In the present study, local insitu observations are utilized in the Land Data Assimilation System (LDAS) to generate high-resolution (4 km and hourly) soil moisture (SM) and soil temperature (ST) data over India. Further, the impact of the LDAS-derived SM and ST initialization on simulation of pre-monsoon (March–May) thunderstorms over the Gangetic West Bengal region are assessed. The high-resolution (4 km and hourly) land surface conditions such as SM and ST data are prepared for the period from 2010 to 2013 using the LDAS forced with various insitu observations from Automatic Weather Stations (AWS), Meteorological Aviation Reports (METAR), and micro-meteorological tower observations over India. Four thunderstorm (TS) events during the pre-monsoon season of 2010 are considered for the numerical experiments using climatological SM and ST at coarser resolution (CNTR) and LDAS-generated high-resolution SM and ST (WLDAS) for initializing the Weather Research and Forecasting (WRF) Model. The efficacy of the LDAS-generated SM and ST data are verified against micro-meteorological tower observations at Kharagpur, West Bengal, and the results indicate the magnitude and variation in the data product are close to observations. The initialization of high-resolution LDAS-generated SM and ST in the WRF improves the simulation of near-surface air temperature, humidity, and pressure at Kharagapur. Most importantly, the location and timing of the storm are relatively better simulated in the WLDAS than CNTR over the Kolkata region. The study encourages the use of more local observations in the generation of high-resolution SM and ST data for application in the simulation of pre-monsoon TSs.

中文翻译：

---

地面资料在陆地资料同化系统中的结合及在季风前雷暴中尺度模拟中的应用

在本研究中，土地数据同化系统 (LDAS) 中利用当地原位观测来生成印度上空的高分辨率（4 公里和每小时）土壤水分 (SM) 和土壤温度 (ST) 数据。此外，还评估了 LDAS 衍生的 SM 和 ST 初始化对恒河西孟加拉地区的季风前（3 月至 5 月）雷暴模拟的影响。2010 年至 2013 年期间的高分辨率（4 公里和每小时）地表条件，例如 SM 和 ST 数据是使用 LDAS 强制使用来自自动气象站 (AWS)、气象航空报告 (METAR) 的各种现场观测结果的，以及印度上空的微气象塔观测。考虑使用 2010 年季风前季节的四次雷暴 (TS) 事件进行数值实验，使用较粗分辨率 (CNTR) 的气候 SM 和 ST 以及 LDAS 生成的高分辨率 SM 和 ST (WLDAS) 来初始化天气研究和预测 (WRF) 模型。LDAS 生成的 SM 和 ST 数据的有效性在西孟加拉邦 Kharagpur 的微气象塔观测中得到验证，结果表明数据产品的量级和变化与观测值接近。WRF 中高分辨率 LDAS 生成的 SM 和 ST 的初始化改进了对 Kharagapur 近地表气温、湿度和压力的模拟。最重要的是，与加尔各答地区的 CNTR 相比，WLDAS 中风暴的位置和时间相对更好地模拟。