Early warnings of hazardous thunderstorms over Lake Victoria

Journal Article (2017)
Author(s)

Wim Thiery (Vrije Universiteit Brussel, ETH Zürich)

Lukas Gudmundsson (ETH Zürich)

Kristopher Bedka (NASA Langley Research Center)

Fredrick H.M. Semazzi (University of North Carolina)

Stef Lhermitte (TU Delft - Civil Engineering & Geosciences)

Patrick Willems (Vrije Universiteit Brussel, Katholieke Universiteit Leuven)

Nicole P. M. van Lipzig (Katholieke Universiteit Leuven)

Sonia I. Seneviratne (ETH Zürich)

Research Group
Mathematical Geodesy and Positioning
DOI related publication
https://doi.org/10.1088/1748-9326/aa7521 Final published version
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Publication Year
2017
Language
English
Research Group
Mathematical Geodesy and Positioning
Issue number
7
Volume number
12
Article number
074012
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433
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Abstract

Weather extremes have harmful impacts on communities around Lake Victoria in East Africa. Every year, intense nighttime thunderstorms cause numerous boating accidents on the lake, resulting in thousands of deaths among fishermen. Operational storm warning systems are therefore crucial. Here we complement ongoing early warning efforts based on numerical weather prediction, by presenting a new satellite data-driven storm prediction system, the prototype Lake Victoria Intense storm Early Warning System (VIEWS). VIEWS derives predictability from the correlation between afternoon land storm activity and nighttime storm intensity on Lake Victoria, and relies on logistic regression techniques to forecast extreme thunderstorms from satellite observations. Evaluation of the statistical model reveals that predictive power is high and independent of the type of input dataset. We then optimise the configuration and show that false alarms also contain valuable information. Our results suggest that regression-based models that are motivated through process understanding have the potential to reduce the vulnerability of local fishing communities around Lake Victoria. The experimental prediction system is publicly available under the MIT licence at http://github.com/wthiery/VIEWS.