Future intensification of hydro-meteorological extremes: downscaling using the weather research and forecasting model
KAUST DepartmentPhysical Sciences and Engineering (PSE) Division
Earth Science and Engineering Program
Permanent link to this recordhttp://hdl.handle.net/10754/623838
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AbstractA set of ten downscaling simulations at high spatial resolution (3 km horizontally) were performed using the Weather Research and Forecasting (WRF) model to generate future climate projections of annual and seasonal temperature and precipitation changes over the Eastern Mediterranean (with a focus on Lebanon). The model was driven with the High Resolution Atmospheric Model (HiRAM), running over the whole globe at a resolution of 25 km, under the conditions of two Representative Concentration Pathways (RCP) (4.5 and 8.5). Each downscaling simulation spanned one year. Two past years (2003 and 2008), also forced by HiRAM without data assimilation, were simulated to evaluate the model’s ability to capture the cold and wet (2003) and hot and dry (2008) extremes. The downscaled data were in the range of recent observed climatic variability, and therefore corrected for the cold bias of HiRAM. Eight future years were then selected based on an anomaly score that relies on the mean annual temperature and accumulated precipitation to identify the worst year per decade from a water resources perspective. One hot and dry year per decade, from 2011 to 2050, and per scenario was simulated and compared to the historic 2008 reference. The results indicate that hot and dry future extreme years will be exacerbated and the study area might be exposed to a significant decrease in annual precipitation (rain and snow), reaching up to 30% relative to the current extreme conditions.
CitationEl-Samra R, Bou-Zeid E, Bangalath HK, Stenchikov G, El-Fadel M (2017) Future intensification of hydro-meteorological extremes: downscaling using the weather research and forecasting model. Climate Dynamics 49: 3765–3785. Available: http://dx.doi.org/10.1007/s00382-017-3542-z.
SponsorsThis study was funded by the United States Agency for International Development through the USAID-NSF PEER initiative (Grant#–AID-OAA-A_I1_00012) in conjunction with support from the US National Science Foundation (Grant #CBET-1058027). EBZ was also supported by the US National Science Foundation’s Sustainability Research Network Cooperative Agreement 1444758. NCAR provided supercomputing resources through project P36861020. The research conducted by the KAUST team was supported by the King Abdullah University of Science and Technology. For computer time, HIRAM simulations used the resources of the Supercomputing Laboratory at KAUST in Thuwal, Saudi Arabia.