Assessing the performance of WRF model in predicting high-impact weather conditions over Central and Western Africa: an ensemble-based approach

P. Moudi Igri, Roméo S. Tanessong, D. A. Vondou, Jagabandhu Panda (), Adamou Garba, F. Kamga Mkankam and A. Kamga
Additional contact information
P. Moudi Igri: University of Yaounde I, Cameroon
Roméo S. Tanessong: University of Yaounde I, Cameroon
D. A. Vondou: University of Yaounde I, Cameroon
Jagabandhu Panda: National Institute of Technology Rourkela
Adamou Garba: Ecole Africaine de la Météorologie et de l’Aviation Civile (EAMAC)
F. Kamga Mkankam: University of Yaounde I, Cameroon
A. Kamga: African Center for Meteorological Applications and Development (ACMAD)

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2018, vol. 93, issue 3, No 22, 1565-1587

Abstract: Abstract For numerical weather prediction over a particular region, it is important to know the best combination of physical parameterizations available in the considered modelling frame work. The main objective of the study is to obtain the best combination of the weather research and forecasting (WRF) model physics for accurately simulating high-impact weather conditions, especially the rainfall over Western and Central Africa. For this purpose, performance of WRF from various simulations with specific configurations is assessed by comparing the results to the Tropical Rainfall Measurement Mission data. Each of the simulations is carried out for 30 h and initialized at 00 UTC. The spin-up time considered for the study is 6 h. A flood event (21–22 July 2010) is simulated by considering five cumulus physics schemes with multiple cloud microphysics, planetary boundary layer and land surface parameterizations. Analysis of the model results indicates that some of the physics combinations have good agreement with observations, especially the new (GFS) simplified Arakawa–Schubert and the modified Tiedtke cumulus parameterizations combined with Thompson and Morrison microphysics. However, most of the combinations over-estimated the rainfall over the study domain, while the simulations with Betts–Miller–Janjic cumulus parameterizations showed negative bias over designated regions of Africa.

Keywords: WRF; Rainfall; Weather prediction; Africa (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://link.springer.com/10.1007/s11069-018-3368-y Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:nathaz:v:93:y:2018:i:3:d:10.1007_s11069-018-3368-y

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11069

DOI: 10.1007/s11069-018-3368-y

Access Statistics for this article

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards is currently edited by Thomas Glade, Tad S. Murty and Vladimír Schenk

More articles in Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards from Springer, International Society for the Prevention and Mitigation of Natural Hazards
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().