Sub-daily precipitation returns levels in ungauged locations: Added value of combining observations with convection permitting simulations

• We quantified the added value of combining rainfall observations with Convection Permitting Model (CPM) simulations to estimate sub-daily extreme rainfall return levels in ungauged locations. • At the highest station density (1/196 km²), traditional interpolation methods outperform the CPM-informed method for durations under 6 hours and performances becomes comparable between 6 and 24 hours • For lower station densities (1/400 and 1/800 km²), the CPM-informed method outperforms the traditional method, showing a larger average reductions in fractional standard error. Extreme rainfall events trigger natural hazards, including floods and debris flows, posing serious threats to society and the economy. Accurately quantifying extreme rainfall return levels in ungauged locations is crucial for improving flood protection infrastructure and mitigating water-related risks. This paper quantifies the added value of combining rainfall observations with Convection Permitting Model (CPM) simulations to estimate sub-daily extreme rainfall return levels in ungauged locations. We assess the performance of CPM-informed estimates of extreme return level against a traditional interpolation techniques. We find that kriging methods with external drift outperform inverse distance weighting for both traditional and CPM-informed approaches. We then assess the effectiveness of the two methods under different scenarios of station density. At the highest station density (1/196 km²), traditional interpolation methods outperform the CPM-informed method for durations under 6 hours. The performance becomes comparable between 6 and 24 hours. For lower station densities (1/400 and 1/800 km²), the CPM-informed method outperforms the traditional method, with average reductions in fractional standard error of 24%, 13%, and 8% for return periods of 2, 10 and 50 years, respectively for a rain gauge density of 1/800 km², and 16%, 8%, and 3% for density of 1/400 km². Information from CPM simulations can thus be useful for estimating sub-daily extreme rainfall events in ungauged sites, particularly in data-scarce areas in which the density of rain gauges is low.

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Publication Details

Journal
Advances in Water Resources
Published
2024-11-04
DOI
https://doi.org/10.1016/j.advwatres.2024.104851
Citations
8
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
2.26

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article

Sub-daily precipitation returns levels in ungauged locations: Added value of combining observations with convection permitting simulations

Giuseppe Formetta, Marco Borga, Francesco Marra, Eleonora Dallan
8 citations
Advances in Water Resources
Climate variability and models
2.26
article

Sub-daily precipitation returns levels in ungauged locations: Added value of combining observations with convection permitting simulations

Giuseppe Formetta, Marco Borga, Francesco Marra, Eleonora Dallan
article en
8 citations

Abstract

• We quantified the added value of combining rainfall observations with Convection Permitting Model (CPM) simulations to estimate sub-daily extreme rainfall return levels in ungauged locations. • At the highest station density (1/196 km²), traditional interpolation methods outperform the CPM-informed method for durations under 6 hours and performances becomes comparable between 6 and 24 hours • For lower station densities (1/400 and 1/800 km²), the CPM-informed method outperforms the traditional method, showing a larger average reductions in fractional standard error. Extreme rainfall events trigger natural hazards, including floods and debris flows, posing serious threats to society and the economy. Accurately quantifying extreme rainfall return levels in ungauged locations is crucial for improving flood protection infrastructure and mitigating water-related risks. This paper quantifies the added value of combining rainfall observations with Convection Permitting Model (CPM) simulations to estimate sub-daily extreme rainfall return levels in ungauged locations. We assess the performance of CPM-informed estimates of extreme return level against a traditional interpolation techniques. We find that kriging methods with external drift outperform inverse distance weighting for both traditional and CPM-informed approaches. We then assess the effectiveness of the two methods under different scenarios of station density. At the highest station density (1/196 km²), traditional interpolation methods outperform the CPM-informed method for durations under 6 hours. The performance becomes comparable between 6 and 24 hours. For lower station densities (1/400 and 1/800 km²), the CPM-informed method outperforms the traditional method, with average reductions in fractional standard error of 24%, 13%, and 8% for return periods of 2, 10 and 50 years, respectively for a rain gauge density of 1/800 km², and 16%, 8%, and 3% for density of 1/400 km². Information from CPM simulations can thus be useful for estimating sub-daily extreme rainfall events in ungauged sites, particularly in data-scarce areas in which the density of rain gauges is low.

Advances in Water ResourcesVol. 194
University of Padua (IT), University of Trento (IT)
Eidgenössische Technische Hochschule Zürich, Provincia Autonoma di Trento, Provincia autonoma di Bolzano - Alto Adige
Climate action
Openalex Percentile: Top 12%
Climate variability and models
2.26
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