Global Seasonal-Scale Meteorological Droughts. Part I: Detection, Metrics, and Inland/Coastal Types

Abstract

Knowledge of spatiotemporal characteristics and process evolutions is the fundamental basis of understanding drought mechanisms, especially from a global perspective. For a comprehensive investigation, we implemented event detection, type grouping, and spatiotemporal metrics from 3-dimensional (3D, longitude–latitude–time) perspectives. The major procedures and achievements were as follows. First, we identified global-scale seasonal-scale meteorological drought events following the recently proposed 3D DBSCAN (Density-Based Spatial Clustering of Applications with Noise)-based workflow of event detection. The 3D DBSCAN clustering algorithm can directly obtain arbitrarily shaped point collections over a given 3D space, as drought events can spread over space and evolve over time. Subsequently, these detected drought events are further grouped into inland and coastal types, as the observations revealed that some droughts over coastal regions originate from, extend to, or are accompanied by long-term precipitation deficits over adjacent oceans. Third, typical spatiotemporal characteristics (e.g., lifetime, genesis locations, migration/local developments, and process evolutions) were investigated with coastal/inland-type differences considered. The drought ratios originating from continents in all coastal-type droughts were ~50% over Africa, Asia, and South America, indicating the nonnegligible extension from continents to oceans. Additionally, process evolution-based analysis revealed intensity variations in intensification or recession phases, and coastal types overall displayed larger intensity variations than inland types. Moreover, ~92% of inland types and ~70% of coastal types can be treated as having symmetric development. Notably, the grouping type and spatiotemporal metrics herein can provide adequate preliminary knowledge for global-scale drought mechanism exploration.