Global Warming Seen from Satellites: A Recent Debate on Tropospheric Temperature Trends

1. Global Warming Seen from Satellites: A Recent Debate on Tropospheric Temperature Trends Qiang Fu Dept. of Atmospheric Sciences University of Washington

2. Presentation Outline Tropospheric Temperature Versus Surface Temperature Warming: A Paradox MSUs on NOAA Polar Orbiting Satellites Stratospheric Contamination & Correction Some Independent Checks Summary

3. Global Surface Temperature Variations Randel et al 2001, fig 6 HALOE H2O Convection Frequency (0.5, 1, 5, 10%) Tropopause

4. IPCC2001 “It is likely that there have been real differences between the rate of warming in the troposphere and the surface over the last twenty years, which are not fully understood” __IPCC (2001).

5. GCM versus Obs. for Trend Differences Santer et al. (2000, Science)

6. How Can We Explain the Paradox • Global climate models are missing something important? (e.g., Bengtsson et al. 1999; Santer et al. 2000; 2003; Hegerl and Wallace 2002; Hansen et al. 2002) • Problems in surface temperature data? (e.g., Kalnay and Cai 2003; Trenberth 2004) • Problems in tropospheric temperature data? (e.g., Seidel et al. 2004; Hurrell and Trenberth 1997; Mears et al. 2003; Vinnikov and Grody et al. 2003) The US Climate Change Science Program (CCSP) calls for the creation of more than 20 synthesis and assessment reports by the end of 2007: The first topic is temperature trends in the lower atmosphere.

7. Radiosonde Temperatures Advantages • Long record (1950s) • Good vertical resolution Disadvantages • Many changes in instruments and observation methods • Known and unknown biases • Sparse coverage -0.03 to 0.04 K/decade for 1979-2001 (Seidel et al. 2004)

8. MSU Observations from NOAA Polar-Orbiting Satellites • Global coverage • Data since late of 1978 • All weather conditions MSU: 4 channels (AMSU:15) • Channel 2: Mid-troposphere (53.74 GHz) • Channel 4: Stratosphere (57.95 GHz) Climate monitoring (Spencer & Christy 1990)

9. Satellite Data Analyses • Satellite local sampling-time drifts • MSU calibrations (inter-satellites) • Satellite orbit decays (e.g., Christy et al. 1995; Wentz et al. 1998; Christy et al. 1998; Prabhakara et al. 2000; Christy et al. 2000; Mo et al. 2001; Christy et al. 2003; Mears et al. 2003; Vinnikov and Grody 2003) A continuing data-analysis effort has been made to satisfy climate research requirements of homogeneity and calibration.

10. MSU Scan Pattern T4 = (T44+T45+T46+T47+T48)/5 T2 = (T24+T25+T26+T27+T28)/5 T2LT = (T23+T24+T28+T29)-3(T21+T22+T210+T211)/4 (Spencer and Christy 1992)

11. Tropospheric Temperature Trends from MSU (1/1979-12/2001) • Univ. of Alabama at Huntsville (UAH) Mid-troposphere (T2): 0.01K/decade Low-mid troposphere (T2LT): 0.055K/decade (Christy et al. 2003) • Remote Sensing System (RSS) Mid-troposphere (T2): 0.1K/decade (Mears et al. 2003) • Surface Trend 0.17K/decade (Jones & Moberg 2003) We argue that the trends reported by both teams for the “mid-troposphere” channel are substantially smaller than the actual trend of the mid-tropospheric temperature. ___ Fu et al. (2004)

12. Satellite Observed Brightness Temperature where Ts is the surface temperature, Ws the surface contribution factor, T(z) the atmospheric temperature profile, and W(z) the weighting function.

13. Weighting Function and Tb Response Fu et al. (2004)

14. Observed Stratospheric Cooling Ramaswamy et al. (2001) Therefore T2 by itself is not a good indicator for the temperature trend in the troposphere because it reflects combined influences of stratospheric and tropospheric changes, which largely cancel each other.

15. Removing Stratospheric Contamination T2LT created by Spencer and Christy (1992) [T2LT = (T23+T24+T28+T29)-3(T21+T22+T210+T211)/4] • Amplify noise by more than an order of magnitude • Increase inter-satellite calibration biases • Sensitive to surface variations and mountainous terrain (e.g., Hurrell & Trenberth 1997; Wentz & Schabel 1998; Swanson 2003) Although a stratospheric influence on the T2 trend has long been recognized, it has never been well quantified. __ Fu et al. (2004) What is the tropospheric temperature trend based on satellite MSU observations?

16. Methodology • A new approach to remove the stratospheric contamination by using data from MSU channel 4 • Free of the complications afflicting T2LT We define the free-tropospheric temperature as the mean temperature between 850 and 300 hPa (T850-300). We derive this temperature from the measured brightness temperatures of MSU channels 2 and 4, as T850-300 = a0 + a2T2 + a4T4. __ Fu et al. (2004)

17. Coefficients a0, a2 & a4 (1) • Radiosonde data from Lanzante, Klein, Seidel (LKS) 87 stations • 15 pressure layers • 1000-10 hPa • 1958 - 1997 • Lanzante et al. (2003) • Applying the weighting functions to the radiosonde data to simulate T2 and T4 Global-, hemispheric- and tropical-average monthly anomalies for T850-300, T2, and T4

18. Coefficients a0, a2 & a4 (2) Fu et al. (2004)

19. Comparison of monthly mean, global-average temperature anomaly time series Fu et al. (2004)

20. Time Series of Monthly mean, global temperature anomalies Fu et al. (2004)

21. Temperature Trends (1) Fu et al. (2004)

22. Temperature Trends (2) • The stratospheric contamination in T2 trend is 0.08 K/decade. • Based on RSS MSU data, the ratio of tropospheric temperature trend to surface temperature trend is ~1.1 for the globe and 1.6 for the tropics. • For T2 trends of 0.01 (Christy et al. 2003), 0.1 (Mears et al. 2003), and 0.24 K/decade (Vinnikov & Grody 2003), we have a T850-300 trends of 0.09, 0.18, and 0.34 K/decade, respectively.

23. Inconsistency in UAH data In the tropics (30N-30S), the UAH reported T2LT (bulk temperatures for the low-middle troposphere) has a trend of -0.01 K/decade while its T2 trend there is 0.03 K/decade, that is the UAH T2LT is cooling at -0.04 K/decade relative to the UAH T2. In view of the cooling trend in the stratosphere at all latitude, one would expect that T2LT should be warming relative to T2. This apparent inconsistency may be attributed to complications involving the T2LT retrieval, as well as to the techniques used by UAH to analyse the MSU channel 2 data. __ Fu et al. (2004)

25. When is global warming really a cooling? By Roy Spencer Published 05/05/2004 http://www.techcentralstation.com/050504H.html New climate study finds ‘global warming’ by substracting cooling that wasn’t there University of Alabama at Huntsville (UAH) News Release 05/05/2004 Assault from above A Report Produced by The CO2 & Climate Team Published 05/06/2004 http://www.co2andclimate.org/wca/2004/wca_17apf.html

26. Spencer (05/05/2004) The Fu et al. weighting function shows substantial negative weight above 100 hPa, a pressure altitude above which strong cooling has been observed by weather balloon data. This leads to a misinterpretation of stratospheric cooling as tropospheric warming. __ Spencer (05/05/2004)

27. Methodology We use the observed vertical profile of stratospheric temperature trend to directly evaluate the magnitude of stratospheric contamination in various techniques used to estimate the tropospheric temperature trends:

28. Stratospheric Trend Profile Fig.1. Mean vertical profile of temperature trend in the stratosphere as compiled by Ramaswamy et al. (2001) using radiosonde, satellite, and analyzed data sets, rescaled to the global trend of UAH MSU T4 over the 1979-2001 period. The solid and dashed lines represent trend profiles using linear extrapolation with respect to height and pressure, respectively, below 15 km (~120 hPa). Also shown are the global temperature trends for the layer between 100 and 300 hPa for the same time span, as derived from four radiosonde datasets: Angell-63 (Angell-54 (+), HadRT (o), and RIHMI (x) (See Seidel et al. 2004 for detailed descriptions of these datasets).

29. A Direct Error Estimates Fig.3. Stratospheric contributions to the MSU-derived tropospheric temperature trends using the three different weighting functions shown in Fig.2. Fu and Johanson (2004, J. Climate)

30. Trends in Vertical Structure of Tropical Tropospheric Temperatures

31. Discussions on T2LT (I) UAH T2LT trend in the tropics is not physically plausible.

32. Discussions on T2LT (II) Fu &Johanson (2005, GRL) UAH T2LT trend bias can be largely attributed to the periods when satellites had large local equator crossing time drifts.

33. Santer et al. (2005, Science)

34. SUMMARY • Trends in T2 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 T2 using MSU channel 4, which records only stratospheric temperatures. • We find that the stratospheric contamination in T2 trend is -0.08 K/decade for the period from 1/1/1979 to 12/31/2001.

35. The satellite-inferred tropospheric temperature trends after removing the stratospheric contamination are physically consistent with the observed surface temperature trends. • The methodology used in Fu et al. (2004) is validated with a direct error analysis. • The UAH T2LT trend in the tropics is physically implausible. • We can quantify the trend in tropical tropospheric temperature vertical structure by using combinations of MSU T2, T3, and T4. • The satellite-inferred tropical air temperature trends based on RSS MSU data increase with height.