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Global Warming Seen from Satellites: A Recent Debate on Tropospheric Temperature Trends Qiang Fu Dept. of Atmospheric Sciences University of Washington Presentation Outline Tropospheric Temperature Versus Surface Temperature Warming: A Paradox MSUs on NOAA Polar Orbiting Satellites Stratospheric Contamination & Correction Vertical Structure of Tropical Tropospheric Temperature Trends Pole-ward Shift of Tropospheric Jet Streams and Hadley Circulation Broadening Tropospheric Trend Patterns in the Antarctica Global Surface Temperature Variations IPCC 2007: Summary for Policymakers 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). GCM versus Obs. for Trend Differences Santer et al. (2000, Science) 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; Parker 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) is preparing more than 20 synthesis and assessment reports by the end of 2007: The first topic is temperature trends in the lower atmosphere (April 2006). 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) 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) 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. 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) 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) Satellite Observed Brightness Temperature Tb TsWs T (z)W (z)dz, 0 where Ts is the surface temperature, Ws the surface contribution factor, T(z) the atmospheric temperature profile, and W(z) the weighting function. 1 Height (km) Stratospheric Temperature Anomaly (K) Stratospheric Temperature Anomaly (K) Weighting Function and Tb Response 1.2 48 (a) MSU Channel 4 MSU Channel 2 10 Pressure (hPa) 31 Stratosphere 100 (b) MSU2 0.2 0.6 0.1 0 0 -0.1 -0.6 -0.2 -1.2 -0.2 -0.1 0 0.1 0.2 Tropospheric Temperature Anomaly (K) 1.2 (c) MSU4 1 16 Tropopause Troposphere 1000 0 0.02 0.04 0.06 0.08 0 0.1 0.12 Weighting Function (km-1) 0.6 0 -0.6 0.5 0 -0.5 -1 -1.2 -0.2 -0.1 0 0.1 0.2 Tropospheric Temperature Anomaly (K) Fu et al. (2004) 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. 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 quantified. __ Fu et al. (2004) What is the tropospheric temperature trend based on satellite MSU observations? 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 (TTR). We derive this temperature from the measured brightness temperatures of MSU channels 2 and 4, as TTR = a0 + a2T2 + a4T4. __ Fu et al. (2004) 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 TTR, T2, and T4 Time Series of Monthly mean, global temperature anomalies Global Temperature Anomalies (K) 1.5 1 0.5 0 -0.5 RSS: T_2 -1 RSS: T_4 RSS: T_850-300 -1.5 197919811983198519871989199119931995199719992001 Year Fu et al. (2004) Temperature Trends (1) 0.3 Temperature Trends (K/decade) (a) UAH: T_2 0.25 RSS: T_2 0.2 Surface Temp. (4, 5) 0.15 0.1 0.05 0 -0.05 1979-2001 -0.1 Globe NH SH Tropics 0.3 Temperature Trends (K/decade) (b) UAH: T_850-300 0.25 RSS: T_850-300 0.2 Surface Temp. (4, 5) 0.15 0.1 0.05 0 -0.05 1979-2001 -0.1 Globe NH SH Tropics Fu et al. (2004) Temperature Trends (2) • The stratospheric contamination in T2 trend is -0.08 K/decade (Fu et al. 2004). • 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 (Fu et al. 2004). • For T2 trends of 0.01 (Christy et al. 2003), 0.1 (Mears et al. 2003), and 0.20 K/decade (Vinnikov et al. 2006), we have a TTR trends of 0.09, 0.18, and 0.29 K/decade, respectively. 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 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) 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: TÝ 200 TÝ( p)W ( p)dp 0 Stratospheric Trend Profile 0 20 40 Pressure (hPa) 60 80 100 120 140 R_H 160 R_P 180 200 -1.2 HadRT -1 #+ -0.8 -0.6 -0.4 Trend (K/decade) ox -0.2 0 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). Stratospheric Contamination (K decade -1) A Direct Error Estimates 0.02 0 -0.02 -0.04 R_H -0.06 R_P HadRT -0.08 -0.1 W_2 W_2LT W_FT Fu and Johanson (2004, J. Climate) QuickTime™ and a TIFF (Uncompressed) decompressor are needed to see this picture. According to the published report, “there is no longer a discrepancy in the rate of global average temperature increase for the surface compared with higher levels in the atmosphere. This discrepancy had previously been used to challenge the validity of climate models used to detect and attribute the causes of observed climate change”. Climate Change 2007: The Physical Science Basis Summary for Policymakers Warming of the climate system is unequivocal, as is now evident from observations of increases in global average air and ocean temperatures, widespread melting of snow and ice, and rising global average sea level (see Figure SPM-3). … New analyses of balloon-borne and satellite measurements of lower- and mid-tropospheric temperature show warming rates that are similar to those of the surface temperature record and are consistent within their respective uncertainties, largely reconciling a discrepancy noted in the TAR. … QuickTime™ and a TIFF (Uncompressed) decompressor are needed to see this picture. “One issue does remain however, and that is related to the rates of warming in the tropics. Here, models and theory predict an amplification of surface warming higher in the atmosphere. However, this greater warming aloft is not evident in three of the five observational data sets used in the report. Whether this is a result of uncertainties in the observed data, flaws in climate models, or a combination of these is not yet known.” Water vapour feedback structure:major contributions BMRC model: TOA Radiative impact of water vapour changes, 2CO2 1CO2 (Wm-2K-1100hPa-1) Courtesy of Colman Some Basics on Tropical Tropospheric Temperature Profiles Uniform tropical upper-air temperature Larger SST variations Rainfall, cloud cover, and humidity all roughly follow warm SST Mechanisms Setting Tropical Temperature Distribution In the tropical atmosphere: • The troposphere is stably stratified outside convective regions. • Release of latent heat in deep convective systems balances radiative cooling and heat export. • These systems keep the local temperature profile roughly moist-adiabatic. 15 km z TLH zLCL T+gz/cp • Moist static energy h = cpT + Lq + gz roughly conserved in deep cumulus updrafts • hsat = cpT+Lqsat(T,z)+ gz = hABL • Cumulative latent heating TLH(z) = L{qsat(T)-qsat(TLCL)}/cp For TLCL = 296 K, TLH = 40 K at z = 4.5 km (T=0). • A change in Tsfc with constant relative humidity changes the temperature profile like dT/dTsfc = (1 + gLCL)/(1+g(T)) > 1, g = (L/cp)dqsat/dT (lapse rate feedback). Currently gLCL = 3, g(273 K) = 1.2, at the tropical freezing level, dTair/d(SST) = 1.9. Courtesy of Bretherton Stratified Adjustment • Coriolis parameter f = 2W sin(latitude) • Gravity waves efficiently spread heat over a Rossby radius R = NH/f • This maintains a horizontally uniform temperature profile over the entire tropics determined by moist adiabatic lifting of near-surface air over warm moist parts of the tropics (e.g., Charney 1963; Schneider 1977; Held and Hou 1980; Bretherton and Smolarkiewicz 1989; Sobel and Bretherton 2000). Q z C ~ 50 m s-1 T+gz/cp T+gz/cp Courtesy of Bretherton ENSO Example: Warm-Phase SST Anomalies Vertical Structure of ENSO-Regressed Air Temperature Variation IS nearly MoistAdiabatic Enhanced upper tropospheric warming Chiang and Sobel (2002) (Chiang and Sobel 2002) Some Tropical Climate Basics • In the deep tropics, air temperature is nearly horizontally uniform above the atmospheric boundary layer, which is coupled to warmest SSTs and roughly moist-adiabatic vertically. • The physics behind those seems suggest that they probably also hold in changed tropical climates. • Show supporting observations using current-day climatology versus ENSO as an example ‘climate variation’. We might expect that across the tropics, tropospheric temperatures would respond uniformly to climate changes. They should be locked to warm tail of SSTs and the T changes should amplify moist-adiabatically with elevation. Formulation of MSU Effective Weighting Functions for Different Tropical Tropospheric Layers 0 (a) Pressure (hPa) 100 W3 W4 0 (b) 100 200 200 300 300 400 W2 (0.05) 500 600 W2LT (0.1) 400 WTT (0.055) 500 WTLT (0.08) 600 700 700 800 800 900 900 1000 1000 -0.003 0 0.0030.006 0.009 0.012 -0.003 0 0.0030.006 0.0090.012 Weighting Function (1/hPa) Weighting Function (1/hPa) Fu & Johanson (2005, GRL) Temperature Trends (K/decade) Vertical Structure of Tropical Tropospheric Temperature Trends 0.5 30N-30S: 1987-2003 0.4 Ts: HadCRU2v 0.3 T TLT 0.2 T TTT TTT Ts s 0.1 0 T 2LT -0.1 RSS UAH Fu and Johanson (2005, GRL) TTLT-T2LT (K) TTLT-T2LT (K) Discussions on T2LT 0.55 (a) 0.45 0.35 0.25 0.15 0.05 -0.05 30N-30S: Ocean Only -0.15 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 0.55 (b) 0.45 0.35 0.25 0.15 0.05 -0.05 30N-30S: Land Only -0.15 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 Year Fu &Johanson (2005, GRL) UAH T2LT trend bias is largely attributed to the periods when satellites had large local equator crossing time drifts. Mears & Wentz (2005, Science) SUMMARY NOTES • • • • 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. The results of Fu et al. (2004) are validated with a direct error analysis and are also independently repeated by Gillett, Santer & Weaver (2004, Nature) and Kiehl et al. (2005). • • • • The satellite-inferred tropospheric temperature trends after removing the stratospheric contamination are physically consistent with the observed surface temperature trends. The UAH T2LT trend in the tropics is physically implausible, which is verified by Mears & Wentz. We 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. Global Stratospheric & Tropospheric Temperature Trends (1979-2005) Qu ickTime ™ a nd a TIFF (U nco mpresse d) d eco mpresso r are ne eded to s ee this p ictu re. Fu, Johanson, Wallace and Reichler (2006, Science) Pole-ward Shift* of Tropospheric Jet Streams from MSU Obs. DJF MAM JJA SON NH 0.8 1.2 1.4 -0.2 SH -1.6 -0.4 -0.8 0.0 Total 2.4 1.6 2.2 -0.2 *degree for last 27 years Hadley Circulation Broadening Seen from OLR ERBS Edition 3_Rev1 Wong et al. (2006) HIRS Pathfinder Mehta & Susskind (1999) QuickTime™ and a TIFF (Uncompressed) decompressor are needed to see this picture. AVHRR Pathfinder Jacobowitz et al. (2003) ISCCP FD Zhang et al. (2004) GEWEX RFA Stackhouse et al. (2004) Hadley Circulation Broadening Seen from OLR since 1979 QuickTime™ and a TIFF (LZW) decompressor are needed to see this picture. Hu and Fu (2007) HIRS Pathfinder: 4.8o; ISCCP FD: 4.0o; GEWEX RFA: 2.3o Hadley Circulation Broadening Seen from Meridional mass stream function Total expansion from reanalyzes ECMWF 2.6° NCEP/NCAR 2.7° NCEP/DOE 3.1° Hartmann (Global Physical Climatology, 1994) Evolution of zonal mean meridional mass stream function at 500 hPa in the northern hemisphere for (SON) (Hu and Fu 2007) Hadley Circulation Broadening Seen Satellite observed ozone TOMS total ozone field for March 11th, 1990. Monthly mean relative areas Tropical Sub-arctic Mid-latitude Polar Hudson et al. (2006) Tropical and mid-latitude boundaries separated by upper troposphere jet Between 1979 and 2003, the tropical regime expanded by ~2.7 degrees in the northern hemisphere alone Models versus Observations Observed expansion (based on OLR) cannot be explained by natural variability Expansion in GFDL model simulations is weak, non-existent, or in opposite direction as observations SUMMARY NOTES • • • • Three reanalyses, three OLR datasets, satellite ozone obs. and satellite MSU obs. in terms of MMS, OLR, ozone, and tropospheric temperature trends all indicate a significant broadening of Hadley circulation (~2 to 5o) since 1979. GCMs cannot reproduce the observed Hadley cell expansions. The 21st century climate change simulations of the IPCC AR4 suggest a robust pole-ward expansion of the Hadley circulation (Lu et al. 2007) but they are much weaker than those based on observations. Important implication to midlatitude drought (e.g., Hoerling & Kumar 2003, Science; Lau et al. 2005). An indication of GCMs’ inability to simulate Eocene equator-to-pole surface temperature gradient??? Tropospheric Temperature Trends in Antarctica (1979-2005) • • • • Recent debates on the Antarctic climate change (Doran et al. 2002, Nature; Turner et al. 2002, Nature; Jones & Widman 2004, Nature; Bertler et al. 2004). Antarctic cooling in the summer-fall season (Thompson & Solomon 2002, Science; Shindell &Schmidt 2004). Significant uniform Antarctic winter tropospheric warming (Turner et al. 2006, Science). No significant change in snowfall (Monaghan et al. Science 2006), which seems inconsistent with winter tropospheric warming. Turner et al. (2006) used radiosonde data at nine stations over Antarctic: “…satellite product (T2lt) may not be reliable around Antarctica in the winter because of the effects of the sea ice.” Comparison of Tropospheric Temperature Trends between Radiosonde and MSU (T2&T4) Johanson & Fu (2007) Trend Pattern in Antarctica Troposphere Stratosphere Johanson and Fu (2006) Summary Notes • The tropospheric temperature trends retrieved from MSU T2 and T4 agree with those from eight Antarctic radiosonde stations (but not at Bellingshausen where there is a large false warming from the radiosonde). • The Antarctic continent is cooling in summer-fall season since 1979, which agrees with previous study. • About half of the Antarctic continent is not warming but even cooling in the winter, which does not support Turner et al. (Science 2006) but is consistent with the snowfall change reported by Monaghan et al. (2006, Science). • We identify major stratospheric warming in part of the Antarctica in the winter-spring season, which requires an explanation. QuickTime™ and a TIFF (LZW) decompressor are needed to see this picture.