Assessment of WRF model simulations of extreme rainfall events in West Africa: a comprehensive review

Abstract

The need to advance operational capacities in numerical weather prediction models across West Africa is becoming increasingly urgent, given the rising frequency and intensity of extreme rainfall events in the region, particularly in Nigeria. This study conducted a systematic review to investigate the sensitivity and performance of the weather research and forecasting (WRF) model in simulating extreme rainfall events in Nigeria, employing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist for data filtering. The study synthesizes findings, revealing significant latitudinal variations in rainfall occurrences and an increasing trend in high rainfall amounts. Additionally, the WRF model’s capacity for short-range and probabilistic rainfall forecasting is highlighted. Other key takeaways include critical challenges related to model configurations, such as physics parameterization, initial lateral and boundary conditions, and model resolution. Notably, the study uncovered a research gap in simulating deep convective systems (e.g., Mesoscale convective systems (MCSs)), which are vital and could serve as a proxy for extreme rainfall prediction in Nigeria. Despite certain limitations affecting the performance of the WRF model in most of the selected studies, it remains a valuable tool for both operational and research purposes. Its potential applications include realistic weather simulations for quantitative rainfall predictions. The study provides valuable insights into the current state of extreme rainfall events in Nigeria, using the WRF model. Therefore, we recommend future studies focusing on multiple WRF experiments to explore the rainfall-associated dynamics across Nigeria.