Articles | Volume 13, issue 9
https://doi.org/10.5194/essd-13-4385-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-13-4385-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
07 Sep 2021
Data description paper |
| 07 Sep 2021
| 07 Sep 2021
Development of observation-based global multilayer soil moisture products for 1970 to 2016
Yaoping Wang
Institute for a Secure and Sustainable Environment, University of
Tennessee, Knoxville, TN 37902, USA
Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA
Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA
Mingzhou Jin
Institute for a Secure and Sustainable Environment, University of
Tennessee, Knoxville, TN 37902, USA
Department of Industrial and Systems Engineering, University of
Tennessee, Knoxville, TN 37996, USA
Forrest M. Hoffman
Computational Sciences and Engineering Division and Climate Change
Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA
Xiaoying Shi
Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA
Stan D. Wullschleger
Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA
Yongjiu Dai
School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou, 519082, China
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Cited
12 citations as recorded by crossref.
- Quantification of human contribution to soil moisture-based terrestrial aridity Y. Wang et al. 10.1038/s41467-022-34071-5
- Human and natural impacts on the U.S. freshwater salinization and alkalinization: A machine learning approach B. E et al. 10.1016/j.scitotenv.2023.164138
- Global Evaluation of the Noah‐MP Land Surface Model and Suggestions for Selecting Parameterization Schemes J. Li et al. 10.1029/2021JD035753
- A 1 km daily soil moisture dataset over China using in situ measurement and machine learning Q. Li et al. 10.5194/essd-14-5267-2022
- Impacts of Topography‐Driven Water Redistribution on Terrestrial Water Storage Change in California Through Ecosystem Responses X. Zhang et al. 10.1029/2023WR035572
- Scenarios for the Altamira cave CO2 concentration from 1950 to 2100 M. Sáez et al. 10.1038/s41598-024-60149-9
- Flood fatalities and displacement influence human migration in floodplains of developing countries N. Wang et al. 10.1038/s43247-025-02293-2
- Implementation and evaluation of a dynamic root water uptake scheme in the Beijing climate center atmosphere-vegetation interaction model L. Yang et al. 10.1007/s00382-025-07615-w
- In silico calculation of soil pH by SCEPTER v1.0 Y. Kanzaki et al. 10.5194/gmd-17-4515-2024
- SGD-SM 2.0: an improved seamless global daily soil moisture long-term dataset from 2002 to 2022 Q. Zhang et al. 10.5194/essd-14-4473-2022
- A Long-term Consistent Artificial Intelligence and Remote Sensing-based Soil Moisture Dataset O. Skulovich & P. Gentine 10.1038/s41597-023-02053-x
- Effects of Mosaic Representation of Land Use/Land Cover on Skin Temperature and Energy Fluxes in Noah‐MP Land Surface Model Over China G. Zhang et al. 10.1029/2021JD034542
12 citations as recorded by crossref.
- Quantification of human contribution to soil moisture-based terrestrial aridity Y. Wang et al. 10.1038/s41467-022-34071-5
- Human and natural impacts on the U.S. freshwater salinization and alkalinization: A machine learning approach B. E et al. 10.1016/j.scitotenv.2023.164138
- Global Evaluation of the Noah‐MP Land Surface Model and Suggestions for Selecting Parameterization Schemes J. Li et al. 10.1029/2021JD035753
- A 1 km daily soil moisture dataset over China using in situ measurement and machine learning Q. Li et al. 10.5194/essd-14-5267-2022
- Impacts of Topography‐Driven Water Redistribution on Terrestrial Water Storage Change in California Through Ecosystem Responses X. Zhang et al. 10.1029/2023WR035572
- Scenarios for the Altamira cave CO2 concentration from 1950 to 2100 M. Sáez et al. 10.1038/s41598-024-60149-9
- Flood fatalities and displacement influence human migration in floodplains of developing countries N. Wang et al. 10.1038/s43247-025-02293-2
- Implementation and evaluation of a dynamic root water uptake scheme in the Beijing climate center atmosphere-vegetation interaction model L. Yang et al. 10.1007/s00382-025-07615-w
- In silico calculation of soil pH by SCEPTER v1.0 Y. Kanzaki et al. 10.5194/gmd-17-4515-2024
- SGD-SM 2.0: an improved seamless global daily soil moisture long-term dataset from 2002 to 2022 Q. Zhang et al. 10.5194/essd-14-4473-2022
- A Long-term Consistent Artificial Intelligence and Remote Sensing-based Soil Moisture Dataset O. Skulovich & P. Gentine 10.1038/s41597-023-02053-x
- Effects of Mosaic Representation of Land Use/Land Cover on Skin Temperature and Energy Fluxes in Noah‐MP Land Surface Model Over China G. Zhang et al. 10.1029/2021JD034542
Latest update: 14 May 2025
Short summary
We developed seven global soil moisture datasets (1970–2016, monthly, half-degree, and multilayer) by merging a wide range of data sources, including in situ and satellite observations, reanalysis, offline land surface model simulations, and Earth system model simulations. Given the great value of long-term, multilayer, gap-free soil moisture products to climate research and applications, we believe this paper and the presented datasets would be of interest to many different communities.
We developed seven global soil moisture datasets (1970–2016, monthly, half-degree, and...
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