Articles | Volume 18, issue 8
https://doi.org/10.5194/essd-18-5871-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-18-5871-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
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14 Aug 2026
Data description article | Highlight paper |
| 14 Aug 2026
| 14 Aug 2026
A global high-resolution dataset of snowmelt runoff onset timing from Sentinel-1 SAR, 2015–2024
Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195, USA
David Shean
Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195, USA
Scott Henderson
Department of Earth and Space Sciences, University of Washington, Seattle, WA 98195, USA
eScience Institute, University of Washington, Seattle, WA 98195, USA
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Editorial statement
This paper presents a global, high-resolution dataset of snowmelt runoff onset spanning a decade of Sentinel-1 observations. Its combination of global coverage, fine spatial resolution, comprehensive documentation, and broad applicability makes it a valuable resource for hydrology, cryosphere research, and water resource management.
This paper presents a global, high-resolution dataset of snowmelt runoff onset spanning a decade...
Short summary
Meltwater from seasonal snow sustains over a billion people globally, making the timing of snowmelt runoff onset a critical hydrological parameter. We used satellite radar images, which can detect liquid water in snowpack regardless of cloud cover, to create a global dataset of snowmelt runoff onset timing from 2015 to 2024 at 80 m resolution. The dataset shows close agreement with a network of ground-based snow sensors, and can support water resource management in snow-dominated watersheds.
Meltwater from seasonal snow sustains over a billion people globally, making the timing of...
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