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Very high resolution, altitude-corrected, TMPA-based monthly satellite precipitation product over the CONUS
The Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) product provided over 17 years of gridded precipitation datasets. However, the accuracy and spatial resolution of TMPA limits the applicability in hydrometeorological applications. We present a dataset that e...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7054268/ https://www.ncbi.nlm.nih.gov/pubmed/32127530 http://dx.doi.org/10.1038/s41597-020-0411-0 |
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author | Hashemi, Hossein Fayne, Jessica Lakshmi, Venkat Huffman, George J. |
author_facet | Hashemi, Hossein Fayne, Jessica Lakshmi, Venkat Huffman, George J. |
author_sort | Hashemi, Hossein |
collection | PubMed |
description | The Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) product provided over 17 years of gridded precipitation datasets. However, the accuracy and spatial resolution of TMPA limits the applicability in hydrometeorological applications. We present a dataset that enhances the accuracy and spatial resolution of the TMPA monthly product (3B43). We resample the TMPA data to a 1 km grid and apply a correction function derived from the Parameter-elevation Regressions on Independent Slopes Model (PRISM) to reduce bias in the data. We confirm a linear relationship between bias and elevation above 1,500 meters where TMPA underestimates measured precipitation, providing a proof-of-concept of how simple linear scaling can be used to augment existing satellite datasets. The result of the correction is the High-Resolution Altitude-Corrected Precipitation product (HRAC-Precip) for the CONUS. Using 9,200 precipitation stations from the Global Historical Climatology Network (GHCN), we compare the accuracy of TMPA 3B43 versus the new HRAC-Precip product. The results show an improvement of the mean absolute error of 12.98% on average. |
format | Online Article Text |
id | pubmed-7054268 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-70542682020-03-19 Very high resolution, altitude-corrected, TMPA-based monthly satellite precipitation product over the CONUS Hashemi, Hossein Fayne, Jessica Lakshmi, Venkat Huffman, George J. Sci Data Data Descriptor The Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) product provided over 17 years of gridded precipitation datasets. However, the accuracy and spatial resolution of TMPA limits the applicability in hydrometeorological applications. We present a dataset that enhances the accuracy and spatial resolution of the TMPA monthly product (3B43). We resample the TMPA data to a 1 km grid and apply a correction function derived from the Parameter-elevation Regressions on Independent Slopes Model (PRISM) to reduce bias in the data. We confirm a linear relationship between bias and elevation above 1,500 meters where TMPA underestimates measured precipitation, providing a proof-of-concept of how simple linear scaling can be used to augment existing satellite datasets. The result of the correction is the High-Resolution Altitude-Corrected Precipitation product (HRAC-Precip) for the CONUS. Using 9,200 precipitation stations from the Global Historical Climatology Network (GHCN), we compare the accuracy of TMPA 3B43 versus the new HRAC-Precip product. The results show an improvement of the mean absolute error of 12.98% on average. Nature Publishing Group UK 2020-03-03 /pmc/articles/PMC7054268/ /pubmed/32127530 http://dx.doi.org/10.1038/s41597-020-0411-0 Text en © The Author(s) 2020 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article. |
spellingShingle | Data Descriptor Hashemi, Hossein Fayne, Jessica Lakshmi, Venkat Huffman, George J. Very high resolution, altitude-corrected, TMPA-based monthly satellite precipitation product over the CONUS |
title | Very high resolution, altitude-corrected, TMPA-based monthly satellite precipitation product over the CONUS |
title_full | Very high resolution, altitude-corrected, TMPA-based monthly satellite precipitation product over the CONUS |
title_fullStr | Very high resolution, altitude-corrected, TMPA-based monthly satellite precipitation product over the CONUS |
title_full_unstemmed | Very high resolution, altitude-corrected, TMPA-based monthly satellite precipitation product over the CONUS |
title_short | Very high resolution, altitude-corrected, TMPA-based monthly satellite precipitation product over the CONUS |
title_sort | very high resolution, altitude-corrected, tmpa-based monthly satellite precipitation product over the conus |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7054268/ https://www.ncbi.nlm.nih.gov/pubmed/32127530 http://dx.doi.org/10.1038/s41597-020-0411-0 |
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