Rainfall variability associated with the South Asian Summer Monsoon has increased in recent decades, particularly at the northwestern monsoon margins over Pakistan, leading to more frequent and intense hydro-meteorological extremes that have adversely affected the agrarian economy, water and food security in the country. Devising effective strategies to ensure sustainable development in Pakistan thus requires that the monsoonal rainfall be predicted on an inter-annual scale. Here, we predicted the inter- and intra-annual variability of the monsoonal rainfall over Pakistan and its possible drivers using a linear statistical forecast model of the principal component (PC) regression analysis. For this purpose, highly correlated PCs of the National Centre for Environmental Prediction (NCEP) based sea level pressure, horizontal and meridional winds to the observed rainfall for the period 2001–2013 were ingested in a stepwise multiple regression model, which was further validated for the duration of 2014–2015. Our results suggest that featuring correlation coefficient, mean absolute error, mean bias, and root mean square error of 0.75, 42.23, −14.92 and 60.65, respectively, the model exhibits robust skill in predicting the inter-annual monsoonal rainfall variability at its extreme northwestern margins over Pakistan.

近几十年来，与南亚夏季风有关的降雨多变性增加了，特别是在巴基斯坦的西北季风边缘，导致更频繁，更强烈的水文气象极端事件，对该国的农业经济，水和粮食安全产生了不利影响。因此，制定有效的战略以确保巴基斯坦的可持续发展，就要求对季风降雨进行年际预测。在这里，我们使用主成分（PC）回归分析的线性统计预测模型预测了巴基斯坦季风降雨的年际和年际变化及其可能的驱动因素。为此，基于美国国家环境预测中心（NCEP）的高度相关的PC的海平面压力，在逐步多元回归模型中吸收了2001-2013年期间观测到的水平和子午风到观测到的降水量，该模型在2014-2015年期间得到了进一步验证。我们的结果表明，该模型的相关系数，平均绝对误差，均值偏差和均方根误差分别为0.75、42.23，−14.92和60.65，该模型在预测其极端西北地区的年际季风降水变化方面表现出强大的技巧巴基斯坦的利润率。