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Decadal Variability in Water Vapour Richard Allan, Tony Slingo Environmental Systems Science Centre, University of Reading Mark Ringer Hadley Centre, Met Office. INTRODUCTION. Can we determine water vapour feedback from observations of present day climate?
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Decadal Variability in Water VapourRichard Allan, Tony SlingoEnvironmental Systems Science Centre, University of ReadingMark RingerHadley Centre, Met Office
INTRODUCTION • Can we determine water vapour feedback from observations of present day climate? • How does water vapour respond to changes in surface temperature? • Can we use reanalyses? • How do the results link in present day changes in cloudiness?
Previous studies Observational determination of water vapour feedback (e.g. Raval and Ramanathan 1989; Cess 1989; Soden et al. 2002) Theoretical/ Modelling studies (e.g. Manabe and Wetherald 1967; Ingram 2002)
Climate sensitivity DTs=l DQ, l=-1/(bBB +bWV +bG+bCld+….), bWV~-(dOLR/dwv)(dwv/dTs) bG bWV bCld Theory, Measurement Observations
Interannual variability of Column Water vapour (Allan et al. 2003, QJ, p.3371) 1980 1985 1990 1995 See also Soden (2000) J.Clim 13
CWV Sensitivity to Ts • dCWV/dTs = 3.5 kgm-2 K-1 for HadAM3 and Satellite Microwave Observations over tropical oceans • Corresponds to ~9%K-1 in agreement with Wentz & Schabel (2000) who analysed observed trends • What about upper tropospheric moisture?
Can we use reanalyses? Renalyses are currently unsuitable for detection of subtle trends associated with water vapour feedbacks
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 in HadAM3 • Modified “satellite-like” clear-sky diagnostics
Interannual monthly anomalies: tropical oceans ga=1-(OLRc/sTs4) (Allan et al. 2003, QJ, p.3371)
(+additional forcings) (Allan et al. 2003, QJ, p.3371)
Large changes in OLR from 7 independent satellite instruments (Wielicki et al, 2002)
Allan & Slingo 2002, GRL, 29(7) OLR Clear-sky OLR RSW +Altitude Correction?
- 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
Summary (1) • Climate model simulates low-level water vapour changes • Need to accurately measure upper tropospheric water vapour • Reanalyses are not an option at present • Satellite measurements of 6.7 mm radiances RH • Future use of GERB+SEVIRI
Summary (2) • Simulations of satellite brightness temperatures: Consistent decadal variability suggests small DRH realistic • can multiple satellite intercalibration artificially remove decadal trends in the UTH radiances? • Changes in atmospheric T also influences T6.7 decadal fluctuations • BUT…Satellite measurements suggest that cloudiness variations are much larger than produced by climate models. • Uncertainty remains over precise decadal variability of radiation • More wide-field of view instruments required? (simple yet well-calibrated for variability)
EOF analysis of spatio-temporal variability in water vapour radiance
Info on upper tropospheric water vapour T6.7 500mb omega Clear-sky OLR
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)
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)
Clear-sky sampling: interannual variability Light blue: Type I (weighted by clear-sky fraction) Dark Blue: Type II (unweighted mean)