The coastal districts of Tamil Nadu (CDT) receive a maximum portion of rainfall during the Northeast Monsoon (NEM) season from October to December (OND). It is during this season that the coastal community of Tamil Nadu encounters severe cyclonic storms causing floods, and the lack of uniform rainfall during this season leads to drought. The study focuses on analyzing the intraseasonal, interannual and interdecadal trend between the El Niño Southern Oscillation (ENSO) northeast monsoon rainfall (NEMR) and ENSO southwest monsoon rainfall (SWMR) for the years from 1971 to 2015. The direct dependence of excess and deficit rainfall on the El Niño and La Niña events, respectively, during the last five decades is evident from the obtained results. Moreover, the intraseasonal climate anomaly values have been used to account for the deviations from normal in the rainfall pattern. Projection of extreme NEM events in the CDT up to mid-century (2050) was derived from CMIP5 (Coupled Model Intercomparison Project Phase 5) simulations for Representative Concentration Pathways (RCPs) 4.5 and 8.5 scenarios. The bias-corrected sea surface temperature (SST) data from the models were used to calculate the Oceanic Niño Index (ONI) for the historical period (1971–2015) which was then compared to the observed data. The same was also used for NEM extreme event validation and evaluation. The proposed approach has important implications for climatological studies and also for evaluating the impact of climate change on localized regions, which will aid in predicting future extreme events.

泰米尔纳德邦 (CDT) 沿海地区在 10 月至 12 月 (OND) 的东北季风 (NEM) 季节期间降雨量最大。正是在这个季节，泰米尔纳德邦沿海社区遭遇严重的气旋风暴导致洪水泛滥，而这个季节缺乏均匀的降雨导致干旱。研究重点分析了1971-2015年厄尔尼诺南方涛动(ENSO)东北季风降水(NEMR)和ENSO西南季风降水(SWMR)之间的季内、年际和年代际趋势。从获得的结果可以明显看出过去五年中厄尔尼诺和拉尼娜事件的降雨量。而且，季节内气候异常值已被用于解释降雨模式与正常情况的偏差。到本世纪中叶（2050 年）CDT 中极端 NEM 事件的预测源自代表浓度路径 (RCP) 4.5 和 8.5 情景的 CMIP5（耦合模型比对项目第 5 阶段）模拟。来自模型的偏差校正海面温度 (SST) 数据用于计算历史时期 (1971-2015) 的海洋尼诺指数 (ONI)，然后将其与观测数据进行比较。同样也用于 NEM 极端事件验证和评估。提议的方法对气候学研究以及评估气候变化对局部地区的影响具有重要意义，这将有助于预测未来的极端事件。到本世纪中叶（2050 年）CDT 中极端 NEM 事件的预测源自代表浓度路径 (RCP) 4.5 和 8.5 情景的 CMIP5（耦合模型比对项目第 5 阶段）模拟。来自模型的偏差校正海面温度 (SST) 数据用于计算历史时期 (1971-2015) 的海洋尼诺指数 (ONI)，然后将其与观测数据进行比较。同样也用于 NEM 极端事件验证和评估。提议的方法对气候学研究以及评估气候变化对局部地区的影响具有重要意义，这将有助于预测未来的极端事件。到本世纪中叶（2050 年）CDT 中极端 NEM 事件的预测源自代表浓度路径 (RCP) 4.5 和 8.5 情景的 CMIP5（耦合模型比对项目第 5 阶段）模拟。来自模型的偏差校正海面温度 (SST) 数据用于计算历史时期 (1971-2015) 的海洋尼诺指数 (ONI)，然后将其与观测数据进行比较。同样也用于 NEM 极端事件验证和评估。提议的方法对气候学研究以及评估气候变化对局部地区的影响具有重要意义，这将有助于预测未来的极端事件。