Scaling precipitation extremes with temperature in the Mediterranean: past climate assessment and projection in anthropogenic scenarios
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1 Scaling precipitation extremes with temperature in the Mediterranean: past climate assessment and projection in anthropogenic scenarios P. Drobinski (1), N. Da Silva (1), G., Panthou (2) S. Bastin (3), C. Muller (4), B. Ahrens (5), M. Borga (6), D. Conte (7), G. Fosser (8), F. Giorgi (9), I. Güttler (10), V. Kotroni (11), L. Li (1), E. Morin (12), B. Onol (13), P. Quintana-Segui (14), R. Romera (15), Torma Csaba Zsolt (9) (1) IPSL/LMD, Palaiseau and Paris, France; (2) IPSL/LSCE, Gif sur Yvette, France; (3) IPSL/LATMOS, Guyancourt, France; (4) LADHYX, Palaiseau, France; (5) IAU, Goethe-University Frankfurt, Frankfurt, Germany; (6) University of Padova, Legnaro, Italy; (7) CMCC, Lecce, Italy; (8) Meteo- France/CNRM, Toulouse, France; (9) ICTP, Trieste, Italy; (10) DHMZ, Zagreb, Croatia; (11) NOA, Athens, Greece; (12) Hebrew University of Jerusalem, Jerusalem, Israel; (13) Istanbul Technical University, Istanbul, Turkey; (14) Ebro Observatory, Roquetes, Tarragona, Spain; (15) Environmental Sciences Institute, University of Castilla-La Mancha, Toledo, Spain
2 Issues Fall Mediterranean HPE Météo-France weather stations Spring convection Winter frontal precipitation Arid summer, lower precipitation efficiency Southern France Drobinski et al. (2015) 1. Is there a relationship between maximum water vapor content and precipitation extremes? 2. Why do precipitation extremes change differ from CC-scaling? 3. Is the scaling of precipitation extremes predictive for future climate? 4. Is the scaling spatially variable over the Mediterranean region? Temperature break
3 Data and method Data RCM validation Type Data (time series) Location In-situ HyMeX Temperatures, precipitation 10 min-12h 6 countries: Spain, France, Italy, Croatia, Greece, Israel E-OBS Temperatures, precipitation, 24h Whole Mediterranean 14 RCMs ERA-I, CMIP5 (HIST, RCP8.5) Temperatures, precipitation, specific humidity 3h Whole Mediterranean Geographical patterns Method selection of rainy events (daily) sorted in increasing order of temperature (daily averaged) bins of 100 samples 99 ème qu. Pr. 50 ème qu. T C 99 ème qu. Pr. 50 ème qu. T C T C
4 Precipitation from stations at various time sampling Scaling of precipitation extremes in present climate 10 min., 20 min., 30 min., 1-hr, 3-h, 1-day in-situ, 1-day E-OBS 1. Hook shape robust whatever the time sampling ( Utsumi et al. 2011) 2. Temperature break decreases when going eastward (increasing aridity)
5 Daily precipitation from observations and RCM Scaling of precipitation extremes in present climate CMCC, CNRM, ICTP, ITU, IPSL, GUF, UCLM, LMD, 1-day in-situ, 1-day E-OBS 1. Inter-model spread in precipitation intensity 2. Simulated scaling of precipitation extremes well reproduced
6 Scaling of precipitation extremes in future climate CMCC, CNRM, ICTP, ITU, IPSL, GUF, UCLM, LMD, 1. Inter-model spread in precipitation extremes intensity similar scaling between ERA-Interim and CMIP5 historical runs 2. Good agreement for precipitation extremes scaling between ERA-Interim and CMIP5 historical runs
7 Scaling of precipitation extremes in future climate (RCP 8.5) CMCC, CNRM, ICTP, ITU, IPSL, GUF, UCLM, LMD +4 C +4 C 1. Temperature break increases by about 4-5 C (i.e. the average regional warming) 2. Temperature range with CC-scaling increases in future climate 3. Hook less steep, i.e. increased precipitation extremes intensity
8 Scaling of precipitation extremes in future climate CMCC, CNRM, ICTP, ITU, IPSL, GUF, UCLM, LMD, 1. Temperature-temperature change relationships characterized by a large spread across models 2. Non-linear scaling between temperature and temperature change 3. Non linear distortion of the temperature scale not enough to explain change in change of precipitation extremes scaling
9 Scaling of precipitation extremes in future climate Historical runs Future climate projections Corrected historical runs CMCC, CNRM, ICTP, ITU, IPSL, GUF, UCLM, LMD 1. Corrected historical runs agree with scaling of precipitation extremes in future climate projections 2. Applying CC-scaling correction using the simulated temperature range assumes conservation of relative humidity 3. Unexpected absence of trend of relative humidty at all Mediterranean sites (warming and drying)
10 Scaling of precipitation extremes in future climate ITU simulations Trenberth et al. (2003) Allen (2011) 1. Relative humidity decreases in arid regions (continental Europe, north Africa, Arabic Peninsula) 2. Relative humidity remains constant in the regions affected by marine source of humidity from the European Seas 3. Mediterranean Sea, source of moisture which compensates expected relative humidity decrease
11 RegCM4, Spain Conclusion Daily precipitations extremes (mm/h) Historical Corrected historical Conservation assumptions for future climate : Weather regimes (dynamics) Precipitations efficiency Relative humidity CC scaling Non predictive scaling Daily mean temperature ( C) 1. The scaling of precipitation extremes in the Mediterranean displays a robust hook shape 2. In a drying and warming region, the «Mediterranean» relative humidity remains constant in a changing climate 3. Increase of Mediterranean precipitation extremes expected to follow CC-scaling, i.e. ~7%/ C 4. Mediterranean Sea, most probably the origin of the increase of precipitation extremes intensity
12 With this pessimistic conclusion Genoa - Italy (October 2014) I thank you for your attention Questions? Gunja - Croatia (May 2014) Cannes France (October 2015)
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