Articles | Volume 22, issue 11
https://doi.org/10.5194/hess-22-5711-2018
© 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-22-5711-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
05 Nov 2018
Research article |
| 05 Nov 2018
| 05 Nov 2018
Assimilation of passive microwave AMSR-2 satellite observations in a snowpack evolution model over northeastern Canada
Fanny Larue
CORRESPONDING AUTHOR
CARTEL, Université de Sherbrooke, Québec, Canada
Centre d'Études Nordiques, Québec, Canada
IREQ, Hydro-Québec, Québec, Canada
Alain Royer
CARTEL, Université de Sherbrooke, Québec, Canada
Centre d'Études Nordiques, Québec, Canada
Danielle De Sève
IREQ, Hydro-Québec, Québec, Canada
Alexandre Roy
CARTEL, Université de Sherbrooke, Québec, Canada
Centre d'Études Nordiques, Québec, Canada
Département de Géographie, Université de Montréal,
Québec, Canada
now at: Université du Québec à Trois-Rivière,
Québec, Canada
Emmanuel Cosme
Institut des Géosciences de l'Environnement, IGE, UGA-CNRS, Grenoble,
France
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Cited
26 citations as recorded by crossref.
- Review article: Global monitoring of snow water equivalent using high-frequency radar remote sensing L. Tsang et al. https://doi.org/10.5194/tc-16-3531-2022
- Assimilation of synthetic observations of radar backscatters at Ku-band improves SWE estimates N. Leroux et al. https://doi.org/10.5194/tc-20-2773-2026
- Estimating Terrestrial Snow Mass via Multi‐Sensor Assimilation of Synthetic AMSR‐E Brightness Temperature Spectral Differences and Synthetic GRACE Terrestrial Water Storage Retrievals J. Wang et al. https://doi.org/10.1029/2021WR029880
- Assimilation of airborne gamma observations provides utility for snow estimation in forested environments E. Cho et al. https://doi.org/10.5194/hess-27-4039-2023
- Exploring the Utility of Machine Learning-Based Passive Microwave Brightness Temperature Data Assimilation over Terrestrial Snow in High Mountain Asia Y. Kwon et al. https://doi.org/10.3390/rs11192265
- Characterizing tundra snow sub-pixel variability to improve brightness temperature estimation in satellite SWE retrievals J. Meloche et al. https://doi.org/10.5194/tc-16-87-2022
- Toward Snow Cover Estimation in Mountainous Areas Using Modern Data Assimilation Methods: A Review C. Largeron et al. https://doi.org/10.3389/feart.2020.00325
- Spatiotemporal Variation of Snow Depth in the Northern Hemisphere from 1992 to 2016 X. Xiao et al. https://doi.org/10.3390/rs12172728
- Improving the Snow Volume Scattering Algorithm in a Microwave Forward Model by Using Ground-Based Remote Sensing Snow Observations L. Dai et al. https://doi.org/10.1109/TGRS.2021.3064309
- Development of a Snow Depth Estimation Algorithm over China for the FY-3D/MWRI J. Yang et al. https://doi.org/10.3390/rs11080977
- Improved Estimation of O-B Bias and Standard Deviation by an RFI Restoration Method for AMSR-2 C-Band Observations over North America W. Shen et al. https://doi.org/10.3390/rs14215558
- Review of snow water equivalent retrieval methods using spaceborne passive microwave radiometry N. Saberi et al. https://doi.org/10.1080/01431161.2019.1654144
- CrocO_v1.0: a particle filter to assimilate snowpack observations in a spatialised framework B. Cluzet et al. https://doi.org/10.5194/gmd-14-1595-2021
- Exploration of Synthetic Terrestrial Snow Mass Estimation via Assimilation of AMSR‐E Brightness Temperature Spectral Differences Using the Catchment Land Surface Model and Support Vector Machine Regression J. Wang et al. https://doi.org/10.1029/2020WR027490
- Propagating information from snow observations with CrocO ensemble data assimilation system: a 10-years case study over a snow depth observation network B. Cluzet et al. https://doi.org/10.5194/tc-16-1281-2022
- Estimating alpine snow depth by combining multifrequency passive radiance observations with ensemble snowpack modeling R. Kim et al. https://doi.org/10.1016/j.rse.2019.03.016
- Snow Water Equivalent Monitoring—A Review of Large-Scale Remote Sensing Applications S. Schilling et al. https://doi.org/10.3390/rs16061085
- Large-scale snow data assimilation using a spatialized particle filter: recovering the spatial structure of the particles J. Odry et al. https://doi.org/10.5194/tc-16-3489-2022
- Assimilation of surface reflectance in snow simulations: Impact on bulk snow variables J. Revuelto et al. https://doi.org/10.1016/j.jhydrol.2021.126966
- Reviews and syntheses: Recent advances in microwave remote sensing in support of terrestrial carbon cycle science in Arctic–boreal regions A. Mavrovic et al. https://doi.org/10.5194/bg-20-2941-2023
- Remote Sensing of Environmental Changes in Cold Regions: Methods, Achievements and Challenges J. Du et al. https://doi.org/10.3390/rs11161952
- Analyzing satellite and airborne Ka-band passive microwave observations over land for temperature and vegetation monitoring R. de Jeu et al. https://doi.org/10.3389/frsen.2025.1574072
- Perspective on satellite-based land data assimilation to estimate water cycle components in an era of advanced data availability and model sophistication G. De Lannoy et al. https://doi.org/10.3389/frwa.2022.981745
- Enhancing simulations of snowpack properties in land surface models with the Soil, Vegetation and Snow scheme v2.0 (SVS2) V. Vionnet et al. https://doi.org/10.5194/gmd-18-9119-2025
- Improving snow depth simulations on Arctic Sea ice by assimilating a passive microwave-derived record H. Li et al. https://doi.org/10.1016/j.coldregions.2023.103929
- Estimation of Snow Mass Information via Assimilation of C-Band Synthetic Aperture Radar Backscatter Observations Into an Advanced Land Surface Model J. Park et al. https://doi.org/10.1109/JSTARS.2021.3133513
26 citations as recorded by crossref.
- Review article: Global monitoring of snow water equivalent using high-frequency radar remote sensing L. Tsang et al. https://doi.org/10.5194/tc-16-3531-2022
- Assimilation of synthetic observations of radar backscatters at Ku-band improves SWE estimates N. Leroux et al. https://doi.org/10.5194/tc-20-2773-2026
- Estimating Terrestrial Snow Mass via Multi‐Sensor Assimilation of Synthetic AMSR‐E Brightness Temperature Spectral Differences and Synthetic GRACE Terrestrial Water Storage Retrievals J. Wang et al. https://doi.org/10.1029/2021WR029880
- Assimilation of airborne gamma observations provides utility for snow estimation in forested environments E. Cho et al. https://doi.org/10.5194/hess-27-4039-2023
- Exploring the Utility of Machine Learning-Based Passive Microwave Brightness Temperature Data Assimilation over Terrestrial Snow in High Mountain Asia Y. Kwon et al. https://doi.org/10.3390/rs11192265
- Characterizing tundra snow sub-pixel variability to improve brightness temperature estimation in satellite SWE retrievals J. Meloche et al. https://doi.org/10.5194/tc-16-87-2022
- Toward Snow Cover Estimation in Mountainous Areas Using Modern Data Assimilation Methods: A Review C. Largeron et al. https://doi.org/10.3389/feart.2020.00325
- Spatiotemporal Variation of Snow Depth in the Northern Hemisphere from 1992 to 2016 X. Xiao et al. https://doi.org/10.3390/rs12172728
- Improving the Snow Volume Scattering Algorithm in a Microwave Forward Model by Using Ground-Based Remote Sensing Snow Observations L. Dai et al. https://doi.org/10.1109/TGRS.2021.3064309
- Development of a Snow Depth Estimation Algorithm over China for the FY-3D/MWRI J. Yang et al. https://doi.org/10.3390/rs11080977
- Improved Estimation of O-B Bias and Standard Deviation by an RFI Restoration Method for AMSR-2 C-Band Observations over North America W. Shen et al. https://doi.org/10.3390/rs14215558
- Review of snow water equivalent retrieval methods using spaceborne passive microwave radiometry N. Saberi et al. https://doi.org/10.1080/01431161.2019.1654144
- CrocO_v1.0: a particle filter to assimilate snowpack observations in a spatialised framework B. Cluzet et al. https://doi.org/10.5194/gmd-14-1595-2021
- Exploration of Synthetic Terrestrial Snow Mass Estimation via Assimilation of AMSR‐E Brightness Temperature Spectral Differences Using the Catchment Land Surface Model and Support Vector Machine Regression J. Wang et al. https://doi.org/10.1029/2020WR027490
- Propagating information from snow observations with CrocO ensemble data assimilation system: a 10-years case study over a snow depth observation network B. Cluzet et al. https://doi.org/10.5194/tc-16-1281-2022
- Estimating alpine snow depth by combining multifrequency passive radiance observations with ensemble snowpack modeling R. Kim et al. https://doi.org/10.1016/j.rse.2019.03.016
- Snow Water Equivalent Monitoring—A Review of Large-Scale Remote Sensing Applications S. Schilling et al. https://doi.org/10.3390/rs16061085
- Large-scale snow data assimilation using a spatialized particle filter: recovering the spatial structure of the particles J. Odry et al. https://doi.org/10.5194/tc-16-3489-2022
- Assimilation of surface reflectance in snow simulations: Impact on bulk snow variables J. Revuelto et al. https://doi.org/10.1016/j.jhydrol.2021.126966
- Reviews and syntheses: Recent advances in microwave remote sensing in support of terrestrial carbon cycle science in Arctic–boreal regions A. Mavrovic et al. https://doi.org/10.5194/bg-20-2941-2023
- Remote Sensing of Environmental Changes in Cold Regions: Methods, Achievements and Challenges J. Du et al. https://doi.org/10.3390/rs11161952
- Analyzing satellite and airborne Ka-band passive microwave observations over land for temperature and vegetation monitoring R. de Jeu et al. https://doi.org/10.3389/frsen.2025.1574072
- Perspective on satellite-based land data assimilation to estimate water cycle components in an era of advanced data availability and model sophistication G. De Lannoy et al. https://doi.org/10.3389/frwa.2022.981745
- Enhancing simulations of snowpack properties in land surface models with the Soil, Vegetation and Snow scheme v2.0 (SVS2) V. Vionnet et al. https://doi.org/10.5194/gmd-18-9119-2025
- Improving snow depth simulations on Arctic Sea ice by assimilating a passive microwave-derived record H. Li et al. https://doi.org/10.1016/j.coldregions.2023.103929
- Estimation of Snow Mass Information via Assimilation of C-Band Synthetic Aperture Radar Backscatter Observations Into an Advanced Land Surface Model J. Park et al. https://doi.org/10.1109/JSTARS.2021.3133513
Saved (final revised paper)
Latest update: 09 Jun 2026
Short summary
A data assimilation scheme was developed to improve snow water equivalent (SWE) simulations by updating meteorological forcings and snowpack states using passive microwave satellite observations. A chain of models was first calibrated to simulate satellite observations over northeastern Canada. The assimilation was then validated over 12 stations where daily SWE measurements were acquired during 4 winters (2012–2016). The overall SWE bias is reduced by 68 % compared to original SWE simulations.
A data assimilation scheme was developed to improve snow water equivalent (SWE) simulations by...
