Global Seasonal-Scale Meteorological Droughts. Part II: Temperature Anomaly-Based Classifications

Abstract

Although compound drought and heatwave extremes have recently drawn much attention, whether droughts are always concurrent with heatwaves remains unknown. Moreover, how temperature abnormalities evolve spatiotemporally during drought development and how their associated categories are distributed globally are not fully understood. Part II investigated this fundamental issue from the perspectives of temperature abnormality-based drought classification and statistical characteristics of process evolution. The major procedures and achievements were as follows. First, the detected global-scale drought events in Part I were employed and assigned to Hot, Cold, Normal, and Hybrid categories utilizing a self-designed temperature abnormality-based classification algorithm; the associated global-scale occurrences of these 4 event categories were approximately 40%, 10%, 30%, and 20%, respectively, and in turn, they displayed statistically significant ( P value < 0.05) increasing, decreasing, decreasing, and increasing trends, respectively, during 1980 to 2020. The Hot and Normal types appeared mostly within 45°S to 45°N in warm seasons, with Cold types over mid-high latitudes in cold seasons. In relation to coastal/inland group differences, Hot and Normal types were the common major features of the 2 drought groups (i.e., inland and coastal), while most Cold types were mostly associated with coastal droughts. Second, through self-designed intensity-based parameters reflecting extreme values and phase variation, we found that 60% of Hot types and 75% of Cold types experienced prominent intensification with ~0.5 values of standardized temperature. Regarding approximately 80% of Hot types, hot extremes followed drought extremes. The achievements may provide robust event-based insights into the physical mechanisms behind global droughts and concurrent temperature anomalies.