Nowcasting convective activity for the Sahel: a simple probabilistic approach using real‐time and historical satellite data on cloud‐top temperature

Anderson, Seonaid R. ORCID: https://orcid.org/0000-0001-8556-577X; Cole, Steven J. ORCID: https://orcid.org/0000-0003-4294-8687; Klein, Cornelia ORCID: https://orcid.org/0000-0001-6686-0458; Taylor, Christopher M. ORCID: https://orcid.org/0000-0002-0120-3198; Diop, Cheikh Abdoulahat; Kamara, Mouhamadou. 2024 Nowcasting convective activity for the Sahel: a simple probabilistic approach using real‐time and historical satellite data on cloud‐top temperature. Quarterly Journal of the Royal Meteorological Society, 150 (759). 597-617. https://doi.org/10.1002/qj.4607

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Abstract/Summary

Flash flooding from intense rainfall frequently results in major damage and loss of life across Africa. In the Sahel, automatic prediction and warning systems for these events, driven by Mesoscale Convective Systems (MCSs), are limited, and Numerical Weather Prediction (NWP) forecasts continue to have little skill. The ground observation network is also sparse, and very few operational meteorological radars exist to facilitate conventional nowcasting approaches. Focusing on the western Sahel, we present a novel approach for producing probabilistic nowcasts of convective activity out to six hours ahead, using the current location of observed convection. Convective parts of the MCS, associated with extreme and heavy precipitation, are identified from 16 years of Meteosat Second Generation thermal–infrared cloud-top temperature data, and an offline database of location-conditioned probabilities calculated. From this database, real-time nowcasts can be quickly produced with minimal calculation. The nowcasts give the probability of convection occurring within a square neighbourhood surrounding each grid point, accounting for the inherent unpredictability of convection at small scales. Compared to a climatological reference, formal verification approaches show the nowcasts to be skilful at predicting convective activity over the study region, for all times of day and out to the six-hour lead time considered. The nowcasts are also skilful at capturing extreme 24-hour rain gauge accumulations over Dakar, Senegal. The nowcast skill peaks in the afternoon, with a minimum in the evening. We find that the optimum neighbourhood size varies with lead time, from 10 km at the nowcast origin to around 100 km at a six-hour lead time. This simple and skilful nowcasting method could be highly valuable for operational warnings across West Africa and other regions with long-lived thunderstorms, and help to reduce the impacts from heavy rainfall and flooding.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1002/qj.4607
UKCEH and CEH Sections/Science Areas:	Hydro-climate Risks (Science Area 2017-)
ISSN:	0035-9009
Additional Information. Not used in RCUK Gateway to Research.:	Open Access paper - full text available via Official URL link.
NORA Subject Terms:	Meteorology and Climatology Atmospheric Sciences Data and Information
Related URLs:	Dataset Other
Date made live:	29 Jan 2024 08:34 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/536337

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