In regions with significant elevation variability like Italy, interpolation methods applied to rainfall depths should explicitly account for the elevation effect. This study examines the spatial variability of sub-daily rainfall extremes across Italy, focusing on assessing the role of elevation. Utilizing the Improved Italian - Rainfall Extreme Dataset (I2-RED), we analyzed average annual maxima from approximately 3,800 time series spanning at least 10 years between 1916 and 2020. To assess orographic influences, a local geo-regression approach was employed, aggregating stations located within a certain search radius centered in each 1km size cell used to segment the territory. Various constraints were applied to address challenges posed by low data density in certain regions and elevation-related extrapolation issues, and different criteria for selecting local samples were evaluated. Our findings corroborate previous studies with enhanced detail, revealing a general increase of the 24-hour average annual maxima with elevation (orographic effect), with the exception of few hilly/mountainous areas. Conversely, for 1-hour maxima, negative gradients (reverse orographic effect) were observed in extensive mountainous regions, suggesting decreased short-duration rainfall extremes at higher elevations. These insights contribute to a deeper understanding of rainfall patterns in Italy and can inform the development of improved hydrological models and infrastructure planning

The role of elevation in the spatial distribution of sub-daily rainfall extremes / Mazzoglio, Paola; Butera, Ilaria; Claps, Pierluigi. - ELETTRONICO. - (2025), pp. 243-245. ( Geomorphometry 2025 Perugia (Ita) 9-13 June 2025) [10.5281/zenodo.15212750].

The role of elevation in the spatial distribution of sub-daily rainfall extremes

Mazzoglio, Paola;Butera, Ilaria;Claps, Pierluigi
2025

Abstract

In regions with significant elevation variability like Italy, interpolation methods applied to rainfall depths should explicitly account for the elevation effect. This study examines the spatial variability of sub-daily rainfall extremes across Italy, focusing on assessing the role of elevation. Utilizing the Improved Italian - Rainfall Extreme Dataset (I2-RED), we analyzed average annual maxima from approximately 3,800 time series spanning at least 10 years between 1916 and 2020. To assess orographic influences, a local geo-regression approach was employed, aggregating stations located within a certain search radius centered in each 1km size cell used to segment the territory. Various constraints were applied to address challenges posed by low data density in certain regions and elevation-related extrapolation issues, and different criteria for selecting local samples were evaluated. Our findings corroborate previous studies with enhanced detail, revealing a general increase of the 24-hour average annual maxima with elevation (orographic effect), with the exception of few hilly/mountainous areas. Conversely, for 1-hour maxima, negative gradients (reverse orographic effect) were observed in extensive mountainous regions, suggesting decreased short-duration rainfall extremes at higher elevations. These insights contribute to a deeper understanding of rainfall patterns in Italy and can inform the development of improved hydrological models and infrastructure planning
2025
978-88-8080-765-0
File in questo prodotto:
File Dimensione Formato  
Proceedings_Geomorphometry_2025_Mazzoglio.pdf

accesso aperto

Tipologia: 2a Post-print versione editoriale / Version of Record
Licenza: Creative commons
Dimensione 639.86 kB
Formato Adobe PDF
639.86 kB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/3009294