Simulation of wet and dry West African monsoon rainfall seasons using the Weather Research and Forecasting model
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This paper presents an evaluation of the Weather Research and Forecasting (WRF) model in simulating wet and dry West African monsoon (WAM) rainfall seasons. Three model experiments with varying selected microphysics (MP), cumulus convection (CU), and planetary boundary layer (PBL) schemes based on previous study were performed. Each of the model combinations is used to run four WAM seasons that consist of two wet (2008 and 2010) and two dry years (2001 and 2011). To investigate the behavior of WAM in the context of wet and dry years, the four seasons were used to compute composites of wet and dry WAM seasons in terms of rainfall amount. The analyses majorly focus on the rainfall composites relative to rainfall from Global Precipitation Climatology Project (GPCP) and Tropical Rainfall Measurement Mission (TRMM) as well as temperature, moisture, and atmospheric circulation fields with respect to NCEP reanalyses. This study documents significant sensitivity in simulation of the West African monsoon to the choices of the MP, CU, and PBL schemes. The simulation with the combination of WRF single moment 5 (WSM5) MP, Yonsei University (YSU) PBL, and new Simplified Arakawa-Schubert CU (WSM5-YSU-nSAS) shows good spatial distribution pattern of rainfall and the dynamics associated with the monsoon. Quantitatively, the combination shows less agreement in distinguishing the selected WAM seasons compared with the Goddard MP, Mellor-Yamada-Janjic PBL, and Betts-Miller-Janjić CU (GD-MYJ-BMJ) and the WSM5, Mellor-Yamada-Nakanishi-Niino 2.5 level and new Tiedtke CU (WSM5-MYNN-nTDK). Also, the dynamical structures of the wet and dry WAM circulation composites are reasonably reproduced in GD-MYJ-BMJ and WSM5-YSU-nSAS. The GD-MYJ-BMJ was able to distinguish between wet and dry years and thus underscores its potential to reproduce climate change signals in future work.
Many thanks to NCAR’s MMM Laboratory for supporting the research work. We would like to acknowledge high-performance computing support from Cheyenne (doi: https://doi.org/10.5065/D6RX99HX) provided by NCAR’s Computational and Information Systems Laboratory, sponsored by the National Science Foundation. Also, thanks to the anonymous reviewers for the insightful comments and suggestions that helped to improve the quality of the paper.
The German Federal Ministry of Education and Research (BMBF) primarily funded this research through the Doctorate Research Programme-West African Climate System (DRP-WACS) hosted in the Federal University of Technology Akure (FUTA), Ondo State, Nigeria.
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