High resolution modelling of snow transport in complex terrain using simulated wind fields

Abstract. Snow transport is one of the most dominant processes influencing the snow cover accumulation and ablation in high alpine mountain environments. Hence, the spatial and temporal variability of the snow cover is significantly modified with respective consequences on the total amount of water in the snow pack, on the temporal dynamics of the runoff and on the energy balance of the surface. For the presented study we used the snow transport model SnowTran-3D in combination with MM5 (Penn State University – National Center for Atmospheric Research MM5 model) generated wind fields. In a first step the MM5 wind fields were downscaled by using a semi-empirical approach which accounts for the elevation difference of model and real topography, as well as aspect, inclination and vegetation. The target resolution of 30 m corresponds to the resolution of the best available DEM and land cover map. For the numerical modelling, data of six automatic meteorological stations were used, comprising the winter season (September–August) of 2003/04 and 2004/05. In addition we had automatic snow depth measurements and periodic manual measurements of snow courses available for the validation of the results. In this paper we describe the downscaling of the wind fields and discuss the results of the snow transport simulations with respect to the measurements and remotely sensed data.

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High resolution modelling of snow transport in complex terrain using downscaled MM5 wind fields

The Cryosphere ◽

10.5194/tc-4-99-2010 ◽

2010 ◽

Vol 4 (1) ◽

pp. 99-113 ◽

Cited By ~ 38

Author(s):

M. Bernhardt ◽

G. E. Liston ◽

U. Strasser ◽

G. Zängl ◽

K. Schulz

Keyword(s):

Snow Cover ◽

Temporal Dynamics ◽

Transport Model ◽

Winter Season ◽

Model Performance ◽

Test Site ◽

High Mountain ◽

Spatial And Temporal Variability ◽

Wind Fields ◽

Snow Transport

Abstract. Snow transport is one of the most dominant processes influencing the snow cover accumulation and ablation in high mountain environments. Hence, the spatial and temporal variability of the snow cover is significantly modified with respective consequences on the total amount of water in the snow pack, on the temporal dynamics of the runoff and on the energy balance of the surface. For the present study we used the snow transport model SnowModel in combination with MM5 (Penn State University – National Center for Atmospheric Research MM5 model) generated wind fields. In a first step the MM5 wind fields were downscaled by using a semi-empirical approach which accounts for the elevation difference of model and real topography, and vegetation. The target resolution of 30 m corresponds to the resolution of the best available DEM and land cover map of the test site Berchtesgaden National Park. For the numerical modelling, data of six automatic meteorological stations were used, comprising the winter season (September–August) of 2003/04 and 2004/05. In addition we had automatic snow depth measurements and periodic manual measurements of snow courses available for the validation of the results. It could be shown that the model performance of SnowModel could be improved by using downscaled MM5 wind fields for the test site. Furthermore, it was shown that an estimation of snow transport from surrounding areas to glaciers becomes possible by using downscaled MM5 wind fields.

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Shortwave Radiative Fluxes on Slopes

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-15-0178.1 ◽

2016 ◽

Vol 55 (7) ◽

pp. 1513-1532

Author(s):

Yingtao Ma ◽

Rachel T. Pinker ◽

Margaret M. Wonsick ◽

Chuan Li ◽

Laura M. Hinkelman

Keyword(s):

United States ◽

Snow Cover ◽

Spatial Resolution ◽

Snow Water Equivalent ◽

The United States ◽

Spatial And Temporal Variability ◽

Remotely Sensed Data ◽

Radiative Fluxes ◽

Attractive Option ◽

Moderate Resolution Imaging Spectroradiometer

AbstractSnow-covered mountain ranges are a major source of water supply for runoff and groundwater recharge. Snowmelt supplies as much as 75% of the surface water in basins of the western United States. Net radiative fluxes make up about 80% of the energy balance over snow-covered surfaces. Because of the large extent of snow cover and the scarcity of ground observations, use of remotely sensed data is an attractive option for estimating radiative fluxes. Most of the available methods have been applied to low-spatial-resolution satellite observations that do not capture the spatial variability of snow cover, clouds, or aerosols, all of which need to be accounted for to achieve accurate estimates of surface radiative fluxes. The objective of this study is to use high-spatial-resolution observations that are available from the Moderate Resolution Imaging Spectroradiometer (MODIS) to derive surface shortwave (0.2–4.0 μm) downward radiative fluxes in complex terrain, with attention on the effect of topography (e.g., shadowing or limited sky view) on the amount of radiation received. The developed method has been applied to several typical melt seasons (January–July during 2003, 2004, 2005, and 2009) over the western part of the United States, and the available information was used to derive metrics on spatial and temporal variability of shortwave fluxes. Issues of scale in both the satellite and ground observations are also addressed to illuminate difficulties in the validation process of satellite-derived quantities. It is planned to apply the findings from this study to test improvements in estimation of snow water equivalent.

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Variability of snow line elevation, snow cover area and depletion in the main Slovak basins in winters 2001–2014

Journal of Hydrology and Hydromechanics ◽

10.1515/johh-2016-0011 ◽

2016 ◽

Vol 64 (1) ◽

pp. 12-22 ◽

Cited By ~ 9

Author(s):

Pavel Krajčí ◽

Ladislav Holko ◽

Juraj Parajka

Keyword(s):

Snow Cover ◽

Winter Season ◽

High Mountain ◽

Spatial And Temporal Variability ◽

Considerable Variability ◽

Snow Cover Area ◽

The Third ◽

Snow Line ◽

Maximum Elevation ◽

Basin Elevation

Abstract Spatial and temporal variability of snow line (SL) elevation, snow cover area (SCA) and depletion (SCD) in winters 2001–2014 is investigated in ten main Slovak river basins (the Western Carpathians). Daily satellite snow cover maps from MODIS Terra (MOD10A1, V005) and Aqua (MYD10A1, V005) with resolution 500 m are used. The results indicate three groups of basins with similar variability in the SL elevation. The first includes basins with maximum elevations above 1500 m a.s.l. (Poprad, Upper Váh, Hron, Hornád). Winter median SL is equal or close to minimum basin elevation in snow rich winters in these basins. Even in snow poor winters is SL close to the basin mean. Second group consists of mid-altitude basins with maximum elevation around 1000 m a.s.l. (Slaná, Ipeľ, Nitra, Bodrog). Median SL varies between 150 and 550 m a.s.l. in January and February, which represents approximately 40–80% snow coverage. Median SL is near the maximum basin elevation during the snow poor winters. This means that basins are in such winters snow free approximately 50% of days in January and February. The third group includes the Rudava/Myjava and Lower Váh/Danube. These basins have their maximum altitude less than 700 m a.s.l. and only a small part of these basins is covered with snow even during the snow rich winters. The evaluation of SCA shows that snow cover typically starts in December and last to February. In the highest basins (Poprad, Upper Váh), the snow season sometimes tends to start earlier (November) and lasts to March/April. The median of SCA is, however, less than 10% in these months. The median SCA of entire winter season is above 70% in the highest basins (Poprad, Upper Váh, Hron), ranges between 30–60% in the mid-altitude basins (Hornád, Slaná, Ipeľ, Nitra, Bodrog) and is less than 1% in the Myjava/Rudava and Lower Váh/Danube basins. However, there is a considerable variability in seasonal coverage between the years. Our results indicate that there is no significant trend in mean SCA in the period 2001–2014, but periods with larger and smaller SCA exist. Winters in the period 2002–2006 have noticeably larger mean SCA than those in the period 2007–2012. Snow depletion curves (SDC) do not have a simple evolution in most winters. The snowmelt tends to start between early February and the end of March. The snowmelt lasts between 8 and 15 days on average in lowland and high mountain basins, respectively. Interestingly, the variability in SDC between the winters is much larger than between the basins.

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Commentary on comparison of MODIS snow cover and albedo products with ground observations over the mountainous terrain of Turkey

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-3-3655-2006 ◽

2006 ◽

Vol 3 (6) ◽

pp. 3655-3673 ◽

Cited By ~ 3

Author(s):

A. Ü. Şorman ◽

Z. Akyürek ◽

A. Şensoy ◽

A. A. Şorman ◽

A. E. Tekeli

Keyword(s):

Snow Cover ◽

Snow Depth ◽

Snow Water Equivalent ◽

Winter Season ◽

Spatial And Temporal Variability ◽

Mountainous Terrain ◽

Mountainous Regions ◽

In Situ Data ◽

Snow Cover Extent

Abstract. The MODerate-resolution Imaging Spectroradiometer (MODIS) snow cover product was evaluated by Parajka and Blösch (2006) over the territory of Austria. The spatial and temporal variability of the MODIS snow product classes are analyzed, the accuracy of the MODIS snow product against numerous in situ snow depth data are examined and the main factors that may influence the MODIS classification accuracy are identified in their studies. The authors of this paper would like to provide more discussion to the scientific community on the "Validation of MODIS snow cover images" when similar methodology is applied to mountainous regions covered with abundant snow but with limited number of ground survey and automated stations. Daily snow cover maps obtained from MODIS images are compared with ground observations in mountainous terrain of Turkey for the winter season of 2002–2003 and 2003–2004 during the accumulation and ablation periods of snow. Snow depth and density values are recorded to determine snow water equivalent values at 19 points in and around the study area in Turkey. Comparison of snow maps with in situ data show good agreement with overall accuracies in between 62 to 82 percent considering a 2-day shift during cloudy days. Studies show that the snow cover extent can be used for forecasting of runoff hydrographs resulting mostly from snowmelt for a mountainous basin in Turkey. MODIS-Terra snow albedo products are also compared with ground based measurements over the ablation stage of 2004 using the automated weather operating stations (AWOS) records at fixed locations as well as from the temporally assessed measuring sites during the passage of the satellite. Temporarily assessed 20 ground measurement sites are randomly distributed around one of the AWOS stations and both MODIS and ground data were aggregated in GIS for analysis. Reduction in albedo is noticed as snow depth decreased and SWE values increased.

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The atmospheric snow-transport model: SnowDrift3D

Journal of Glaciology ◽

10.3189/002214311796905677 ◽

2011 ◽

Vol 57 (203) ◽

pp. 526-542 ◽

Cited By ~ 22

Author(s):

Simon Schneiderbauer ◽

Alexander Prokop

Keyword(s):

High Resolution ◽

Laser Scanning ◽

Transport Model ◽

Weather Prediction ◽

Shear Velocity ◽

Numerical Weather Prediction Model ◽

Wind Fields ◽

Atmospheric Particle ◽

Local Erosion ◽

Snow Transport

AbstractSnowDrift3D, a high-resolution, atmospheric snow-transport model, is presented for the first time. In contrast to most state-of-the-art snowdrift models, atmospheric particle transport, i.e. saltation and suspension, is accounted for by one passive transport equation. The model uses unsteady wind fields (spatial resolution of up to 2 m) computed with an atmospheric computational fluid dynamics model that is directly connected to the numerical weather prediction model ALADIN. Sensitivity runs show that (1) the saltation mass flux is a function of cubic shear velocity, , (2) the model is marginally sensitive to the grid spacing at high resolutions (up to 2 m), (3) the model computes the redistribution of snow at high resolution in real time on dual core personal computers and (4) the changing topography of the snow cover should be included in cases of local erosion or deposition of a large amount of snow. Finally, we present a comparison of modeled and measured snow distributions obtained by terrestrial laser scanning showing area-wide linear correlation up to R = 0.33.

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Commentary on comparison of MODIS snow cover and albedo products with ground observations over the mountainous terrain of Turkey

Hydrology and Earth System Sciences ◽

10.5194/hess-11-1353-2007 ◽

2007 ◽

Vol 11 (4) ◽

pp. 1353-1360 ◽

Cited By ~ 39

Author(s):

A. Ü. Şorman ◽

Z. Akyürek ◽

A. Şensoy ◽

A. A. Şorman ◽

A. E. Tekeli

Keyword(s):

Snow Cover ◽

Snow Depth ◽

Snow Water Equivalent ◽

Winter Season ◽

Spatial And Temporal Variability ◽

Mountainous Terrain ◽

Mountainous Regions ◽

In Situ Data ◽

Snow Cover Extent

Abstract. The MODerate-resolution Imaging Spectroradiometer (MODIS) snow cover product was evaluated by Parajka and Blösch (2006) over the territory of Austria. The spatial and temporal variability of the MODIS snow product classes are analyzed, the accuracy of the MODIS snow product against numerous in situ snow depth data are examined and the main factors that may influence the MODIS classification accuracy are identified in their studies. The authors of this paper would like to provide more discussion to the scientific community on the "Validation of MODIS snow cover images" when similar methodology is applied to mountainous regions covered with abundant snow but with limited number of ground survey and automated stations. Daily snow cover maps obtained from MODIS images are compared with ground observations in mountainous terrain of Turkey for the winter season of 2002–2003 and 2003–2004 during the accumulation and ablation periods of snow. Snow depth and density values are recorded to determine snow water equivalent (SWE) values at 19 points in and around the study area in Turkey. Comparison of snow maps with in situ data show good agreement with overall accuracies in between 62 to 82 percent considering a 2-day shift during cloudy days. Studies show that the snow cover extent can be used for forecasting of runoff hydrographs resulting mostly from snowmelt for a mountainous basin in Turkey. MODIS-Terra snow albedo products are also compared with ground based measurements over the ablation stage of 2004 using the automated weather operating stations (AWOS) records at fixed locations as well as from the temporally assessed measuring sites during the passage of the satellite. Temporarily assessed 20 ground measurement sites are randomly distributed around one of the AWOS stations and both MODIS and ground data were aggregated in GIS for analysis. Reduction in albedo is noticed as snow depth decreased and SWE values increased.

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Evaluation of spatial and temporal variability of snow cover in a large mountainous basin in Iran

Hydrology Research ◽

10.2166/nh.2007.027 ◽

2007 ◽

Vol 38 (1) ◽

pp. 45-58 ◽

Cited By ~ 9

Author(s):

M. Reza Ghanbarpour ◽

Bahram Saghafian ◽

Mohsen M. Saravi ◽

Karim C. Abbaspour

Keyword(s):

Snow Cover ◽

Temporal Variability ◽

Large Scale ◽

Meteorological Data ◽

Remotely Sensed ◽

Important Variable ◽

Balance Model ◽

Spatial And Temporal Variability ◽

Remotely Sensed Data ◽

Mountainous Basin

Determination of snow characteristics in mountainous basins is difficult due to the complex spatial and temporal variability of snow cover. Accurate representation of snow cover variations in space and time is an important factor in snowmelt modeling, hydrological forecasts, water resources planning, and drought management. This study demonstrates how remotely sensed data can complement the measurements of ground hydro-meteorological data to simulate the spatial and temporal variations of snow cover characteristics in a mountainous basin. In this paper, we studied Karun basin, located in the south west of Iran, because of its importance in accumulating large snow reserves, and subsequently contributing snowmelt to the total runoff. Snow cover variability was simulated by extraction of maps of snow cover indices using remotely sensed data. Contribution of snowmelt to the runoff was determined using a seasonal water balance model as well as estimations based on indirect approaches by modeling variables such as critical temperature, which is an important variable in snow studies. Agreement between indirect approaches used in this paper is an encouraging result that shows the reliability of the procedure where snow data is scarce. The results of correlation analysis between topographic and meteorological variables with snow cover indices suggested that elevation is the single most important variable on large-scale snow variability.

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Changes in Air Temperature and Snow Cover in Winter in Poland

Atmosphere ◽

10.3390/atmos12010068 ◽

2021 ◽

Vol 12 (1) ◽

pp. 68

Author(s):

Arkadiusz M. Tomczyk ◽

Ewa Bednorz ◽

Katarzyna Szyga-Pluta

Keyword(s):

Snow Cover ◽

Air Temperature ◽

Winter Season ◽

Primary Objective ◽

Climatic Conditions ◽

Cover Depth ◽

North Eastern ◽

Northern Regions ◽

Maximum Air Temperature ◽

Snow Cover Depth

The primary objective of the paper was to characterize the climatic conditions in the winter season in Poland in the years 1966/67–2019/20. The study was based on daily values of minimum (Tmin) and maximum air temperature (Tmax), and daily values of snow cover depth. The study showed an increase in both Tmin and Tmax in winter. The most intensive changes were recorded in north-eastern and northern regions. The coldest winters were recorded in the first half of the analyzed multiannual period, exceptionally cold being winters 1969/70 and 1984/85. The warmest winters occurred in the second half of the analyzed period and among seasons with the highest mean Tmax, particularly winters 2019/20 and 1989/90 stood out. In the study period, a decrease in snow cover depth statistically significant in the majority of stations in Poland was determined, as well as its variability both within the winter season and multiannual.

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Assessment of changes in the state of the rangelands of Inner Mongolia, China between 1998 and 2007 using remotely sensed data

The Rangeland Journal ◽

10.1071/rj11055 ◽

2012 ◽

Vol 34 (1) ◽

pp. 103 ◽

Cited By ~ 5

Author(s):

Z. M. Hu ◽

S. G. Li ◽

J. W. Dong ◽

J. W. Fan

Keyword(s):

Inner Mongolia ◽

Vegetation Index ◽

Net Primary Productivity ◽

Temporal Dynamics ◽

Remotely Sensed ◽

The State ◽

Mean Annual Precipitation ◽

Aboveground Net Primary Productivity ◽

Remotely Sensed Data ◽

Normalised Difference Vegetation Index

The spatial annual patterns of aboveground net primary productivity (ANPP) and precipitation-use efficiency (PUE) of the rangelands of the Inner Mongolia Autonomous Region of China, a region in which several projects for ecosystem restoration had been implemented, are described for the years 1998–2007. Remotely sensed normalised difference vegetation index and ANPP data, measured in situ, were integrated to allow the prediction of ANPP and PUE in each 1 km2 of the 12 prefectures of Inner Mongolia. Furthermore, the temporal dynamics of PUE and ANPP residuals, as indicators of ecosystem deterioration and recovery, were investigated for the region and each prefecture. In general, both ANPP and PUE were positively correlated with mean annual precipitation, i.e. ANPP and PUE were higher in wet regions than in arid regions. Both PUE and ANPP residuals indicated that the state of the rangelands of the region were generally improving during the period of 2000–05, but declined by 2007 to that found in 1999. Among the four main grassland-dominated prefectures, the recovery in the state of the grasslands in the Erdos and Chifeng prefectures was highest, and Xilin Gol and Chifeng prefectures was 2 years earlier than Erdos and Hunlu Buir prefectures. The study demonstrated that the use of PUE or ANPP residuals has some limitations and it is proposed that both indices should be used together with relatively long-term datasets in order to maximise the reliability of the assessments.

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The optical behaviour of snow during a melting season at Ny Ålesund (Svalbard, Norway)

10.5194/egusphere-egu21-14667 ◽

2021 ◽

Author(s):

Roberto Salzano ◽

Christian Lanconelli ◽

Giulio Esposito ◽

Marco Giusto ◽

Mauro Montagnoli ◽

...

Keyword(s):

Climate Change ◽

Snow Cover ◽

Full Range ◽

Time Lapse ◽

Test Site ◽

Remotely Sensed ◽

Optical Behaviour ◽

Remotely Sensed Data ◽

Snow Cover Area ◽

Significant Information

Polar areas are the most sensitive targets of the climate change and the continuous monitoring of the cryosphere represents a critical issue. The satellite remote sensing can fill this gap but further integration between remotely-sensed multi-spectral images and field data is crucial to validate retrieval algorithms and climatological models. The optical behaviour of snow, at different wavelengths, provides significant information about the micro-physical characteristics of the surface and this allow to discriminate different snow/ice covers. The aim of this work is to present an approach based on combining unmanned observations on spectral albedo and on the analysis of time-lapse images of sky and ground conditions in an Arctic test-site (Svalbard, Norway). Terrestrial photography can provide, in fact, important information about the cloud cover and support the discrimination between white-sky or clear-sky illuminating conditions. Similarly, time-lapse cameras can provide a detailed description of the snow cover, estimating the fractional snow cover area. The spectral albedo was obtained by a narrow band device that was compared to a full-range commercial system and to remotely sensed data acquired during the 2015 spring/summer period at the Amundsen - Nobile Climate Change Tower (Ny &#197;lesund). The results confirmed the possibility to have continuous observations of the snow surface (microphisical) characteristics and highlighted the opportunity to monitor the spectral variations of snowed surfaces during the melting period. It was possible, therefore, to estimate spectral indexes, such as NDSI and SWIR albedo, and to found interesting links between both features and air/ground temperatures, wind-speed and precipitations. Different melting phases were detected and different processes were associated with the observed spectral variations.

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