Tropical cyclones (TCs) generate extreme precipitation with severe impacts across large coastal and inland areas, calling for accurate frequency estimation methods. Statistical approaches that take into account the physical mechanisms responsible for these extremes can help reduce the estimation uncertainty. Here we formulate a mixed-population Metastatistical Extreme Value Distribution explicitly incorporating non-TC and TC-induced rainfall and evaluate its implications on long series of daily rainfall for six major U.S. urban areas impacted by these storms. We find statistically significant differences between the distributions of TC- and non-TC-related precipitation; moreover, including mixtures of distributions improves the estimation of the probability of extreme precipitation where TCs occur more frequently. These improvements are greater when rainfall aggregated over durations longer than one day are considered.

Analyses Through the Metastatistical Extreme Value Distribution Identify Contributions of Tropical Cyclones to Rainfall Extremes in the Eastern United States

Miniussi A.;Marani M.
2020

Abstract

Tropical cyclones (TCs) generate extreme precipitation with severe impacts across large coastal and inland areas, calling for accurate frequency estimation methods. Statistical approaches that take into account the physical mechanisms responsible for these extremes can help reduce the estimation uncertainty. Here we formulate a mixed-population Metastatistical Extreme Value Distribution explicitly incorporating non-TC and TC-induced rainfall and evaluate its implications on long series of daily rainfall for six major U.S. urban areas impacted by these storms. We find statistically significant differences between the distributions of TC- and non-TC-related precipitation; moreover, including mixtures of distributions improves the estimation of the probability of extreme precipitation where TCs occur more frequently. These improvements are greater when rainfall aggregated over durations longer than one day are considered.
File in questo prodotto:
File Dimensione Formato  
Geophysical Research Letters - 2020 - Miniussi - Analyses Through the Metastatistical Extreme Value Distribution Identify-1_compressed.pdf

accesso aperto

Descrizione: Articolo
Tipologia: Published (Publisher's Version of Record)
Licenza: Accesso libero
Dimensione 405.46 kB
Formato Adobe PDF
405.46 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/11577/3365370
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 35
  • ???jsp.display-item.citation.isi??? 35
  • OpenAlex ND
social impact