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- Publisher
- Springer Journals
- Copyright
- Copyright © Pleiades Publishing, Ltd. 2020
- ISSN
- 1024-8560
- eISSN
- 2070-0393
- DOI
- 10.1134/S1024856020020086
- Publisher site
- See Article on Publisher Site
Abstract
First results of the study of the effect of lightning detection network data assimilation on the numerical weather forecast are analyzed. Methods for lightning data assimilation in weather prediction models are briefly overviewed. An algorithm used is described, as well as the results of numerical experiments and their analysis for seven weather forecasts for thunderstorms observed in the Krasnodar Territory, Russia, in 2017. It is found that the average absolute errors for all quantities due to thunderstorms are reduced. The work of the algorithm is shown in the comparison of daily precipitation maps for the seven weather forecasts with and without WWLLN network data assimilation. It was shown that the configuration of forecast precipitation fields and their intensity is significantly closer to the observations, especially for light precipitation (0–7 mm).
Journal
Atmospheric and Oceanic Optics – Springer Journals
Published: Mar 7, 2020