Snow accumulation and ablation measurements in a midlatitude mountain coniferous forest (Col de Porte, France, 1325 m altitude): the Snow Under Forest (SnoUF) field campaign data set

Sicart, Jean Emmanuel ; Ramseyer, Victor ; Picard, Ghislain ; Arnaud, Laurent ; Coulaud, Catherine ; Freche, Guilhem ; Soubeyrand, Damien ; Lejeune, Yves ; Dumont, Marie ; Gouttevin, Isabelle ; Le Gac, Erwan ; Berger, Frédéric ; Monnet, Jean-Matthieu ; Borgniet, Laurent ; Mermin, Éric ; Rutter, Nick ; Webster, Clare ; Essery, Richard

Année de publication
2023
Résumé
<p align=justify>Forests strongly modify the accumulation, metamorphism and melting of snow in midlatitude and high-latitude regions. Recently, snow routines in hydrological and land surface models were improved to incorporate more accurate representations of forest snow processes, but model intercomparison 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 2016-2017 and 2017-2018, 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, the instrumentation and the collection and postprocessing methods. The observations include distributed forest characteristics (tree inventory, lidar measurements of forest structure, subcanopy hemispherical photographs), meteorology (automatic weather station and an array of radiometers), snow cover and depth (snow pole 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 has provided 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 <a href="https://doi.org/10.17178/SNOUF.2022">https://doi.org/10.17178/SNOUF.2022</a> (Sicart et al., 2022).</p>
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