scholarly journals ESCIMO.spread (v2): parameterization of a spreadsheet-based energy balance snow model for inside-canopy conditions

2016 ◽  
Vol 9 (2) ◽  
pp. 633-646 ◽  
Author(s):  
T. Marke ◽  
E. Mair ◽  
K. Förster ◽  
F. Hanzer ◽  
J. Garvelmann ◽  
...  
Keyword(s):  
Energy Balance ◽  
Snow Cover ◽  
Forest Canopy ◽  
Model Performance ◽  
Snow Accumulation ◽  
Meteorological Conditions ◽  
Mountain Range ◽  
Point Energy ◽  
Snow Model ◽  
Mean Square Errors

Abstract. 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.

scholarly journals ESCIMO.spread (v2): parameterization of a spreadsheet-based energy balance snow model for inside-canopy conditions

2015 ◽  
Vol 8 (9) ◽  
pp. 8155-8191
Author(s):  
T. Marke ◽  
E. Mair ◽  
K. Förster ◽  
F. Hanzer ◽  
J. Garvelmann ◽  
...  
Keyword(s):  
Energy Balance ◽  
Snow Cover ◽  
Forest Canopy ◽  
Model Performance ◽  
Snow Accumulation ◽  
Meteorological Conditions ◽  
West Germany ◽  
Mountain Range ◽  
Point Energy ◽  
Snow Model

Abstract. This article describes the extension of the spreadsheet-based point energy balance snow model ESCIMO.spread by (i) an advanced approach for precipitation phase detection, (ii) a concept for cold and liquid water storage consideration and (iii) a canopy sub-model that allows to quantify the effect of a forest canopy 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 in 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 in- 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 (south-west Germany). The validation results indicate a good overall model performance in and outside the forest canopy. The newly developed version of the model refered to as ESCIMO.spread (v2) is provided free of charge together with one year of sample data including the meteorological data and snow observations used in this study.

A Novel Perspective on Mapping Snow Cover Under Forest Canopy With Sentinel-2 Multispectral Optical Satellite Sensor Over Black Forest Germany

2020 ◽  
Author(s):  
Arnab Muhuri
Keyword(s):  
Snow Cover ◽  
Forest Canopy ◽  
Snow Accumulation ◽  
Optical Data ◽  
Federal State ◽  
Mountain Range ◽  
Black Forest ◽  
Forested Areas ◽  
Forested Landscapes ◽  
Sentinel 2

<p>Previous investigations have reported that the performance of the traditional snow cover mapping algorithms based on the Normalized Difference Snow Index (NDSI), derived from a multispectral optical airborne/spaceborne sensor, significantly degrades on transitioning from non-forested to forested landscapes. The thick canopy cover in forested landscapes obscures both the upwelling and the downwelling radiance and hence impairs the detection of the underlying snow cover on the forest floor via NDSI thresholding due to the shift in the apparent threshold. Although NDSI has been reported to be an ineffective index for extracting snow information from forested areas, this investigation presents contrary views. A novel perspective is introduced on exploiting the temporal NDSI-NDVI statistics for extracting snow information under the canopy, as has been also reported important in the past literature when considered together, to reconstruct the actual snow cover scenario over the mixed landscape, comprising both forested areas of varying densities and open vegetation-free patches. The Black Forest (Schwarzwald) is a large forested mountainous terrain at about 200-1500 m above sea level situated in the Federal State of Baden-Württemberg in the southwest corner of Germany. The region is bounded by the Rhine river valley to the west and south stretching in an oblong manner with a length of about 160 km and breadth of up to 50 km. The Black Forest consists of approximately 80% coniferous (spruce, fir, and pine) and 20% deciduous (beech, birch, and oak), with about 70% of the region under forest cover. Seasonal snowmelt water and natural springs originating in this region sources major European rivers like the Danube and the tributaries of the Rhein like the Murg and the Neckar. Therefore, it is essential to monitor snow accumulation under the canopy to accurately forecast and investigate the influence of the snowmelt runoff in such major catchments. One of the test sites is situated in the Murg catchment at Hundseck near the town of Baden-Baden at the north-western border of the Black Forest mountain range. This investigation employs Sentinel-2 multispectral optical data from the previous season in order to test the proposed approach. The proposed method is tested with the European Space Agency's open-access Sentinel-2 multispectral optical satellite data, over the Hundseck test site in the Black Forest. The snow extent map is validated with the Normalized Difference Forest Snow Index (NDFSI), which was proposed as an alternative for NDSI to map the canopy underlying snow in evergreen forests. The proposed algorithm is simple and computationally frugal. Temporal NDSI-NDVI statistics in conjunction with mathematical morphological operation has resulted in significant improvement in the detection of under canopy snow cover. It is noteworthy that the performance of the algorithm inherently shows a dependence on the forest LAI. An improvement of more than 50% is achieved in the under-canopy snow cover mapping. A priori knowledge regarding the LAI of forests will enable adaptive tuning of the algorithm locally for better performance under dense canopy conditions.</p>

scholarly journals Two years with extreme and little snowfall: effects on energy partitioning and surface energy exchange in a high-Arctic tundra ecosystem

2016 ◽  
Vol 10 (4) ◽  
pp. 1395-1413 ◽  
Author(s):  
Christian Stiegler ◽  
Magnus Lund ◽  
Torben Røjle Christensen ◽  
Mikhail Mastepanov ◽  
Anders Lindroth
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Snow Cover ◽  
Energy Exchange ◽  
Surface Energy Balance ◽  
Arctic Tundra ◽  
High Arctic ◽  
Snow Accumulation ◽  
Heat Fluxes ◽  
Tundra Ecosystem

Abstract. Snow cover is one of the key factors controlling Arctic ecosystem functioning and productivity. In this study we assess the impact of strong variability in snow accumulation during 2 subsequent years (2013–2014) on the land–atmosphere interactions and surface energy exchange in two high-Arctic tundra ecosystems (wet fen and dry heath) in Zackenberg, Northeast Greenland. We observed that record-low snow cover during the winter 2012/2013 resulted in a strong response of the heath ecosystem towards low evaporative capacity and substantial surface heat loss by sensible heat fluxes (H) during the subsequent snowmelt period and growing season. Above-average snow accumulation during the winter 2013/2014 promoted summertime ground heat fluxes (G) and latent heat fluxes (LE) at the cost of H. At the fen ecosystem a more muted response of LE, H and G was observed in response to the variability in snow accumulation. Overall, the differences in flux partitioning and in the length of the snowmelt periods and growing seasons during the 2 years had a strong impact on the total accumulation of the surface energy balance components. We suggest that in a changing climate with higher temperature and more precipitation the surface energy balance of this high-Arctic tundra ecosystem may experience a further increase in the variability of energy accumulation, partitioning and redistribution.

scholarly journals A new Snow-SVAT to simulate the accumulation and ablation of seasonal snow cover beneath a forest canopy

2004 ◽  
Vol 50 (169) ◽  
pp. 171-182 ◽  
Author(s):  
Melody J. Tribbeck ◽  
Robert J. Gurney ◽  
Elizabeth M. Morris ◽  
David W. C. Pearson
Keyword(s):  
Solar Radiation ◽  
Snow Cover ◽  
Forest Canopy ◽  
Correlation Coefficients ◽  
Field Measurements ◽  
Radiation Model ◽  
Physically Based ◽  
Boreal Ecosystem ◽  
Snow Model

AbstractA new snow—soil—vegetation—atmosphere transfer (Snow-SVAT) scheme, which simulates the accumulation and ablation of the snow cover beneath a forest canopy, is presented. The model was formulated by coupling a canopy optical and thermal radiation model to a physically based multi-layer snow model. This canopy radiation model is physically based yet requires few parameters, so can be used when extensive in situ field measurements are not available. Other forest effects such as the reduction of wind speed, interception of snow on the canopy and the deposition of litter were incorporated within this combined model, SNOWCAN, which was tested with data taken as part of the Boreal Ecosystem—Atmosphere Study (BOREAS) international collaborative experiment. Snow depths beneath four different canopy types and at an open site were simulated. Agreement between observed and simulated snow depths was generally good, with correlation coefficients ranging between r2 = 0.94 and r2 = 0.98 for all sites where automatic measurements were available. However, the simulated date of total snowpack ablation generally occurred later than the observed date. A comparison between simulated solar radiation and limited measurements of sub-canopy radiation at one site indicates that the model simulates the sub-canopy downwelling solar radiation early in the season to within measurement uncertainty.

scholarly journals A two-layer canopy with thermal inertia for an improved modelling of the sub-canopy snowpack energy-balance

2015 ◽  
Vol 8 (1) ◽  
pp. 209-262 ◽  
Author(s):  
I. Gouttevin ◽  
M. Lehning ◽  
T. Jonas ◽  
D. Gustafsson ◽  
M. Mölder
Keyword(s):  
Energy Balance ◽  
Temperature Drop ◽  
Model Performance ◽  
Thermal Inertia ◽  
Thermal Response ◽  
Canopy Temperature ◽  
Night Time ◽  
The Difference ◽  
Snow Model ◽  
The Impact

Abstract. A new, two-layer canopy module with thermal inertia as part of the detailed snow model SNOWPACK (version 3.2.1) is presented and evaluated. This module is designed to reproduce the difference in thermal response between leafy and woody canopy elements, and their impact on the underlying snowpack energy balance. Given the number of processes resolved, the SNOWPACK model with its enhanced canopy module constitutes a very advanced, physics-based atmosphere-to-soil-through-canopy-and-snow modelling chain. Comparisons of modelled sub-canopy thermal radiation to stand-scale observations at an Alpine site (Alptal, Switzerland) demonstrate the improvements of the new canopy module. Both thermal heat mass and the two-layer canopy formulation contribute to reduce the daily amplitude of the modelled canopy temperature signal, in agreement with observations. Particularly striking is the attenuation of the night-time drop in canopy temperature, which was a key model bias. We specifically show that a single-layered canopy model is unable to produce this limited temperature drop correctly. The impact of the new parameterizations on the modelled dynamics of the sub-canopy snowpack is analysed and yields consistent results but the frequent occurrence of mixed-precipitation events at Alptal prevents a conclusive assessment of model performance against snow data. The new model is also successfully tested without specific tuning against measured tree temperatures and biomass heat storage fluxes at the boreal site of Norunda (Sweden). This provides an independent assessment of its physical consistency and stresses the robustness and transferability of the parameterizations used.

scholarly journals A seasonal algorithm of the snow-covered area fraction for mountainous terrain

2021 ◽  
Author(s):  
Nora Helbig ◽  
Michael Schirmer ◽  
Jan Magnusson ◽  
Flavia Mäder ◽  
Alec van Herwijnen ◽  
...  
Keyword(s):  
Snow Cover ◽  
Snow Water Equivalent ◽  
Model Performance ◽  
Ground Surface ◽  
Grid Cell ◽  
Mountainous Terrain ◽  
Fine Scale ◽  
Snow Covered Area ◽  
Covered Area ◽  
Mean Square Errors

Abstract. The snow cover spatial variability in mountainous terrain changes considerably over the course of a snow season. In this context, fractional snow-covered area (fSCA) is therefore an essential model parameter characterizing how much of the ground surface in a grid cell is currently covered by snow. We present a seasonal fSCA algorithm using a recent scale-independent fSCA parameterization. For the seasonal implementation we track snow depth (HS) and snow water equivalent (SWE) and account for several alternating accumulation-ablation phases. Besides tracking HS and SWE, the seasonal fSCA algorithm only requires computing subgrid terrain parameters from a fine-scale summer digital elevation model. We implemented the new algorithm in a multilayer energy balance snow cover model. For a spatiotemporal evaluation of modelled fSCA we compiled three independent fSCA data sets. Evaluating modelled 1 km fSCA seasonally with fSCA derived from airborne-acquired fine-scale HS data, satellite- as well as terrestrial camera-derived fSCA showed overall normalized root mean square errors of respectively 9 %, 20 % and 22 %, and represented seasonal trends well. The overall good model performance suggests that the seasonal fSCA algorithm can be applied in other geographic regions by any snow model application.

scholarly journals Sensitivity of the French Alps snow cover to the variation of climatic variables

1994 ◽  
Vol 12 (5) ◽  
pp. 469-477 ◽  
Author(s):  
E. Martin ◽  
E. Brun ◽  
Y. Durand
Keyword(s):  
Snow Cover ◽  
Internal State ◽  
Regional Scale ◽  
Climatic Conditions ◽  
Meteorological Conditions ◽  
French Alps ◽  
Snow Model ◽  
Analysis System ◽  
The Impact ◽  
Data Period

Abstract. In order to study the sensitivity of snow cover to changes in meteorological variables at a regional scale, a numerical snow model and an analysis system of the meteorological conditions adapted to relief were used. This approach has been successfully tested by comparing simulated and measured snow depth at 37 sites in the French Alps during a ten year data period. Then, the sensitivity of the snow cover to a variation in climatic conditions was tested by two different methods, which led to very similar results. To assess the impact of a particular "doubled CO2" scenario, coherent perturbations were introduced in the input data of the snow model. It was found that although the impact would be very pronounced, it would also be extremely differentiated, dependent on the internal state of the snow cover. The most sensitive areas are the elevations below 2400 m, especially in the southern part of the French Alps.

scholarly journals Modeling Snow–Canopy Processes on an Idealized Mountain

2011 ◽  
Vol 12 (4) ◽  
pp. 663-677 ◽  
Author(s):  
Ulrich Strasser ◽  
Michael Warscher ◽  
Glen E. Liston
Keyword(s):  
Snow Cover ◽  
Forest Canopy ◽  
Distributed Simulation ◽  
Coniferous Forest ◽  
Snow Accumulation ◽  
Radiative Energy ◽  
Late Winter ◽  
Canopy Interception ◽  
Simulation Engine ◽  
Shadowing Effect

Abstract Snow interception in a coniferous forest canopy is an important hydrological feature, producing complex mass and energy exchanges with the surrounding atmosphere and the snowpack below. Subcanopy snowpack accumulation and ablation depends on the effects of canopy architecture on meteorological conditions and on interception storage by stems, branches, and needles. Mountain forests are primarily composed of evergreen conifer species that retain their needles throughout the year and hence intercept snow efficiently during winter. Canopy-intercepted snow can melt, fall to the ground, and/or sublimate into the air masses above and within the canopy. To improve the understanding of snow–canopy interception processes and the associated influences on the snowpack below, a series of model experiments using a detailed, physically based snow–canopy and snowpack evolution model [Alpine Multiscale Numerical Distributed Simulation Engine (AMUNDSEN)] driven with observed meteorological forcing was conducted. A cone-shaped idealized mountain covered with a geometrically regular pattern of coniferous forest stands and clearings was constructed. The model was applied for three winter seasons with different snowfall intensities and distributions. Results show the effects of snow–canopy processes and interactions on the pattern of ground snow cover, its duration, and the amount of meltwater release, in addition to showing under what conditions the protective effect of a forest canopy overbalances the reduced accumulation of snow on the ground. The simulations show considerable amounts of canopy-intercepted snowfall can sublimate, leading to reduced snow accumulation beneath the forest canopy. In addition, the canopy produces a shadowing effect beneath the trees that leads to reduced radiative energy reaching the ground, reduced below-canopy snowmelt rates, and increased snow-cover duration relative to nonforested areas. During snow-rich winters, the shadowing effect of the canopy dominates and snow lasts longer inside the forest than in the open, but during winters with little snow, snow sublimation losses dominate and snow lasts longer in the open areas than inside the forest. Because of the strong solar radiation influence on snowmelt rates, the details of these relationships vary for northern and southern radiation exposures and time of year. In early and high winter, the radiation protection effect of shadowing by the canopy is small. If little snow is available, an intermittent melt out of the snow cover inside the forest can occur. In late winter and spring, the shadowing effect becomes more efficient and snowmelt is delayed relative to nonforested areas.

Features of snow accumulation and snow cover parameters оn the Elkon mountain rang

2020 ◽  
Vol 26 (7) ◽  
pp. 62-76
Author(s):  
A. Kirillin ◽  
◽  
M. Zheleznyak ◽  
A. Zhirkov ◽  
I. Misailov ◽  
...  
Keyword(s):  
Snow Cover ◽  
Natural Environment ◽  
Industrial Development ◽  
Environmental Changes ◽  
Atmospheric Precipitation ◽  
Snow Accumulation ◽  
Chemical Pollution ◽  
Mountain Range ◽  
Regional Features ◽  
The Subject

With the intensive industrial development of South Yakutia, in particular the Elkon mountain range, the natural environment is experiencing an enormous anthropogenic load. To assess the state of the natural environment, it is important to obtain information about its background state before the start of an intensive technogenic impact. Snow cover seems to be the optimal indicator of chemical pollution of atmospheric air and atmospheric precipitation, as it is one of the significant natural factors that form natural conditions. To take effective preventive measures to eliminate severe consequences, reliable data on the characteristics and conditions of snow cover formation are required. The object of research is the Elkon mountain range, located in the northern part of the Aldan-Stanovoy Upland. The subject is the peculiarities of the formation of snow cover in this region. The purpose of the study is to determine the main meteorological parameters and physical characteristics that affect the conditions for the formation of snow cover. A set of methods was used in the study, including snow survey and routine observations of snow parameters in key areas. As a result of the study, new data were obtained on the regional features of the formation of snow cover. The practical focus of the study is to improve the reliability of engineering-geological and geocryological mapping and forecasting environmental changes

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