Can the climatology of heavy storm characteristics explain extreme precipitation statistics?

The assessment of extreme precipitation statistics is essential for managing flood hazards and developing effective climate change adaptation strategies. These design values are typically estimated through the frequency analysis of precipitation data, with limited understanding of their generative atmospheric phenomena. We aim to go beyond the statistical extrapolation of observed extremes with extreme value distributions towards enhancing their physical comprehension: this may be beneficial for improving our estimates of extreme precipitation probability and our predictions of future changes. Our analysis is based on a network of ∼300 rain gauges and temperature stations in a complex-orography region of the Alps. We estimate the magnitude of extreme precipitation from sub-hourly to daily durations for return periods up to 100 years (1% annual exceedance probability). We employ a non-asymptotic extreme value approach based on the concept of storms (independent meteorological objects) and ordinary events (duration maxima within each storm). We focus on the ordinary events exceeding high percentiles (e.g., 85^th, 90^th, 95^th) at some duration, and we extract several characteristics of the corresponding storms, such as the event peak and average intensity, total lifetime, seasonality, temporal profile, peakedness, temperature, etc. We then assess their relationships with the parameters of our non-asymptotic extreme value model.

Our preliminary results show that variations in the model parameters depend on topography and event duration. Heavier tails in the extreme precipitation distribution emerge at sub-hourly durations in mountainous regions and for parts of the lowlands, but at longer durations in the pre-Alps. The scale parameter is generally higher in the lowlands and the pre-Alps. As a result, extreme precipitation intensity for short duration is generally higher in the lowlands than in the mountains (“reverse orographic effect”), with higher intensities in the pre-Alps at longer durations. Storm characteristics also vary with topography, precipitation duration, and event extremeness. In summer, front-loaded storms are prevalent at short durations, where heavier tails are observed. In the pre-Alps, storms are characterized by the highest extremes at long durations, have a more symmetric temporal profile, are most common in autumn, and have a longer total lifetime compared to the rest of the region.

Further investigation is needed to clarify the relationship between storm characteristics and statistical properties. This work enhances understanding of the key processes shaping precipitation extremes and provides insights for improving predictive models, ultimately aiding in risk assessment and climate resilience planning.

 

This study is carried out within the RETURN Extended Partnership and received funding from the European Union Next-GenerationEU (National Recovery and Resilience Plan – NRRP, Mission 4, Component 2, Investment 1.3 – D.D. 1243 2/8/2022, PE0000005).