An evaluation of operational and research weather forecasts for southern West Africa using observations from the DACCIWA field campaign in June–July 2016

Abstract

Reliable and accurate weather forecasts, particularly those of rainfall and its extremes, have the potential to improve living conditions in densely populated southern West Africa (SWA). The limited availability of observations has long impeded a rigorous evaluation of current state-of-the-art forecast models.The field campaign of the Dynamics-Aerosol-Chemistry-Cloud Interactions in West Africa (DACCIWA) project in June-July 2016 has created an unprecedentedly dense set of measurements from surface stations and radiosondes.Here we present results from a comprehensive evaluation of both numerical model forecasts and satellite products using these data on a regional and local level. Results reveal a substantial observational uncertainty showing considerable underestimations in satellite estimates of rainfall and low-cloud cover with little correlation at the local scale. Models have a dry bias of 0.1-1.9 mm ⋅ day −1 in rainfall and too low column relative humidity. They tend to underestimate low clouds, leading to excess surface solar radiation of 43 W ⋅ m −2 . Remarkably, most models show some skill in representing regional modulations of rainfall related to synoptic-scale disturbances, while local variations in rainfall and cloudiness are hardly captured. Slightly better results are found with respect to temperature and for the post-onset rather than for the pre-onset period. Delicate local features such as the Maritime Inflow phenomenon are also rather poorly represented, leading to too cool, dry and cloudy conditions at the coast. Differences between forecast days 1 and 2 are relatively small and hardly systematic, suggesting a relatively quick error saturation. Using explicit convection leads to more realistic spatial variability in rainfall, but otherwise no marked improvement. Future work should aim at improving the subtle balance between the diurnal This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Receiver operating characteristic (ROC) movies, universal ROC (UROC) curves, and coefficient of predictive ability (CPA)

“…9b-c) resemble each other, but show remarkable differences to the RMSE based analysis. Most notable are their low values in the tropics, which indicate poor performance of all forecasts, well in line with recent findings in meteorology (Kniffka et al 2020). In contrast, the low RMSE suggests superior performance in this region.…”

The influence of DACCIWA radiosonde data on the quality of ECMWF analyses and forecasts over southern West Africa

“…For higher‐resolution deterministic forecasts, Kniffka et al . () find very little correlation between station observations of rainfall and collocated forecasts, while propagating synoptic‐scale vortices and waves (Knippertz et al ., ) appear to enhance predictability for southern West Africa as a whole.…”

Verification of operational numerical weather prediction model forecasts of precipitation using satellite rainfall estimates over Africa

“…In many countries, global NWP centers are well connected with their National Meteorological Agencies or Forecasting Offices, where forecasters are well trained and make best use of NWP products. The variations in skill of NWM across African geographies and climatologies are well studied (Gebremichael et al, 2022; Gebrechorkos et al, 2018; Kniffka et al, 2020; Linden et al, 2020; Maidment et al, 2013; Ogutu et al, 2017; Taraphdar et al, 2016; Tompkins & Feudale, 2010 among others). However, a large proportion of research efforts have focused on seasonal or climate timescales, or restricted analysis to specific regions of Africa, or individual weather phenomena or events.…”