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Trends in Water Cycle meeting, Paris, November 2004
Cloud and water vapour variability: models, reanalyses
and observations
Richard P. Allan and Tony SlingoEnvironmental Systems Science Centre, University of Reading
Trends in Water Cycle meeting, Paris, November 2004
INTRODUCTION– Hydrological cycle and climate
feedbacks» What determines the trends and variability of water cycle?
» Unless we understand reasons for variation there is little chance for initiating improvement in climate model processes and predictions
– Analysis of decadal changes in cloud, water vapour and the radiation budget
» satellite data
» experiments with HadAM3 model
» can we use reanalyses (e.g. ERA40)?
Trends in Water Cycle meeting, Paris, November 2004
Decadal variability of Column Water Vapour (see Allan et al. 2003, QJRMS, p.3371)
1980 1985 1990 1995
SST
CWV
Trends in Water Cycle meeting, Paris, November 2004
Robust, positive water vapour feedback at low-altitudes over low-latitude oceans
– dCWV/dTs ~ 3.5 kgm-2 K-1 ~ 10%/K
– e.g. Wentz and Shabel (2000) Nature 403 p.414, Soden (2000) J.Clim 13, p.538,
Allan et al. (2003) QJRMS, 129, p.3371, ….
What about free tropospheric humidity?– Unsaturated, not governed by simple
thermodynamic processes?
Can we use reanalyses?
Trends in Water Cycle meeting, Paris, November 2004
Allan et al. 2004, JGR, vol. 109
Variability in low latitude column integrated water vapour (1979-2002)
Reanalyses (ERA40 and NCEP), HadAM3 model and microwave observations (SMMR; SSM/I)
Trends in Water Cycle meeting, Paris, November 2004
Allan et al. 2004, JGR, vol. 109 Reanalyses are currently unsuitable for detection of subtle trends associated with water vapour feedbacks
– BUT… Climatology from ERA40 is good.
– Variability from 24 hr forecast from ERA40 is much better.
– Use of dynamical parameters with observations of hydrological cycle of considerable utility
– See also…Bengtsson et al. (2004) JGR 109; Ringer and Allan (2004) Tellus A, 56, p.308.
Can we use clear-sky OLR to infer information on free tropospheric humidity?
– Models and obs agree: dOLRc/dTs ~ 2 Wm-2 K-1
– Interannual variability OK (Soden 2000, Allan et al. 2003)
Trends in Water Cycle meeting, Paris, November 2004
dOLRc/dTs~2 Wm-2 K-1 doesn’t indicate consistent water vapour
feedback?
Allan et al. 2002, JGR, 107(D17), 4329.
HadAM3
GFDL
dTa(p)/dTs dq(p)/dTs
HadAM3
GFDL
Trends in Water Cycle meeting, Paris, November 2004
Explicit simulations of 6.7 m water vapour radiances in
HadAM3
Use John Edwards’ radiance solver within Hadley Centre climate model
Simulate HIRS 6.7 m radiance Account for inconsistent satellite
sampling of clear-skies See Allan et al. (2003) QJRMS p.3371
Trends in Water Cycle meeting, Paris, November 2004
Interannual monthly anomalies of 6.7 m radiance: HadAM3 vs HIRS (tropical oceans)
(Allan et al. 2003, QJRMS, p.3371)
Models and data both suggest only small changes in RH over decadal time-scale
Trends in Water Cycle meeting, Paris, November 2004
Changes in tropical radiation budget and
cloudiness Evidence suggests constant RH water
vapour feedback is robust and well simulated by models
Satellite and other data suggests the radiative effect of cloud is highly dynamic and poorly simulated by models
Trends in Water Cycle meeting, Paris, November 2004
Following: Wielicki et al. (2002); Allan & Slingo (2002)
+Altitude and orbit corrections (40S-40N)
Clear LW
LW
SW
Trends in Water Cycle meeting, Paris, November 2004
– Satellite data suggest large decadal variability of radiative energy balance
» 1980’s to 1990’s: increase in OLR of ~ 2 Wm-2 decrease in RSW of ~3 Wm-2 Clear-sky OLR variation small
– Models do not capture these changes changes in simulated OLR determined exclusively by the
changes in clear-sky OLR which are strongly influenced by the surface temperature variation due to constant RH
– Satellite data suggest reduced tropical cloudiness
» Evidence to suggest intensification of hydrological cycle (Chen et al. 2002, Science)
» surface heating and atmospheric cooling destabilising
Trends in Water Cycle meeting, Paris, November 2004
Additional evidence… ISCCP – reduction in cloud fraction
Cess and Udelhofen (2002) GRL
Consistent changes in ISCCP-derived radiation budget to ERBS
– Zhang et al. (2004) JGR; Hatzianastassiou et al. (2004) Atmos. Chem. Phys. Hatzidimitriou et al. (2004) Atmos. Chem. Phys.
SAGE II reduction in high cloud (Wang et al. 2002, GRL)
Earthshine measurements of reduced albedo Palle et al. (2004) Science
Surface obs – reduction in high cloud (J. Norris, pers. Comm.)
Trends in Water Cycle meeting, Paris, November 2004
What is the spatiotemporal signature of the changes in the radiative energy
balance?
Trends in Water Cycle meeting, Paris, November 2004
EOFs of May-June OLR using
altitude and orbit corrected
WFOVdata
(1985-1999)
EOF1 (ENSO-like)
EOF2 (“trend”-like?)
Trends in Water Cycle meeting, Paris, November 2004
EOF2 (ENSO-like)
EOF1 (“trend”-like?)
EOFs of May-June
Reflected Shortwav
e Radiation
(RSW) using
altitude and orbit- corrected
WFOVdata
(1985-1999)
Trends in Water Cycle meeting, Paris, November 2004
CONCLUSIONS Models can simulate the interannual
thermodynamic changes in low-altitude moisture– Reanalyses cannot
Changes in OLRc and RH small in models&data Climate models do not simulate observed
decadal changes in radiation budget 1979-99– OLR increases ~2 Wm-2 and RSW decreases ~3 Wm-2
Radiation Budget changes symptomatic of reduced low-latitude cloudiness from 1980’s-90’s
– Initially, changes in radiation budget should force surface heating and atmospheric cooling
– Radiation Budget / T-Lapse Rate / Dynamics interaction