Spatial structure and evolution of meteorological droughts using an intensity-field framework: A multi-timescale analysis across China

Study area: China Study focus: Accurately characterizing the spatial structure of drought is crucial for understanding drought propagation and risk assessment. Existing approaches overlook intensity effects on spatial dynamics. In this study, we propose a framework for measuring spatial extents (SPEs) of meteorological droughts that incorporates drought intensity fields (DIF). Based on the principles of spatial autocorrelation and anisotropy, we apply a semivariogram-based method to quantify the coupling between intensity and spatiotemporal structure. We quantify the climatological SPEs of meteorological droughts in China using multi-timescale (1-, 3-, 6-, and 12-month) SPI derived from four high-resolution precipitation datasets (ERA5, PERSIANN-CDR, GPM, and TRMM), and analyze the spatial morphological structure and spatiotemporal evolution patterns. New hydrological insights for the regions: The results show that: (1) The DIF-based method provides more accurate estimates of drought SPEs. It effectively reduces the biases inherent in the binary approach; (2) SPEs expand with increasing timescale, accompanied by an enhancement in the heterogeneity and uncertainty of spatial structure. High-impact drought areas show a southward migration trend; (3) SPEs in humid regions expand significantly at mid-term to long-term timescales, indicating the need for close monitoring of long-term drought risks in southern China. The proposed framework improves the understanding of drought spatiotemporal dynamics. It also supports research on drought migration and propagation, and provides important insights for drought monitoring, prediction, and water resource management.