Dear Colleagues,

Water stored in the snow pack represents an important component of water balance in many regions throughout the world. Snow cover variability is affected by and translates into changes of atmosphere-land surface interactions, both at spatial and temporal scales. The monitoring and modeling of snow accumulation and melt is thus an important but very challenging task, particularly in regions with limited availability and large spatial variability of hydrological and weather data. The objective of this Special Issue is to present and integrate studies focusing on snow within the context of catchment hydrology, snow as a land surface, snow-vegetation interaction, and snow as a source for glacial ice. The aim is to integrate and share knowledge and experience in the fields of experimental research, remote sensing, and hydrological modeling.

Specifically, contributions addressing the following topics are welcome:
1) Experimental research on snow properties and processes, which need to be implemented in hydrologic catchment, glacier, and land-surface models;
2) Experimental research and innovative modeling approaches addressing the effects of snow-vegetation interactions;
3) Assessment and evaluation of different remote sensing technologies and classification approaches focusing, e.g., on snow cover, albedo, snow depth, and snow water equivalent mapping;
4) Practical implementation of snow data assimilation in operational hydrological and weather prediction models.

Dr. Juraj Parajka
Dr. Cécile Ménard
Dr. Ladislav Holko
Guest Editors

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• snow cover
• snow water equivalent
• snow accumulation and melt
• modeling
• remote sensing
• snow vegetation interaction
• catchment hydrology

Title: Glacier Runoff Determined from Transient Snow Line Migration Observations
Author: M.S. Pelto
Affiliation: Department of Environmental Science, Nichols College, Dudley, MA 01571, USA; Email: [email protected]
Abstract: Identification of the transient snowline (TSL) from high spatial resolution Landsat imagery on the Juneau Icefield, Southeast Alaska was used to quantify ablation rates during the 1998-2014 period.  The product of the rate of rise of the TSL during the ablation season and the observed balance gradient provides a measure of the ablation rate. On both Lemon Creek Glacier and Taku Glacier field mass balance measurement identify the balance gradient.  TSL observations from multiple dates during the ablation season from 1998–2014 at Lemon Creek Glacier and Taku Glacier are used to explore the consistency of the TSL rate of rise from year to year and glacier to glacier.  The rate of rise is also used to calculate annual ablation rate. On Lemon Creek Glacier and Taku Glacier the satellite derived mean TSL migration rates were 3.6 ± 0.7 md^-1 and 4.0 ± 0.0.8 md^-1 respectively. This yields ablation rates of 23 ± 4 mmd^-1 for Lemon Creek Glacier and 18 ± 4 mmd^-1 for Taku Glacier, using a TSL-balance-gradient method.
Keywords: Transient snow line, mass balance, ablation, glacier, Juneau Icefield

Title: Simulation of surface energy fluxes and snow interception using a higher order closure multi-layer soil-vegetation-atmospheric model: The effect of canopy shape and structure
Authors: Laura McGowan ¹, Helen E.Dahlke ¹, Kyaw Tha Paw U ¹
Affiliation: 1 Department of Land, Air and Water Resources, University of California at Davis, Davis, CA, USA
Abstract: Snow cover is a critical driver of the Earth’s surface energy budget, climate change, and water resources. Variations in snow cover not only affect the energy budget of the land surface but also represent a major water supply source. In California, US on average as much as 35 percent of the annual stream flow is provided by snowmelt runoff. Consequently estimates of snow depth, extent, and melt in the Sierra Nevada are critical to estimating the amount of water available for both California agriculture and urban users. However, accurate estimates of snow cover and snow melt processes in forested area still remain a challenge. Canopy structure influences the vertical and spatiotemporal distribution of snow, and therefore ultimately determines the degree and extent by which snow alters both the surface energy balance and water availability in forested regions. In this study we use the Advanced Canopy-Atmosphere-Soil algorithm (ACASA), a multi-layer soil-vegetation-atmosphere numerical model, to simulate the effect of different snow-covered canopy structures on the energy budget, and temperature and other scalar profiles within different forest types in the Sierra Nevada, California. ACASA incorporates a higher order turbulence closure scheme which allows the detailed simulation of turbulent fluxes of heat and water vapor as well as the CO₂ exchange of several layers within the canopy. As such ACASA can capture the counter gradient fluxes within canopies that may occur frequently, but are typically unaccounted for, in most snow hydrology models. Six different canopy types were modeled ranging from coniferous forests (e.g. most biomass near the ground) to top-heavy (e.g. most biomass near the top of the crown) deciduous forests to multi-layered forest canopies (e.g. mixture of young and mature trees). Preliminary results indicate that the canopy shape and structure associated with different canopy types fundamentally influence the vertical scalar profiles (including those of temperature, moisture, and wind speed) in the canopy and thus alter the interception and snow melt dynamics in forested land surfaces. The turbulent transport dynamics, including counter-gradient fluxes, and radiation features including land surface albedo, are discussed in the context of the snow energy balance.

Title: Modelling Snow Quantity and Properties in Boreal Forests: Assessment over a Range of Sites in Northern Scandinavia
Authors: Isabelle Gouttevin¹, Sirpa Rasmus², Charles Fierz³, Jouko Kumpula⁴, Jukka Siitari^4
1 IRSTEA LYON, FRANCE
² University of Jyväskylä, FINLAND
³ WSL Institute for Snow and Avalanche Research SLF, SWITZERLAND
⁴ Natural Resources Institute Finland, FINLAND
Abstract: Northern hemisphere is governed by boreal forests; these are covered by snow for the best part of the year. Snow is an integral and interactive part of boreal ecosystems, and accumulation, evolution and melt of the snow cover are major components in the annual hydrological cycle. However, modelling of these processes below varying forest canopies is not a straightforward task. Especially tools to simulate the snow properties (stratigraphy and physical properties of the snow layers, both relevant for ecological and hydrological applications) are not well validated in such environments. In this work we make use of the detailed snow-cover model SNOWPACK, which is now equipped with an improved canopy module, and test its ability to simulate the quantity and properties of snow at a range of boreal forested sites in northern Scandinavia. Meteorological forcing data from 32 separate winters from 14 boreal sites from Finnish Lapland (2-4 winters per site) have been gathered together with information on local forest conditions to provide input material for the simulations. In model validation we utilize a valuable data set obtained from these sites that consists of more than 2000 observations on snow depth, basal snow layer type, snow temperature, density and hardness. For each site, the SNOWPACK results are compared to observations via the use of the ProfEval tool (Fierz et al., 2014). Focus is especially set as to the model’s capability to produce a realistic snow cover with respect to depth, layers of depth hoar and ice layers: these features are indeed of particular importance for the boreal ecosystem and human activities (like reindeer herding). The ability to model these conditions could provide a valuable tool for ecosystem monitoring and could help to anticipate the future changes in snow conditions that would affect boreal hydrological cycles and ecosystem functions.
Reference:Fierz, C., Gerber, F., & Lehning, M. (2014). Comparison of modelled and measured point snow profiles : a tool for validating snow-cover models of the next generation ? Proceedings of the International Snow Science Workshop, Banff, 2014. p825-826.

Title: Spatiotemporal Variations in Snow and Soil Frost- A Review of Measurement Techniques.
Authors: Angela Lundberg, David Gustafsson, et al.
Abstract: Climate warming is affecting spatiotemporal variations in snow and ground frost, but the results are sometimes contradicting and measurement difficulties have hampered progress in assessing how these variations impact on snowmelt infiltration and there are also indications that groundwater recharge response is scale dependent.   It is thus important to measure snow and soil frost properties with temporal and spatial scales appropriate to improve infiltration process knowledge. The main aim with this paper is therefore to review ground based methods to measure snow properties (depth, density, water equivalent, wetness and layering) and soil frost properties (depth, water and ice content, permeability, distance to groundwater) and to make recommendations for process studies aiming to improve knowledge regarding infiltration in regions with seasonal frost. Ground based radar (GPR), comes in many different combinations and can, depending on design be used to asses both spatial and temporal variations in snow and frost so combinations of GPR and tracer techniques can be recommended, but study design must be adapted to the scales, the aims and the resources of the study.