Impact of urbanization on the simulation of extreme rainfall in the city of Jeddah, Saudi Arabia
KAUST DepartmentEarth Fluid Modeling and Prediction Group
Earth Science and Engineering Program
Physical Science and Engineering (PSE) Division
Red Sea Research Center (RSRC)
KAUST Grant NumberREP/1/3268-01-01
Online Publication Date2020-04-22
Print Publication Date2020-05
Embargo End Date2020-10-22
Permanent link to this recordhttp://hdl.handle.net/10754/662650
MetadataShow full item record
AbstractThe city of Jeddah, Kingdom of Saudi Arabia is characterized by a hot and arid desert climate. Occasionally, however, extreme precipitation events have led to flooding that caused extensive damage in human life and infrastructure. This study investigates the effect of incorporating an urban canopy model and urban land cover when simulating severe weather events over Jeddah using the Weather Research and Forecasting (WRF) model at a convective-permitting scale (1.5-km resolution). Two experiments were conducted for 10 heavy rainfall events associated with the dominant large-scale patterns favoring convection over Jeddah: (i) an “urban” experiment included the urban canopy model and modern-day land cover, and (ii) a “desert” experiment replaced the city area with its pre-settlement, natural land cover. The results suggest that urbanization plays an important role in modifying rainfall around city area. The “urban” experiment enhances the amount of rainfall by 26% on average over the Jeddah city area comparing to the “desert” experiment in these extreme events. The changes in model-simulated precipitation are primarily tied to a nocturnal heat island effect that modifies the planetary boundary layer and atmospheric instability of the convective events.
CitationLuong, T. M., Dasari, H. P., & Hoteit, I. (2020). Impact of urbanization on the simulation of extreme rainfall in the city of Jeddah, Saudi Arabia. Journal of Applied Meteorology and Climatology. doi:10.1175/jamc-d-19-0257.1
SponsorsThis work was funded by King Abdullah University of Science and Technology (KAUST) under the Virtual Red Sea Initiative Grant # REP/1/3268-01-01. The research made use of the Supercomputing Core Laboratory resources at KAUST. Parts of the material in Sections 1 and 2 first appeared in Appendix B of Chapter 2 from (Luong 2015) and are repeated here for the readers' information.
PublisherAmerican Meteorological Society