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INTRODUCTION

Exploiting observations of water vapour to investigate simulations of water vapour feedback processes Richard Allan, Tony Slingo Environmental Systems Science Centre, University of Reading Mark Ringer Hadley Centre, Met Office. INTRODUCTION.

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INTRODUCTION

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  1. Exploiting observations of water vapour to investigate simulations of water vapour feedback processesRichard Allan, Tony SlingoEnvironmental Systems Science Centre, University of ReadingMark RingerHadley Centre, Met Office

  2. INTRODUCTION • How does water (vapour/liquid/ice) respond to global warming? • Cruicial for Climate Sensitivity • Direct feedback: water vapour • Fundamental test of models • Can we determine water vapour feedback from observations of present day climate? • Can we use reanalyses? • do results link into present day changes in cloudiness?

  3. Previous studies Observational determination of water vapour feedback (e.g. Raval and Ramanathan 1989; Cess 1989; Soden et al. 2002; Forster & Collins 2004) Theoretical/ Modelling studies (e.g. Manabe and Wetherald 1967; Held and Soden 2000; Ingram 2002, Minschwaner and Dessler 2004)

  4. Climate sensitivity DTs~l DQ, l=-1/(bBB +bWV +bG+bCld+….), bWV~-(dOLR/dwv)(dwv/dTs) bG  bWV bCld Theory, Measurement Observations

  5. dOLRc/dwvtheoretical calculations

  6. OLR Sensitivity to Water Vapour

  7. dwv/dTs • Theoretical basis (Clausius Clapeyron) • dwv/dTs ~ 6 - 7.5%K-1(Wentz&Schabel 2000) • Can only measure dwv/dTs

  8. Interannual variability of Column Water vapour (Allan et al. 2003, QJRMS, p.3371) SST CWV 1980 1985 1990 1995 See also Soden (2000) J.Clim 13

  9. CWV Sensitivity to SST • dCWV/dTs = 3.5 kgm-2 K-1 for HadAM3 and Satellite Microwave Observations (SMMR, SSM/I) over tropical oceans • Corresponds to ~9%K-1 in agreement with Wentz & Schabel (2000) who analysed observed trends • But what about moisture away from the marine Boundary Layer?

  10. Can we use reanalyses? Reanalyses are currently unsuitable for detection of subtle trends associated with water vapour feedbacks Allan et al. 2004, JGR, accepted

  11. Observations of clear-sky OLR and the greenhouse parameter • Clear-sky OLR sensitive to Ts and RH • dOLRc/dTs as proxy for water vapour feedback • e.g. Cess et al. (1990) – agreement between climate model dOLRc/dTs

  12. Observed and modelled changes in OLRc: ENSO • Soden (2000): ERBS vs AMIP multi model ensemble • Tropics, AMIP I 2 0 -2 dOLRc (Wm-2) 1983 1985 1987 1989

  13. Interannual monthly anomalies: tropical oceansHadAM3 vs ERBS, ScaRaB and CERESdga/dTs ~ 4 x 10-3 K-1Raval and Ramanathan (1989) get ~3.4x10-3 K-1 spatially ga=1-(OLRc/sTs4) 1980 1985 1990 1995 (Allan et al. 2003, QJRMS, p.3371)

  14. Does dOLRc/dTs indicate consistent water vapour feedback? • Consider GFDL & HadAM3 AMIP experiments • Interannual variability • dOLRc/dTs ~ 2 Wm-2 K-1 • BUT: differing height dependent Temperature and water vapour response • (Allan, Ramaswamy, Slingo, JGR 2002)

  15. Does dOLRc/dTs~2 Wm-2 K-1 indicate consistent water vapour feedback? HadAM3 GFDL HadAM3 GFDL dTa(p)/dTs dq(p)/dTs Allan et al. 2002, JGR, 107(D17), 4329.

  16. Water vapour / T-lapse rate • Compensation between water vapour and temperature lapse rate feedback in models • e.g. Colman (2003) • Sensitivity to convective parametrizations?

  17. Relative Humidity Feedback(include main component of bWV into bBB ?) DTs~l DQ, l=-1/(bBB +bRH +bCld+….), bRH~-(dOLR/dRH)(dwv/dRH) bBB: constant RH, G Theory, Measurement Observations

  18. Evaluation of upper tropospheric humidity feedback in HadAM3 • 6.7 mm cloud cleared radiance sensitive to upper tropospheric Relative Humidity • Explicitly simulate 6.7 mm radiance in HadAM3 • Modified “satellite-like” clear-sky diagnostics

  19. Sensitivity of OLRc to UTH

  20. Interannual monthly anomalies of 6.7 micron radiance: HadAM3 vs HIRS (tropical oceans) (Allan et al. 2003, QJRMS, p.3371) Small changes in T_6.7 (or RH) in model and obs (dUTH/dTs ~ 0 ?)

  21. (+additional forcings) (Allan et al. 2003, QJRMS, p.3371)

  22. Small changes in RH but apparently larger changes in tropical cloudiness? (Wielicki et al, 2002)

  23. +Altitude and orbit corrections (40S-40N) Clear LW LW SW Following: Wielicki et al. (2002); Allan & Slingo (2002)

  24. - Even considering the latest corrections to the ERBS WFOV data, models still appear to underestimate the variation of tropical mean cloudiness - This is despite the apparent agreement between models and observations that tropical mean Relative Humidity varies only slightly on a decadal time-scale

  25. Summary • reanalyses not yet suitable for analysis of climate sensitivity • Climate model captures: • low-level water vapour changes • Sensitivity: dCWV/dTs~3.5 kgm-2 K-1 • Decadal variation in clear-sky OLR • Sensitivity: dOLRc/dTs~2 Wm-2 K-1 • Small decadal changes in free-tropospheric RH • Sensitivity: dOLRc/dRH ~ – 0.5 to –1 Wm-2 %-1 • dRH/dTs ~ 0 % K-1 • But satellite data suggests larger variation in radiation budget due to cloud compared to models

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