A deficit in rainy days can affect crop production and escalate groundwater abstraction leading to groundwater depletion, thus may threaten food and water security in the Indian subcontinent. The available researches on rainfall occurrence in India represent inconsistency in several fundamental considerations (spatial scale of analysis, the definition of rainfall classes, methods, dataset, study period, etc.) and lack of studies for non-monsoon seasons over large parts of the subcontinent. Here we attempt to deal with these inconsistencies by examining space–time patterns in seasonal count of rainfall events and their count in different rainfall classes during 1951–2015 for all meteorological seasons of India using high resolution (0.25°) gridded daily rainfall dataset. The results show a widespread decline in monsoon rainy days over major crop-growing regions including north-central, central, and northeast India. A reduction in rainy days is also observed over parts of central India in premonsoon; over north-central and northeast India in postmonsoon; and over peninsular India in winter. These trends are mainly observed in events with rainfall <95th percentile (light to heavy rainfall events) in all the seasons. Occurrence of extreme events (above 95th and 99th percentile) exhibits contrasting trends over different zones with mainly an increase over central and south-central India and decline over central-north India. However, trends in extremes are highly dispersed in space and are conclusive only over a few regions. The observed trends substantially deviate from the patterns reported in past studies for different regions. Rainfall occurrence in different meteorological zones also represents strong interannual and decadal variability, however, the observed trends have emerged beyond the inherent natural variability. The present findings provide an essential foundation for several future explorations with improved understanding of change in rainfall frequency and its possible impacts. It would also assist in developing a comprehensive framework for year-wide management of water resources and agriculture, considering all crop seasons.

雨天不足会影响作物生产并增加地下水抽取量，导致地下水枯竭，从而可能威胁到印度次大陆的粮食和水安全。现有的关于印度降雨发生的研究在几个基本考虑因素（分析的空间尺度、降雨类别的定义、方法、数据集、研究周期等）方面存在不一致，并且缺乏对印度大部分地区的非季风季节的研究。次大陆。在这里，我们尝试通过使用高分辨率（0.25°）网格日降雨量数据集检查 1951-2015 年印度所有气象季节降雨事件季节性计数的时空模式及其在不同降雨等级中的计数来处理这些不一致。结果显示，包括印度中北部、中部和东北部在内的主要作物种植区的季风雨天普遍减少。在前季风期间，印度中部部分地区的雨天也有所减少；季风过后的印度中北部和东北部；和在冬天的印度半岛上空。这些趋势主要在所有季节降雨量<95%（轻到强降雨事件）的事件中观察到。极端事件的发生率（超过 95% 和 99%）在不同区域表现出不同的趋势，主要是在印度中部和中南部增加，在印度中部和北部减少。然而，极端趋势在空间中高度分散，并且仅在少数地区具有决定性。观察到的趋势与过去不同地区研究报告的模式大不相同。不同气象区的降雨发生也表现出强烈的年际和年代际变率，然而，观测到的趋势已经超出了固有的自然变率。目前的发现为未来的一些探索提供了重要的基础，可以更好地了解降雨频率的变化及其可能的影响。考虑到所有作物季节，它还将有助于为水资源和农业的全年管理制定一个综合框架。目前的发现为未来的一些探索提供了重要的基础，可以更好地了解降雨频率的变化及其可能的影响。考虑到所有作物季节，它还将有助于为水资源和农业的全年管理制定一个综合框架。目前的发现为未来的一些探索提供了重要的基础，可以更好地了解降雨频率的变化及其可能的影响。考虑到所有作物季节，它还将有助于为水资源和农业的全年管理制定一个综合框架。