1. Observed and Simulated Decadal Variability in Clouds and Water Vapour Richard Allan, Tony Slingo Environmental Systems Science Centre, University of Reading Mark Ringer Hadley Centre, Met Office

2. INTRODUCTION Climate Sensitivity and Feedback
How does cloud and water vapour respond to changes in surface temperature?
How well are interannual variations in cloud and water vapour simulated by a climate model?
HadAM3 Simulations ( )
Explicitly calculate “UTH” radiances
Satellite-like clear-sky diagnostics
Evaluation of HadAM3 using satellite data

3. EXPERIMENTS [Allan et al. 2003, accepted QJ]
Ensemble of AMIP-type HadAM3 runs
Standard res, 19 levels, HadISST SST/sea ice forcing
Radiance code [see Ringer et al., 2002, QJ, 129, ]
Modified clear-sky diagnostics: OLRc & water vapour radiance
Additional “all-forcings” run
SATELLITE DATA
- column water vapour, CWV [SMMR , SSM/I ]
- clear-sky OLR [ERBS , ScaRaB 1994/5, CERES 1998]
- Water Vapour channel brightness temperature, T6.7 [HIRS ]

4. Interannual variability of Column Water vapour
See also Soden (2000) J.Clim 13

5. Can we use reanalysis CWV?
ERA-40

6. Upper tropospheric moisture
Clear-sky OLR sensitive to Ts and RH
6.7 mm cloud cleared radiance sensitive to upper tropospheric Relative Humidity
Explicitly simulate 6.7 mm radiance
Modified “satellite-like” clear-sky diagnostics

7. Model-obs differences & Clear-sky Sampling
Type II HadAM3-OBS Type-I
DT 6.7
DOLRc

8. EOF analysis of spatio-temporal variability in water vapour radiance

9. Interannual monthly anomalies: tropical oceans
ga=1-(OLRc/sTs4)

10. (+additional forcings)

11. Clear-sky sampling: interannual variability
Light blue: Type I (weighted by clear-sky fraction)
Dark Blue: Type II (unweighted mean)

12. Large changes in OLR from 7 independent satellite instruments (Wielicki et al, 2002)

13. Allan & Slingo 2002, GRL, 29(7)
OLR
Clear-sky OLR
RSW

14. EITHER:
(1) satellite data wrong: cannot measure decadal changes in tropical radiation budget (and hence cloudiness variations) using most well-calibrated, stable radiometers
OR:
(2) Our understanding of what determines decadal changes in clouds and radiation is overly simplistic
REGARDLESS: measurements of tropical radiation budget provide vital information on tropical cloudiness changes

15. Summary Climate model simulates low-level water vapour changes
Clear-sky sampling important for infrared channel climatologies but not interannual variability
Simulations of satellite brightness temperatures: Consistent decadal variability suggests small DRH realistic
Climate models cannot capture the large decadal changes in the tropical radiation budget ( )
More wide-field of view instruments (simple yet well-calibrated & stable)
Note of caution:
can multiple satellite intercalibration artificially remove decadal trends in the UTH radiances?
Changes in atmospheric T also influences T6.7 decadal fluctuations

16. Climatological mean over 60oS-60oN oceans

17. Info on upper tropospheric water vapour
500mb omega
Clear-sky OLR

18. Water vapour feedback: recent advances
(1) Insensitive to resolution (Ingram 2002, J Climate, 15, )
(2) Consistent with observations following post-Pinatubo cooling (Soden et al 2002, Science, 296, 727)

19. Is water vapour feedback really consistent between models?
dOLRc/dTs ~ 2 Wm-2K-1 dOLR/dTs uncertain (Cess et al. 1990, JGR, 95, 16601)
Allan et al. 2002, JGR, 107(D17), doi: /2001JD
- Temperature lapse rate (Gaffen et al 2000, Science, 287, 1242)
- Tropical Cloudiness (Wielicki et al, 2002, Science, 295, 841)