Abstract In this study, the impact of different land initial conditions on the simulation of thunderstorms and monsoon depressions is investigated using the Weather Research and Forecasting (WRF) model. A control run (CNTL) and a simulation with an improved land state (soil moisture and temperature) using the High Resolution Land Data Assimilation System (HRLDAS, experiment name: EHRLDAS) are compared for three different rainfall cases in order to examine the robustness of the assimilation system. The study comprises two thunderstorm cases (one in the pre-monsoon and one during the monsoon) and one monsoon depression case that occurred during the Interaction of Convective Organisation, Atmosphere, Surface and Sea (INCOMPASS) field campaign of the 2016 Indian monsoon. EHRLDAS is shown to yield improvements in the representation of location-specific rainfall, particularly over land. Further, it is found that surface fluxes as well as convective indices are better captured for the pre-monsoon thunderstorm case in EHRLDAS. By analysing components of the vorticity tendency equation, it is found that the vertical advection term is the major contributor towards the positive vorticity tendency in EHRLDAS compared to CNTL, hence improving localised convection and consequently facilitating rainfall. Significant improvements in the simulation of the pre-monsoon thunderstorm are noted, as seen using Automatic Weather Station (AWS) validation, whereas improvements in the monsoon depression are minimal. Further, it is found that vertical advection (moisture flux convergence) is the major driver modulating the convective circulation in localised thunderstorm (monsoon depression) cases and these dynamics are better represented by EHRLDAS compared to CNTL. These findings underline the importance of accurate and high resolution land-state conditions in model initial conditions for forecasting severe weather systems, particularly the simulation of localised thunderstorms over India.

中文翻译：

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使用高分辨率陆地数据同化模拟特定地点的严重雷暴事件

摘要 本研究利用天气研究与预报（WRF）模型研究了不同陆地初始条件对雷暴和季风洼地模拟的影响。将控制运行 (CNTL) 和使用高分辨率土地数据同化系统 (HRLDAS，实验名称：EHRLDAS) 改进土地状态（土壤湿度和温度）的模拟对三种不同降雨情况进行比较，以检查同化系统。该研究包括两个雷暴案例（一个在季风前，一个在季风期间）和一个在 2016 年印度季风的对流组织、大气、表面和海洋相互作用 (INCOMPASS) 现场活动期间发生的季风低压案例。EHRLDAS 被证明可以改善特定地点降雨的表示，特别是在陆地上。此外，还发现 EHRLDAS 中季风前雷暴情况可以更好地捕获地表通量和对流指数。通过分析涡度趋势方程的组成部分，发现与 CNTL 相比，垂直平流项是 EHRLDAS 中正涡度趋势的主要贡献者，从而改善了局部对流，从而促进了降雨。如使用自动气象站 (AWS) 验证所见，季风前雷暴的模拟得到了显着改善，而季风低气压的改善则微乎其微。更多，发现垂直平流（水分通量会聚）是调节局部雷暴（季风低压）情况下对流环流的主要驱动因素，与 CNTL 相比，EHRLDAS 更好地代表了这些动态。这些发现强调了准确和高分辨率的陆地状态条件在预测恶劣天气系统的模型初始条件中的重要性，特别是对印度局部雷暴的模拟。