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首页> 外文期刊>Pure and Applied Geophysics >Intra-Seasonal Rainfall Variations and Linkage with Kharif Crop Production: An Attempt to Evaluate Predictability of Sub-Seasonal Rainfall Events
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Intra-Seasonal Rainfall Variations and Linkage with Kharif Crop Production: An Attempt to Evaluate Predictability of Sub-Seasonal Rainfall Events

机译：季节性季节性降雨变化和与<重点类型=“斜体”> Kharif 作物生产：试图评估次季节降雨事件的可预测性

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摘要

Abstract The sub-seasonal variation of Indian summer monsoon rainfall highly impacts Kharif crop production in comparison with seasonal total rainfall. The rainfall frequency and intensity corresponding to various rainfall events are found to be highly related to crop production and therefore, the predictability of such events are considered to be diagnosed. Daily rainfall predictions are made available by one of the coupled dynamical model National Centers for Environmental Prediction Climate Forecast System (NCEPCFS). A large error in the simulation of daily rainfall sequence influences to take up a bias correction and for that reason, two approaches are used. The bias-corrected GCM is able to capture the inter-annual variability in rainfall events. Maximum prediction skill of frequency of less rainfall (LR) event is observed during the month of September and a similar result is also noticed for moderate rainfall event with maximum skill over the central parts of the country. On the other hand, the impact of rainfall weekly rainfall intensity is evaluated against the Kharif rice production. It is found that weekly rainfall intensity during July is having a significant impact on Kharif rice production, but the corresponding skill was found very low in GCM. The GCM are able to simulate the less and moderate rainfall frequency with significant skill.
机译：摘要印度夏季季风降雨量的季节性变化高度影响喀里法庄稼生产与季节性降雨相比。发现与各种降雨事件相对应的降雨频率和强度与作物生产高度相关，因此，认为这种事件的可预测性被认为被诊断出来。每日降雨预测是由一个耦合的动态模型国家中心提供的环境预测气候预测系统（NCEPCFS）提供。每日降雨序列的模拟中的误差会影响偏压校正，因此使用两种方法。偏置的GCM能够捕获降雨事件中的年间变异性。在9月份的月份期间观察到降雨量减少（LR）事件的最大预测技能，并且对于中央区域的适度降雨事件，还注意到了类似的结果。另一方面，对kharif稻米生产评估了降雨周上降雨强度的影响。有人发现，7月期间每周降雨强度对Kharif大米生产​​产生重大影响，但相应的技能在GCM中非常低。 GCM能够模拟具有显着技能的较少和中等的降雨频率。

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