In this study, a dynamically downscaled regional climate model (RegCM4.3) is used to study the Indian summer monsoon (ISM) surface air temperature over the South-Asia CORDEX domain using six convection schemes during 1986–2010. The spatial and temporal variability of mean surface air temperature has been analysed with reference to the India Meteorological Department (IMD) analysis data using various statistical scores. The sensitivity experiments in selecting the best convective parameterized schemes have been performed in simulating the surface air temperature during the summer monsoon season (June–September) over India and its five sub-regions such as Northwest India, Northcentral India, West Peninsular India, Eastern Peninsular India, and Southern Peninsular India. The model results show the tendency of overestimation of surface air temperature mainly in four cumulus parameterization schemes (CPSs) that is, Tiedtke, Emanuel, Mix98, and Mix99 of RegCM4.3 during the JJAS, where Grell and Kuo CPSs show better agreement with the IMD data. Overall, Grell CPS has a close resemblance to the observation data with a minimum root mean square error, mean absolute error, lowest mean absolute percentage error (MAPE), and higher correlation coefficient. The model simulated results have also been investigated further using modified Nash Sutcliffe efficiency and modified Willmott's degree of index. These analyses confirm the potentiality of the Grell CPS followed by the Kuo CPS in simulating interannual variability of the surface air temperature over Indian and its five sub-regions. The MAPE in Grell and Kuo CPSs are 0.004 and 0.013°C during monsoon season over India, respectively. The inter-scheme difference in simulating surface air temperature is linked with the generation of low cloud convection and warming-induced atmospheric moisture advection in the schemes. Therefore, Emanuel, Tiedtke, and Mix98 CPSs have shown a persistent nature of overestimation in surface air temperature variability during JJAS. It is also inferred that after removing the systematic mean bias from the RegCM4.3 model simulated outputs; the skill of Emanuel, Mix98, and Mix99 could be useful over the Indian subcontinent except for the southern peninsular region.

中文翻译：

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使用区域气候模式研究印度及其地区夏季风地表气温的时空变化

在这项研究中，动态缩小的区域气候模型 (RegCM4.3) 用于研究 1986-2010 年期间使用六种对流方案在南亚 CORDEX 域上的印度夏季风 (ISM) 地表气温。参考印度气象部门 (IMD) 分析数据，使用各种统计分数分析了平均地表气温的空间和时间变化。选择最佳对流参数化方案的敏感性实验已经在模拟印度及其五个子区域（例如印度西北部、印度中北部、印度半岛西部、东部）夏季季风季节（6 月至 9 月）的地表气温中进行。印度半岛和南印度半岛。模型结果表明，在 JJAS 期间，RegCM4.3 的 Tiedtke、Emanuel、Mix98 和 Mix99 四种积云参数化方案（CPS）存在高估地表气温的趋势，其中 Grell 和 Kuo CPS 与IMD 数据。总体而言，Grell CPS 与观测数据非常相似，具有最小均方根误差、平均绝对误差、最低平均绝对百分比误差 (MAPE) 和更高的相关系数。还使用修正的 Nash Sutcliffe 效率和修正的 Willmott 指数程度进一步研究了模型模拟结果。这些分析证实了 Grell CPS 和 Kuo CPS 在模拟印度及其五个子区域地表气温年际变化方面的潜力。Grell 和 Kuo CPS 中的 MAPE 为 0。印度季风季节分别为 004 和 0.013°C。模拟地表气温的方案间差异与方案中低云对流和变暖引起的大气水分平流的产生有关。因此，Emanuel、Tiedtke 和 Mix98 CPS 在 JJAS 期间表现出持续高估地表气温变化的性质。还可以推断，在从 RegCM4.3 模型模拟输出中去除系统平均偏差后；伊曼纽尔、Mix98 和 Mix99 的技能在印度次大陆除了南部半岛地区外都可能有用。模拟地表气温的方案间差异与方案中低云对流和变暖引起的大气水分平流的产生有关。因此，Emanuel、Tiedtke 和 Mix98 CPS 在 JJAS 期间表现出持续高估地表气温变化的性质。还可以推断，在从 RegCM4.3 模型模拟输出中去除系统平均偏差后；伊曼纽尔、Mix98 和 Mix99 的技能在印度次大陆除了南部半岛地区外都可能有用。模拟地表气温的方案间差异与方案中低云对流和变暖引起的大气水分平流的产生有关。因此，Emanuel、Tiedtke 和 Mix98 CPS 在 JJAS 期间表现出持续高估地表气温变化的性质。还可以推断，在从 RegCM4.3 模型模拟输出中去除系统平均偏差后；Emanuel、Mix98 和 Mix99 的技能在印度次大陆（南部半岛地区除外）可能有用。