Code and Supplementary Materials for: "Storm Burstiness Decouples Rainfall Volume from Erosive Forcing in Drylands"

This repository contains the Python code and supplementary materials used in the study “Storm Burstiness Decouples Rainfall Volume from Erosive Forcing in Drylands.” The project investigates how the internal temporal structure of rainfall events controls geomorphic forcing in arid environments using high-resolution satellite precipitation observations. The analysis is based on five years (2014–2018) of half-hourly precipitation data from the GPM Integrated Multi-satellite Retrievals for GPM (IMERG) Final Run Version 07 dataset across the Arabian Peninsula. The scripts provided here process satellite precipitation data, extract storm events, compute storm-scale rainfall metrics, and estimate rainfall erosivity using both conventional formulations and the Arid-Burst Erosivity Index (ABE), a burst-resolved metric designed to quantify the geomorphic impact of temporally concentrated rainfall intensity. The repository includes scripts used to: process satellite precipitation data and construct the storm event catalogue compute rainfall erosivity metrics and burstiness indicators reproduce the statistical analyses presented in the manuscript generate the supplementary figures and robustness diagnostics (Figures S1–S7) The code is written in Python and relies on common scientific computing libraries including NumPy, Pandas, Matplotlib, and Xarray. The scripts are organized to facilitate reproducibility of the analysis pipeline used in the manuscript. The associated manuscript demonstrates that erosive forcing in dryland environments is strongly decoupled from rainfall totals and instead governed by the temporal concentration of rainfall intensity within storms. Storm-scale analysis reveals that a small fraction of highly burst-dominated storms contributes the majority of regional erosive forcing, highlighting the importance of resolving rainfall temporal structure when assessing soil erosion risks in drylands.