Comparison of Two Kinds of Momentum Control Variables in 3DVAR During Assimilating Low-resolution Observations in a Convective-scale Model: a Case Study of Torrential Rainfall in North China

Dong, Qiru; Wang, Xuelian; Fan, Shuiyong; Li, Yinghua; Qiu, Xiaobin; Liu, Huan

doi:10.1007/s13143-022-00290-5

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“…EXP_CV7 improves the convective precipitation forecasts and distinctly reduces the spurious precipitation forecasted by EXP_CV5. This is consistent with the results of previous studies for assimilating both radar and other observations (Li et al, 2016;Sun et al, 2016;Thiruvengadam et al, 2019;Wang et al, 2020;Dong et al, 2022). In addition, it also significantly reduces the prediction error of surface variables.…”

Section: Summary and Discussionsupporting

confidence: 92%

“…Xu (2019) demonstrated that the choice of different momentum control variables is theoretically equivalent in the case that the error covariance function satisfies the derived relationship. Dong et al (2022) investigated the role of two control variable schemes for assimilating conventional observation data with a 3 km resolution model. With UV control variables, 0~6-h ground forecast was improved.…”

Section: Introductionmentioning

confidence: 99%

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Comparison of different momentum control variables on assimilating radar observations for the forecasts of a dispersive convective event

et al. 2023

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In this study, the effects of background error covariance (BE) using the stream function ψ and unbalanced velocity potential χu as momentum control variables (CV5 scheme) and BE using the velocity U and V as momentum control variables (CV7 scheme) on assimilating radar radial velocity and reflectivity data for short-term forecasts of dispersive convection in a weak environmental field are explored based on the weather research and forecasting model (WRF) model and its 3DVAR assimilation system. The 4 km resolution forecast samples are generated to formulate the CV5 and CV7 BE by the National Meteorological Center (NMC) method. The single-observation experiments reveal that the differences between the two BE statistics are mainly reflected on the momentum control variables. The increment of wind field from CV7 shows more small-scale local characteristics. Comparing with control experiment, real radar observation assimilation tests of CV5 and CV7 both improve the reflectivity and precipitation forecasts. But the CV7 scheme improves the forecasting of strong convective systems in weak environmental fields better than CV5. First, the CV7 scheme improves both reflectivity and dispersive precipitation forecasts and significantly suppresses the spurious precipitation forecasts when compared with the CV5 scheme. In addition, CV7 also significantly reduces the forecast errors of surface variables and the wind analysis from CV7 is more local. Further analysis shows that the CV7 improves the water vapor convergence conditions compared to the CV5 scheme, which may be the reason for its better performance in the subsequent forecasts.

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