Drought Trends and Projections (Drought trends over and projections until 2100)
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1 Drought Trends and Projections (Drought trends over and projections until 2100) Jonathan Spinoni, PhD European Commission JRC - Unit E1 (Disaster Risk Management) jonathan.spinoni@ec.europa.eu EDO User Meeting, 9-10 November 2017, Ispra (IT)
2 Context and Motivations BEWARE We here discuss only one type of droughts, namely: METEOROLOGICAL DROUGHTS PAST Moderate global drought increase in the last decades Decreasing drought tendency in Northern Europe, increasing in Southern Europe in the last 50-60y FUTURE Climate change is expected to foster more frequent and severe drought events as the century passes But to what extent? And where? However, some results could also apply to agricultural and hydrological droughts, due to multiple time-scales investigated
3 Objectives and Goals Investigate European drought trends in the last six-seven decades Analyze meteorological drought trends and events at global scale Improve the spatial resolution of past and future drought outputs Use new data/simulations to study drought projections over Europe Complete the first global drought analysis using CORDEX data/runs Investigate the relation between drought and future desertification
4 Data and Methods (1) EUROPE Input Data Homog. ECA&D E-OBS v10-v16 (PAST) Monthly precipitation // /16 // 0.25 Monthly temperature // /16 // 0.25 Bias-adj. EURO-CORDEX (FUTURE) Monthly precipitation // // 0.11 Monthly temperature // // scenarios (RCP4.5 and RCP8.5), 11 simulations Standardized Precipitation Index (SPI) Underlying distribution: Gamma function Used for: past trends and future projections Standardized Precipitation-Evapotranspiration Index (SPEI) Underlying distribution: Log-logistic function Used for: past trends and future projections Reconnaissance Drought Indicator (RDI) Underlying distribution: Log-normal function Used for: past trends Composite drought indicator (SPI-SPEI-RDI) Used for: past trends Drought Indicators Baseline for all the indicators: the entire period analyzed Time-scales for all the indicators: 3 and 12 months PET: Thornthwaite or Hargreaves-Samani
5 Data and Methods (2) GLOBAL Input Data GPCCv5-v7 (PAST) Monthly precipitation // /13 // 0.5 CRUTSv (PAST) Monthly PET Penman-Monteith // // 0.5 Monthly precipitation // // 0.5 CORDEX (FUTURE) Monthly precipitation // // 0.44 Monthly temperature // // scenarios (RCP4.5 & RCP8.5), >85 simulations for 11 regions Drought Indicators Standardized Precipitation Index (SPI) Underlying distribution: Gamma function Used for: past trends and future projections Standardized Precipitation-Evapotranspiration Index (SPEI) Underlying distribution: Log-logistic function Used for: past trends and future projections Baseline for all the indicators: the entire period analyzed Time-scales for all the indicators: 3 and 12 months PET: Thornthwaite, Hargreaves-Samani, or Penman-Monteith More than 45 scientists contributed to provide us with CORDEX data for the 11 (+3) regions. The analyses for global drought projections based on CORDEX data are currently ongoing. Results are expected by spring 2018
6 Data and Methods (3) Event-based approach We focus on the drought events, not on cumulated variables Consequently we analyze the drought trends and projections of drought quantities related to drought events. Following this approach, we try to answer these questions: - Did the frequency of drought events increase in the last decades? Will it increase in 21 st century? - Did the drought events last longer, become more severe and/or intense in the last decades? Will they do in 21 st century? Key point: all the results are compared to a reference period ( for the past and for the future) Drought quantities Drought Frequency (DF) Usually computed as number of events per decade (10 years) Extreme Drought Frequency (ExDF) An extreme drought event is a drought event which has at least two consecutive months in extreme drought conditions Drought Duration (DD) Expressed in months, including the start and the end month of the drought Drought Severity (DS) Sum of the indicator value during the drought event If computed per country or region, it is normalized by dividing DS for the drought event threshold (which depends on the country or region and is always -1 at grid point scale) Exceptionally, we computed TDS (total drought severity), which is the sum of DS of each event for that period Drought Intensity (DI) Obtained as the ratio between drought severity and drought intensity Area in drought (DA) Average area in drought conditions during the drought event
7 Results (1) European past trends DF TDS TDD European drought trends ( ) Composite indicator (Spei, Spi, Rdi), E-OBS as input (In this case the approach is not event-based) Seasonal EU drought trends ( ) Spei and Spi computed separately, E-OBS as input DS Win DS Spr DS Sum DS Aut
8 Results (2) European future projections European drought projections ( ) under moderate emission scenario Spi and Spei computed separately Only one simulation used (A1B scenario) European drought projections ( ) Spei & Spi computed separately, EU-CORDEX as input 2 emission scenarios (rcp45 & rcp85) and 11 hi-res bias-adjusted simulations DF DD DS DI DF ExDF DS
9 Results (3) Global past trends DF TDS World drought frequency, duration, and severity maps ( ) This study is based on Spi-12 only, GPCC as input (In this case the approach is not event-based) TDD Results derived from drought events database ( ) Spei & Spi computed separately, GPCC & CRU as input Global tendency of combined DF and DS
10 Results (4) Global future projections Global drought projections ( ) Spei & Spi computed separately, CORDEX as input 2 emission scenarios (rcp45 & rcp85) and at least 8 simulations for each of the 11(+3) regions considered Expected results also include global projections of aridity maps, climate classification, desertification risk, and bio-classification shifts under climate change CSIRO CLMcom CLMcom CLMcom CLM DMI KNMI KNMI KNMI MPI CSC SMHI CCCma UQAM MOHC CNRM IPSL INERIS CCAM CCLM CCLM CLM3 5 CCLM RegCM4 3 HIRHAM5 RACMO22T RACMO22E RACMO21P REMO2009 RCA4 CanRCM4 CRCM5 HadGEM3 RA ALADIN53 WRF331F GLOB 44s AFR 44 AUS 44 EAS 44 AFR 44 AFR 44 MPI ESM LR AUS 44i ARC 44 CAM 44 (r21) MPI ESM MR CAS 44 CNRM CM5 GLOB 44s AFR 44 EAS 44 AFR 44 AUS 44i ACCESS1 0 GLOB 44s AUS 44i CCSM4 GLOB 44s AUS 44i NorESM1 M GLOB 44s AFR 44 AFR 44 AUS 44i ARC 44 GFDL CM3 GLOB 44s AUS 44i GFDL ESM2M AFR 44 CCCma CanESM2 AFR 44 AFR 44 NAM 44 ARC 44 ARC 44 NAM 44 NAM 44 CSIRO MK3 AFR 44 IPSL CM5A MR AFR 44 HadGEM2 ES AFR 44 AFR 44 EAS 44 CAS 44 AFR 44 ANT 44 CAM 44 ICHEC EC EARTH AFR 44 EAS 44 AFR 44 ANT 44 AFR 44 AUS 44 AFR 44 AFR 44 EAS 44 ARC 44 ARC 44 NAM 44 NAM 44 CAM 44 EAS 44 (r12) MIROC5 AFR 44 CCLM CCLM RCA4 RegCM4 3v0 v1 ALADIN52 WRF351 HadGEM2 ES MED 44 MED 44 MPI ESM LR MED 44 CNRM CM5 MENA 44 MED 44 NCAR CESM1 MENA 44 GFDL ESM2M MENA 44 Results expected by spring 2018 ICHEC EC EARTH MENA 44 CMCC CM MED 44 List of simulations used for this study
11 Next steps Implement the results in EDO/GDO Complete the analyses for global drought projections based on CORDEX data Compare the results with other similar studies Derive global projections for aridity, climate classification, and desertification risk Include vegetation-based indicator(s) Published Papers Spinoni J., Naumann G., Vogt J., Barbosa P., Dosio A.: Will drought events become more frequent and severe in Europe? International Journal of Climatology. Early view online, published on 9 October DOI: /joc.5291 Spinoni J., Naumann G., Vogt J.: Pan-European seasonal trends and recent changes of drought frequency and severity. Global Planetary Change, Vol. 148, pages Spinoni J., Naumann G., Vogt J.: Spatial patterns of European droughts under a moderate emission scenario. Adv. Sc. Res. 12, , Spinoni J., Naumann G., Vogt J., Barbosa P.: European drought climatologies and trends based on a multi-indicator approach. Glo. Pla.Cha. 127: 50-57, Spinoni J., Barbosa P., Carrao H., Naumann G., Vogt J.: World drought frequency, severity, and duration for Int. J. Climatol 34(8):
12 Any questions? You can find me
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