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Multiple-data-based monthly geopotential model set LDCmgm90

While the GRACE (Gravity Recovery and Climate Experiment) satellite mission is of great significance in understanding various branches of Earth sciences, the quality of GRACE monthly products can be unsatisfactory due to strong longitudinal stripe-pattern errors and other flaws. Based on corrected G...

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Autores principales: Chen, Wei, Luo, Jiesi, Ray, Jim, Yu, Nan, Li, Jian Cheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6811530/
https://www.ncbi.nlm.nih.gov/pubmed/31645550
http://dx.doi.org/10.1038/s41597-019-0239-7
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author Chen, Wei
Luo, Jiesi
Ray, Jim
Yu, Nan
Li, Jian Cheng
author_facet Chen, Wei
Luo, Jiesi
Ray, Jim
Yu, Nan
Li, Jian Cheng
author_sort Chen, Wei
collection PubMed
description While the GRACE (Gravity Recovery and Climate Experiment) satellite mission is of great significance in understanding various branches of Earth sciences, the quality of GRACE monthly products can be unsatisfactory due to strong longitudinal stripe-pattern errors and other flaws. Based on corrected GRACE Mascon (mass concentration) gridded mass transport time series and updated LDCgam (Least Difference Combination global angular momenta) data, we present a new set of monthly gravity models called LDCmgm90, in the form of Stokes coefficients with order and degree both up to 90. The LDCgam inputs are developed by assimilating degree-2 Stokes coefficients from various versions of GRACE (including Mascon products) and SLR (Satellite Laser Ranging) monthly gravity data into combinations of outputs from various global atmospheric, oceanic, and hydrological circulation models, under the constraints of accurately measured Earth orientation parameters in the Least Difference Combination (LDC) scheme. Taking advantages of the relative strengths of the various input solutions, the LDCmgm90 is free of stripes and some other flaws of classical GRACE products.
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spelling pubmed-68115302019-10-30 Multiple-data-based monthly geopotential model set LDCmgm90 Chen, Wei Luo, Jiesi Ray, Jim Yu, Nan Li, Jian Cheng Sci Data Data Descriptor While the GRACE (Gravity Recovery and Climate Experiment) satellite mission is of great significance in understanding various branches of Earth sciences, the quality of GRACE monthly products can be unsatisfactory due to strong longitudinal stripe-pattern errors and other flaws. Based on corrected GRACE Mascon (mass concentration) gridded mass transport time series and updated LDCgam (Least Difference Combination global angular momenta) data, we present a new set of monthly gravity models called LDCmgm90, in the form of Stokes coefficients with order and degree both up to 90. The LDCgam inputs are developed by assimilating degree-2 Stokes coefficients from various versions of GRACE (including Mascon products) and SLR (Satellite Laser Ranging) monthly gravity data into combinations of outputs from various global atmospheric, oceanic, and hydrological circulation models, under the constraints of accurately measured Earth orientation parameters in the Least Difference Combination (LDC) scheme. Taking advantages of the relative strengths of the various input solutions, the LDCmgm90 is free of stripes and some other flaws of classical GRACE products. Nature Publishing Group UK 2019-10-23 /pmc/articles/PMC6811530/ /pubmed/31645550 http://dx.doi.org/10.1038/s41597-019-0239-7 Text en © The Author(s) 2019 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/. 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
Chen, Wei
Luo, Jiesi
Ray, Jim
Yu, Nan
Li, Jian Cheng
Multiple-data-based monthly geopotential model set LDCmgm90
title Multiple-data-based monthly geopotential model set LDCmgm90
title_full Multiple-data-based monthly geopotential model set LDCmgm90
title_fullStr Multiple-data-based monthly geopotential model set LDCmgm90
title_full_unstemmed Multiple-data-based monthly geopotential model set LDCmgm90
title_short Multiple-data-based monthly geopotential model set LDCmgm90
title_sort multiple-data-based monthly geopotential model set ldcmgm90
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6811530/
https://www.ncbi.nlm.nih.gov/pubmed/31645550
http://dx.doi.org/10.1038/s41597-019-0239-7
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