Articles | Volume 19, issue 1
https://doi.org/10.5194/tc-19-201-2025
© Author(s) 2025. 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-19-201-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
17 Jan 2025
Research article |
| 17 Jan 2025
| 17 Jan 2025
Benchmarking of snow water equivalent (SWE) products based on outcomes of the SnowPEx+ Intercomparison Project
Climate Research Division, Environment and Climate Change Canada, Toronto, M3H 5T4, Canada
Colleen Mortimer
Climate Research Division, Environment and Climate Change Canada, Toronto, M3H 5T4, Canada
Chris Derksen
Climate Research Division, Environment and Climate Change Canada, Toronto, M3H 5T4, Canada
Aleksandra Elias Chereque
Department of Physics, University of Toronto, Toronto, M5S 1A7, Canada
Paul Kushner
Department of Physics, University of Toronto, Toronto, M5S 1A7, Canada
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Cited
21 citations as recorded by crossref.
- New insights from the bias-corrected simulations of CMIP6 in Northern Hemisphere’s snow drought Y. Hu et al. https://doi.org/10.1038/s43247-026-03187-7
- Applying U-Net for Estimating AVHRR-Based Snow Cover Fraction (ESA CCI+ Snow) During Cloud Cover and Polar Night in Scandinavia F. Jakob et al. https://doi.org/10.3390/rs18122030
- Impact of topography and meteorological forcing on snow simulation in the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) L. Wang et al. https://doi.org/10.5194/gmd-18-6597-2025
- Bias-adjusted projections of snow cover over eastern Canada using an ensemble of regional climate models É. Bresson et al. https://doi.org/10.5194/tc-20-333-2026
- Creeping snow drought threatens Canada’s water supply R. Sarpong et al. https://doi.org/10.1038/s43247-025-03162-8
- Insights into the North Hemisphere daily snowpack at high resolution from the new Crocus–ERA5 product S. Ramos Buarque et al. https://doi.org/10.5194/essd-17-7227-2025
- Interpreting Global Terrestrial Water Storage Dynamics and Drivers with Explainable Deep Learning H. Huang et al. https://doi.org/10.3390/rs17132118
- Can streamflow observations constrain snow mass reconstructions? Lessons from two synthetic numerical experiments P. Wiersma et al. https://doi.org/10.5194/hess-30-3331-2026
- Regional frequency analysis, bias correction and downscaling of ERA5-Land snow related variables S. Fontana et al. https://doi.org/10.1016/j.wace.2026.100922
- Northern Hemisphere in situ snow water equivalent dataset (NorSWE, 1979–2021) C. Mortimer & V. Vionnet https://doi.org/10.5194/essd-17-3619-2025
- Localized positive snow water equivalent anomalies in the Hindu Kush Himalaya under 1.5–5.0 °C warming levels Z. Zuo et al. https://doi.org/10.1016/j.accre.2026.06.019
- Estimating Snow-Related Daily Change Events in the Canadian Winter Season: A Deep Learning-Based Approach K. Malik et al. https://doi.org/10.3390/jimaging11070239
- Global 0.25-degree gridded Snow water equivalent data derived from machine learning using in-situ measurements J. Seo et al. https://doi.org/10.1038/s41597-026-06895-z
- Determining the cause of inconsistent onset-season trends in the Northern Hemisphere snow cover extent record A. Elias Chereque et al. https://doi.org/10.1126/sciadv.adv7926
- Hybrid approach for estimating snow water equivalent in Siberian basins using GRACE and climate data H. Mohasseb & S. Yi https://doi.org/10.1016/j.jhydrol.2026.135483
- Evaluating a hierarchy of bias correction methods for ERA5-Land SWE across Canada N. Kanda & C. Fletcher https://doi.org/10.1088/2515-7620/aded5a
- Assessment of snow water equivalent characteristics in time and space over the Mackenzie River basin M. Soltani et al. https://doi.org/10.1080/07011784.2026.2616002
- CAMELS-FI: hydrometeorological time series and landscape properties for 320 catchments in Finland I. Seppä et al. https://doi.org/10.5194/essd-18-4745-2026
- Hyper-resolution large-scale hydrological modelling benefits from improved process representation in mountain regions J. Janzing et al. https://doi.org/10.5194/hess-29-7041-2025
- Identification and correction of snow depth bias in ERA5 datasets over Central Europe using machine learning G. Stachura & Z. Ustrnul https://doi.org/10.5194/tc-20-2295-2026
- Possibility of SWE estimation from snow cover extent using the dynamic non-Gaussian snow depletion curve N. Ohara & R. Perdigão https://doi.org/10.1016/j.jhydrol.2026.135981
21 citations as recorded by crossref.
- New insights from the bias-corrected simulations of CMIP6 in Northern Hemisphere’s snow drought Y. Hu et al. https://doi.org/10.1038/s43247-026-03187-7
- Applying U-Net for Estimating AVHRR-Based Snow Cover Fraction (ESA CCI+ Snow) During Cloud Cover and Polar Night in Scandinavia F. Jakob et al. https://doi.org/10.3390/rs18122030
- Impact of topography and meteorological forcing on snow simulation in the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) L. Wang et al. https://doi.org/10.5194/gmd-18-6597-2025
- Bias-adjusted projections of snow cover over eastern Canada using an ensemble of regional climate models É. Bresson et al. https://doi.org/10.5194/tc-20-333-2026
- Creeping snow drought threatens Canada’s water supply R. Sarpong et al. https://doi.org/10.1038/s43247-025-03162-8
- Insights into the North Hemisphere daily snowpack at high resolution from the new Crocus–ERA5 product S. Ramos Buarque et al. https://doi.org/10.5194/essd-17-7227-2025
- Interpreting Global Terrestrial Water Storage Dynamics and Drivers with Explainable Deep Learning H. Huang et al. https://doi.org/10.3390/rs17132118
- Can streamflow observations constrain snow mass reconstructions? Lessons from two synthetic numerical experiments P. Wiersma et al. https://doi.org/10.5194/hess-30-3331-2026
- Regional frequency analysis, bias correction and downscaling of ERA5-Land snow related variables S. Fontana et al. https://doi.org/10.1016/j.wace.2026.100922
- Northern Hemisphere in situ snow water equivalent dataset (NorSWE, 1979–2021) C. Mortimer & V. Vionnet https://doi.org/10.5194/essd-17-3619-2025
- Localized positive snow water equivalent anomalies in the Hindu Kush Himalaya under 1.5–5.0 °C warming levels Z. Zuo et al. https://doi.org/10.1016/j.accre.2026.06.019
- Estimating Snow-Related Daily Change Events in the Canadian Winter Season: A Deep Learning-Based Approach K. Malik et al. https://doi.org/10.3390/jimaging11070239
- Global 0.25-degree gridded Snow water equivalent data derived from machine learning using in-situ measurements J. Seo et al. https://doi.org/10.1038/s41597-026-06895-z
- Determining the cause of inconsistent onset-season trends in the Northern Hemisphere snow cover extent record A. Elias Chereque et al. https://doi.org/10.1126/sciadv.adv7926
- Hybrid approach for estimating snow water equivalent in Siberian basins using GRACE and climate data H. Mohasseb & S. Yi https://doi.org/10.1016/j.jhydrol.2026.135483
- Evaluating a hierarchy of bias correction methods for ERA5-Land SWE across Canada N. Kanda & C. Fletcher https://doi.org/10.1088/2515-7620/aded5a
- Assessment of snow water equivalent characteristics in time and space over the Mackenzie River basin M. Soltani et al. https://doi.org/10.1080/07011784.2026.2616002
- CAMELS-FI: hydrometeorological time series and landscape properties for 320 catchments in Finland I. Seppä et al. https://doi.org/10.5194/essd-18-4745-2026
- Hyper-resolution large-scale hydrological modelling benefits from improved process representation in mountain regions J. Janzing et al. https://doi.org/10.5194/hess-29-7041-2025
- Identification and correction of snow depth bias in ERA5 datasets over Central Europe using machine learning G. Stachura & Z. Ustrnul https://doi.org/10.5194/tc-20-2295-2026
- Possibility of SWE estimation from snow cover extent using the dynamic non-Gaussian snow depletion curve N. Ohara & R. Perdigão https://doi.org/10.1016/j.jhydrol.2026.135981
Saved (final revised paper)
Latest update: 21 Jul 2026
Short summary
We evaluate and rank 23 different datasets on their ability to accurately estimate historical snow amounts. The evaluation uses new a set of surface snow measurements with improved spatial coverage, enabling evaluation across both mountainous and nonmountainous regions. Performance measures vary tremendously across the products: while most perform reasonably in nonmountainous regions, accurate representation of snow amounts in mountainous regions and of historical trends is much more variable.
We evaluate and rank 23 different datasets on their ability to accurately estimate historical...
