In this study, projected changes in mean northeast monsoon (NEM) rainfall and associated extreme rainfall and temperature events, over peninsular India (PI) and its six subdivisions, are quantified. High-resolution dynamically downscaled simulations of the Weather Research and Forecasting (WRF) regional climate model driven by the boundary conditions from the Community Climate System Model version 4 (CCSM4) model (WRF-CCSM4) are compared with statistically downscaled simulations of NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP). Over PI, these downscaled simulations show low bias in mean NEM rainfall (≤ − 0.44 mm·day⁻¹) and high pattern correlation coefficient (≥0.75), giving confidence in their future projections. Under future warming over PI, both downscaled simulations project future significant enhancement in NEM rainfall with WRF-CCSM4 projecting 1.98 mm·day⁻¹ (83.78% change with respect to the present-day mean) whereas the multimodel ensemble (MME) of eight NEX-GDDP models project 0.67 ± 0.58 mm·day⁻¹ (19.78%) by the midddle of the century and 1.42 ± 0.97 mm·day⁻¹ (42.76%) by the end of the century. Analysis of extreme rainfall events shows that WRF-CCSM4 projects future enhancement (reduction) in extreme rainfall (R95p) days over 91.4% (8.6%) of grid-points over PI. In future, coastal areas of Karnataka and Andhra Pradesh will likely experience increased extreme rainfall occurrence by more than 25 days and 15–20 days respectively. Projected future enhancement in the mean and extreme NEM rainfall is attributed to the increased precipitable water under a warming climate. Future projection of extreme temperature indices shows an increase in minimum and maximum temperatures over PI during the NEM season. Over PI, future winter nights and days are found to be warmer than those in the present day and the temperature change in future winter nights is found to be larger than that in winter days. This climate change information would help decision-makers in evaluating existing policies and devising revised policies to reduce risk due to climate change.

中文翻译：

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印度半岛东北季风降雨的高分辨率气候变化预测

在这项研究中，对印度半岛 (PI) 及其六个分区的平均东北季风 (NEM) 降雨和相关极端降雨和温度事件的预测变化进行了量化。由社区气候系统模型第 4 版 (CCSM4) 模型 (WRF-CCSM4) 中的边界条件驱动的天气研究和预报 (WRF) 区域气候模型的高分辨率动态缩小模拟与 NASA 地球交换的统计缩小模拟进行比较全球每日缩减预测 (NEX-GDDP)。在 PI 上，这些按比例缩小的模拟显示平均 NEM 降雨量（≤ − 0.44 mm·day ⁻¹) 和高模式相关系数 (≥0.75)，使他们对未来的预测充满信心。在未来 PI 变暖的情况下，两个缩小的模拟预测未来 NEM 降雨量将显着增加，WRF-CCSM4 预测 1.98 毫米·天^-1（相对于当前平均值变化 83.78%），而 8 个 NEX 的多模式集合 (MME) -GDDP 模型预测到本世纪中叶0.67 ± 0.58 mm·day ^-1 (19.78%) 和 1.42 ± 0.97 mm·day ^-1(42.76%) 到本世纪末。对极端降雨事件的分析表明，WRF-CCSM4 预测未来极端降雨 (R95p) 天数超过 PI 网格点的 91.4% (8.6%)。未来，卡纳塔克邦和安得拉邦沿海地区的极端降雨量可能分别增加超过 25 天和 15-20 天。预计未来平均和极端 NEM 降雨量的增加归因于气候变暖下可降水量的增加。极端温度指数的未来预测显示，在 NEM 季节，最低和最高温度高于 PI。在PI上，发现未来冬夜和白天比现在更暖和，并且发现未来冬夜的温度变化大于冬日。