Advances in Numerical Weather Prediction in sub-Saharan Africa

Numerical Weather Prediction (NWP) models rely on numerous parameterizations to represent atmospheric processes that cannot be explicitly quantified because they happen on very small scales, such as droplet formation. However, these parameterizations are critical for a correct forecast of heavy rainfall. New sensitivity experiments have highlighted how important the mixing in the lower atmosphere is to correctly reproduce heavy rainfall dynamics.

On the African continent, there are very few examples of high-resolution numerical studies that try to model heavy rainfall events and study their dependence on the above-mentioned parameterizations. Two critical numerical schemes are (1) the microphysical one, which describes how cloud droplets form, grow and evolve (among many processes that it considers), and (2) the Planetary Boundary Layer one, which models the dynamics of the lowest layer of the atmosphere, that is characterized by very strong turbulent fluctuations.

By exploiting satellite rainfall products as validation, a set of numerical simulations performed with the Weather Research and Forecasting (WRF) model has shown that the way mixing in the lower atmosphere is treated can lead to major differences in the forecast of the heavy rainfall spatial distribution. In particular, the mixing role of large eddies in the lower atmosphere cannot be overlooked.

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Sensitivity experiments and the consequent definition of the most suitable parameterizations are a first step towards NWP model assimilation experiments of water vapor products derived from GNSS and SAR data processing. This step is expected to improve further weather predictions and to impact all the TWIGA services based on them


Meroni A. N., K. A. Oundo, R. Muita, M.-J. Bopape, T. R. Maisha, M. Lagasio, A. Parodi and G. Venuti (2021) Sensitivity of some African heavy rainfall events to microphysics and planetary boundary layer schemes: Impacts on localized storms, Quarterly Journal of the Royal Meteorological Society, 147, 2448-2468,