Takong et al. (2025) Simulating Widespread Extreme Rainfall Events Over the Drakensberg using the WRF and MPAS Models

Identification

• Journal: Earth Systems and Environment
• Year: 2025
• Date: 2025-11-18
• Authors: Ridick Roland Takong, Babatunde J. Abiodun
• DOI: 10.1007/s41748-025-00919-1

Research Groups

• Climate System Analysis Group, Department of Environmental and Geographical Science, University of Cape Town, Cape Town, South Africa
• Nansen-Tutu Centre for Marine Environmental Research, Department of Oceanography, University of Cape Town, Cape Town, South Africa

Short Summary

This study investigates the characteristics of widespread extreme rainfall events (WEREs) over the Drakensberg Mountain Range and evaluates the performance of the WRF and MPAS climate models in simulating these events and their associated synoptic features. The models realistically simulate rainfall patterns and synoptic drivers, identifying the eastern slopes as hotspots for intense WEREs primarily due to moisture transport from the Indian Ocean and Mozambique Channel.

Objective

• To examine the characteristics of widespread extreme rainfall events (WEREs) over the Drakensberg Mountain Range.
• To evaluate how well the WRF (Regional Climate Model) and MPAS (Variable-resolution Global Climate Model) represent these events and their associated synoptic features.
• To understand the characteristics of extreme rainfall events over the Drakensberg under different synoptic conditions.

Study Configuration

• Spatial Scale: Drakensberg Mountain Range (28°S to 32°S, 26°E to 32°E) within Southern Africa. WRF model domain with 25 km horizontal resolution; MPAS model with variable resolution from 92 km globally to 25 km over Southern Africa.
• Temporal Scale: Analysis period from 1 January 1987 to 31 December 2016 (30 years). Model simulations covered 1 December 1985 to 1 January 2017, with the first year removed for spin-up.

Methodology and Data

• Models used:
  • Weather Research and Forecasting (WRF) model (version 3.8, Advanced Research WRF core).
  • Model for Prediction Across Scales (MPAS) (version 7.0, Atmospheric model).
  • Self-Organizing Map (SOM) for classifying synoptic conditions and WERE patterns.
• Data sources:
  • Observational datasets (for evaluation): ARC2, CHIRPS, PERSIANN, WFDEI-CRU, WFDEI-GPCC.
  • Reanalysis data (for initial/boundary conditions and evaluation): NCEP Climate Forecast System Reanalysis (CFSR) and NCEP Climate Forecast System Version 2 (CFSRv2).
  • Extreme rainfall definition: A grid point experiences extreme rainfall if daily rainfall is ≥ 95th percentile. A WERE occurs when ≥ 40% of Drakensberg grid points simultaneously experience extreme rainfall.
  • Rainfall indices: Total precipitation (RTOT), Simple Daily Intensity Index (SDII), 95th percentile of daily precipitation (R95p), and total precipitation from R95p days (R95pTOT).

Main Results

• Both WRF and MPAS realistically simulate precipitation characteristics over Southern Africa, capturing the west–east gradient and local maxima over the Drakensberg and coastal regions.
• MPAS outperforms WRF in simulating total precipitation (RTOT) (spatial correlation r = 0.79, RMSE = 139 mm/year for MPAS; r = 0.78, RMSE = 176 mm/year for WRF).
• WRF excels in simulating the spatial pattern of daily intensity (SDII) (r = 0.61 for WRF; r = 0.39 for MPAS) and reproducing the precipitation-frequency curve over the Drakensberg, staying within observational spread for high intensities.
• Both models overestimate extreme precipitation (R95p and R95pTOT) over the Drakensberg and underestimate it over Mozambique.
• Nine dominant synoptic patterns were identified over Southern Africa, with tropical temperate troughs (TTTs, TTTe, DTT) and ridging highs (RSE, RHS) being most conducive to WERE formation.
• Four major WERE spatial patterns were identified: Eastern Widespread Rainfall (EWR), Northern Widespread Rainfall (NWR), Southern Widespread Rainfall (SWR), and Western Widespread Rainfall (WWR).
• EWR and NWR are the most common WERE groups, indicating the northern and eastern slopes as hotspots for extreme rainfall.
• The EWR pattern produces the widest and most intense rainfall, primarily driven by moisture transport from the tropical Indian Ocean and Mozambique Channel, with orographic lifting playing a critical role.

Contributions

• First study to apply both a Regional Climate Model (WRF) and a Variable-resolution Global Climate Model (MPAS) to simulate and understand widespread extreme rainfall events (WEREs) over the Drakensberg under various synoptic conditions.
• Provides a comprehensive evaluation of WRF and MPAS performance in simulating WEREs over complex terrain, detailing their strengths and biases across multiple precipitation indices.
• Offers a more defined classification of dominant synoptic patterns over Southern Africa (e.g., distinguishing three types of tropical temperate troughs) and explicitly links them to WERE occurrences.
• Identifies and maps specific hotspots and spatial extents of WERE patterns across the Drakensberg, providing crucial information for targeted mitigation and planning efforts.
• Reinforces the understanding of moisture transport dynamics, confirming the Indian Ocean and Mozambique Channel as primary moisture sources for WEREs in the region and highlighting the critical role of ridging highs and orographic lifting.

Funding

• National Research Foundation (NRF, South Africa) (Reference Number: RPOAM231218201502)
• International Development Research Centre (IDRC, Canada)
• Foreign, Commonwealth & Development Office (FCDO, UK)
• Pan-African and Transdisciplinary Lens in the Margins: Tackling the Risks of Extreme Events (PALM-TREEs)
• University of Cape Town Faculty of Science Ph.D. Fellowship
• International Students and Refugees Scholarship of the Postgraduate Funding Office
• Water Research Commission (WRC, South Africa)
• Degree Initiative

Citation

@article{Takong2025Simulating,
  author = {Takong, Ridick Roland and Abiodun, Babatunde J.},
  title = {Simulating Widespread Extreme Rainfall Events Over the Drakensberg using the WRF and MPAS Models},
  journal = {Earth Systems and Environment},
  year = {2025},
  doi = {10.1007/s41748-025-00919-1},
  url = {https://doi.org/10.1007/s41748-025-00919-1}
}