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INTRODUCTION

Evaluating moisture in the Hadley Centre Climate Model using 20 years of satellite data Richard Allan Environmental Systems Science Centre, University of Reading Thanks to Mark Ringer, Tony Slingo and John Edwards. INTRODUCTION. Using moisture to evaluate/improve climate models

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INTRODUCTION

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  1. Evaluating moisture in the Hadley Centre Climate Model using 20 years of satellite dataRichard AllanEnvironmental Systems Science Centre, University of ReadingThanks to Mark Ringer, Tony Slingo and John Edwards

  2. INTRODUCTION • Using moisture to evaluate/improve climate models • Development/improvement of parametrizations • Evaluation of moist processes and feedbacks • RH distribution and variability crucial to water vapour/cloud feedback • HadAM3 Simulations of UTH radiances • Evaluation of HadAM3 using satellite data

  3. 60_ CWV (kgm-2) Water vapour and OLR 30_ • Clausius Clapeyron • Radiative Transfer 0 270 280 290 300 Surface Temperature (K)

  4. - Column integrated water vapour - Upper tropospheric moisture ?? Sensitivity of OLR to RH (using ERA-15)(Allan et al. 1999, QJ, 125, 2103) dOLR/dRH (Wm-2%-1) RH (%)

  5. Water vapour feedback: recent advances (1) Insensitive to resolution (Ingram 2002, J Climate, 15, 917-921) (2) Consistent with observations following post-Pinatubo cooling (Soden et al 2002, Science, 296, 727)

  6. 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), 4329. doi: 10.1029/2001JD001131. - Temperature lapse rate (Gaffen et al 2000, Science, 287, 1242) - Tropical Cloudiness (Wielicki et al, 2002, Science, 295, 841)

  7. Large changes in OLR from 7 independent satellite instruments (Wielicki et al, 2002) HadAM3/HadCM3 cannot simulate recent changes in cloudy portion of tropical radiation budget even when current climate forcings are applied (Allan & Slingo 2002, GRL, 29(7), doi: 10.1029/2001GL014620)

  8. EXPERIMENTS [Allan et al. 2003, accepted QJ] • Ensemble of AMIP-type HadAM3 runs • Standard res, 19 levels, 1978-1999. HadISST SST/sea ice forcing • Radiance code[see Ringer et al., 2002, QJ, 129, 1169-1190] • Modified clear-sky diagnostics: OLRc & water vapour radiance • Additional “all-forcings” run • SATELLITE DATA • - column water vapour, CWV[SMMR 1979-84, SSM/I 1987-99] • - clear-sky OLR[ERBS 1985-89, ScaRaB 1994/5, CERES 1998] • - Water Vapour channel brightness temperature, T6.7 [HIRS 1979-1998]

  9. Climatological mean over 60oS-60oN oceans

  10. COLUMN WATER VAPOUR OBSERVATIONS HadAM3 JJA HadAM3-OBS difference DJF

  11. Interannual variability of Column Water vapour 1980 1985 1990 1995

  12. Can we use reanalysis CWV? ERA-40

  13. Info on upper tropospheric water vapour T6.7 500mb omega Clear-sky OLR

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

  15. Interannual monthly anomalies: tropical oceans

  16. (+additional forcings)

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

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

  19. Using ERA40 clear-sky OLR to evaluate dynamical regimes ERA40-CERES similar ERA40 < CERES ERA40 minus CERES clear-sky OLR (January-August 1998)

  20. Summary • Simulations of satellite brightness temperatures • Consistent decadal variability suggests small DRH realistic • Clear-sky sampling important for infrared channel climatologies but not interannual variability • Overactive circulation in HadAM3? • Note of caution: • can multiple satellite intercalibration artificially remove decadal trends? • Changes in atmos. T also influences T6.7 decadal fluctuations

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