© University of Reading 2009 1 Monitoring and understanding current changes in the global energy & water cycles Richard Allan.

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© University of Reading Monitoring and understanding current changes in the global energy & water cycles Richard Allan

© University of Reading Increased Precipitation More Intense Rainfall More droughts Wet regions get wetter, dry regions get drier Precipitation Change (%) CLIMATE MODEL PROJECTIONS IPCC WGI Precipitation Intensity Dry Days

© University of Reading Scenario Feedbacks e.g. Hawkins & Sutton (2009) BAMS How will the water cycle respond to warming? Can we effectively monitor current changes in the Earths energy balance and water cycle? What information can Earth Observation datasets provide on cloud feedbacks? Are cloud feedback/water cycle issues linked? Can we provide near-real time monitoring of models and observations using satellite data?

© University of Reading Some background Joke slide Does anyone want to buy my nearly-new research student?

© University of Reading Winning my freedom from Met Office…(but only as far as ESSC) Some background

© University of Reading Winning my freedom from Met Office…(but only as far as ESSC) Important numbers! Some background

© University of Reading Low-level water vapour rises with temperature at ~7%/K in models & observations John et al. (2009) GRL; Allan (2009) J Climate models Water Vapour (mm)

© University of Reading For a given precipitation event, more moisture would suggest more intense rainfall Can realism of model projections be assessed?

© University of Reading Frequency of rainfall intensities vary with SST in models and obs Frequency of intense rainfall increases with warming in models and satellite data Model scaling close to 7%/K expected from Clausius Clapeyron SSM/I satellite data suggest a greater response of intense rainfall to warming dP/dSST=7%/K Allan and Soden (2008) Science

© University of Reading Trenberth et al. (2009) BAMS

© University of Reading Models simulate robust response of clear-sky radiation to warming (~2-3 Wm -2 K -1 ) and a resulting increase in precipitation to balance (~3 %K -1 ) e.g. Allen and Ingram (2002) Nature, Stephens & Ellis (2008) J. Clim Radiative cooling, clear (Wm -2 K -1 ) Allan (2009) J Clim

© University of Reading Contrasting precipitation response expected Precipitation Heavy rain follows moisture (~7%/K) Mean Precipitation linked to radiation balance (~3%/K) Light Precipitation (-?%/K) Temperature e.g.Held & Soden (2006) J. Clim; Trenberth et al. (2003) BAMS; Allen & Ingram (2002) Nature

© University of Reading Contrasting precipitation response in ascending and descending portions of the tropical circulation GPCP/NCEPModels ascent descent Allan and Soden (2007) GRL Precipitation change (mm/day)

© University of Reading Future Plans

© University of Reading NERC PREPARE project (Met Office; ETH Zurich) - HadIR/JCRP projects (Met Office, NCEO) - leading ERL special focus issue (with Beate Liepert) - Planned UK/Danish Met Services NERC partnership grant on GPS ; NERC Changing Water Cycle program; NCEO; Royal Society - Changes in African and Asian Rainfall (Grimes, Turner, NCAS) Monitoring and understanding changes in the global energy/water cycles Precipitation Anomaly (mm/day) Radiation Anomaly (Wm -2 )

© University of Reading Allan et al. (2007) QJRMS 2008 Are the cloud feedback and water/energy cycles issues linked? - Radiative and microphysical properties of marine stratiform cloud (Stephens, Colorado; ECMWF) and ice cloud (Hogan) - CloudSat/CALIPSO, GERB/CERES, SSM/I (NCEO, Imperial, NASA) - Surface and Atmospheric Radiation Budget and aerosol (NASA, ETH)

© University of Reading Continuous Monitoring of models and observations Example 1: Global water cycle and Earths energy balance Essential Climate variables (ESA Harwell, NCEO) Reanalyses for climate (ECMWF)

© University of Reading Continuous Monitoring of models and observations Example 2: Model development with Met Office/NCAS from NWP (below, Milton, Brooks) to climate (Ringer, Williams) via Cascade (Woolnough) 13 th March | 14 th March 2006 Model SW albedo Change in model minus GERB flux differences: relate to change in model physics implementation Identify problem and fix: convective cloud decay time-scale Monitor improvement using GERB/CloudSat 12 3 Allan et al. (2007) QJRMS

© University of Reading Courtesy of Jim Haywood Continuous Monitoring of models and observations Example 3: field campaigns (e.g. RADAGAST; GERBILS; FENNEC) and opportunistic case studies… Met Office NAME model NOAA17 satellite image 20 March :06

© University of Reading Courtesy of Jim Haywood

© University of Reading Courtesy of Jim Haywood

© University of Reading Courtesy of Jim Haywood

© University of Reading Courtesy of Jim Haywood

© University of Reading Courtesy of Jim Haywood

© University of Reading Courtesy of Jim Haywood

© University of Reading Using GERB/SEVIRI to quantify radiative effects of persistent contrail cirrus

© University of Reading Conclusions Radiative energy and water cycles –fundamentally linked –crucial for climate impacts Combining observations with models and a robust physical basis is essential for –understanding current changes in climate –quantifying and assessing feedbacks operating –improving confidence in predictions Continuous monitoring of observations and model simulations enable us to –track current trajectory of climate change –detect surprises in the climate system –link and develop seamless prediction systems