| dc.description.abstract | The occurrence of the heavy rainfall event over northern Taiwan on 8 September 2018 involves different weather systems, including a front, a tropical depression, and afternoon thunderstorms. This study investigates the establishment of a series of precipitation events by performing rapid update analyses with the WRF-LETKF Radar Assimilation System (WLRAS). In addition to using a standard convective-scale localization for radar observation, we apply a multi-scale correction scheme, the Successive Covariance Localization approach (SCL), to emphasize the importance of interaction between different scales. Moreover, we also assimilate the surface station data and the “no-rain” type of radar observation to improve the near-surface analysis.
First, the influence of radar data quality on the analysis using SCL is discussed. Using the quality-controlled radar data, we examine the optimal settings for SCL. With the optimized settings, the main focuses include the large-scale adjustment and its impact on the frontal wind structure, the importance of the surface wind structure, and how these factors further lead to the development of the local deep convections over the Taipei Basin. For the area with the frontal system, the magnitude of the prefrontal southwesterly flow and frontal circulation is essential. When the SCL method is applied in the radar assimilation, the large-scale adjustment can be achieved, which can help establish a well-structured frontal system with a more accurate position, but the intensity of convections is slightly underestimated due to insufficient secondary circulation. Through the adjusted large-scale dynamics, strong convection can be better maintained over the top of the Xueshan Range, and the resulting outflow of the cold pool further triggers the rapid development of the local thunderstorm over the Taipei Basin. Consequently, both the experiments using SCL and surface wind data can provide a suitable 4-D rapid update analysis field: The SCL can provide an environmental structure that facilitates the multiscale interaction, and the surface wind data can give a better representation of the near-surface environmental structure. This study suggests that to well represent the local convection development in a high-resolution convective scale data assimilation analysis, it is necessary to analyze not only the dynamic and thermodynamic structure of local convections but also the environment’s dynamic field. | en_US |