A first assessment of satellite and reanalysis estimates of surface and root-zone soil moisture over the permafrost region of Qinghai-Tibet Plateau
International audience Long-term and high-quality surface soil moisture (SSM) and root-zone soil moisture (RZSM) data is crucial for understanding the land-atmosphere interactions of the Qinghai-Tibet Plateau (QTP). More than 40% of QTP is covered by permafrost, yet few studies have evaluated the ac...
Published in: | Remote Sensing of Environment |
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Main Authors: | , , , , , , , , , , , , , , , , , , , , , |
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Format: | Article in Journal/Newspaper |
Language: | English |
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HAL CCSD
2021
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Online Access: | https://hal.inrae.fr/hal-03612873 https://doi.org/10.1016/j.rse.2021.112666 |
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ftccsdartic:oai:HAL:hal-03612873v1 |
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Open Polar |
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Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe) |
op_collection_id |
ftccsdartic |
language |
English |
topic |
Qinghai-Tibet Plateau Permafrost Microwave remote sensing Reanalysis datasets Surface soil moisture Root-zone soil moisture SMOS SMAP AMSR2 ASCAT ESA CCI ERAS-land GLDAS-Noah Inter-comparison [SDE]Environmental Sciences |
spellingShingle |
Qinghai-Tibet Plateau Permafrost Microwave remote sensing Reanalysis datasets Surface soil moisture Root-zone soil moisture SMOS SMAP AMSR2 ASCAT ESA CCI ERAS-land GLDAS-Noah Inter-comparison [SDE]Environmental Sciences Xing, Zanpin Fan, Lei Zhao, Lin de Lannoy, Gabrielle Frappart, Frédéric Peng, Jian Li, Xiaojun Zeng, Jiangyuan Al-Yaari, Amen Yang, Kun Zhao, Tianjie Shi, Jiancheng Wang, Mengjia Liu, Xiangzhuo Hu, Guojie Xiao, Yao Du, Erji Li, Ren Qiao, Yongping Shi, Jianzong Wen, Jianguang J.-P., Wigneron A first assessment of satellite and reanalysis estimates of surface and root-zone soil moisture over the permafrost region of Qinghai-Tibet Plateau |
topic_facet |
Qinghai-Tibet Plateau Permafrost Microwave remote sensing Reanalysis datasets Surface soil moisture Root-zone soil moisture SMOS SMAP AMSR2 ASCAT ESA CCI ERAS-land GLDAS-Noah Inter-comparison [SDE]Environmental Sciences |
description |
International audience Long-term and high-quality surface soil moisture (SSM) and root-zone soil moisture (RZSM) data is crucial for understanding the land-atmosphere interactions of the Qinghai-Tibet Plateau (QTP). More than 40% of QTP is covered by permafrost, yet few studies have evaluated the accuracy of SSM and RZSM products derived from microwave satellite, land surface models (LSMs) and reanalysis over that region. This study tries to address this gap by evaluating a range of satellite and reanalysis estimates of SSM and RZSM in the thawed soil overlaying permafrost in the QTP, using in-situ measurements from sixteen stations. Here, seven SSM products were evaluated: Soil Moisture Active Passive L3 (SMAP L3) and L4 (SMAP-L4), Soil Moisture and Ocean Salinity in version IC (SMOS IC), Land Parameter Retrieval Model (LPRM) Advanced Microwave Scanning Radiometer 2 (AMSR2), European Space Agency Climate Change Initiative (ESA CCI), Advanced Scatterometer (ASCAT), and the fifth generation of the land component of the European Centre for Medium-Range Weather Forecasts atmospheric reanalysis (ERAS-Land). We also evaluated three RZSM products from SMAP-L4, ERA5-Land, and the Noah land surface model driven by Global Land Data Assimilation System (GLDAS-Noah). The assessment was conducted using five statistical metrics, i. e. Pearson correlation coefficient (R), bias, slope, Root Mean Square Error (RMSE), and unbiased RMSE (ubRMSE) between SSM or RZSM products and in-situ measurements. Our results showed that the ESA CCI, SMAP-L4 and SMOS-IC SSM products outperformed the other SSM products, indicated by higher correlation coefficients (R) (with a median R value of 0.63, 0.44 and 0.57, respectively) and lower ubRMSE (with a median ubRMSE value of 0.05, 0.04 and 0.07 m(3)/m(3), respectively). Yet, SSM overestimation was found for all SSM products. This could be partly attributed to ancillary data used in the retrieval (e.g. overestimation of land surface temperature for SMAP-L3) and to the fact that the products ... |
author2 |
University of Chinese Academy of Sciences Beijing (UCAS) Southwest University Chongqing Nanjing University of Science and Technology (NJUST) Catholic University of Leuven = Katholieke Universiteit Leuven (KU Leuven) Laboratoire d'études en Géophysique et océanographie spatiales (LEGOS) Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3) Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP) Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Centre National de la Recherche Scientifique (CNRS) Leipzig University Interactions Sol Plante Atmosphère (UMR ISPA) Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) Chinese Academy of Sciences Beijing (CAS) Tsinghua University Beijing (THU) |
format |
Article in Journal/Newspaper |
author |
Xing, Zanpin Fan, Lei Zhao, Lin de Lannoy, Gabrielle Frappart, Frédéric Peng, Jian Li, Xiaojun Zeng, Jiangyuan Al-Yaari, Amen Yang, Kun Zhao, Tianjie Shi, Jiancheng Wang, Mengjia Liu, Xiangzhuo Hu, Guojie Xiao, Yao Du, Erji Li, Ren Qiao, Yongping Shi, Jianzong Wen, Jianguang J.-P., Wigneron |
author_facet |
Xing, Zanpin Fan, Lei Zhao, Lin de Lannoy, Gabrielle Frappart, Frédéric Peng, Jian Li, Xiaojun Zeng, Jiangyuan Al-Yaari, Amen Yang, Kun Zhao, Tianjie Shi, Jiancheng Wang, Mengjia Liu, Xiangzhuo Hu, Guojie Xiao, Yao Du, Erji Li, Ren Qiao, Yongping Shi, Jianzong Wen, Jianguang J.-P., Wigneron |
author_sort |
Xing, Zanpin |
title |
A first assessment of satellite and reanalysis estimates of surface and root-zone soil moisture over the permafrost region of Qinghai-Tibet Plateau |
title_short |
A first assessment of satellite and reanalysis estimates of surface and root-zone soil moisture over the permafrost region of Qinghai-Tibet Plateau |
title_full |
A first assessment of satellite and reanalysis estimates of surface and root-zone soil moisture over the permafrost region of Qinghai-Tibet Plateau |
title_fullStr |
A first assessment of satellite and reanalysis estimates of surface and root-zone soil moisture over the permafrost region of Qinghai-Tibet Plateau |
title_full_unstemmed |
A first assessment of satellite and reanalysis estimates of surface and root-zone soil moisture over the permafrost region of Qinghai-Tibet Plateau |
title_sort |
first assessment of satellite and reanalysis estimates of surface and root-zone soil moisture over the permafrost region of qinghai-tibet plateau |
publisher |
HAL CCSD |
publishDate |
2021 |
url |
https://hal.inrae.fr/hal-03612873 https://doi.org/10.1016/j.rse.2021.112666 |
genre |
permafrost |
genre_facet |
permafrost |
op_source |
ISSN: 0034-4257 EISSN: 0034-4257 Remote Sensing of Environment https://hal.inrae.fr/hal-03612873 Remote Sensing of Environment, 2021, 265, pp.112666. ⟨10.1016/j.rse.2021.112666⟩ |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.rse.2021.112666 hal-03612873 https://hal.inrae.fr/hal-03612873 doi:10.1016/j.rse.2021.112666 WOS: 000697358300003 |
op_doi |
https://doi.org/10.1016/j.rse.2021.112666 |
container_title |
Remote Sensing of Environment |
container_volume |
265 |
container_start_page |
112666 |
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1790606674309939200 |
spelling |
ftccsdartic:oai:HAL:hal-03612873v1 2024-02-11T10:07:52+01:00 A first assessment of satellite and reanalysis estimates of surface and root-zone soil moisture over the permafrost region of Qinghai-Tibet Plateau Xing, Zanpin Fan, Lei Zhao, Lin de Lannoy, Gabrielle Frappart, Frédéric Peng, Jian Li, Xiaojun Zeng, Jiangyuan Al-Yaari, Amen Yang, Kun Zhao, Tianjie Shi, Jiancheng Wang, Mengjia Liu, Xiangzhuo Hu, Guojie Xiao, Yao Du, Erji Li, Ren Qiao, Yongping Shi, Jianzong Wen, Jianguang J.-P., Wigneron University of Chinese Academy of Sciences Beijing (UCAS) Southwest University Chongqing Nanjing University of Science and Technology (NJUST) Catholic University of Leuven = Katholieke Universiteit Leuven (KU Leuven) Laboratoire d'études en Géophysique et océanographie spatiales (LEGOS) Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3) Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP) Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Centre National de la Recherche Scientifique (CNRS) Leipzig University Interactions Sol Plante Atmosphère (UMR ISPA) Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) Chinese Academy of Sciences Beijing (CAS) Tsinghua University Beijing (THU) 2021-11 https://hal.inrae.fr/hal-03612873 https://doi.org/10.1016/j.rse.2021.112666 en eng HAL CCSD info:eu-repo/semantics/altIdentifier/doi/10.1016/j.rse.2021.112666 hal-03612873 https://hal.inrae.fr/hal-03612873 doi:10.1016/j.rse.2021.112666 WOS: 000697358300003 ISSN: 0034-4257 EISSN: 0034-4257 Remote Sensing of Environment https://hal.inrae.fr/hal-03612873 Remote Sensing of Environment, 2021, 265, pp.112666. ⟨10.1016/j.rse.2021.112666⟩ Qinghai-Tibet Plateau Permafrost Microwave remote sensing Reanalysis datasets Surface soil moisture Root-zone soil moisture SMOS SMAP AMSR2 ASCAT ESA CCI ERAS-land GLDAS-Noah Inter-comparison [SDE]Environmental Sciences info:eu-repo/semantics/article Journal articles 2021 ftccsdartic https://doi.org/10.1016/j.rse.2021.112666 2024-01-21T00:28:48Z International audience Long-term and high-quality surface soil moisture (SSM) and root-zone soil moisture (RZSM) data is crucial for understanding the land-atmosphere interactions of the Qinghai-Tibet Plateau (QTP). More than 40% of QTP is covered by permafrost, yet few studies have evaluated the accuracy of SSM and RZSM products derived from microwave satellite, land surface models (LSMs) and reanalysis over that region. This study tries to address this gap by evaluating a range of satellite and reanalysis estimates of SSM and RZSM in the thawed soil overlaying permafrost in the QTP, using in-situ measurements from sixteen stations. Here, seven SSM products were evaluated: Soil Moisture Active Passive L3 (SMAP L3) and L4 (SMAP-L4), Soil Moisture and Ocean Salinity in version IC (SMOS IC), Land Parameter Retrieval Model (LPRM) Advanced Microwave Scanning Radiometer 2 (AMSR2), European Space Agency Climate Change Initiative (ESA CCI), Advanced Scatterometer (ASCAT), and the fifth generation of the land component of the European Centre for Medium-Range Weather Forecasts atmospheric reanalysis (ERAS-Land). We also evaluated three RZSM products from SMAP-L4, ERA5-Land, and the Noah land surface model driven by Global Land Data Assimilation System (GLDAS-Noah). The assessment was conducted using five statistical metrics, i. e. Pearson correlation coefficient (R), bias, slope, Root Mean Square Error (RMSE), and unbiased RMSE (ubRMSE) between SSM or RZSM products and in-situ measurements. Our results showed that the ESA CCI, SMAP-L4 and SMOS-IC SSM products outperformed the other SSM products, indicated by higher correlation coefficients (R) (with a median R value of 0.63, 0.44 and 0.57, respectively) and lower ubRMSE (with a median ubRMSE value of 0.05, 0.04 and 0.07 m(3)/m(3), respectively). Yet, SSM overestimation was found for all SSM products. This could be partly attributed to ancillary data used in the retrieval (e.g. overestimation of land surface temperature for SMAP-L3) and to the fact that the products ... Article in Journal/Newspaper permafrost Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe) Remote Sensing of Environment 265 112666 |