Open AccessExperiments on lightning data assimilation: preliminary results
Author(s) -
K. G. Rubinstein,
I. M. Gubenko,
Yu. I. Yusupov,
N. D. Tikhonenko
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/698/4/044038
Subject(s) - weather research and forecasting model , meteorology , lightning (connector) , precipitation , data assimilation , numerical weather prediction , environmental science , storm , low pressure area , quantitative precipitation forecast , humidity , atmospheric pressure , atmospheric sciences , geology , geography , physics , power (physics) , quantum mechanics
This article is devoted to the analysis of the first results of the impact of lightning data assimilation on the numerical weather forecast. The article includes a description of the used algorithm and the results of the conducted numerical experiments for the convective storms over Krasnodar region of Russia observed in 2017. Numerical weather prediction model WRF-ARW (Weather Research and Forecast) and lighting data gathered from WWLLN (Worldwide Lightning Location Network) are used [1. 2]. It was found that the average absolute errors of the temperature. atmospheric pressure. humidity. precipitation and wind are reduced. It is shown that the configuration of prognostic precipitation fields and their intensity is much closer to the observations. This is especially clearly seen for shallow precipitation (0-7 mm).