Articles | Volume 24, issue 9
https://doi.org/10.5194/hess-24-4291-2020
© Author(s) 2020. 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-24-4291-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
02 Sep 2020
Research article |
| 02 Sep 2020
| 02 Sep 2020
Data assimilation for continuous global assessment of severe conditions over terrestrial surfaces
Clément Albergel
CORRESPONDING AUTHOR
CNRM, Université de Toulouse, Météo-France, CNRS,
Toulouse, France
now at: European Space Agency Climate Office, ECSAT, Harwell Campus, Oxfordshire, Didcot OX11 0FD, UK
Yongjun Zheng
CNRM, Université de Toulouse, Météo-France, CNRS,
Toulouse, France
Bertrand Bonan
CNRM, Université de Toulouse, Météo-France, CNRS,
Toulouse, France
Emanuel Dutra
Instituto Dom Luiz, IDL, Faculty of Sciences, University of Lisbon, Lisbon, Portugal
Nemesio Rodríguez-Fernández
CESBIO, Université de Toulouse, CNRS, CNES, IRD, Toulouse,
France
Simon Munier
CNRM, Université de Toulouse, Météo-France, CNRS,
Toulouse, France
Clara Draper
CIRES/NOAA Earth System Research Laboratories, Boulder, CO, USA
Patricia de Rosnay
European Centre for Medium-Range Weather Forecasts, Shinfield Road,
Reading RG2 9AX, UK
Joaquin Muñoz-Sabater
European Centre for Medium-Range Weather Forecasts, Shinfield Road,
Reading RG2 9AX, UK
Gianpaolo Balsamo
European Centre for Medium-Range Weather Forecasts, Shinfield Road,
Reading RG2 9AX, UK
David Fairbairn
European Centre for Medium-Range Weather Forecasts, Shinfield Road,
Reading RG2 9AX, UK
Catherine Meurey
CNRM, Université de Toulouse, Météo-France, CNRS,
Toulouse, France
Jean-Christophe Calvet
CNRM, Université de Toulouse, Météo-France, CNRS,
Toulouse, France
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Cited
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- Assimilation of Leaf Area Index and Soil Water Index from Satellite Observations in a Land Surface Model in Hungary H. Tóth & B. Szintai 10.3390/atmos12080944
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- Impact of leaf area index assimilation and gauge-corrected precipitation on land surface variables in LDAS-Monde: a case study over China E. Liu et al. 10.1016/j.jhydrol.2025.133304
- Multiscale Assimilation of Sentinel and Landsat Data for Soil Moisture and Leaf Area Index Predictions Using an Ensemble-Kalman-Filter-Based Assimilation Approach in a Heterogeneous Ecosystem N. Montaldo et al. 10.3390/rs14143458
- Catchment Functioning Under Prolonged Drought Stress: Tracer‐Aided Ecohydrological Modeling in an Intensively Managed Agricultural Catchment X. Yang et al. 10.1029/2020WR029094
- High-resolution data assimilation for two maritime extreme weather events: a comparison between 3D-Var and EnKF D. Carrió et al. 10.5194/nhess-25-2999-2025
- Global Assimilation of Remotely Sensed Leaf Area Index: The Impact of Updating More State Variables Within a Land Surface Model A. Rahman et al. 10.3389/frwa.2021.789352
- Skilful seasonal streamflow forecasting using a fully coupled global climate model G. Narváez-Campo & C. Ardilouze 10.5194/hess-29-4739-2025
- Interconnected hydrologic extreme drivers and impacts depicted by remote sensing data assimilation T. Lahmers et al. 10.1038/s41598-023-30484-4
- Bias-blind and bias-aware assimilation of leaf area index into the Noah-MP land surface model over Europe S. Scherrer et al. 10.5194/hess-27-4087-2023
- The International Soil Moisture Network: serving Earth system science for over a decade W. Dorigo et al. 10.5194/hess-25-5749-2021
- From Monitoring to Forecasting Land Surface Conditions Using a Land Data Assimilation System: Application over the Contiguous United States A. Mucia et al. 10.3390/rs12122020
25 citations as recorded by crossref.
- Sensitivity of Surface Fluxes in the ECMWF Land Surface Model to the Remotely Sensed Leaf Area Index and Root Distribution: Evaluation with Tower Flux Data D. Stevens et al. 10.3390/atmos11121362
- Simulating carbon and water fluxes using a coupled process-based terrestrial biosphere model and joint assimilation of leaf area index and surface soil moisture S. Li et al. 10.5194/hess-26-6311-2022
- The joint assimilation of satellite observed LAI and soil moisture for the global root zone soil moisture production and its impact on land surface and ecosystem variables Y. Xu et al. 10.1016/j.agrformet.2024.110299
- Assimilation of passive microwave vegetation optical depth in LDAS-Monde: a case study over the continental USA A. Mucia et al. 10.5194/bg-19-2557-2022
- Estimation of 100 m root zone soil moisture by downscaling 1 km soil water index with machine learning and multiple geodata T. Mahmood et al. 10.1007/s10661-024-12969-5
- A comprehensive evaluation of satellite-based and reanalysis soil moisture products over the upper Blue Nile Basin, Ethiopia A. Alaminie et al. 10.1016/j.srs.2024.100173
- 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
- Deep desiccation of soils observed by long-term high-resolution measurements on a large inclined lysimeter M. Merk et al. 10.5194/hess-25-3519-2021
- The Impact of Spatial Dynamic Error on the Assimilation of Soil Moisture Retrieval Products X. Bai et al. 10.3390/rs17020239
- A comprehensive country-based day-ahead wind power generation forecast model by coupling numerical weather prediction data and CatBoost with feature selection methods for Turkey C. Özen & A. Deniz 10.1177/0309524X221078536
- Assimilating ASCAT normalized backscatter and slope into the land surface model ISBA-A-gs using a Deep Neural Network as the observation operator: Case studies at ISMN stations in western Europe X. Shan et al. 10.1016/j.rse.2024.114167
- Assimilation of ASCAT Radar Backscatter Coefficients over Southwestern France T. Corchia et al. 10.3390/rs15174258
- Cross-ECV consistency at global scale: LAI and FAPAR changes B. Mota et al. 10.1016/j.rse.2021.112561
- The Joint Assimilation of Remotely Sensed Leaf Area Index and Surface Soil Moisture into a Land Surface Model A. Rahman et al. 10.3390/rs14030437
- Assimilation of Leaf Area Index and Soil Water Index from Satellite Observations in a Land Surface Model in Hungary H. Tóth & B. Szintai 10.3390/atmos12080944
- Soil Moisture Monitoring at Kilometer Scale: Assimilation of Sentinel-1 Products in ISBA O. Rojas-Munoz et al. 10.3390/rs15174329
- Impact of leaf area index assimilation and gauge-corrected precipitation on land surface variables in LDAS-Monde: a case study over China E. Liu et al. 10.1016/j.jhydrol.2025.133304
- Multiscale Assimilation of Sentinel and Landsat Data for Soil Moisture and Leaf Area Index Predictions Using an Ensemble-Kalman-Filter-Based Assimilation Approach in a Heterogeneous Ecosystem N. Montaldo et al. 10.3390/rs14143458
- Catchment Functioning Under Prolonged Drought Stress: Tracer‐Aided Ecohydrological Modeling in an Intensively Managed Agricultural Catchment X. Yang et al. 10.1029/2020WR029094
- High-resolution data assimilation for two maritime extreme weather events: a comparison between 3D-Var and EnKF D. Carrió et al. 10.5194/nhess-25-2999-2025
- Global Assimilation of Remotely Sensed Leaf Area Index: The Impact of Updating More State Variables Within a Land Surface Model A. Rahman et al. 10.3389/frwa.2021.789352
- Skilful seasonal streamflow forecasting using a fully coupled global climate model G. Narváez-Campo & C. Ardilouze 10.5194/hess-29-4739-2025
- Interconnected hydrologic extreme drivers and impacts depicted by remote sensing data assimilation T. Lahmers et al. 10.1038/s41598-023-30484-4
- Bias-blind and bias-aware assimilation of leaf area index into the Noah-MP land surface model over Europe S. Scherrer et al. 10.5194/hess-27-4087-2023
- The International Soil Moisture Network: serving Earth system science for over a decade W. Dorigo et al. 10.5194/hess-25-5749-2021
Latest update: 13 Oct 2025
Short summary
LDAS-Monde is a global offline land data assimilation system (LDAS) that jointly assimilates satellite-derived observations of surface soil moisture (SSM) and leaf area index (LAI) into the ISBA (Interaction between Soil Biosphere and Atmosphere) land surface model (LSM). This study demonstrates that LDAS-Monde is able to detect, monitor and forecast the impact of extreme weather on land surface states.
LDAS-Monde is a global offline land data assimilation system (LDAS) that jointly assimilates...
