Preprints
https://doi.org/10.5194/gmd-2024-194
https://doi.org/10.5194/gmd-2024-194
Submitted as: development and technical paper
 | 
05 Nov 2024
Submitted as: development and technical paper |  | 05 Nov 2024
Status: this preprint is currently under review for the journal GMD.

Impact of Multiple Radar Wind Profilers Data Assimilation on Convective Scale Short-Term Rainfall Forecasts: OSSE Studies over the Beijing-Tianjin-Hebei region

Juan Zhao, Jianping Guo, and Xiaohui Zheng

Abstract. The optimal spatial layout for a radar wind profiler (RWP) network in rainfall forecasting, especially over complex terrain, remains uncertain. This study explores the benefits of assimilating vertical wind measurements from various RWP network layouts into convective-scale numerical weather prediction (NWP) through observing system simulation experiments (OSSEs). Synthetic RWP data were assimilated into the Weather Research and Forecasting (WRF) model using the National Severe Storms Laboratory three-dimensional variational data assimilation (DA) system for three southwest (SW)-type heavy rainfall events in the Beijing-Tianjin-Hebei region. Four types of DA experiments were conducted and compared: a control experiment (CTL) that assimilates data solely from the operational RWP network, and three additional experiments incorporating foothill (FH), ridge (RD), and combined foothill-ridge (FH_RD) RWP network layouts. A detailed examination of the 21 July 2023 case reveals that the FH_RD experiment generally exhibits more skillful storm forecasts in terms of areal coverage, storm mode, and orientation, benifiting from refined mesoscale wind analysis. Particularly, in the RD experiment, RWP data assimilation notably reduces wind errors and enhances mesoscale dynamics near the Taihang Mountains upstream of Beijing, crucial for convective initiation (CI). Aggregated score metrics across all cases also indicate that both FH and RD experiments offer substantial added value over the operational network alone. Further sensitivity experiments on vertical resolution and maximum detection height indicate that the RWP system configuration with the highest detection height achieves the best performance, while lower detection height degrades forecast quality. These findings highlight the importance of strategic RWP network placement along the Taihang Mountains' ridge and foothill for short-term quantitative precipitation forecast in the Beijing-Tianjin-Hebei region.

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Juan Zhao, Jianping Guo, and Xiaohui Zheng

Status: open (until 31 Dec 2024)

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Juan Zhao, Jianping Guo, and Xiaohui Zheng
Juan Zhao, Jianping Guo, and Xiaohui Zheng

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Short summary
A series of observing system simulation experiments are conducted to assess the impact of multiple radar wind profiler (RWP) networks on convective scale numerical weather prediction. Results from three southwest-type heavy rainfall cases in the Beijing-Tianjin-Hebei region suggest the added forecast skill of ridge and foothill networks associated with the Taihang Mountains over the existing RWP network. This research provides valuable guidance for designing optimal RWP networks in the region.