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Journal Article

Customized framework of the WRF model for regional climate simulation over the Eastern NILE basin


Lelieveld,  Jos
Atmospheric Chemistry, Max Planck Institute for Chemistry, Max Planck Society;

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Abdelwares, M., Haggag, M., Wagdy, A., & Lelieveld, J. (2018). Customized framework of the WRF model for regional climate simulation over the Eastern NILE basin. Theoretical and Applied Climatology, 134(3-4), 1135-1151. doi:10.1007/s00704-017-2331-2.

Cite as: http://hdl.handle.net/21.11116/0000-0003-0762-7
Different configurations of the Weather and Research Forecasting (WRF-ARW) regional climate model, centered over the Eastern Nile Basin, have been investigated. Extensive sensitivity analyses were carried out to test the model performance in simulating precipitation and surface air temperature, focusing on the horizontal extent of the simulation domain, the mesh size and the parameterizations of the boundary layer, radiation, cloud microphysics, and convection. A simulation period of 2 years (1998–1999) was used to assess the model performance during the rainy season (June–September) and the dry season (December–March). Three sets of numerical experiments were conducted. The first tested the effects of changing the horizontal extent of the simulation domain; three domains have been examined to investigate, e.g., the effect of including a larger part of the Indian Ocean, for which no significant impact was found. The second set of experiments tested the sensitivity of WRF to the horizontal mesh size (about 16, 12, and 10 km). It was found that increased resolution results in a more accurate simulation of precipitation and surface temperature. The third set of experiments was designed to select the optimal combination of physics parameterizations. All simulations were forced by ERA-Interim reanalysis data to provide initial and boundary conditions, including sea surface temperature, and the Noah land surface model (NPAH) was used to simulate land surface processes. To rate the model performance, we used a range of statistical metrics, summarized with a scoring technique to obtain a single index that ranks different alternatives. The simulated precipitation was found to be much more sensitive to the choice of physics parameterization compared to the surface air temperature. Precipitation was most sensitive to changing the cumulus and the planetary boundary layer schemes, and least sensitive to changing the microphysics scheme. Modifying the long-wave radiation scheme led to more significant changes compared to the short-wave radiation scheme.