https://doi.org/10.5194/essd-2023-174

Sicart, J. E., Ramseyer, V., Picard, G., Arnaud, L., Coulaud, C., Freche, G., Soubeyrand, D., Lejeune, Y., Dumont, M., Gouttevin, I., Le Gac, E., Berger, F., Monnet, J. M., Borgniet, L., Mermin, E., Rutter, N., Webster, C., and Essery, R.: Snow accumulation and ablation measurements in a mid-latitude mountain coniferous forest (Col de Porte, France, 1325 m alt.): The Snow Under Forest field campaigns dataset, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2023-174, in review, 2023

Forests strongly modify the accumulation, metamorphism and melting of snow in mid and high-latitude regions. Recently, snow routines in hydrological and land surface models have been improved to incorporate more accurate representations of forest snow processes, but model inter-comparison projects have identified deficiencies, partly due to incomplete knowledge of the processes controlling snow cover in forests. The Snow Under Forest (SnoUF) project was initiated to enhance knowledge of the complex interactions between snow and vegetation. Two field campaigns, during the winters 2016–17 and 2017–18, were conducted in a coniferous forest bordering the snow study at Col de Porte (1325 m a.s.l, French Alps) to document the snow accumulation and ablation processes. This paper presents the field site, instrumentation, and collection methods. The observations include distributed forest characteristics (tree inventory, LIDAR measurements of forest structure, sub-canopy hemispherical photographs), meteorology (automatic weather station and radiometers array), snow cover and depth (snow poles transect and laser scan), and snow interception by the canopy during precipitation events. The weather station installed under dense canopy during the first campaign has been maintained since then and provides continuous measurements throughout the year since 2018. Data are publicly available from the repository of the Observatoire des Sciences de l’Univers de Grenoble (OSUG) data center at http://dx.doi.org/10.17178/SNOUF.2022

Journal Article
https://doi.org/10.5194/essd-2023-174
Data
http://dx.doi.org/10.17178/SNOUF.2022