Ranked Multiscale Catalog of Precipitation Extremes using Cross Scale Extremity for the Indian Peninsular Region

Extreme precipitation events (EPEs) are expected to increase in frequency and intensity under global warming and can trigger various impacts such as floods and landslides, which can undermine the socio-economic stability by raising the risk of loss of human lives, infrastructure failure and agricultural losses. Consequently, the study of hydroclimatic extremes has grown substantially in the recent decades, supported by high-resolution data and multivariate event-based analytical frameworks that improve understanding and resilience to climate-related risks. The rainfall induced impacts often show a compound nature because the underlying processes are scale-dependent and can overlap and intensify each another. Therefore it is important to consider extremeness across spatio-temporal scales when assessing EPEs. However, the the complex topography and diverse climatic conditions in the Indian Peninsular region pose a key challenge in assessing and characterizing the EPEs. In this context, a comprehensive ranked catalog of EPEs is developed from the 73 year long data set, based on their extremity across spatio-temporal scales. To increase the robustness of the underlying statistical analysis and to make an optimal use of the data, a combination of the peak-over-threshold (POT) method and the cross-scale weather extremity index (xWEI) is introduced to quantify the spatiotemporal extremity. In addition, the study exemplifies the applicability of POT method and compares the resulting extremeness with the conventional annual maxima approach. The catalog identifies EPEs that are jointly extreme across spatial and temporal scales and distinguishes short-lived localized storms from persistent, widespread events, thereby enabling a systematic characterization of EPE typologies. By linking each EPEs xWEI value to the season and meteorological divisions, the catalog offers a consistent basis for comparing historical events, and advances process-based understanding of regional hazard regimes. In summary, the resulting catalog can be a valuable tool in improving the robustness of quantitative risk assessments and enhancing the reliability of climate change attribution analyses.