Drought is one of the complex meteorological disasters affecting water resources, agriculture, livestock, and socioeconomic patterns of a region. Although drought prediction is difficult, it can be monitored based on climatological information. In this study, we provide high spatiotemporal resolution drought climatology, using observational, gridded precipitation data (0.5°×0.5°) from the Global Precipitation Climatological Center and soil moisture data from the Climate Prediction Center for the 60-yr period 1951–2010. The standardized precipitation index (SPI) based on a fitted Gamma distribution and Run method has been calculated from the regional drought identification model (ReDIM) for 3, 6, 9, 12, and 24 months. The results show strong temporal correlations among anomalies of precipitation, soil moisture, and SPI. Analysis of long-term precipitation data reveals that the drought vulnerability concentrates on monsoon season (July–September), which contributes 72.4% and 82.1% of the annual precipitation in northern and southern Sindh, respectively. Annual and seasonal analyses show no significant changes in the observed precipitation. The category classification criteria are defined to monitor/forecast drought in the selected area. Further analysis identifies two longest episodes of drought, i.e., 1972–1974 and 2000–2002, while 1969, 1974, 1987, and 2002 are found to be the most severe historical drought years. A drought hazard map of Sindh was developed, in which 10 districts are recognized as highly vulnerable to drought. This study helps to explain the time, duration, intensity, and frequency of meteorological droughts over Sindh as well as its neighboring regions, and provides useful information to disaster management agencies and forecasters for assessing both the regional vulnerability of drought and its seasonal predictability in Pakistan.

The climatology of precipitation and drought are analyzed by using different indices in the region of south central Asia (SCA). The spatial precipitation pattern is delineated by using principal component analysis (PCA) over the period of 1951–2010, which identifies six subregions in the SCA. The monthly and annual trends of precipitation were analyzed by applying the five statistical tests: Student’s t, Mann–Kendall, and Spearman’s rho tests for linear trend and turning point analysis and Sen’s slope for randomness and slope magnitude, respectively, at the α = 0.05 significance level. The time series analysis shows data similarity between Global Precipitation Climatology Centre (GPCC) and area-weighted precipitation of 52 meteorological stations in Pakistan, which results in a high correlation (R2 = 0.93). Two main drought periods were identified (1971 and 2000–02); also, 2001 was an extremely dry year in the SCA region. The drought in 1952 was the most severe in Pakistan; the longest drought period was 2000–02. Intense droughts were reported in the whole SCA region when the annual percent of precipitation was below 80%. It is noted that the A-5 region (northeast SCA), where 19 droughts were reported, is the most vulnerable. The monthly precipitation analysis shows a significant increasing trend in the months of September and June in the A-3 (northwest SCA) and A-5 regions, respectively, while a decreasing trend is observed in January and August in the A-4 region (east SCA). The decadal analysis shows significant decreasing trend (−21.5 mm decade−1) in region A-4, while the highest increasing trends (17.1 and 7.5 mm decade−1) are observed in Pakistan and the A-5 region respectively.