Understanding mesoscale convective processes over the Congo Basin using the Model for Prediction Across Scales-Atmosphere (MPAS-A)

  • Siyu Zhao
  • , Rong Fu
  • , Kelly Núñez Ocasio
  • , Robert Nystrom
  • , Cenlin He
  • , Jiaying Zhang
  • , Xianan Jiang
  • , Joao Teixeira

Research output: Contribution to journalArticlepeer-review

Abstract

The Congo Basin in Central Africa is one of three convective centers in the tropics, characterized by a high proportion of precipitation produced by mesoscale convective systems (MCSs). However, process-level understanding of these systems and their relationship to environmental factors over the Congo Basin remains unclear, largely due to scarce in-situ observations. This study employs the Model for Prediction Across Scales–Atmosphere (MPAS-A), a global cloud-resolving model, to investigate MCSs in this region. Compared to satellite-observed brightness temperature (Tb), MPAS-A realistically simulates key MCS features, allowing a detailed comparison between two mesoscale convective complex (MCC) cases: one over the southern mountainous region (MCC-south) and the other over the northern lowland forests (MCC-north). MCC-south is larger, longer-lived, and moves a longer distance than MCC-north. Our analysis shows that MCC-south is supported by higher convective energy and more favorable vertical wind shear. The shear extends up to 400 km ahead of the convection center, exhibits a strong association with Tb variability, and is well balanced by a moderately strong cold pool. In contrast, MCC-north features weaker, localized shear near the center and a stronger cold pool. The African Easterly Jet helps maintain the shear in both cases, but an overly strong jet may suppress low-level westerlies and weaken convection. These results show how latitude and topography modulate environmental influences on Congo Basin MCS developments. The findings underscore the value of global cloud-resolving models for understanding convective systems and their impacts on weather extremes and societal risks in data-sparse regions.

Original languageEnglish
Pages (from-to)17301-17318
Number of pages18
JournalAtmospheric Chemistry and Physics
Volume25
Issue number23
DOIs
StatePublished - Dec 2 2025
Externally publishedYes

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