Enregistré dans:
Détails bibliographiques
Auteur principal: Mure-Ravaud, Mathieu
Format: Preprint
Publié: 2026
Sujets:
Accès en ligne:https://arxiv.org/abs/2602.19233
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
_version_ 1866908932411228160
author Mure-Ravaud, Mathieu
author_facet Mure-Ravaud, Mathieu
contents Most methods for estimating probable maximum precipitation (PMP) -- the greatest depth of precipitation that is physically possible over a given area and duration -- rely on storm transposition (ST), the process of transporting a storm, either historically observed or simulated, from its original location to a target basin. Existing ST approaches, whether classical or physically based, involve assumptions and manipulations that can introduce inconsistencies, leaving the physical validity of the transposed storm uncertain. In this study, the internal variability leveraging (IVL) approach is used to transpose an atmospheric river cluster that affected the U.S. West Coast during 20-29 October 2021. Steering the storm toward the target basin and determining its transposition region are achieved by considering an ensemble of plausible storm evolutions and trajectories obtained from archived ECMWF medium-range forecasts. The Willamette River and Nass River watersheds, located approximately 6 deg N, 2 deg W and 16 deg N, 8 deg W, respectively, from the area most affected by the observed precipitation, were selected as target basins. For each basin, the IVL realization yielding the largest 24-h basin-average precipitation depth was identified, and the initial and boundary condition shifting method was subsequently applied to further enhance its impact, producing 24-h precipitation depths of 119 mm for the Willamette and 98 mm for the Nass.
format Preprint
id arxiv_https___arxiv_org_abs_2602_19233
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle On Using Medium-Range Ensemble Forecasts for Storm Transposition of Synoptic-Scale Systems in Probable Maximum Precipitation Estimation
Mure-Ravaud, Mathieu
Atmospheric and Oceanic Physics
Most methods for estimating probable maximum precipitation (PMP) -- the greatest depth of precipitation that is physically possible over a given area and duration -- rely on storm transposition (ST), the process of transporting a storm, either historically observed or simulated, from its original location to a target basin. Existing ST approaches, whether classical or physically based, involve assumptions and manipulations that can introduce inconsistencies, leaving the physical validity of the transposed storm uncertain. In this study, the internal variability leveraging (IVL) approach is used to transpose an atmospheric river cluster that affected the U.S. West Coast during 20-29 October 2021. Steering the storm toward the target basin and determining its transposition region are achieved by considering an ensemble of plausible storm evolutions and trajectories obtained from archived ECMWF medium-range forecasts. The Willamette River and Nass River watersheds, located approximately 6 deg N, 2 deg W and 16 deg N, 8 deg W, respectively, from the area most affected by the observed precipitation, were selected as target basins. For each basin, the IVL realization yielding the largest 24-h basin-average precipitation depth was identified, and the initial and boundary condition shifting method was subsequently applied to further enhance its impact, producing 24-h precipitation depths of 119 mm for the Willamette and 98 mm for the Nass.
title On Using Medium-Range Ensemble Forecasts for Storm Transposition of Synoptic-Scale Systems in Probable Maximum Precipitation Estimation
topic Atmospheric and Oceanic Physics
url https://arxiv.org/abs/2602.19233