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Journal Article

Citation

Mittermaier M, Wilkinson J, Csima G, Goodman S, Virts K. Meterol. Appl. 2022; 29(3): e2038.

Copyright

(Copyright © 2022, John Wiley and Sons)

DOI

10.1002/met.2038

PMID

unavailable

Abstract

Recently a new lightning diagnostic was added to convective-scale configurations of the Met Office Unified Model (UM). The characteristics and skill of the hourly total 'flash origin density' in the 4.4 km Tropical Africa UM were evaluated against Earth Network (EN) lightning observations specifically deployed in the greater Lake Victoria region as part of the HIGHWeather impact lAke sYstem (HIGHWAY) project. Lightning poses a significant risk to fishermen on Lake Victoria, and better forecasts over the lake would be advantageous for the development of better warning systems. The model lightning density was evaluated in two ways: a classical gridded categorical data analysis and the spatial coverage-distance-intensity method. Given the spatial sparseness of the observation type, Gaussian kernel dressing was applied for the latter, to increase the horizontal 'footprint', partly to reflect that lightning can travel horizontally for more than 10 km, and to reduce the representativeness mismatch between the lightning observations and the model forecast lightning density. Considering hourly forecasts, lightning shows a marked diurnal, geographical and seasonal variation over to the west and east of the lake. The model is not producing enough lightning flashes over the lake, nor does it produce enough spatially, especially overnight. The forecast location of lightning shows little skill, with timing differences in the peak, especially over the lake. For warnings, the removal of timing offsets through the creation of a 'maximum-in-the-day' field is considerably less biased and more skilful than using the hourly flash densities.


Language: en

Keywords

forecasting; hazards; lightning; remote sensing; severe weather; short-range

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