Precipitation-Temperature scaling in the Alps: The role of storm typology and temperature aggregation

The relationship theorized by Clausius-Clapeyron (CC) provides a thermodynamic baseline for how moisture content scales with temperature, and extreme precipitation could be expected to scale accordingly. Specifically, the CC equation predicts an increase in atmospheric water vapor holding capacity of approximately 7% per degree Celsius. Despite this theoretical basis, observed extreme precipitation often deviates from this scaling due to local atmospheric dynamics and specific event characteristics. In this study, we investigate precipitation-temperature (P-T) scaling across the Greater Alpine Region to better understand these deviations. We rely on a comprehensive observational dataset in which extreme precipitation is classified into distinct storm types, specifically separating convective-like from other types of events, such as stratiform rainfall. Using quantile regression, we explore the sensitivity of the P-T scaling rates to precipitation type and to the aggregation time interval used to define the temperature. Given the complex topography of the Alps, we analyze the spatial variability of the scaling relationship to assess how local climate and orography modulate the precipitation response. Preliminary results suggest that P-T scaling behaves differently depending on the dominant storm type, with convective-like rainfall exhibiting higher scaling rates (≈7%) compared to stratiform-like events (≈5%). Instead, when the two storm types are considered together, the scaling slope becomes steeper (≈10%). This occurs because convective and stratiform events are systematically distributed in different ways across the temperature range. By presenting this work, we hope to discuss how adopting an event-based typology can help refine our understanding of extreme precipitation drivers in mountain regions.