Contrasting Precipitation Responses to Warming: Models and Satellite Data

1. Contrasting Precipitation Responses to Warming: Models and Satellite Data Richard P. Allan1 and Brian J. Soden2 1Environmental Systems Science Centre, University of Reading, UK 2Rosenstiel School of Marine and Atmospheric Sciences, University of Miami, USA Email: r.p.allan@reading.ac.uk R.Allan supported by NERC grant NE/C51785X/1 GPCP CMAP AMIP3 • CURRENT AND FUTURE TRENDS • Analysing separately the ascending and descending portions of the tropical circulation reveals contrasting precipitation trends • Positive trends in the moist, ascending regimes and negative trends in the dry, descending regions, are identified • Observed trends are larger in magnitude than current model simulations and future projections [Allan and Soden, 2007] DESCENT ASCENT Precipitation Changes (mm/day) ascent • Are the observed trends reliable? • Do the models fail to represent the hydrological cycle adequately? • Or do current trends relate to changes in radiative energy balance due to changes in aerosols? [Wild et al. 2008] CMIP3 models • INTRODUCTION • Changes in the hydrological cycle are of crucial importance to society [IPCC 2007] • Climate models predict an increase in the intensity of rainfall yet an increased severity of drought • Are the climate projections for the 21st century realistic? • Using satellite observations we examine present day variability and trends in precipitation and its intensity and evaluate model simulations Precipitation Changes (mm/day) descent GPCP Present day fluctuations in surface temperature, moisture and precipitation relate to El Niño Southern Oscillation cycles in addition to trends. Both offer a means to assess how the hydrological cycle may respond to future warming [Allan and Soden, 2008] • CHANGES IN THE INTENSITY OF PRECIPITATION • We compare daily precipitation from climate models with SSM/I data [Wentz et al. 2007] • An increase in the frequency of the heaviest rainfall is identified during warm El Niño years • Changes in lighter rainfall bins do not correspond well between the models and data • The models appear to underestimate the response of the heaviest rainfall frequency to warming compared with the SSM/I data • It is unclear whether this relates to a limitation of the satellite data or the models. For more details, see Allan and Soden (2008) • IMPLICATIONS • Convective rainfall relies on supply of moisture • Water vapour is observed and simulated to rise at the rate expected from the Clausius Clapeyron equation, about 7%/K • Mean precipitation is constrained by the slow changes in the atmospheric energy balance to rise at around 2-3 %/K [Allen and Ingram, 2002; Trenberth et al. 2003] References: R. P. Allan, B. J. Soden, Geophys. Res. Lett.34, L18705 (2007) R. P. Allan, B. J. Soden, Science321, 1481 (2008) M. R. Allen, W. J. Ingram, Nature419, 224 (2002). IPCC, Climate Change 2007 – Impacts, Adaptation and Vulnerability (2007) K. E. Trenberth, A. Dai, R. M. Rasmussen, D. B. Parsons, Bull. Am. Met. Soc.84, 1205 (2003). F. J. Wentz, L. Ricciardulli, K. Hilburn, C. Mears, Science317, 233 (2007) M. Wild, J. Grieser, C. Schär, Geophys. Res. Lett.35, L17706 (2008) Temperature  • Therefore rainfall is expected to diminish away from convective regimes • Do models and observations represent contrasting precipitation changes in the ascending and descending regions? • CONCLUSIONS • Models predict substantial changes in the global water cycle • There is evidence that the models may be underestimating responses of precipitation and its intensity to warming • It is first important to establish that the satellite datasets are reliable in addition to questioning the model forcing and physics Heavy rain follows moisture (~7%/K) Mean Precipitation linked to radiation balance (~3%/K) Precipitation  Light Precipitation (-?%/K)