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An Observation-Based Dataset of Global Sub-Daily Precipitation Indices (GSDR-I)
Precipitation indices based on daily gauge observations are well established, openly available and widely used to detect and understand climate change. However, in many areas of climate science and risk management, it has become increasingly important to understand precipitation characteristics, var...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10287747/ https://www.ncbi.nlm.nih.gov/pubmed/37349333 http://dx.doi.org/10.1038/s41597-023-02238-4 |
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author | Pritchard, David Lewis, Elizabeth Blenkinsop, Stephen Patino Velasquez, Luis Whitford, Anna Fowler, Hayley J. |
author_facet | Pritchard, David Lewis, Elizabeth Blenkinsop, Stephen Patino Velasquez, Luis Whitford, Anna Fowler, Hayley J. |
author_sort | Pritchard, David |
collection | PubMed |
description | Precipitation indices based on daily gauge observations are well established, openly available and widely used to detect and understand climate change. However, in many areas of climate science and risk management, it has become increasingly important to understand precipitation characteristics, variability and extremes at shorter (sub-daily) durations. Yet, no unified dataset of sub-daily indices has previously been available, due in large part to the lesser availability of suitable observations. Following extensive efforts in data collection and quality control, this study presents a new global dataset of sub-daily precipitation indices calculated from a unique database of 18,591 gauge time series. Developed together with prospective users, the indices describe sub-daily precipitation variability and extremes in terms of intensity, duration and frequency properties. The indices are published for each gauge where possible, alongside a gridded data product based on all gauges. The dataset will be useful in many fields concerned with variability and extremes in the climate system, as well as in climate model evaluation and management of floods and other risks. |
format | Online Article Text |
id | pubmed-10287747 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-102877472023-06-24 An Observation-Based Dataset of Global Sub-Daily Precipitation Indices (GSDR-I) Pritchard, David Lewis, Elizabeth Blenkinsop, Stephen Patino Velasquez, Luis Whitford, Anna Fowler, Hayley J. Sci Data Data Descriptor Precipitation indices based on daily gauge observations are well established, openly available and widely used to detect and understand climate change. However, in many areas of climate science and risk management, it has become increasingly important to understand precipitation characteristics, variability and extremes at shorter (sub-daily) durations. Yet, no unified dataset of sub-daily indices has previously been available, due in large part to the lesser availability of suitable observations. Following extensive efforts in data collection and quality control, this study presents a new global dataset of sub-daily precipitation indices calculated from a unique database of 18,591 gauge time series. Developed together with prospective users, the indices describe sub-daily precipitation variability and extremes in terms of intensity, duration and frequency properties. The indices are published for each gauge where possible, alongside a gridded data product based on all gauges. The dataset will be useful in many fields concerned with variability and extremes in the climate system, as well as in climate model evaluation and management of floods and other risks. Nature Publishing Group UK 2023-06-22 /pmc/articles/PMC10287747/ /pubmed/37349333 http://dx.doi.org/10.1038/s41597-023-02238-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Data Descriptor Pritchard, David Lewis, Elizabeth Blenkinsop, Stephen Patino Velasquez, Luis Whitford, Anna Fowler, Hayley J. An Observation-Based Dataset of Global Sub-Daily Precipitation Indices (GSDR-I) |
title | An Observation-Based Dataset of Global Sub-Daily Precipitation Indices (GSDR-I) |
title_full | An Observation-Based Dataset of Global Sub-Daily Precipitation Indices (GSDR-I) |
title_fullStr | An Observation-Based Dataset of Global Sub-Daily Precipitation Indices (GSDR-I) |
title_full_unstemmed | An Observation-Based Dataset of Global Sub-Daily Precipitation Indices (GSDR-I) |
title_short | An Observation-Based Dataset of Global Sub-Daily Precipitation Indices (GSDR-I) |
title_sort | observation-based dataset of global sub-daily precipitation indices (gsdr-i) |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10287747/ https://www.ncbi.nlm.nih.gov/pubmed/37349333 http://dx.doi.org/10.1038/s41597-023-02238-4 |
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