Cargando…
Downscaling GRACE total water storage change using partial least squares regression
The Gravity Recovery And Climate Experiment (GRACE) satellite mission recorded temporal variations in the Earth’s gravity field, which are then converted to Total Water Storage Change (TWSC) fields representing an anomaly in the water mass stored in all three physical states, on and below the surfac...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7998002/ https://www.ncbi.nlm.nih.gov/pubmed/33772016 http://dx.doi.org/10.1038/s41597-021-00862-6 |
_version_ | 1783670452134084608 |
---|---|
author | Vishwakarma, Bramha Dutt Zhang, Jinwei Sneeuw, Nico |
author_facet | Vishwakarma, Bramha Dutt Zhang, Jinwei Sneeuw, Nico |
author_sort | Vishwakarma, Bramha Dutt |
collection | PubMed |
description | The Gravity Recovery And Climate Experiment (GRACE) satellite mission recorded temporal variations in the Earth’s gravity field, which are then converted to Total Water Storage Change (TWSC) fields representing an anomaly in the water mass stored in all three physical states, on and below the surface of the Earth. GRACE provided a first global observational record of water mass redistribution at spatial scales greater than 63000 km(2). This limits their usability in regional hydrological applications. In this study, we implement a statistical downscaling approach that assimilates 0.5° × 0.5° water storage fields from the WaterGAP hydrology model (WGHM), precipitation fields from 3 models, evapotranspiration and runoff from 2 models, with GRACE data to obtain TWSC at a 0.5° × 0.5° grid. The downscaled product exploits dominant common statistical modes between all the hydrological datasets to improve the spatial resolution of GRACE. We also provide open access to scripts that researchers can use to produce downscaled TWSC fields with input observations and models of their own choice. |
format | Online Article Text |
id | pubmed-7998002 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-79980022021-04-16 Downscaling GRACE total water storage change using partial least squares regression Vishwakarma, Bramha Dutt Zhang, Jinwei Sneeuw, Nico Sci Data Data Descriptor The Gravity Recovery And Climate Experiment (GRACE) satellite mission recorded temporal variations in the Earth’s gravity field, which are then converted to Total Water Storage Change (TWSC) fields representing an anomaly in the water mass stored in all three physical states, on and below the surface of the Earth. GRACE provided a first global observational record of water mass redistribution at spatial scales greater than 63000 km(2). This limits their usability in regional hydrological applications. In this study, we implement a statistical downscaling approach that assimilates 0.5° × 0.5° water storage fields from the WaterGAP hydrology model (WGHM), precipitation fields from 3 models, evapotranspiration and runoff from 2 models, with GRACE data to obtain TWSC at a 0.5° × 0.5° grid. The downscaled product exploits dominant common statistical modes between all the hydrological datasets to improve the spatial resolution of GRACE. We also provide open access to scripts that researchers can use to produce downscaled TWSC fields with input observations and models of their own choice. Nature Publishing Group UK 2021-03-26 /pmc/articles/PMC7998002/ /pubmed/33772016 http://dx.doi.org/10.1038/s41597-021-00862-6 Text en © The Author(s) 2021, corrected publication 2022 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/) . The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) applies to the metadata files associated with this article. |
spellingShingle | Data Descriptor Vishwakarma, Bramha Dutt Zhang, Jinwei Sneeuw, Nico Downscaling GRACE total water storage change using partial least squares regression |
title | Downscaling GRACE total water storage change using partial least squares regression |
title_full | Downscaling GRACE total water storage change using partial least squares regression |
title_fullStr | Downscaling GRACE total water storage change using partial least squares regression |
title_full_unstemmed | Downscaling GRACE total water storage change using partial least squares regression |
title_short | Downscaling GRACE total water storage change using partial least squares regression |
title_sort | downscaling grace total water storage change using partial least squares regression |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7998002/ https://www.ncbi.nlm.nih.gov/pubmed/33772016 http://dx.doi.org/10.1038/s41597-021-00862-6 |
work_keys_str_mv | AT vishwakarmabramhadutt downscalinggracetotalwaterstoragechangeusingpartialleastsquaresregression AT zhangjinwei downscalinggracetotalwaterstoragechangeusingpartialleastsquaresregression AT sneeuwnico downscalinggracetotalwaterstoragechangeusingpartialleastsquaresregression |