Articles | Volume 15, issue 6
https://doi.org/10.5194/tc-15-2969-2021
© 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/tc-15-2969-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
28 Jun 2021
Research article |
| 28 Jun 2021
| 28 Jun 2021
Impact of dynamic snow density on GlobSnow snow water equivalent retrieval accuracy
Finnish Meteorological Institute, P.O. Box 503, 00101 Helsinki,
Finland
Kari Luojus
Finnish Meteorological Institute, P.O. Box 503, 00101 Helsinki,
Finland
Juha Lemmetyinen
Finnish Meteorological Institute, P.O. Box 503, 00101 Helsinki,
Finland
Jouni Pulliainen
Finnish Meteorological Institute, P.O. Box 503, 00101 Helsinki,
Finland
Mikko Moisander
Finnish Meteorological Institute, P.O. Box 503, 00101 Helsinki,
Finland
Matias Takala
Finnish Meteorological Institute, P.O. Box 503, 00101 Helsinki,
Finland
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Cited
22 citations as recorded by crossref.
- Comparison of Machine Learning-Based Snow Depth Estimates and Development of a New Operational Retrieval Algorithm over China J. Yang et al. 10.3390/rs14122800
- Physical Modeling and Compensation for Systematic Negative Errors in GNSS-R Snow Depth Retrieval Z. Zhang et al. 10.1109/TGRS.2023.3260808
- Retrieval of ground, snow, and forest parameters from space borne passive L band observations. A case study over Sodankylä, Finland M. Holmberg et al. 10.1016/j.rse.2024.114143
- Global Sensitivity Analysis of the MEMLS Model for Retrieving Snow Water Equivalent S. Gao et al. 10.1109/TGRS.2021.3134695
- Last Glacial Maximum and early deglaciation in the Stura Valley, southwestern European Alps A. Ribolini et al. 10.1016/j.quascirev.2022.107770
- A novel global snow depth retrieval method considering snow metamorphism and forest influence S. Gao et al. 10.1016/j.rse.2023.113712
- Canadian historical Snow Water Equivalent dataset (CanSWE, 1928–2020) V. Vionnet et al. 10.5194/essd-13-4603-2021
- Revisiting the Global Seasonal Snow Classification: An Updated Dataset for Earth System Applications M. Sturm & G. Liston 10.1175/JHM-D-21-0070.1
- Spatial and temporal variability in snow density across the Northern Hemisphere W. Zhao et al. 10.1016/j.catena.2023.107445
- Moderate-resolution snow depth product retrieval from passive microwave brightness data over Xinjiang using machine learning approach Y. Liu et al. 10.1080/17538947.2023.2299208
- A Meteorology and Snow Data Set From Adjacent Forested and Meadow Sites at Crested Butte, CO, USA H. Bonner et al. 10.1029/2022WR033006
- A long-term daily gridded snow depth dataset for the Northern Hemisphere from 1980 to 2019 based on machine learning Y. Hu et al. 10.1080/20964471.2023.2177435
- Benchmarking algorithm changes to the Snow CCI+ snow water equivalent product C. Mortimer et al. 10.1016/j.rse.2022.112988
- Why Do CMIP6 Models Fail to Simulate Snow Depth in Terms of Temporal Change and High Mountain Snow of China Skillfully? H. Zhang et al. 10.1029/2022GL098888
- Implementing spatially and temporally varying snow densities into the GlobSnow snow water equivalent retrieval P. Venäläinen et al. 10.5194/tc-17-719-2023
- Snow Density Retrieval in Quebec Using Space-Borne SMOS Observations X. Gao et al. 10.3390/rs15082065
- Spatio-Temporal Characteristics and Differences in Snow Density between the Tibet Plateau and the Arctic W. Zhao et al. 10.3390/rs15163976
- Evaluation of passive microwave dry snow detection algorithms and application to SWE retrieval during seasonal snow accumulation L. Zschenderlein et al. 10.1016/j.rse.2023.113476
- Snow Cover and Climate Change and Their Coupling Effects on Runoff in the Keriya River Basin during 2001–2020 W. Yan et al. 10.3390/rs15133435
- Snow Water Equivalent Monitoring—A Review of Large-Scale Remote Sensing Applications S. Schilling et al. 10.3390/rs16061085
- Validation of EUMETSAT H-SAF space-born snow water equivalent product (H13) for the 2020-2021 snow year over Turkey S. KUTER et al. 10.53516/ajfr.1145662
- Investigation of Environmental Effects on Coherence Loss in SAR Interferometry for Snow Water Equivalent Retrieval J. Ruiz et al. 10.1109/TGRS.2022.3223760
22 citations as recorded by crossref.
- Comparison of Machine Learning-Based Snow Depth Estimates and Development of a New Operational Retrieval Algorithm over China J. Yang et al. 10.3390/rs14122800
- Physical Modeling and Compensation for Systematic Negative Errors in GNSS-R Snow Depth Retrieval Z. Zhang et al. 10.1109/TGRS.2023.3260808
- Retrieval of ground, snow, and forest parameters from space borne passive L band observations. A case study over Sodankylä, Finland M. Holmberg et al. 10.1016/j.rse.2024.114143
- Global Sensitivity Analysis of the MEMLS Model for Retrieving Snow Water Equivalent S. Gao et al. 10.1109/TGRS.2021.3134695
- Last Glacial Maximum and early deglaciation in the Stura Valley, southwestern European Alps A. Ribolini et al. 10.1016/j.quascirev.2022.107770
- A novel global snow depth retrieval method considering snow metamorphism and forest influence S. Gao et al. 10.1016/j.rse.2023.113712
- Canadian historical Snow Water Equivalent dataset (CanSWE, 1928–2020) V. Vionnet et al. 10.5194/essd-13-4603-2021
- Revisiting the Global Seasonal Snow Classification: An Updated Dataset for Earth System Applications M. Sturm & G. Liston 10.1175/JHM-D-21-0070.1
- Spatial and temporal variability in snow density across the Northern Hemisphere W. Zhao et al. 10.1016/j.catena.2023.107445
- Moderate-resolution snow depth product retrieval from passive microwave brightness data over Xinjiang using machine learning approach Y. Liu et al. 10.1080/17538947.2023.2299208
- A Meteorology and Snow Data Set From Adjacent Forested and Meadow Sites at Crested Butte, CO, USA H. Bonner et al. 10.1029/2022WR033006
- A long-term daily gridded snow depth dataset for the Northern Hemisphere from 1980 to 2019 based on machine learning Y. Hu et al. 10.1080/20964471.2023.2177435
- Benchmarking algorithm changes to the Snow CCI+ snow water equivalent product C. Mortimer et al. 10.1016/j.rse.2022.112988
- Why Do CMIP6 Models Fail to Simulate Snow Depth in Terms of Temporal Change and High Mountain Snow of China Skillfully? H. Zhang et al. 10.1029/2022GL098888
- Implementing spatially and temporally varying snow densities into the GlobSnow snow water equivalent retrieval P. Venäläinen et al. 10.5194/tc-17-719-2023
- Snow Density Retrieval in Quebec Using Space-Borne SMOS Observations X. Gao et al. 10.3390/rs15082065
- Spatio-Temporal Characteristics and Differences in Snow Density between the Tibet Plateau and the Arctic W. Zhao et al. 10.3390/rs15163976
- Evaluation of passive microwave dry snow detection algorithms and application to SWE retrieval during seasonal snow accumulation L. Zschenderlein et al. 10.1016/j.rse.2023.113476
- Snow Cover and Climate Change and Their Coupling Effects on Runoff in the Keriya River Basin during 2001–2020 W. Yan et al. 10.3390/rs15133435
- Snow Water Equivalent Monitoring—A Review of Large-Scale Remote Sensing Applications S. Schilling et al. 10.3390/rs16061085
- Validation of EUMETSAT H-SAF space-born snow water equivalent product (H13) for the 2020-2021 snow year over Turkey S. KUTER et al. 10.53516/ajfr.1145662
- Investigation of Environmental Effects on Coherence Loss in SAR Interferometry for Snow Water Equivalent Retrieval J. Ruiz et al. 10.1109/TGRS.2022.3223760
Latest update: 23 Nov 2024
Short summary
Information about snow water equivalent (SWE) is needed in many applications, including climate model evaluation and forecasting fresh water availability. Space-borne radiometer observations combined with ground snow depth measurements can be used to make global estimates of SWE. In this study, we investigate the possibility of using sparse snow density measurement in satellite-based SWE retrieval and show that using the snow density information in post-processing improves SWE estimations.
Information about snow water equivalent (SWE) is needed in many applications, including climate...
