Version 1
: Received: 16 February 2022 / Approved: 18 February 2022 / Online: 18 February 2022 (17:41:50 CET)
How to cite:
Shiferaw, A.; Tadesse, T.; Rowe, C. Weather Research and Forecasting Model Sensitivity to Choice of Parameterization over Ethiopia. Preprints2022, 2022020239. https://doi.org/10.20944/preprints202202.0239.v1
Shiferaw, A.; Tadesse, T.; Rowe, C. Weather Research and Forecasting Model Sensitivity to Choice of Parameterization over Ethiopia. Preprints 2022, 2022020239. https://doi.org/10.20944/preprints202202.0239.v1
Shiferaw, A.; Tadesse, T.; Rowe, C. Weather Research and Forecasting Model Sensitivity to Choice of Parameterization over Ethiopia. Preprints2022, 2022020239. https://doi.org/10.20944/preprints202202.0239.v1
APA Style
Shiferaw, A., Tadesse, T., & Rowe, C. (2022). Weather Research and Forecasting Model Sensitivity to Choice of Parameterization over Ethiopia. Preprints. https://doi.org/10.20944/preprints202202.0239.v1
Chicago/Turabian Style
Shiferaw, A., Tsegaye Tadesse and Clinton Rowe. 2022 "Weather Research and Forecasting Model Sensitivity to Choice of Parameterization over Ethiopia" Preprints. https://doi.org/10.20944/preprints202202.0239.v1
Abstract
A 3-month (June-August) regime of the year 2002 summer rainfall (JJA2002) was simulated with 30 physics combinations using the Weather Research and Forecasting (WRF) model at 12-km horizontal grid resolution. The objective is to examine summer rainfall sensitivity to parameterization of microphysical, convective, and boundary layer processes and identify the best possible combination of parameterization options that perform relatively better in simulating the spatial and temporal distribution of summer rains over Ethiopia. The WRF simulated rainfall was evaluated against station data and satellite rainfall products (CHIRPS and ENACTS) using mean absolute error, Pearson and Pattern correlation coefficients (PCC), pattern correlation, and error in a number of rainy days as evaluation metrics. Summer rainfall is found to be most sensitive to the choice of cumulus parameterization and least sensitive to cloud microphysics. All simulations captured the spatial distribution of mean seasonal precipitation with PCC ranging from 0.89-0.94. However, all simulations overestimated precipitation amount and number of rainy days. Out of the 30, the simulations that use a combination of Grell-3D cumulus scheme, ACM2 boundary layer, Lin Microphysics, Dudhai shortwave radiation, and RRTM longwave radiation scheme ranked the top and provided the most realistic simulation in terms of amount and spatio-temporal distribution of summer rainfall.
Environmental and Earth Sciences, Atmospheric Science and Meteorology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
