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Do convection-permitting ensembles lead to more skilful short-range probabilistic rainfall forecasts over tropical East Africa?

Cafaro, C. ORCID:, Woodhams, B. J., Stein, T. ORCID:, Birch, C. E., Webster, S., Bain, C. L., Hartley, A., Clarke, S., Ferrett, S. and Hill, P. (2021) Do convection-permitting ensembles lead to more skilful short-range probabilistic rainfall forecasts over tropical East Africa? Weather and Forecasting, 36 (2). pp. 697-716. ISSN 1520-0434

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To link to this item DOI: 10.1175/WAF-D-20-0172.1


Convection-permitting ensemble prediction systems (CP-ENS) have been implemented in the mid-latitudes for weather forecasting timescales over the past decade, enabled by the increase in computational resources. Recently, efforts are being made to study the benefits of CP-ENS for tropical regions. This study examines CP-ENS forecasts produced by the UK Met Office over tropical East Africa, for 24 cases in the period April-May 2019. The CP-ENS, an ensemble with parametrized convection (Glob-ENS), and their deterministic counterparts are evaluated against rainfall estimates derived from satellite observations (GPM-IMERG). The CP configurations have the best representation of the diurnal cycle, although heavy rainfall amounts are overestimated compared to observations. Pairwise comparisons between the different configurations reveal that the CP-ENS is generally the most skilful forecast for both 3-h and 24-h accumulations of heavy rainfall (97th percentile), followed by the CP deterministic forecast. More precisely, probabilistic forecasts of heavy rainfall, verified using a neighbourhood approach, show that the CP-ENS is skilful at scales greater than 100 km, significantly better than the Glob-ENS, although not as good as found in the mid-latitudes. Skill decreases with lead time and varies diurnally, especially for CP forecasts. The CP-ENS is under-spread both in terms of forecasting the locations of heavy rainfall and in terms of domain-averaged rainfall. This study demonstrates potential benefits in using CP-ENS for operational forecasting of heavy rainfall over tropical Africa and gives specific suggestions for further research and development, including probabilistic forecast guidance.

Item Type:Article
Divisions:No Reading authors. Back catalogue items
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:96759
Publisher:American Meteorological Society


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