Assessments and Corrections of GLDAS2.0 Forcing Data in Four Large Transboundary Rivers in the Tibetan Plateau and Northeast China
Abstract GLDAS2.0 provides long‐term fine resolution gridded hydrometeorological data sets, which are necessary for water‐related studies, particularly in some transboundary rivers that are partially without observation. Yet, GLDAS2.0 has only been validated at limited locations, and few studies hav...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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American Geophysical Union (AGU)
2022-01-01
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| Series: | Earth and Space Science |
| Subjects: | |
| Online Access: | https://doi.org/10.1029/2020EA001576 |
| _version_ | 1798024896215777280 |
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| author | Wei Qi Junguo Liu Hong Yang Deliang Chen Lian Feng |
| author_facet | Wei Qi Junguo Liu Hong Yang Deliang Chen Lian Feng |
| author_sort | Wei Qi |
| collection | DOAJ |
| description | Abstract GLDAS2.0 provides long‐term fine resolution gridded hydrometeorological data sets, which are necessary for water‐related studies, particularly in some transboundary rivers that are partially without observation. Yet, GLDAS2.0 has only been validated at limited locations, and few studies have been conducted to develop approaches to correct the GLDAS2.0 data for transboundary rivers. This work assessed the GLDAS2.0 data and developed approaches to correct their uncertainties for studies in large transboundary rivers in the Tibetan Plateau and Northeast China (NC). To achieve these goals, observational data from 1982 to 2010 and a water and energy budget‐based distributed hydrological model including biosphere after calibration and validation were employed. We find that the GLDAS2.0 data (except for wind speed) can reasonably replicate observed seasonal variations. However, its specific humidity and wind speed have large uncertainty, and precipitation has large uncertainty in summer. In NC, the trends of its precipitation, air temperature, downward longwave radiation, and wind speed are consistent with the observations. In the Yarlung Tsangpo, Lancang, and Nu Rivers, the trends of all GLDAS2.0 data reproduce the observation very well, that is, wetting, warming, and dimming trends. Validations show that the corrections are effective and the corrected forcing data can be successfully used in hydrological simulation with improved performance than the raw GLDAS2.0 data, which demonstrates the usefulness of the methodology and corrected forcing data to hydrometeorological studies in transboundary rivers in China as well as in other nearby regions/countries. |
| first_indexed | 2024-04-11T18:09:59Z |
| format | Article |
| id | doaj.art-aae83380bcb047929ae02bcfaf8a36d4 |
| institution | Directory Open Access Journal |
| issn | 2333-5084 |
| language | English |
| last_indexed | 2024-04-11T18:09:59Z |
| publishDate | 2022-01-01 |
| publisher | American Geophysical Union (AGU) |
| record_format | Article |
| series | Earth and Space Science |
| spelling | doaj.art-aae83380bcb047929ae02bcfaf8a36d42022-12-22T04:10:11ZengAmerican Geophysical Union (AGU)Earth and Space Science2333-50842022-01-0191n/an/a10.1029/2020EA001576Assessments and Corrections of GLDAS2.0 Forcing Data in Four Large Transboundary Rivers in the Tibetan Plateau and Northeast ChinaWei Qi0Junguo Liu1Hong Yang2Deliang Chen3Lian Feng4School of Environmental Science and Engineering Southern University of Science and Technology Shenzhen ChinaSchool of Environmental Science and Engineering Southern University of Science and Technology Shenzhen ChinaEawag Swiss Federal Institute of Aquatic Science and Technology Duebendorf SwitzerlandDepartment of Earth Sciences Regional Climate Group University of Gothenburg Gothenburg SwedenSchool of Environmental Science and Engineering Southern University of Science and Technology Shenzhen ChinaAbstract GLDAS2.0 provides long‐term fine resolution gridded hydrometeorological data sets, which are necessary for water‐related studies, particularly in some transboundary rivers that are partially without observation. Yet, GLDAS2.0 has only been validated at limited locations, and few studies have been conducted to develop approaches to correct the GLDAS2.0 data for transboundary rivers. This work assessed the GLDAS2.0 data and developed approaches to correct their uncertainties for studies in large transboundary rivers in the Tibetan Plateau and Northeast China (NC). To achieve these goals, observational data from 1982 to 2010 and a water and energy budget‐based distributed hydrological model including biosphere after calibration and validation were employed. We find that the GLDAS2.0 data (except for wind speed) can reasonably replicate observed seasonal variations. However, its specific humidity and wind speed have large uncertainty, and precipitation has large uncertainty in summer. In NC, the trends of its precipitation, air temperature, downward longwave radiation, and wind speed are consistent with the observations. In the Yarlung Tsangpo, Lancang, and Nu Rivers, the trends of all GLDAS2.0 data reproduce the observation very well, that is, wetting, warming, and dimming trends. Validations show that the corrections are effective and the corrected forcing data can be successfully used in hydrological simulation with improved performance than the raw GLDAS2.0 data, which demonstrates the usefulness of the methodology and corrected forcing data to hydrometeorological studies in transboundary rivers in China as well as in other nearby regions/countries.https://doi.org/10.1029/2020EA001576GLDAShydrologymeteorologyAmur RiverTibetan Plateautransboundary river |
| spellingShingle | Wei Qi Junguo Liu Hong Yang Deliang Chen Lian Feng Assessments and Corrections of GLDAS2.0 Forcing Data in Four Large Transboundary Rivers in the Tibetan Plateau and Northeast China Earth and Space Science GLDAS hydrology meteorology Amur River Tibetan Plateau transboundary river |
| title | Assessments and Corrections of GLDAS2.0 Forcing Data in Four Large Transboundary Rivers in the Tibetan Plateau and Northeast China |
| title_full | Assessments and Corrections of GLDAS2.0 Forcing Data in Four Large Transboundary Rivers in the Tibetan Plateau and Northeast China |
| title_fullStr | Assessments and Corrections of GLDAS2.0 Forcing Data in Four Large Transboundary Rivers in the Tibetan Plateau and Northeast China |
| title_full_unstemmed | Assessments and Corrections of GLDAS2.0 Forcing Data in Four Large Transboundary Rivers in the Tibetan Plateau and Northeast China |
| title_short | Assessments and Corrections of GLDAS2.0 Forcing Data in Four Large Transboundary Rivers in the Tibetan Plateau and Northeast China |
| title_sort | assessments and corrections of gldas2 0 forcing data in four large transboundary rivers in the tibetan plateau and northeast china |
| topic | GLDAS hydrology meteorology Amur River Tibetan Plateau transboundary river |
| url | https://doi.org/10.1029/2020EA001576 |
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