Spatial estimation of snow water equivalent by modeling of the melting of seasonal snow and glacier in Iceland

2021 ◽  
Author(s):  
Andri Gunnarsson ◽  
Sigurður M. Garðarsson ◽  
Tómas Jóhannesson ◽  
Finnur Pálsson
Keyword(s):  
Spatial Distribution ◽  
Energy Balance ◽  
Power System ◽  
Mass Balance ◽  
Snow Cover ◽  
Snow Water Equivalent ◽  
Seasonal Snow ◽  
Glacier Melt ◽  
Fractional Snow Cover ◽  
Snow Water

<p>Runoff from seasonal snow- and glacier melt is critical for hydropower production and reservoir storage in Iceland as the energy system is strongly dependent on summer inflow. The isolation and high natural climate variability can pose a risk to the energy security of the power system as drought conditions and low-flow periods are usually not foreseen in great advance. Forecasting the timing, spatial distribution and magnitude of seasonal melt is a challenge and influences the operational control of energy infrastructure and long-term resource planning. As hydropower generation provides over 72% of the total average energy produced in Iceland, accurate forecasting of seasonal melt is essential for the operation of the national power system.</p><p>In this study, we present results from a spatially-distributed energy-balance model combined with gap-filled satellite-based time series of fractional snow cover and surface albedo from MODIS. The model reconstructs seasonal snow and glacier melt for the Icelandic highlands providing insight into the spatio-temporal distribution of snow water equivalent over the study period.  The reconstruction method uses daily, satellite-derived estimates of fractional snow cover and albedo to scale the melt flux at every pixel. Modeled snow melt was integrated over time, reconstructing the maximum snowpack/glacier melt for each year. The model runs at a 500 m spatial resolution, with a daily timestep from 1 March to 30 September during 2000 to 2019 spanning the general seasonal snow and glacier melt period.</p><p>Energy-balance components were validated with in-situ observations from the Icelandic highlands and a network of stations operated annually at various Icelandic glaciers. Ground-based measurements of snow water equivalent (snow pits, surface mass balance) were used to validate the model performance as well as discharge observations. Simulations indicate a good performance compared with summer glacier mass balance records from Vatnajökull, Hofsjökull, Langjökull and Mýrdalsjökull. Sparse and discontinuous measurements of seasonal snow water equivalent from snow pillows or transects from snow courses were available from a few location, providing limited capabilities for direct validation for seasonal snow. Discharge observations in highland catchments indicate acceptable performance.</p><p>The results allow for quantification of the spatial distribution of snow water equivalent, relationships to elevation and other topographical parameters as well as between basins and years. Discrimination between seasonal snow and glacier melt on a catchment scale is valuable to analyze the annual variability in these two critical hydrological water sources and how they are related.</p>

scholarly journals Evaluation of CLASS Snow Simulation over Eastern Canada

2017 ◽  
Vol 18 (5) ◽  
pp. 1205-1225 ◽  
Author(s):  
Diana Verseghy ◽  
Ross Brown ◽  
Libo Wang
Keyword(s):  
Snow Cover ◽  
Land Surface ◽  
Snow Water Equivalent ◽  
Climate Model ◽  
Regional Climate ◽  
Eastern Canada ◽  
Fractional Snow Cover ◽  
Forest Regions ◽  
Snow Water ◽  
Snow Model

Abstract The Canadian Land Surface Scheme (CLASS), version 3.6.1, was run offline for the period 1990–2011 over a domain centered on eastern Canada, driven by atmospheric forcing data dynamically downscaled from ERA-Interim using the Canadian Regional Climate Model. The precipitation inputs were adjusted to replicate the monthly average precipitation reported in the CRU observational database. The simulated fractional snow cover and the surface albedo were evaluated using NOAA Interactive Multisensor Snow and Ice Mapping System and MODIS data, and the snow water equivalent was evaluated using CMC, Global Snow Monitoring for Climate Research (GlobSnow), and Hydro-Québec products. The modeled fractional snow cover agreed well with the observational estimates. The albedo of snow-covered areas showed a bias of up to −0.15 in boreal forest regions, owing to neglect of subgrid-scale lakes in the simulation. In June, conversely, there was a positive albedo bias in the remaining snow-covered areas, likely caused by neglect of impurities in the snow. The validation of the snow water equivalent was complicated by the fact that the three observation-based datasets differed widely. Also, the downward adjustment of the forcing precipitation clearly resulted in a low snow bias in some regions. However, where the density of the observations was high, the CLASS snow model was deemed to have performed well. Sensitivity tests confirmed the satisfactory behavior of the current parameterizations of snow thermal conductivity, snow albedo refreshment threshold, and limiting snow depth and underlined the importance of snow interception by vegetation. Overall, the study demonstrated the necessity of using a wide variety of observation-based datasets for model validation.

scholarly journals Sensing Area‐Average Snow Water Equivalent with Cosmic‐Ray Neutrons: The Influence of Fractional Snow Cover

2019 ◽  
Vol 55 (12) ◽  
pp. 10796-10812 ◽  
Author(s):  
P. Schattan ◽  
M. Köhli ◽  
M. Schrön ◽  
G. Baroni ◽  
S. E. Oswald
Keyword(s):  
Snow Cover ◽  
Snow Water Equivalent ◽  
Cosmic Ray ◽  
Fractional Snow Cover ◽  
Snow Water

scholarly journals Estimated seasonal snow cover and snowfall in Japan

1993 ◽  
Vol 18 ◽  
pp. 179-184
Author(s):  
Tsutomu Nakamura ◽  
Osamu Abe
Keyword(s):  
Snow Cover ◽  
Snow Depth ◽  
Snow Water Equivalent ◽  
Heavy Snowfall ◽  
Seasonal Snow ◽  
Snow Covered Area ◽  
Covered Area ◽  
Prone Area ◽  
Snow Water ◽  
Seasonal Snow Cover

The average amounts of seasonal snow cover and snowfall in Japan were calculated as 7.9 × 1013kg and 1.2 × 1014kg, respectively. The mass of seasonal snow cover of a heavy-snowfall winter, 1980–81 (56-Gosetsu), was calculated as 1.3 × 1014kg. The amount of 7.9 × 1013kg was converted to water equivalent of 230 mm on the whole snow-covered area, including snow-prone area. A mean of 370 mm in snow water equivalent was calculated for the snow area where mean snow depth on the ground was more than 10 cm.

scholarly journals Spatio-temporal variability of snow water equivalent in the extra-tropical Andes Cordillera from distributed energy balance modeling and remotely sensed snow cover

2016 ◽  
Vol 20 (1) ◽  
pp. 411-430 ◽  
Author(s):  
E. Cornwell ◽  
N. P. Molotch ◽  
J. McPhee
Keyword(s):  
Energy Balance ◽  
Snow Cover ◽  
Snow Water Equivalent ◽  
Remotely Sensed ◽  
Snow Accumulation ◽  
Model Assessment ◽  
Continental Divide ◽  
Average Maximum ◽  
Snow Water ◽  
Andes Cordillera

Abstract. Seasonal snow cover is the primary water source for human use and ecosystems along the extratropical Andes Cordillera. Despite its importance, relatively little research has been devoted to understanding the properties, distribution and variability of this natural resource. This research provides high-resolution (500 m), daily distributed estimates of end-of-winter and spring snow water equivalent over a 152 000 km2 domain that includes the mountainous reaches of central Chile and Argentina. Remotely sensed fractional snow-covered area and other relevant forcings are combined with extrapolated data from meteorological stations and a simplified physically based energy balance model in order to obtain melt-season melt fluxes that are then aggregated to estimate the end-of-winter (or peak) snow water equivalent (SWE). Peak SWE estimates show an overall coefficient of determination R2 of 0.68 and RMSE of 274 mm compared to observations at 12 automatic snow water equivalent sensors distributed across the model domain, with R2 values between 0.32 and 0.88. Regional estimates of peak SWE accumulation show differential patterns strongly modulated by elevation, latitude and position relative to the continental divide. The spatial distribution of peak SWE shows that the 4000–5000 m a.s.l. elevation band is significant for snow accumulation, despite having a smaller surface area than the 3000–4000 m a.s.l. band. On average, maximum snow accumulation is observed in early September in the western Andes, and in early October on the eastern side of the continental divide. The results presented here have the potential of informing applications such as seasonal forecast model assessment and improvement, regional climate model validation, as well as evaluation of observational networks and water resource infrastructure development.

scholarly journals Estimated seasonal snow cover and snowfall in Japan

1993 ◽  
Vol 18 ◽  
pp. 179-184
Author(s):  
Tsutomu Nakamura ◽  
Osamu Abe
Keyword(s):  
Snow Cover ◽  
Snow Depth ◽  
Snow Water Equivalent ◽  
Heavy Snowfall ◽  
Seasonal Snow ◽  
Snow Covered Area ◽  
Covered Area ◽  
Prone Area ◽  
Snow Water ◽  
Seasonal Snow Cover

The average amounts of seasonal snow cover and snowfall in Japan were calculated as 7.9 × 1013kg and 1.2 × 1014kg, respectively. The mass of seasonal snow cover of a heavy-snowfall winter, 1980–81 (56-Gosetsu), was calculated as 1.3 × 1014kg. The amount of 7.9 × 1013kg was converted to water equivalent of 230 mm on the whole snow-covered area, including snow-prone area. A mean of 370 mm in snow water equivalent was calculated for the snow area where mean snow depth on the ground was more than 10 cm.

scholarly journals Application of Georadar for Snow Cover Surveying

1998 ◽  
Vol 29 (4-5) ◽  
pp. 361-370 ◽  
Author(s):  
Knut Sand ◽  
Oddbjørn Bruland
Keyword(s):  
Spatial Distribution ◽  
Snow Cover ◽  
Snow Depth ◽  
Snow Water Equivalent ◽  
Good Description ◽  
Areal Distribution ◽  
Snow Water

A commercial georadar was tested over in a Norwegian catchment in order to determine the areal mean snow water equivalent (SWE) and its spatial distribution. The methodology used and the results obtained are described. The radar was run along a number of selected snow courses, and the results were compared with manual measurements of snow depth and density. It was found that georadar is able to give accurate estimates of mean SWE with much less time spent in the field compared to conventional measurements. Georadar also gave a good description of the areal distribution of SWE.

Monitoring snowpack evolution with meteorological reanalysis data in the Atlas Mountains

2021 ◽  
Author(s):  
Wassim Mohamed Baba ◽  
Abdelghani Boudhar ◽  
Simon Gascoin ◽  
Lahoucine Hanich ◽  
Ahmed Marchane ◽  
...  
Keyword(s):  
Snow Cover ◽  
Snow Water Equivalent ◽  
Growing Season ◽  
Reanalysis Data ◽  
Water Runoff ◽  
Snow Cover Area ◽  
Seasonal Snow ◽  
Atlas Mountains ◽  
Snow Water ◽  
Seasonal Snow Cover

<p>The seasonal snow cover in the Altas mountains of Morocco is an important resource, mostly because it provides melt-water runoff for irrigation during the crop growing season. However, the knowledge on physical properties of the snowpack (e.g., snow water equivalent (SWE) and snowmelt) is still very limited due to the scarcity or the lack of ground measurements in the elevated area. In this study we suggest that the recent progresses of meteorological reanalysis data (e.g., MERRA-2 and ERA-5) open new perspectives to overcome this issue. We fed a distributed snowpack evolution model (SnowModel) with downscaled ERA-5 and MERRA-2 reanalyses and evaluate their performance to simulate snow cover. The modeling covers the period 1981 to 2019 (37 water years). SnowModel simulations were assessed using observations of river discharge, snow height and snow cover area derived from MODIS.</p><p>For most of hydrological years, the results show a good performance for both MERRA-2 and ERA-5 with a slight superiority of ERA-5, to reproduce the snowpack state.</p><p><strong>Key words</strong>: snow, snow water equivalent, reanalysis , MERRA-2, ERA-5</p>

Seasonal snow accumulation in the mid-latitude forested catchment

Biologia ◽  
2014 ◽  
Vol 69 (11) ◽  
Author(s):  
Václav Šípek ◽  
Miroslav Tesař
Keyword(s):  
Snow Cover ◽  
Forest Canopy ◽  
Forest Cover ◽  
Snow Water Equivalent ◽  
Elevation Gradient ◽  
Snow Accumulation ◽  
Forested Catchment ◽  
Seasonal Snow ◽  
Snow Water ◽  
Fagus Sylvatica L

AbstractThe study deals with the snow cover characteristics (snow depth — SD and snow water equivalent — SWE) concerning the mid-latitude forested catchment. Namely, the influence of the forest canopy (Picea abies (L.) Karst. and Fagus sylvatica L.) and altitude (ranging from 835 m a.s.l. to 1118 m a.s.l.) was investigated. Forest cover was proved to have a significant influence on the snow cover accumulation, reducing SWE by 50 % on average, compared to open sites. The elevation gradient concerning SWE ranged from 30 to 40 mm and from 5 to 20 mm per 100 m in open and forested sites, respectively. Its magnitude was found to be temporarily variable and positively related to the total seasonal snowfall amount. The SWE/SD variability among measurement sites (with different altitude) was higher in open sites compared to forested ones. The catchment SWE/SD variability increases significantly in the snowmelt period (March–April) both in open and forested locations. The differences among snow interception losses, concerning various elevations and the forest canopy, were not statistically significant.

scholarly journals Spatio-temporal variability of snow water equivalent in the extra-tropical Andes cordillera from a distributed energy balance modeling and remotely sensed snow cover

2015 ◽  
Vol 12 (9) ◽  
pp. 8927-8976
Author(s):  
E. Cornwell ◽  
N. P. Molotch ◽  
J. McPhee
Keyword(s):  
Energy Balance ◽  
Snow Cover ◽  
Water Resource ◽  
Snow Water Equivalent ◽  
Remotely Sensed ◽  
Snow Accumulation ◽  
Model Domain ◽  
Continental Divide ◽  
Snow Water ◽  
Andes Cordillera

Abstract. Seasonal snow cover is the primary water resource precursor for human use and environmental sustain along the extratropical Andes Cordillera. Despite its importance, relatively little research has been devoted to understanding the properties, distribution and variability of this natural resource. This research provides high-resolution distributed estimates of end-of-winter and spring snow water equivalent over a 152 000 km2 domain that includes the mountainous reaches of central Chile and Argentina. Remotely sensed fractional snow covered area and other relevant forcings are combined with extrapolated data from meteorological stations and a simplified physically-based energy balance model in order to obtain melt-season peak SWE. Estimates show an overall coefficient of determination R2 of 0.61 compared to observations at 12 automatic snow water equivalent sensors distributed across the model domain, with R2 values between 0.32 and 0.88. Regional estimates of peak SWE accumulation show differential patterns strongly modulated by elevation, latitude and position relative to the continental divide. Average peak SWE increases by nearly 500 mm for every 1000 m in elevation gain for the central and southern sub-regions of the model domain, but this effect is much less pronounced in the northern reaches. The 3000–4000 m a.s.l. elevation band is the most significant accumulation area for most of the northern and central reaches of the domain, although the 4000–5000 m a.s.l. band, despite a smaller contributing area, almost doubles the accumulation amounts estimated for the lower adjacent subdomain. Snow accumulation reaches an earlier peak in the western Andes, and the eastern side of the continental divide shows lower snow accumulation at all elevations except for the southern region represented by the Neuquén River Basin. The results presented here have the potential of informing applications such as seasonal forecast model assessment and improvement, regional climate model validation, as well as evaluation of observational networks and water resource infrastructure development.

scholarly journals The Spatiotemporal Patterns and Interrelationships of Snow Cover and Climate Change in Tianshan Mountains

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 404
Author(s):  
Tong Heng ◽  
Xinlin He ◽  
Lili Yang ◽  
Jiawen Yu ◽  
Yulin Yang ◽  
...  
Keyword(s):  
Snow Cover ◽  
Snow Water Equivalent ◽  
Warming Trend ◽  
Tianshan Mountains ◽  
Spatiotemporal Patterns ◽  
Tianshan Mountain ◽  
Mountainous Areas ◽  
The Future ◽  
Snow Water ◽  
Nighttime Warming

To reveal the spatiotemporal patterns of the asymmetry in the Tianshan mountains’ climatic warming, in this study, we analyzed climate and MODIS snow cover data (2001–2019). The change trends of asymmetrical warming, snow depth (SD), snow coverage percentage (SCP), snow cover days (SCD) and snow water equivalent (SWE) in the Tianshan mountains were quantitatively determined, and the influence of asymmetrical warming on the snow cover activity of the Tianshan mountains were discussed. The results showed that the nighttime warming rate (0.10 °C per decade) was greater than the daytime, and that the asymmetrical warming trend may accelerate in the future. The SCP of Tianshan mountain has reduced by 0.9%. This means that for each 0.1 °C increase in temperature, the area of snow cover will reduce by 5.9 km2. About 60% of the region’s daytime warming was positively related to SD and SWE, and about 48% of the region’s nighttime warming was negatively related to SD and SWE. Temperature increases were concentrated mainly in the Pamir Plateau southwest of Tianshan at high altitudes and in the Turpan and Hami basins in the east. In the future, the western and eastern mountainous areas of the Tianshan will continue to show a warming trend, while the central mountainous areas of the Tianshan mountains will mainly show a cooling trend.

Sign in / Sign up

Export Citation Format

Share Document