Articles | Volume 22, issue 4
https://doi.org/10.5194/hess-22-2575-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-22-2575-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
26 Apr 2018
Research article |
| 26 Apr 2018
| 26 Apr 2018
Impact of remotely sensed soil moisture and precipitation on soil moisture prediction in a data assimilation system with the JULES land surface model
Ewan Pinnington
CORRESPONDING AUTHOR
Department of Meteorology, University of Reading, Reading, UK
National Centre for Earth Observation, University of Reading, Reading, UK
Tristan Quaife
Department of Meteorology, University of Reading, Reading, UK
National Centre for Earth Observation, University of Reading, Reading, UK
Emily Black
Department of Meteorology, University of Reading, Reading, UK
National Centre for Atmospheric Science, University of Reading, Reading, UK
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- Improve the Performance of the Noah‐MP‐Crop Model by Jointly Assimilating Soil Moisture and Vegetation Phenology Data T. Xu et al. 10.1029/2020MS002394
- Method development for estimating soil organic carbon content in an alpine region using soil moisture data Q. Luo et al. 10.1007/s11430-019-9554-8
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- Stein-based preconditioners for weak-constraint 4D-var D. Palitta & J. Tabeart 10.1016/j.jcp.2023.112068
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- Climatic and anthropogenic controls on groundwater dynamics in the Mekong River Basin T. Kabir et al. 10.1016/j.jhydrol.2023.129761
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- The influence of regional hydrometric data incorporation on the accuracy of gridded reconstruction of monthly runoff G. Ayzel et al. 10.1080/02626667.2020.1762886
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- Field scale computer modeling of soil moisture with dynamic nudging assimilation algorithm O. Kozhushko et al. 10.23939/mmc2022.02.203
- More reliable determination of daily evaporation from the pan in cold regions by limited meteorological factors M. Mohammadi et al. 10.1007/s13201-024-02100-x
- Development of soil moisture profiles through coupled microwave–thermal infrared observations in the southeastern United States V. Mishra et al. 10.5194/hess-22-4935-2018
- Comparing Assimilation of Synthetic Soil Moisture Versus C‐Band Backscatter for Hyper‐Resolution Land Surface Modeling L. Sun et al. 10.1029/2020WR028921
- Retrieval of Soil Moisture by Integrating Sentinel-1A and MODIS Data over Agricultural Fields Y. Han et al. 10.3390/w12061726
- Monitoring and Forecasting the Impact of the 2018 Summer Heatwave on Vegetation C. Albergel et al. 10.3390/rs11050520
- Confronting Soil Moisture Dynamics from the ORCHIDEE Land Surface Model With the ESA-CCI Product: Perspectives for Data Assimilation N. Raoult et al. 10.3390/rs10111786
- Dominant Features of Global Surface Soil Moisture Variability Observed by the SMOS Satellite M. Piles et al. 10.3390/rs11010095
- An Agenda for Land Data Assimilation Priorities: Realizing the Promise of Terrestrial Water, Energy, and Vegetation Observations From Space S. Kumar et al. 10.1029/2022MS003259
- Estimation and evaluation of high-resolution soil moisture from merged model and Earth observation data in the Great Britain J. Peng et al. 10.1016/j.rse.2021.112610
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- Towards a Long-Term Reanalysis of Land Surface Variables over Western Africa: LDAS-Monde Applied over Burkina Faso from 2001 to 2018 M. Tall et al. 10.3390/rs11060735
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- Review of Applications of Remote Sensing towards Sustainable Agriculture in the Northern Savannah Regions of Ghana A. Moomen et al. 10.3390/agriculture14040546
- Exploring a hybrid ensemble–variational data assimilation technique (4DEnVar) with a simple ecosystem carbon model N. Douglas et al. 10.1016/j.envsoft.2025.106361
- Remote sensing of land use-land cover change and climate variability on hydrological processes in Sub-Saharan Africa: key scientific strides and challenges T. Govender et al. 10.1080/10106049.2022.2043451
- Can Data Assimilation Improve Short-Term Prediction of Land Surface Variables? Y. Tian et al. 10.3390/rs14205172
- Suitability of Satellite-Based Precipitation Products for Water Balance Simulations Using Multiple Observations in a Humid Catchment D. Zhang et al. 10.3390/rs11020151
- Exploring the potential of history matching for land surface model calibration N. Raoult et al. 10.5194/gmd-17-5779-2024
- Representation of Stony Surface‐Atmosphere Interactions in WRF Reduces Cold and Wet Biases for the Southern Tibetan Plateau S. Yue et al. 10.1029/2021JD035291
32 citations as recorded by crossref.
- Assimilating shallow soil moisture observations into land models with a water budget constraint B. Dan et al. 10.5194/hess-24-5187-2020
- OpenForecast v2: Development and Benchmarking of the First National-Scale Operational Runoff Forecasting System in Russia G. Ayzel 10.3390/hydrology8010003
- Improve the Performance of the Noah‐MP‐Crop Model by Jointly Assimilating Soil Moisture and Vegetation Phenology Data T. Xu et al. 10.1029/2020MS002394
- Method development for estimating soil organic carbon content in an alpine region using soil moisture data Q. Luo et al. 10.1007/s11430-019-9554-8
- Retrieving Soil Physical Properties by Assimilating SMAP Brightness Temperature Observations into the Community Land Model H. Zhao et al. 10.3390/s23052620
- Stein-based preconditioners for weak-constraint 4D-var D. Palitta & J. Tabeart 10.1016/j.jcp.2023.112068
- More Reliable Determination of Daily Evaporation from the Pan in Cold Regions by Limited Meteorological Factors M. Mohammadi et al. 10.2139/ssrn.3989541
- Using data assimilation to optimize pedotransfer functions using field-scale in situ soil moisture observations E. Cooper et al. 10.5194/hess-25-2445-2021
- Climatic and anthropogenic controls on groundwater dynamics in the Mekong River Basin T. Kabir et al. 10.1016/j.jhydrol.2023.129761
- The Land Variational Ensemble Data Assimilation Framework: LAVENDAR v1.0.0 E. Pinnington et al. 10.5194/gmd-13-55-2020
- Spatio-temporal soil drying in southeastern South America: the importance of effective sampling frequency and observational errors on drydown time scale estimates R. Ruscica et al. 10.1080/01431161.2020.1767825
- The influence of regional hydrometric data incorporation on the accuracy of gridded reconstruction of monthly runoff G. Ayzel et al. 10.1080/02626667.2020.1762886
- Improving soil moisture prediction of a high-resolution land surface model by parameterising pedotransfer functions through assimilation of SMAP satellite data E. Pinnington et al. 10.5194/hess-25-1617-2021
- Field scale computer modeling of soil moisture with dynamic nudging assimilation algorithm O. Kozhushko et al. 10.23939/mmc2022.02.203
- More reliable determination of daily evaporation from the pan in cold regions by limited meteorological factors M. Mohammadi et al. 10.1007/s13201-024-02100-x
- Development of soil moisture profiles through coupled microwave–thermal infrared observations in the southeastern United States V. Mishra et al. 10.5194/hess-22-4935-2018
- Comparing Assimilation of Synthetic Soil Moisture Versus C‐Band Backscatter for Hyper‐Resolution Land Surface Modeling L. Sun et al. 10.1029/2020WR028921
- Retrieval of Soil Moisture by Integrating Sentinel-1A and MODIS Data over Agricultural Fields Y. Han et al. 10.3390/w12061726
- Monitoring and Forecasting the Impact of the 2018 Summer Heatwave on Vegetation C. Albergel et al. 10.3390/rs11050520
- Confronting Soil Moisture Dynamics from the ORCHIDEE Land Surface Model With the ESA-CCI Product: Perspectives for Data Assimilation N. Raoult et al. 10.3390/rs10111786
- Dominant Features of Global Surface Soil Moisture Variability Observed by the SMOS Satellite M. Piles et al. 10.3390/rs11010095
- An Agenda for Land Data Assimilation Priorities: Realizing the Promise of Terrestrial Water, Energy, and Vegetation Observations From Space S. Kumar et al. 10.1029/2022MS003259
- Estimation and evaluation of high-resolution soil moisture from merged model and Earth observation data in the Great Britain J. Peng et al. 10.1016/j.rse.2021.112610
- Simultaneous Assimilation of Remotely Sensed Soil Moisture and FAPAR for Improving Terrestrial Carbon Fluxes at Multiple Sites Using CCDAS M. Wu et al. 10.3390/rs11010027
- Towards a Long-Term Reanalysis of Land Surface Variables over Western Africa: LDAS-Monde Applied over Burkina Faso from 2001 to 2018 M. Tall et al. 10.3390/rs11060735
- Last-decade progress in understanding and modeling the land surface processes on the Tibetan Plateau H. Lu et al. 10.5194/hess-24-5745-2020
- Review of Applications of Remote Sensing towards Sustainable Agriculture in the Northern Savannah Regions of Ghana A. Moomen et al. 10.3390/agriculture14040546
- Exploring a hybrid ensemble–variational data assimilation technique (4DEnVar) with a simple ecosystem carbon model N. Douglas et al. 10.1016/j.envsoft.2025.106361
- Remote sensing of land use-land cover change and climate variability on hydrological processes in Sub-Saharan Africa: key scientific strides and challenges T. Govender et al. 10.1080/10106049.2022.2043451
- Can Data Assimilation Improve Short-Term Prediction of Land Surface Variables? Y. Tian et al. 10.3390/rs14205172
- Suitability of Satellite-Based Precipitation Products for Water Balance Simulations Using Multiple Observations in a Humid Catchment D. Zhang et al. 10.3390/rs11020151
- Exploring the potential of history matching for land surface model calibration N. Raoult et al. 10.5194/gmd-17-5779-2024
Latest update: 01 Apr 2025
Short summary
This paper combines satellite observations of precipitation and soil moisture to understand what key information they offer to improve land surface model estimates of soil moisture over Ghana. When both observations are combined with the chosen land surface model we reduce the unbiased root-mean-squared error in a 5-year model hindcast by 27 %; this bodes well for the production of improved soil moisture estimates over sub-Saharan Africa where subsistence farming remains prevalent.
This paper combines satellite observations of precipitation and soil moisture to understand what...
