EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

NH-SWE: A new Northern Hemisphere Snow Water Equivalent dataset based on in-situ snow depth time series (1950-2022)

Adrià Fontrodona-Bach1, Bettina Schaefli2, Ross Woods3, Ryan Teuling4, and Josh Larsen2
Adrià Fontrodona-Bach et al.
  • 1University of Birmingham, School of Geography, Earth and Environmental Sciences, Birmingham, United Kingdom of Great Britain – England, Scotland, Wales (
  • 2Institute of Geography and Oeschger Centre for Climate Change Research, University of Bern, Switzerland
  • 3Department of Civil Engineering , University of Bristol, UK
  • 4Hydrology and Quantitative Water Management group , Wageningen University, The Netherlands

Ground-based observation datasets of Snow Water Equivalent (SWE) are scarce. In contrast, numerous long-term and good quality ground observations of snow depth are available. Furthermore, an increasing number of models can accurately convert snow depth to SWE. We present a novel dataset of SWE time series over the Northern Hemisphere based on in-situ observations of snow depth. We convert snow depth to SWE using the DeltaSNOW model and we present a method to generalise the conversion model for global use. We calibrate the model over a wide range of climates with the SNOTEL dataset and we regionalise the model parameters based on climate variables. We evaluate this approach on independent datasets such as the Canadian SWE dataset and other European SWE datasets. The key strengths of the modelling approach and the SWE dataset are the excellent performance of peak SWE and timing of snowmelt season onset. The final SWE dataset contains 11,003 stations with daily SWE and snow density time series distributed across the Northern Hemisphere, including mountain regions, at the point scale, and spanning the period 1950-2022. The dataset is available and free to access. It can be used for a variety of applications including validation of remote sensing of snow, hydrological modelling, water resources assessment and climate change impact analyses.

How to cite: Fontrodona-Bach, A., Schaefli, B., Woods, R., Teuling, R., and Larsen, J.: NH-SWE: A new Northern Hemisphere Snow Water Equivalent dataset based on in-situ snow depth time series (1950-2022), EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-12620,, 2023.

Supplementary materials

Supplementary material file