Page 298 - 《高原气象》2026年第2期

高 原 气 象 45 卷
598

The Impact of Thinning Method in Radar Radial Wind

Assimilation on Heavy Rainfall Forecasting

1， 2
1， 2
3
LI Yinghua ， QIU Xiaobin ， WANG Ying ， DONG Qiru ， WANG Xuelian ， LIU Lili 1， 2
1， 2
1， 2
（1. Tianjin Key Laboratory for Oceanic Meteorology， Tianjin 300074， China；
2. Tianjin Institute of Meteorological Science， Tianjin 300074， China；
3. Tianjin Meteorological Observatory， Tianjin 300074， China）
Abstract： Assimilation of thinned radar radial wind data can help improve the model's forecasting capability for
short-term precipitation. However， the thinning method affects the distribution characteristics of the radar radial
wind super-observations（SOs）， which in turn affects the assimilation and prediction results. This study investi‐
gates the impact of radar radial wind thinning method on rainfall forecasting through sensitive experiments.
Based on a heavy rain event in North China， two experimental groups were conducted， employing radar radial
wind SOs with varying grid resolutions （by altering radial spacing or azimuthal interval）. The results show that
changing the radial spacing or azimuthal interval of super-observation box alters the extremes of the SOs and
their locations， thereby influencing both the intensity and position of the jet stream. The radial spacing additional‐
ly affects the jet height by influencing the altitude at which the extremes of the SOs occur， and it has a relatively
significant impact on the quantity of data obtained and the analysis error. The assimilation of radial wind SOs
with different grid resolution similarly adjusts the wind field， which can increase the cyclone of the shear line in
central and southern Hebei and the southerly component of the low-level jet in central Shandong. The grid resolu‐
tion of the SOs mainly affects the curvature of the cyclonic shear and the intensity of the southerly jet. For precipi‐
tation forecasting， assimilation radar radial wind SOs can improve the overall performance of precipitation fore‐
casts for the first 6 h of the model， particularly in capturing heavy precipitation events exceeding 25 mm. Mean‐
while， it provides better scores for 24 h forecasts of light and moderate rainfall and can restrain some false precip‐
itation forecasts. When a higher resolution of radial wind SOs is adopted， the forecasting performance for heavy
precipitation within 12 h improves significantly. The threat score， false alarm ratio， and probability of detection
（POD） of precipitation are more sensitive to changes in radial spacing during thinning， while variations in azi‐
muthal interval have a relatively more pronounced impact on forecasting bias.
Key words： radar radial wind assimilation； thinning； super observation； regional rainstorm