Checking for non-preferred file/folder path names (may take a long time depending on the number of files/folders) ...
This resource contains some files/folders that have non-preferred characters in their name. Show non-conforming files/folders.
This resource contains content types with files that need to be updated to match with metadata changes. Show content type files that need updating.
Analyses through the Metastatistical Extreme Value distribution identify contributions of Tropical Cyclones to rainfall extremes in the Eastern US
| Authors: |
|
|
|---|---|---|
| Owners: |
|
This resource does not have an owner who is an active HydroShare user. Contact CUAHSI (help@cuahsi.org) for information on this resource. |
| Type: | Resource | |
| Storage: | The size of this resource is 21.3 KB | |
| Created: | Mar 26, 2020 at 12:27 p.m. | |
| Last updated: | Apr 13, 2020 at 1:15 p.m. (Metadata update) | |
| Published date: | Apr 13, 2020 at 1:15 p.m. | |
| DOI: | 10.4211/hs.384c9df02fab4051a21db7e4f210eb36 | |
| Citation: | See how to cite this resource |
| Sharing Status: | Published |
|---|---|
| Views: | 1358 |
| Downloads: | 7 |
| +1 Votes: | Be the first one to this. |
| Comments: | 1 comment |
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 reducing 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 TCand 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 duration longer than one day are considered.
Subject Keywords
Coverage
Temporal
| Start Date: | |
|---|---|
| End Date: |
Content
Related Resources
| The content of this resource is derived from | https://www.aoml.noaa.gov/hrd/hurdat/hurdat2.html |
| The content of this resource is derived from | https://www.ncdc.noaa.gov/cdo-web/search |
Credits
Funding Agencies
This resource was created using funding from the following sources:
| Agency Name | Award Title | Award Number |
|---|---|---|
| Foundation "Cassa di Risparmio di Padova e Rovigo" | ||
| National Science Foundation | Quantification of the Impacts of Urban Areas on Heavy Rainfall and Flooding from North Atlantic Tropical Cyclones | EAR-1840742 |
| US Army Corps of Engineers | ||
| Venice Water Authority | Venice 2021 Project | Line 1.3 Modellazione numerica integrata del sistema bacino scolante-laguna-mare |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
Comments
Gabriele Villarini 4 years, 7 months ago
This is based on the paper:
ReplyMiniussi, A., G. Villarini, and M. Marani, Analyses through the metastatistical extreme value distribution identify contributions of tropical cyclones to rainfall extremes in the eastern US, Geophysical Research Letters, 2020 (in press).
New Comment