Preprints
https://doi.org/10.5194/egusphere-2024-869
https://doi.org/10.5194/egusphere-2024-869
13 May 2024
 | 13 May 2024
Status: this preprint is open for discussion.

Snow depth derived from Sentinel-1 compared to in-situ observations in northern Finland

Adriano Lemos and Aku Riihelä

Abstract. Seasonal snow in the northern regions plays an important role providing water resources for both consumption and hydropower generation. Moreover, the snow changes in northern Finland during winter impact the local agriculture, vegetation, tourism and recreational activities. In this study we estimated snow depth using an empirical methodology applied to the dual-polarisation of the Sentinel-1 synthetic aperture radar (SAR) images and compared with in situ measurements collected by automatic weather stations (AWS) in northern Finland. We applied an adapted version of the empirical methodology developed by Lievens et al. (2019) to retrieve snow depth, using Sentinel-1 constellation between 2019 and 2022, and then compared to measurements from three automatic weather stations available over the same period. Overall, the Sentinel-1 snow depth retrievals were underestimated in comparison with the in-situ measurements from the automatic weather stations. We found slightly different patterns for the different years, and an overall correlation factor of 0.41, and a higher correlation in the 2020–2021 season (R=0.52). The high correlation between estimated and measured snow depth at the Inari Nellim location (R=0.81) reinforces the potential ability to derive snow changes in regions where in situ measurements of snow are currently lacking. Further investigation is still necessary to better understand how the physical properties of the snowpack influence the backscatter response over shallow snow regions.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Adriano Lemos and Aku Riihelä

Status: open (until 24 Jun 2024)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
Adriano Lemos and Aku Riihelä
Adriano Lemos and Aku Riihelä

Viewed

Total article views: 167 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
114 48 5 167 12 2 2
  • HTML: 114
  • PDF: 48
  • XML: 5
  • Total: 167
  • Supplement: 12
  • BibTeX: 2
  • EndNote: 2
Views and downloads (calculated since 13 May 2024)
Cumulative views and downloads (calculated since 13 May 2024)

Viewed (geographical distribution)

Total article views: 165 (including HTML, PDF, and XML) Thereof 165 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 19 May 2024
Download
Short summary
Here we used satellite imagery to measure snow depth in northern Finland and compared to on-site weather stations from 2019–2022. We correlated snow depths and vegetation coverage, and found thicker snow over non-vegetated areas and frozen water bodies due to the satellite's sensitivity. Our estimates showed underestimated results of snow depth and need further investigation, but they highlight the potential in monitoring seasonal snow changes, particularly where direct measurements are lacking.