Snow interception by the forest canopy controls the spatial heterogeneity of subcanopy snow accumulation leading to significant differences between forested and nonforested areas at a variety of ...scales. Snow intercepted by the forest canopy can also drastically change the surface albedo. As such, accurately modeling snow interception is of importance for various model applications such as hydrological, weather, and climate predictions. Due to difficulties in the direct measurements of snow interception, previous empirical snow interception models were developed at just the point scale. The lack of spatially extensive data sets has hindered the validation of snow interception models in different snow climates, forest types, and at various spatial scales and has reduced the accurate representation of snow interception in coarse-scale models. We present two novel empirical models for the spatial mean and one for the standard deviation of snow interception derived from an extensive snow interception data set collected in an evergreen coniferous forest in the Swiss Alps. Besides open-site snowfall, subgrid model input parameters include the standard deviation of the DSM (digital surface model) and/or the sky view factor, both of which can be easily precomputed. Validation of both models was performed with snow interception data sets acquired in geographically different locations under disparate weather conditions. Snow interception data sets from the Rocky Mountains, US, and the French Alps compared well to the modeled snow interception with a normalized root mean square error (NRMSE) for the spatial mean of ≤10 % for both models and NRMSE of the standard deviation of ≤13 %. Compared to a previous model for the spatial mean interception of snow water equivalent, the presented models show improved model performances. Our results indicate that the proposed snow interception models can be applied in coarse land surface model grid cells provided that a sufficiently fine-scale DSM is available to derive subgrid forest parameters.
In 2022, Western Europe experienced a precipitation deficit as well as heat waves. The combination of these weather conditions had a profound impact on the cryosphere of the French mountains, ...including the seasonal snow cover. Data from field measurements and remote sensing indicate that the snow cover disappeared early in all the Alps and Pyrenees. However, the analysis reveals regional differences. A strong accumulation deficit and particularly early melting in the Southern Alps caused record summer low flows. Very low summer flows were also reached despite a very wet winter in snowdominated catchments in the Pyrenees and in the Northern Alps.
En 2022, l’Europe de l’Ouest a connu un déficit de précipitations ainsi que des vagues de chaleur. La combinaison de ces conditions météorologiques a eu un impact profond sur la cryosphère des montagnes françaises, dont le manteau neigeux saisonnier. Les données issues de mesures de terrain et de la télédétection indiquent que le manteau neigeux a disparu de façon précoce dans tous les massifs. Toutefois, l’analyse révèle des différences régionales. Un fort déficit d’accumulation et une fonte particulièrement précoce dans les Alpes du Sud ont causé des étiages estivaux record. Des étiages estivaux très bas ont été aussi atteints malgré un hiver très arrosé dans des bassins sous influence nivale des Pyrénées et dans les Alpes du Nord.
Measurements of sensible- and latent-heat fluxes under stable conditions are rare. In order to obtain indirect measurements of turbulent fluxes, meteorological data measured at the Col de Porte ...laboratory (1320 m a.s.l, France) under very stable conditions (cold, clear night with low wind) are used. The radiative fluxes are measured, the conduction within the snowpack is calculated using the snow model Crocus and the turbulent fluxes are determined as a residual term of the surface-energy balance equation. These data were used to fit a new parameterization of the turbulent fluxes for the snow model. The turbulent fluxes are increased as compared to the theory. Crocus was also applied to the data from the LEADEX92 experiment and the turbulent fluxes calculated by the model were compared to the fluxes measured using sonic anemometers/thermometers on the site.
Abstract
The SAFRAN/Crocus/MÉPRA software is used to assess the climatology of the avalanche hazard and its sensitivity to climate change. A natural avalanche-hazard index based on MEPRA analysis is ...defined and validated against natural avalanche observations (triggered avalanches are not taken into account). A 15 year climatology then allows a comparison of avalanche hazard in the different French massifs. Finally a simple climate scenario (with a general increase of precipitation and temperature) shows that avalanche hazard may decrease slightly in winter (mainly February) and more significantly in May/June. The relative proportion of wet-snow avalanches increases.
Determining the precipitation phase-rain or snow-is an important factor in modelling discharge in mountainous basins. In a study carried out in the outer tropical Andes Cordillera of Bolivia, ...half-hourly determination of precipitation phase was obtained by applying a suitable expert system, taking 11 meteorological parameters into consideration that are measured over 21 months at an altitude close to 4800 m. Straightforward relationships between the determined precipitation phase and observed air temperature were analysed in histograms that contain percentage occurrences of snowfall, rainfall and mixed precipitation events for 0.5°C air temperature increments. The graph shows a nearly identical distribution of percentage occurrences of snowfall in the Andes to that on a 1600-m high site in the Swiss Alps. This result suggests that, for hydrological modelling purposes in the outer tropical Andes, the same rain/snow threshold temperature as in the compared Swiss site can be applied.
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
This paper describes in situ meteorological forcing and evaluation data, and
bias-corrected reanalysis forcing data, for cold regions' modelling at 10
sites. The long-term datasets (one maritime, one ...arctic, three boreal, and
five mid-latitude alpine) are the reference sites chosen for evaluating
models participating in the Earth System Model-Snow Model Intercomparison
Project. Periods covered by the in situ data vary between 7 and 20 years of hourly meteorological data, with evaluation data (snow depth, snow
water equivalent, albedo, soil temperature, and surface temperature)
available at varying temporal intervals. Thirty-year (1980–2010) time series
have been extracted from a global gridded surface meteorology dataset
(Global Soil Wetness Project Phase 3) for the grid cells containing the
reference sites, interpolated to 1 h time steps and bias-corrected.
Although the correction was applied to all sites, it was most important for
mountain sites hundreds of metres higher than the grid elevations and for
which uncorrected air temperatures were too high and snowfall amounts too
low. The discussion considers the importance of data sharing to the
identification of errors and how the publication of these datasets
contributes to good practice, consistency, and reproducibility in
geosciences. The Supplement provides information on instrumentation,
an estimate of the percentages of missing values, and gap-filling methods at
each site. It is hoped that these datasets will be used as benchmarks for
future model development and that their ease of use and availability will
help model developers quantify model uncertainties and reduce model errors.
The data are published in the repository PANGAEA and are available at
https://doi.pangaea.de/10.1594/PANGAEA.897575.
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 https://doi.org/10.17178/SNOUF.2022 (Sicart et al., 2022).
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