Abstract
A moderate precipitation event occurring in northern Xinjiang, a region with a continental climate with little rainfall, and in leeward slope areas influenced by topography is important but rarely studied. In this study, the performance of lightning data assimilation is evaluated in the short-term forecasting of a moderate precipitation event along the western margin of the Junggar Basin and eastern Jayer Mountain. Pseudo-water vapor observations driven by lightning data are assimilated in both single and cycling analysis experiments of the Weather Research and Forecast (WRF) three-dimensional variational (3DVAR) system. Lightning data assimilation yields a larger increment in the relative humidity in the analysis field at the observed lightning locations, and the largest increment is obtained in the cycling analysis experiment. Due to the increase in water vapor content in the analysis field, more suitable thermal and dynamic conditions for moderate precipitation are obtained on the leeward slope, and the ice-phase and raindrop particle contents increase in the forecast field. Lightning data assimilation significantly improves the short-term leeward slope moderate precipitation prediction along the western margin of the Junggar Basin and provides the best forecast skill in cycling analysis experiments.
Highlights
The Xinjiang Uygur Autonomous Region is located in the middle of Asia, is not affected by monsoons and exhibits typical continental climate characteristics [1,2]
Influenced by the topography of Jayer Mountain, a moderate precipitation event occurred along the western margin of the Junggar Basin in Xinjiang
In this study, lightning data were assimilated into a numerical model to improve precipitation forecasting
Summary
The Xinjiang Uygur Autonomous Region (hereinafter referred to as Xinjiang) is located in the middle of Asia, is not affected by monsoons and exhibits typical continental climate characteristics [1,2]. Based on the physical mechanism of lightning occurrence, an empirical relationship between ice-phase particles or the graupel content and the flash extent density (FED) can be established, and the FED is assimilated by nudging or ensemble methods [27,38,39,40,41,42] This assimilation method allows a direct update of the hydrometeor variables in the analysis field but lacks adjustment for the water vapor environment, and the innovation of ice and graupel is usually maintained for a limited time in the forecast. Current lightning data assimilation studies have mostly been conducted in monsoon-influenced regions where severe convection frequently occurs, considering thermal field adjustment schemes based on latent heat profiles, dynamic field adjustment schemes of the vertical velocity and hydrometeor variables describing the radar reflectivity and graupel and ice-phase particles or water vapor adjustment schemes.
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