A comprehensive understanding of the variation of Indian summer monsoon (ISM) features is necessary for accurate prediction of seasonal and sub-seasonal scale meteorological parameters. In this study, the summer monsoon features over India are investigated using RegCM simulations over South Asia Coordinated Regional Downscaling Experiment (SA-CORDEX) domain with 45-km spatial resolution. The initial-boundary data are derived from the European Centre for Medium Range Weather Forecasts Re-Analysis (ERA) and Geophysical Fluid Dynamics Laboratory (GFDL) analysis for the period 1989 to 2005. For both model simulations, mixed convection scheme (Emmanuel over ocean and Grell over land), Holtslag planetary boundary layer (PBL) scheme and biosphere atmospheric transfer system (BATS) land surface scheme are used throughout the experiment. The simulation results are validated with Climatic Research Unit (CRU) observations of precipitation and temperature. The spatial distribution of precipitation and temperature is reasonably simulated with ERA and GFDL analysis as compared with CRU observation. However, the simulation of precipitation and temperature with ERA analysis iscloser to CRU observations as compared with GFDL analysis. The seasonal scale (JJAS) simulation of precipitation with ERA and GFDL illustrates wet bias (2 mm per day) as compared to CRU observation, whereas temperature simulated with ERA indicated warm bias (1 °C) and GFDL depicts cold bias (2 °C) against CRU observations. The wind magnitude and distribution of ERA simulations show considerably higher magnitude over the western Himalaya which is connected to low values of specific humidity over the same terrain as compared with GFDL.

要准确预测季节和次季节尺度的气象参数，必须全面了解印度夏季风（ISM）特征的变化。在这项研究中，使用具有45 km空间分辨率的南亚协调区域缩小实验（SA-CORDEX）域上的RegCM模拟，研究了印度的夏季风特征。初始边界数据来自1989年至2005年期间的欧洲中型天气预报中心重新分析（ERA）和地球物理流体动力学实验室（GFDL）分析。对于这两种模型模拟，均采用混合对流方案（海洋上的伊曼纽尔在整个实验过程中，均采用Holtslag行星边界层（PBL）方案和生物圈大气转移系统（BATS）地表方案。通过气候研究单位（CRU）的降水和温度观测值对模拟结果进行了验证。与CRU观测相比，通过ERA和GFDL分析合理地模拟了降水和温度的空间分布。但是，与GFDL分析相比，用ERA分析模拟降水和温度更接近CRU观测结果。与CRU观测相比，使用ERA和GFDL进行的降水量的季节性尺度（JJAS）模拟显示出湿偏向（每天2 mm），而使用ERA模拟的温度显示出偏热（1°C），而GFDL显示出冷偏倚（2°C） ）反对CRU的观察。