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

Qiang FuDept. of Atmospheric SciencesUniversity of Washington

Presentation OutlinePresentation Outline Tropospheric Temperature Versus SurfaceTropospheric Temperature Versus Surface Temperature Warming: A ParadoxTemperature Warming: A Paradox

MSUs on NOAA Polar Orbiting SatellitesMSUs on NOAA Polar Orbiting Satellites

Stratospheric Contamination & CorrectionStratospheric Contamination & Correction

Vertical Structure of Tropical Tropospheric Vertical Structure of Tropical Tropospheric Temperature TrendsTemperature Trends

Pole-ward Shift of Tropospheric Jet Streams and Hadley Circulation Broadening Tropospheric Trend Patterns in the AntarcticaTropospheric 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

• Long record (1950s)• Good vertical resolution• Many changes in instruments and observation methods• Known and unknown biases• Sparse coverage

Disadvantages

Advantages

-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 conditionsMSU: 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)dz0

∞∫ ,

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

Weighting Function and Tb Response

1000

100

10

1

0 0.02 0.04 0.06 0.08 0.1 0.12

Weighting Function (km-1)

MSU Channel 4

MSU Channel 2

1000

100

10

1

0 0.02 0.04 0.06 0.08 0.1 0.12

Weighting Function (km-1)

Tropopause

Stratosphere

Troposphere

0

16

31

48(a)

-0.2

-0.1

0

0.1

0.2

-1.2

-0.6

0

0.6

1.2

-0.2 -0.1 0 0.1 0.2Tropospheric Temperature Anomaly (K)

(b) MSU2

-1

-0.5

0

0.5

1

-1.2

-0.6

0

0.6

1.2

-0.2 -0.1 0 0.1 0.2Tropospheric Temperature Anomaly (K)

(c) MSU4

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 T4Global-, hemispheric- and

tropical-average monthly anomalies for TTR, T2, and T4

Time Series of Monthly mean, global

temperature anomalies

-1.5

-1

-0.5

0

0.5

1

1.5

1979 1981 1983 1985 1987 1989 19911993 1995 1997 1999 2001Year

RSS: T_2

RSS: T_4

RSS: T_850-300

Fu et al. (2004)

Temperature Trends (1)

Globe NH SH Tropics-0.1

-0.05

0

0.05

0.1

0.15

0.2

0.25

0.3

UAH: T_2

RSS: T_2

Surface Temp. (4, 5)

(a)

Globe NH SH Tropics-0.1

-0.05

0

0.05

0.1

0.15

0.2

0.25

0.3

UAH: T_850-300

RSS: T_850-300

Surface Temp. (4, 5)

(b)

1979-2001

1979-2001

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 SpencerPublished 05/05/2004http://www.techcentralstation.com/050504H.html

Assault from aboveA Report Produced by The CO2 & Climate TeamPublished 05/06/2004http://www.co2andclimate.org/wca/2004/wca_17apf.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

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:

€

Δ ˙ T = ˙ T (p)W(p)dp0

200∫

Stratospheric Trend Profile

200

180

160

140

120

100

80

60

40

20

0

-1.2 -1 -0.8 -0.6 -0.4 -0.2 0Trend (K/decade)

R_H

R_P

HadRT

#200

180

160

140

120

100

80

60

40

20

0

-1.2 -1 -0.8 -0.6 -0.4 -0.2 0Trend (K/decade)

o200

180

160

140

120

100

80

60

40

20

0

-1.2 -1 -0.8 -0.6 -0.4 -0.2 0Trend (K/decade)

x200

180

160

140

120

100

80

60

40

20

0

-1.2 -1 -0.8 -0.6 -0.4 -0.2 0Trend (K/decade)

+200

180

160

140

120

100

80

60

40

20

0

-1.2 -1 -0.8 -0.6 -0.4 -0.2 0Trend (K/decade)

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).

A Direct Error Estimates

W_2 W_2LT W_FT-0.1

-0.08

-0.06

-0.04

-0.02

0

0.02

R_H

R_P

HadRT

Fu and Johanson (2004, J. Climate)

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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.…

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“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

Uniform tropical upper-air temperature

Larger SST variations

Rainfall, cloud cover, and humidity all roughly follow warm SST

Some Basics on Tropical Tropospheric Some Basics on Tropical Tropospheric

Temperature ProfilesTemperature Profiles

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.

z

T+gz/cp

TLH

zLCL

• 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 + LCL)/(1+(T)) > 1, = (L/cp)dqsat/dT (lapse rate feedback). Currently LCL = 3, (273 K) = 1.2, at the tropical freezing level, dTair/d(SST) = 1.9.

15 km

Courtesy of Bretherton

Stratified Adjustment

•Coriolis parameter f = 2 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

C ~ 50 m s-1

z

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 Moist-

Adiabatic

Enhanced uppertropospheric warming

(Chiang and Sobel 2002)

Chiang and Sobel (2002)

Some Tropical Climate Basics

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.

• 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’.

Formulation of MSU Effective Weighting

Functions for Different Tropical Tropospheric

Layers

1000

900

800

700

600

500

400

300

200

100

0

-0.003 0 0.003 0.006 0.009 0.012

Weighting Function (1/hPa)

W

TT

(0.055)

W

TLT

(0.08)

(b)

1000

900

800

700

600

500

400

300

200

100

0

-0.003 0 0.003 0.006 0.009 0.012

Weighting Function (1/hPa)

(a)

1000

900

800

700

600

500

400

300

200

100

0

-0.003 0 0.003 0.006 0.009 0.012

Pressure (hPa)

Weighting Function (1/hPa)

W

4W

3

W

2

(0.05)

W

2LT

(0.1)

1000

900

800

700

600

500

400

300

200

100

0

-0.003 0 0.003 0.006 0.009 0.012

Pressure (hPa)

Weighting Function (1/hPa)

Fu & Johanson (2005, GRL)

Vertical Structure of Tropical Tropospheric Temperature Trends

RSS UAH-0.1

0

0.1

0.2

0.3

0.4

0.530N-30S: 1987-2003

Ts: HadCRU2v

Ts

TTLT

TTT

Ts

TTT

T2LT

RSS UAH-0.1

0

0.1

0.2

0.3

0.4

0.5

Fu and Johanson (2005, GRL)

Discussions on T2LT

UAH T2LT trend bias is largely attributed to the periods when satellites had large local equator crossing time drifts.

-0.15-0.050.050.150.250.350.450.55

1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003

-0.15-0.050.050.150.250.350.450.55

1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003Year

30N-30S: Ocean Only

30N-30S: Land Only

(a)

(b)Fu &Johanson (2005, GRL)

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)

Fu, Johanson, Wallace and Reichler (2006, Science)

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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

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ERBS Edition 3_Rev1Wong et al. (2006)

HIRS PathfinderMehta & Susskind

(1999)AVHRR Pathfinder

Jacobowitz et al. (2003)ISCCP FD

Zhang et al. (2004)GEWEX RFA

Stackhouse et al. (2004)

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Hadley Circulation Broadening Seen from OLR

since 1979

Hu and Fu (2007)

HIRS Pathfinder: 4.8o; ISCCP FD: 4.0o; GEWEX RFA: 2.3o

Evolution of zonal mean meridional mass stream function at 500 hPa in the northern hemisphere for (SON) (Hu and Fu 2007)

Total expansion from reanalyzes

ECMWF 2.6°NCEP/NCAR 2.7°NCEP/DOE 3.1°

Hadley Circulation Broadening Seen from Meridional mass

stream function

Hartmann (Global Physical Climatology, 1994)

Monthly mean relative areasTropical Mid-latitude

Sub-arctic Polar

Hudson et al. (2006)

TOMS total ozone field for March 11th, 1990.

Between 1979 and 2003, the tropical regime expanded by ~2.7 degrees in the northern hemisphere alone

Hadley Circulation Broadening Seen Satellite

observed ozone

Tropical and mid-latitude boundaries separated by upper troposphere jet

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

Models versus 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???

• 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.

Tropospheric Temperature Trends in Antarctica (1979-

2005)

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 AntarcticaTroposphere

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.

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