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

2010 ◽  
Vol 4 (1) ◽  
pp. 99-113 ◽  
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.

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

2008 ◽  
Vol 2 (4) ◽  
pp. 513-556 ◽  
Author(s):  
M. Bernhardt ◽  
U. Strasser ◽  
G. E. Liston ◽  
W. Mauser
Keyword(s):  
Snow Cover ◽  
Temporal Dynamics ◽  
Transport Model ◽  
Winter Season ◽  
Spatial And Temporal Variability ◽  
Wind Fields ◽  
Remotely Sensed Data ◽  
Mountain Environments ◽  
Penn State ◽  
Snow Transport

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.

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

2016 ◽  
Vol 64 (1) ◽  
pp. 12-22 ◽  
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.

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

2006 ◽  
Vol 3 (6) ◽  
pp. 3655-3673 ◽  
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.

scholarly journals The atmospheric snow-transport model: SnowDrift3D

2011 ◽  
Vol 57 (203) ◽  
pp. 526-542 ◽  
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.

mGEODAR – a new mobile radar for avalanche mass movement monitoring

2021 ◽  
Author(s):  
Anselm Köhler ◽  
Lai Bun Lok ◽  
Jan-Thomas Fischer
Keyword(s):  
High Resolution ◽  
Snow Cover ◽  
Mass Movement ◽  
Winter Season ◽  
Test Site ◽  
Radar Data ◽  
Data Availability ◽  
Low Resolution ◽  
New Device ◽  
Snow Conditions

<p>Radar imaging has become increasingly important in either the detection of avalanches or in the scientific characterization of the avalanche flow. Detection radars usually base on the Doppler radar principle that is sensitive to the velocity of moving object but lack sufficient resolution which can be circumvented with frequency-modulated pulsed radars. We present a new radar device as a follow up of the successful GEODAR radar that suit the need for both applications – low resolution detection and high resolution <span><span>observation</span></span>. While the original GEODAR is permanently installed in the full-scale avalanche Test site “Vallée de la Sionne" in Valais, Switzerland, our new device is much smaller and can be deployed in fast response to the metrological forecast and avalanche situation. Currently the mGEODAR is installed at Nordkette ski resort above Innsbruck that is known for its frequent artificial avalanche releases. The new radar features a versatile frequency generation scheme using direct digital synthesis and can be quickly reprogrammed into a low-resolution detection mode for continuous data recording that switches to a high-resolution <span><span>observation</span></span> mode as soon as an avalanche is detected.</p><p>Beside the radar system itself, avalanche data are presented of the winter season 2020/21. A focus is on small to medium sized avalanches that are just on the limit to develop into a powder snow avalanche which is characterized by surging in the intermittent frontal region. Connecting the radar data of the dynamic flow evolution with snow conditions will lead to drivers of this flow regime transition. The snow conditions are taken from nearby weather stations and manual snow profiles but also from the radar itself. A continuous scanning of the resting snow cover in the avalanche path during the season further allows snow cover monitoring. This application allows to identify new snow fall, warming and wetting of surface layers as well as diurnal melt-freeze cycles.</p><p>The radar data should be consequently used for model validation, calibration, and development. With the current measurement campaign of small to mid-sized avalanches, we hope to close a gap in data availability for those events as they are increasingly the object of simulation scenarios, but current modelling and simulation tools are usually calibrated for larger and extreme events. In the future, we expect the mGEODAR radar to be deploy on other gravitational mass-movements phenomena like soil slides and rock-fall.</p>

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

2007 ◽  
Vol 11 (4) ◽  
pp. 1353-1360 ◽  
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.

scholarly journals Urban Air Quality Modeling Using Low-Cost Sensor Network and Data Assimilation in the Aburrá Valley, Colombia

Atmosphere ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 91
Author(s):  
Santiago Lopez-Restrepo ◽  
Andres Yarce ◽  
Nicolás Pinel ◽  
O.L. Quintero ◽  
Arjo Segers ◽  
...  
Keyword(s):  
Air Quality ◽  
Data Assimilation ◽  
Transport Model ◽  
Cost Model ◽  
Low Cost ◽  
Model Performance ◽  
Monitoring Network ◽  
Correlation Factor ◽  
Chemical Transport Model ◽  
High Quality

The use of low air quality networks has been increasing in recent years to study urban pollution dynamics. Here we show the evaluation of the operational Aburrá Valley’s low-cost network against the official monitoring network. The results show that the PM2.5 low-cost measurements are very close to those observed by the official network. Additionally, the low-cost allows a higher spatial representation of the concentrations across the valley. We integrate low-cost observations with the chemical transport model Long Term Ozone Simulation-European Operational Smog (LOTOS-EUROS) using data assimilation. Two different configurations of the low-cost network were assimilated: using the whole low-cost network (255 sensors), and a high-quality selection using just the sensors with a correlation factor greater than 0.8 with respect to the official network (115 sensors). The official stations were also assimilated to compare the more dense low-cost network’s impact on the model performance. Both simulations assimilating the low-cost model outperform the model without assimilation and assimilating the official network. The capability to issue warnings for pollution events is also improved by assimilating the low-cost network with respect to the other simulations. Finally, the simulation using the high-quality configuration has lower error values than using the complete low-cost network, showing that it is essential to consider the quality and location and not just the total number of sensors. Our results suggest that with the current advance in low-cost sensors, it is possible to improve model performance with low-cost network data assimilation.

scholarly journals Changes in Air Temperature and Snow Cover in Winter in Poland

Atmosphere ◽  
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.

scholarly journals Influence of the aerosol solar extinction on photochemistry during the 2010 Russian wildfires episode

2015 ◽  
Vol 15 (19) ◽  
pp. 10983-10998 ◽  
Author(s):  
J. C. Péré ◽  
B. Bessagnet ◽  
V. Pont ◽  
M. Mallet ◽  
F. Minvielle
Keyword(s):  
Transport Model ◽  
Regional Scale ◽  
Model Performance ◽  
Surface Concentration ◽  
Near Surface ◽  
Aerosol Mass ◽  
Aerosol Mass Concentration ◽  
Air Quality Measurements ◽  
Photolysis Rates ◽  
Optical Module

Abstract. In this work, impact of aerosol solar extinction on the photochemistry over eastern Europe during the 2010 wildfires episode is discussed for the period from 5 to 12 August 2010, which coincides to the peak of fire activity. The methodology is based on an online coupling between the chemistry-transport model CHIMERE (extended by an aerosol optical module) and the radiative transfer code TUV. Results of simulations indicate an important influence of the aerosol solar extinction, in terms of intensity and spatial extent, with a reduction of the photolysis rates of NO2 and O3 up to 50 % (in daytime average) along the aerosol plume transport. At a regional scale, these changes in photolysis rates lead to a 3–15 % increase in the NO2 daytime concentration and to an ozone reduction near the surface of 1–12 %. The ozone reduction is shown to occur over the entire boundary layer, where aerosols are located. Also, the total aerosol mass concentration (PM10) is shown to be decreased by 1–2 %, on average during the studied period, caused by a reduced formation of secondary aerosols such as sulfates and secondary organics (4–10 %) when aerosol impact on photolysis rates is included. In terms of model performance, comparisons of simulations with air quality measurements at Moscow indicate that an explicit representation of aerosols interaction with photolysis rates tend to improve the estimation of the near-surface concentration of ozone and nitrogen dioxide as well as the formation of inorganic aerosol species such as ammonium, nitrates and sulfates.

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