Distributed sub-canopy datasets from mobile multi-sensor platforms (CH / FIN, 2018-2019) for hyper-resolution forest snow model evaluation

This dataset contains datasets of sub-canopy meteorological variables acquired in coniferous forest stands in Switzerland (Davos, Engadine) and Finland (Sodankylä) during the winters 2018 and 2019. The data are presented and used in the publication: Mazzotti, G., Essery, R., Webster, C., Malle, J., & Jonas T. (2020) Process-level evaluation of a high-resolution forest snow model using observations from mobile multi-sensor platforms Water Resources Research, under review

The above publication must be cited when using this dataset, and the user is referred to the publication for additional detail.

Data are grouped into 4 folders: 1) Point data includes wind speed data measured with stationary meteorological stations 2) Transect data includes data of incoming short- and longwave radiation, air and snow surface temperature acquired with an automated calblecar system along within-stand transects 3) Grid data includes data of incoming short- and longwave radiation, air and snow surface temperature acquired on 40x40m gridded plots using a handheld instrument, as well as snow depth data measured at the same grids.

Canopy structure information derived from hemispherical images is included for each all surveyed locations as well, and an overview of the field sites is provided.

Funding Information:

This work was supported by:
  • Swiss National Science Foundation SNSF (link) (Grant/Award: 169213)
  • INTERACT (link) (Grant/Award: IME4Rad)

Related Publications

Mazzotti, G., Essery, R., Webster, C., Malle, J., & Jonas T. (2020) Process-level evaluation of a high-resolution forest snow model using observations from mobile multi-sensor platforms Water Resources Research, under review

Citation:

Mazzotti, Giulia; Malle, Johanna; Jonas, Tobias (2020). Distributed sub-canopy datasets from mobile multi-sensor platforms (CH / FIN, 2018-2019) for hyper-resolution forest snow model evaluation. EnviDat. doi:10.16904/envidat.162.

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Data and Resources

Metadata

Field Values
DOI 10.16904/envidat.162
Publication State Published
Authors
  • Email: giulia.mazzottifoo(at)slf.ch ORCID: 0000-0003-3857-7449 Given Name: Giulia Family Name: Mazzotti Affiliation: WSL Institute for Snow and Avalanche Research SLF DataCRediT: Collection, Curation, Publication
  • Email: johanna.mallefoo(at)northumbria.ac.uk ORCID: 0000-0002-6185-6449 Given Name: Johanna Family Name: Malle Affiliation: University of Northumbria DataCRediT: Collection, Curation
  • Email: jonasfoo(at)slf.ch ORCID: 0000-0003-0386-8676 Given Name: Tobias Family Name: Jonas Affiliation: WSL Institute for Snow and Avalanche Research SLF DataCRediT: Publication, Supervision
Contact Person Given Name: Giulia Family Name: Mazzotti Email: giulia.mazzottifoo(at)slf.ch Affiliation: WSL Institute for Snow and Avalanche Research SLF ORCID: 0000-0003-3857-7449
Subtitles
Publication Publisher: EnviDat Year: 2020
Dates
  • Type: Collected Date: 2018-01-01 End Date: 2019-05-31
Version 1.0
Type dataset
General Type Dataset
Language English
Location Switzerland, Finland
Content License WSL Data Policy
Last Updated August 23, 2021, 14:22 (UTC)
Created March 21, 2020, 15:28 (UTC)