Articles | Volume 11, issue 2
https://doi.org/10.5194/ascmo-11-257-2025
https://doi.org/10.5194/ascmo-11-257-2025
28 Nov 2025
 | 28 Nov 2025

A bi-level spatiotemporal clustering approach and its application to drought extraction

T. Elana Christian, Amit N. Subrahmanya, Brandi Gamelin, Vishwas Rao, Noelle I. Samia, and Julie Bessac

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Short summary

We present a novel spatiotemporal clustering algorithm to extract spatiotemporal events based on their intensity. Our algorithm proceeds in two steps: (1) extracting intensity structures that are spatiotemporally consistent and, (2) separating individual events. We apply the algorithm to a novel drought index over the continental United States from 19802021 and show that it captures historical drought events over the continental United States and their spatiotemporal extents. 

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