This article describes the extension of the ESCIMO.spread spreadsheet-based point energy balance snow model by (i) an advanced approach for precipitation phase detection, (ii) a method for cold content and liquid water storage consideration and (iii) a canopy sub-model that allows the quantification of canopy effects on the meteorological conditions inside the forest as well as the simulation of snow accumulation and ablation inside a forest stand. To provide the data for model application and evaluation, innovative low-cost snow monitoring systems (SnoMoS) have been utilized that allow the collection of important meteorological and snow information inside and outside the canopy. The model performance with respect to both, the modification of meteorological conditions as well as the subsequent calculation of the snow cover evolution, are evaluated using inside- and outside-canopy observations of meteorological variables and snow cover evolution as provided by a pair of SnoMoS for a site in the Black Forest mountain range (southwestern Germany). The validation results for the simulated snow water equivalent with Nash–Sutcliffe model efficiency values of 0.81 and 0.71 and root mean square errors of 8.26 and 18.07 mm indicate a good overall model performance inside and outside the forest canopy, respectively. The newly developed version of the model referred to as ESCIMO.spread (v2) is provided free of charge together with 1 year of sample data including the meteorological data and snow observations used in this study.

A network of 30 standalone snow monitoring stations was used to investigate the snow cover distribution, snowmelt dynamics, and runoff generation during two rain‐on‐snow (ROS) events in a 40 km2 montane catchment in the Black Forest region of southwestern Germany. A multiple linear regression analysis using elevation, aspect, and land cover as predictors for the snow water equivalent (SWE) distribution within the catchment was applied on an hourly basis for two significant ROS flood events that occurred in December 2012. The available snowmelt water, liquid precipitation, as well as the total retention storage of the snow cover were considered in order to estimate the amount of water potentially available for the runoff generation. The study provides a spatially and temporally distributed picture of how the two observed ROS floods developed in the catchment. It became evident that the retention capacity of the snow cover is a crucial mechanism during ROS. It took several hours before water was released from the snowpack during the first ROS event, while retention storage was exceeded within 1 h from the start of the second event. Elevation was the most important terrain feature. South‐facing terrain contributed more water for runoff than north‐facing slopes, and only slightly more runoff was generated at open compared to forested areas. The results highlight the importance of snowmelt together with liquid precipitation for the generation of flood runoff during ROS and the large temporal and spatial variability of the relevant processes. Copyright © 2015 John Wiley & Sons, Ltd.

Hourly observations of 65 snow monitoring stations were used to investigate the spatiotemporal variability of the surface energy balance during snowmelt in the Black Forest region of southwestern Germany. The study focuses on two rain-on-snow (ROS) events in December 2012 and a clear sky period at the beginning of March 2013 using the same study locations. ROS and clear sky were chosen since they are completely different snowmelt conditions in terms of energy exchanges and dynamics. The results show that snowmelt was dominated by turbulent exchanges at the open field sites and by both turbulent exchanges and net longwave radiation in the forest during ROS. The energy available for snowmelt can be almost identical at open and forest locations during ROS, and a constant energy flux even during night was directed toward the snowpack. During the clear sky conditions, net shortwave radiation was the dominating term in the open, whereas net shortwave and net longwave radiation were most important in the forest. A diurnal signal with positive energy balance during daylight and negative energy balance in the night was observed, with considerably reduced energy available for snowmelt in the forest. Furthermore, the stratified sampling design revealed the strong influence of the canopy and the topography at the locations on the observed energy fluxes. Elevation, aspect, and leaf area index (LAI) were the most important predictor variables during ROS, whereas aspect and LAI were most influential during the clear sky period. The study highlights the distinct spatial variability of the individual energy balance terms over a relatively small area during the differing snowmelt conditions.

The spatial and temporal dynamics of seasonal snow covers play a critical role for many hydrological, ecological, and climatic processes. This paper presents a new, innovative approach to continuously monitor these dynamics using numerous low-cost, standalone snow monitoring stations (SnoMoS). These stations provide snow and related meteorological data with a high temporal and spatial resolution. Data collected by SnoMoS include: snow depth, surface temperature, air temperature and humidity, total precipitation, global radiation, wind speed, and barometric pressure. A total of 99 sensors were placed over the winters 2010/2011 and 2011/2012 at multiple locations within three 40-180 km(2) basins in the Black Forest region of Southern Germany. The locations were chosen to cover a wide range of slopes, elevations, and expositions in a stratified sampling design. Furthermore, paired stations located in close proximity to each other, one in the open and one underneath various forest canopies, were set up to investigate the influence of vegetation on snow dynamics. The results showed that considerable differences in snow depth and, therefore, snow water equivalent (SWE) are present within the study area despite its moderate temperatures and medium elevation range (400-1500 m). The relative impact of topographical factors like elevation, aspect, and of different types of forest vegetation were quantified continuously and were found to change considerably over the winter period. The recorded differences in SWE and snow cover duration were large enough that they should be considered in hydrologic and climate models.

A network of 45 spatially distributed time-lapse cameras was used to carry out a continuous observation of snow processes and snow cover properties throughout three mid-latitude medium elevation mountain catchments in hourly intervals during the winter seasons of 2010/2011 and 2011/2012. A simple technical modification was conducted to enable the deployment of the standard digital cameras in any location. Image analysis software was applied to extract information about snow depth, surface albedo and canopy interception from the digital images. Furthermore, the distributed design of the camera network made it possible to identify the elevation of the snow rain interface for any precipitation event which is very helpful for the interpretation of winter flooding events resulting from snow melt. Exemplary data for all these analyses is presented to show the potential fields of application of this innovative approach. Study results prove that the application of digital time-lapse photography is an appropriate technique to observe the spatial distribution and temporal evolution of seasonal snow covers in a mountainous environment.

This study presents an approach of continuously monitoring the spatial variability of the most important snow cover characteristics and climate factors by using a network of numerous low cost, yet accurate, standalone snow monitoring stations delivering highly distributed data on snow cover and climate conditions. Data collected by the sensors include: snowdepth, air temperature and humidity, total precipitation, global radiation, wind speed, and snow surface temperature. A total of 99 sensors were placed at multiple locations within three study basins to cover a wide range of slope elevations, angles, expositions and vegetation in a stratified sampling design. Additionally, 45 time-lapse cameras provided continuous information on canopy snow interception, the state of precipitation, snowdepth and snow albedo. The study was carried out in the Black Forest region of southern Germany, a mid-elevation, moderate climate and heavily forested mountain region The results showed that even for a mid-elevation mountain range the differences in snow water equivalent (SWE) introduced by the topography and the land cover were substantial. An analysis revealed that for the spatial distribution of the SWE, elevation and vegetation were the most important factors explaining 77% of the spatial variability. Exposure seemed to be important only for open non-forested locations. The continuous nature of the observations also made it possible to determine that the strength of the elevation SWE relationship increased in accumulation periods while dropping during melt periods. The results of this study are aimed at improving the understanding of the processes governing the spatial distribution of snow and therefore improving the interpolation schemes used in many snowmelt models to distribute point snow observations over a model domain. The time lapse photographs furthermore provide a more detailed picture of snow interception in the forest canopies. Especially the removal of intercepted snow from the canopy is often a difficult issue in snowmelt models. The analysis of the hourly photographs along with the respective accompanying climate observations can provide a much clearer picture of this process and could lead to improved model routines for canopy snow interception.

Abstract. A network of 45 spatially distributed time-lapse cameras was used to carry out a continuous observation of snow processes and snow cover properties throughout three mid-latitude medium elevation mountain catchments in hourly intervals. A simple technical modification was conducted to enable the deployment of the standard digital cameras in any location. Image analysis software was applied to extract information about snow depth, surface albedo, and canopy interception from the digital images. Furthermore, the distributed design of the camera network made it possible to identify the elevation of the snow rain interface for any precipitation event for the interpretation of winter flooding events resulting from snow melt. Study results prove that the application of digital time-lapse photography is an appropriate technique to observe the spatial distribution and temporal evolution of seasonal snow covers in a mountainous environment.

Under the Mackenzie GEWEX Study, extensive snowmeit and mff research was cmied out at the Trail Valley and Havikpak Creek remrch b i n s at the tundra-foreat transition zone near Inuvik, Northwest Territoriw. Pmess based research concentrated on snow accumulatio~ the spatial variability of energy fluxes controiling melt, Iwl scale advection of sensible h a t from mow-free patches to snow patches, prcolation of meltwater through the mowpsck, storage of meltwater in stream channels, and hillslope nmoff. Building on these studies. process based models were improved, as shown by a h e r ability to laode1 changes in snow-covered area during the melt period In addition, various landsurFace and hydrologic &Is were test4 demonstrating an enband qability to model melt related runoff. F u t w research is q u i d to accurately model both snow<overed area and m f f at a variety of wales and to inmpmte t o p ~ c and vegetation effects comctly in the models.

The permafrost of the Western Canadian Arctic has a very high ground ice content. As a result, the vast number of thaw lakes in this area are very sensitive to a changing climate. With thaw lakes prone to either increases in area due to thermokarst processes, or complete drainage in less than one day due to melting of channels through ice‐rich permafrost. After a lake drains, it leaves a topographic basin that is often termed a Drained Thaw Lake Basin (DTLB). An analysis of aerial photographs and topographic maps showed that 41 lakes drained in the study area between 1950 and 2000, for a rate of slightly less than one lake per year. The rate of drainage over three time periods (1950–1973, 1973–1985, 1985–2000), decreased from over 1 lake/year to approximately 0·3 lake/year. The reason for this decrease is not known, but it is hypothesized that it is related to the effect of a warming climate. There is a large spatial variation in DTLBs, with higher number of drained lakes in physiographic areas with poor drainage. It is likely that this variation is related to variations in ground ice. Although previous studies have suggested that lakes drain during periods of high water level, it is likely that a combination of a warm summer, a resulting deep active layer, and a moderately high lake level were responsible for the drainage of a lake in the study area during the summer of 1989. Although this study has documented changes in the rate of lake drainage over a 50‐year period, there is a need for further research to better understand the complex interactions between climate, geomorphology, and hydrology responsible for this change, and to further consider the potential hazard rapid lake drainage poses to future industrial or resource development in the area. Copyright © 2008 John Wiley & Sons, Ltd and Her Majesty the Queen in right of Canada. The contributions of P. Marsh, M. Russell, H. Haywood and C. Onclin belong to the Crown in right of Canada and are reproduced with the permission of Environment Canada.