – Jones (1994) “Global mean temperature can be estimated from surface and from tropospheric measurements. Much has been written recently concerning trends in the various time series over short (10–15 year) periods. This paper compares the surface, 850–300 mb and the microwave sounding unit (MSU) channel 2R measurements on the ‘global’ scale. The various series show marked differences in their trends over the 1979–93 period with the surface data showing significant warming and the troposphere no change. The difference can be explained by the shortness of the record and by the transitory nature of volcanic and El Niño/Southern Oscillation effects on global temperatures. Correcting or factoring out these influences and extending the period of analysis leads to a greater conformity in the results, which show temperatures have risen by about 0.1°C per decade since 1958.” Jones, P. D. (1994), Geophys. Res. Lett., 21(12), 1149–1152, doi:10.1029/94GL01042.
Precise Monitoring of Global Temperature Trends from Satellites – Spencer & Christy (1990) “Passive microwave radiometry from satellites provides more precise atmospheric temperature information than that obtained from the relatively sparse distribution of thermometers over the earth’s surface. Accurate global atmospheric temperature estimates are needed for detection of possible greenhouse warming, evaluation of computer models of climate change, and for understanding important factors in the climate system. Analysis of the first 10 years (1979 to 1988) of satellite measurements of lower atmospheric temperature changes reveals a monthly precision of 0.01°C, large temperature variability on time scales from weeks to several years, but no obvious trend for the 10-year period. The warmest years, in descending order, were 1987, 1988, 1983, and 1980. The years 1984, 1985, and 1986 were the coolest.” [Full text]
Papers on tropical troposphere hotspot (has some papers that are directly relevant also to the global troposphere measurements)
Apparently flawed papers
There are some papers on the issue that have been found to contain bad flaws. The papers are Douglass et al. (2007) and Klotzbach et al. (2009) and they are included to the page “Anti-AGW papers debunked”.