1. r.p.allan@reading.ac.uk © University of Reading 2009 1 Monitoring and understanding current changes in the global energy & water cycles Richard Allan

2. r.p.allan@reading.ac.uk © University of Reading 2009 2 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

3. r.p.allan@reading.ac.uk © University of Reading 2009 3 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?

4. r.p.allan@reading.ac.uk © University of Reading 2009 4 Some background Joke slide Does anyone want to buy my nearly-new research student?

5. r.p.allan@reading.ac.uk © University of Reading 2009 5 Winning my freedom from Met Office…(but only as far as ESSC) Some background

6. r.p.allan@reading.ac.uk © University of Reading 2009 6 Winning my freedom from Met Office…(but only as far as ESSC) Important numbers! Some background

7. r.p.allan@reading.ac.uk © University of Reading 2009 7 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)

8. r.p.allan@reading.ac.uk © University of Reading 2009 8 1979-2002 For a given precipitation event, more moisture would suggest more intense rainfall Can realism of model projections be assessed?

9. r.p.allan@reading.ac.uk © University of Reading 2009 9 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

10. r.p.allan@reading.ac.uk © University of Reading 2009 10 Trenberth et al. (2009) BAMS

11. r.p.allan@reading.ac.uk © University of Reading 2009 11 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

12. r.p.allan@reading.ac.uk © University of Reading 2009 12 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

13. r.p.allan@reading.ac.uk © University of Reading 2009 13 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)

14. r.p.allan@reading.ac.uk © University of Reading 2009 14 Future Plans

15. r.p.allan@reading.ac.uk © University of Reading 2009 15 - 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 )

16. r.p.allan@reading.ac.uk © University of Reading 2009 16 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)

17. r.p.allan@reading.ac.uk © University of Reading 2009 17 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)

18. r.p.allan@reading.ac.uk © University of Reading 2009 18 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 2005 2006 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

19. r.p.allan@reading.ac.uk © University of Reading 2009 19 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 2009 10:06

20. r.p.allan@reading.ac.uk © University of Reading 2009 20 Courtesy of Jim Haywood

21. r.p.allan@reading.ac.uk © University of Reading 2009 21 Courtesy of Jim Haywood

22. r.p.allan@reading.ac.uk © University of Reading 2009 22 Courtesy of Jim Haywood

23. r.p.allan@reading.ac.uk © University of Reading 2009 23 Courtesy of Jim Haywood

24. r.p.allan@reading.ac.uk © University of Reading 2009 24 Courtesy of Jim Haywood

25. r.p.allan@reading.ac.uk © University of Reading 2009 25 Courtesy of Jim Haywood

26. r.p.allan@reading.ac.uk © University of Reading 2009 26 Using GERB/SEVIRI to quantify radiative effects of persistent contrail cirrus

27. r.p.allan@reading.ac.uk © University of Reading 2009 27 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