scholarly journals Brief communication: Growth and decay of an Ice Stupa in alpine conditions: a simple model driven by energy-flux observations over a glacier surface

2021 ◽  
Author(s):  
Johannes Oerlemans ◽  
Suryanarayanan Balasubramanian ◽  
Conradin Clavuot ◽  
Felix Keller
Keyword(s):  
Energy Balance ◽  
Simple Model ◽  
Snow Cover ◽  
Rough Surface ◽  
Early Spring ◽  
Glacier Surface ◽  
Temperature Changes ◽  
Model Driven ◽  
Simple Tool ◽  
Exposure Factor

Abstract. We present a simple tool to calculate the evolution of an ice stupa (artificial ice reservoir). The model is formulated for a cone geometry and driven by energy balance measurements over a glacier surface for a 5-year period. An “exposure factor” is introduced to deal with the fact that an ice stupa has a very rough surface and is more exposed to wind than a flat glacier surface. The exposure factor enhances the turbulent fluxes.For characteristic alpine conditions at 2100 m, a stupa may reach a height of typically 6 to 10 m in early spring and obtain a volume of 100 to 250 m3 . We also discuss a case where the stupa grows on an inner structure.We show sensitivites of stupa height to temperature changes and exposure factor. Effects of snow cover, switching off water during daytime, different starting dates, etc. can easily be evaluated.

scholarly journals Brief communication: Growth and decay of an ice stupa in alpine conditions – a simple model driven by energy-flux observations over a glacier surface

2021 ◽  
Vol 15 (6) ◽  
pp. 3007-3012
Author(s):  
Johannes Oerlemans ◽  
Suryanarayanan Balasubramanian ◽  
Conradin Clavuot ◽  
Felix Keller
Keyword(s):  
Energy Balance ◽  
Simple Model ◽  
Snow Cover ◽  
Educational Tool ◽  
High Wind ◽  
Glacier Surface ◽  
Temperature Changes ◽  
Model Driven ◽  
Wind Speeds ◽  
Exposure Factor

Abstract. We present a simple model to calculate the evolution of an ice stupa (artificial ice reservoir). The model is formulated for a cone geometry and driven by energy balance measurements over a glacier surface for a 5-year period. An “exposure factor” is introduced to deal with the fact that an ice stupa has a very rough surface and is more exposed to wind than a flat glacier surface. The exposure factor enhances the turbulent fluxes. For characteristic alpine conditions at 2100 m, an ice stupa may reach a volume of 200 to 400 m3 in early April. We show sensitivities of ice stupa size to temperature changes and exposure factor. The model may also serve as an educational tool, with which the effects of snow cover, switching off water during daytime, different starting dates, switching off water during high wind speeds, etc. can easily be evaluated.

scholarly journals EVAPORATION-CONDENSATION AND SNOWMELT MEASUREMENTS IN FINLAND

1974 ◽  
Vol 5 (1) ◽  
pp. 64-74 ◽  
Author(s):  
RISTO LEMMELÄ ◽  
ESKO KUUSISTO
Keyword(s):  
Regression Analysis ◽  
Theoretical Model ◽  
Energy Balance ◽  
Simple Model ◽  
Snow Cover ◽  
Meteorological Factors ◽  
Model Based ◽  
Experimental Field ◽  
Non Linear ◽  
Basic Parameters

Measurements on evaporation and the melting of snow cover are presented, followed by an explanation of how the measured values depend on meteorological factors and the structure of the snow. The observations were made during the period 1968–1973 on an experimental field situated in southern Finland. The regression analysis of the evaporation gave no motive for the use of a non-linear wind function. A theoretical model based on the energy balance has been sought with the aim of explaining snowmelt. However, a simple model containing certain basic parameters gave better results.

scholarly journals Application of an improved surface energy balance model to two large valley glaciers in the St. Elias Mountains, Yukon

2020 ◽  
pp. 1-16
Author(s):  
Tim Hill ◽  
Christine F. Dow ◽  
Eleanor A. Bash ◽  
Luke Copland
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
Shortwave Radiation ◽  
Balance Model ◽  
Landsat 8 ◽  
Glacier Surface ◽  
Ice Dynamics ◽  
Surface Melt

Abstract Glacier surficial melt rates are commonly modelled using surface energy balance (SEB) models, with outputs applied to extend point-based mass-balance measurements to regional scales, assess water resource availability, examine supraglacial hydrology and to investigate the relationship between surface melt and ice dynamics. We present an improved SEB model that addresses the primary limitations of existing models by: (1) deriving high-resolution (30 m) surface albedo from Landsat 8 imagery, (2) calculating shadows cast onto the glacier surface by high-relief topography to model incident shortwave radiation, (3) developing an algorithm to map debris sufficiently thick to insulate the glacier surface and (4) presenting a formulation of the SEB model coupled to a subsurface heat conduction model. We drive the model with 6 years of in situ meteorological data from Kaskawulsh Glacier and Nàłùdäy (Lowell) Glacier in the St. Elias Mountains, Yukon, Canada, and validate outputs against in situ measurements. Modelled seasonal melt agrees with observations within 9% across a range of elevations on both glaciers in years with high-quality in situ observations. We recommend applying the model to investigate the impacts of surface melt for individual glaciers when sufficient input data are available.

scholarly journals Distributed snow and rock temperature modelling in steep rock walls using Alpine3D

2017 ◽  
Vol 11 (1) ◽  
pp. 585-607 ◽  
Author(s):  
Anna Haberkorn ◽  
Nander Wever ◽  
Martin Hoelzle ◽  
Marcia Phillips ◽  
Robert Kenner ◽  
...  
Keyword(s):  
Energy Balance ◽  
Snow Cover ◽  
Snow Depth ◽  
Spatial Scales ◽  
Swiss Alps ◽  
Balance Model ◽  
Near Surface ◽  
Surface Rock ◽  
Depth Data ◽  
Rock Temperature

Abstract. In this study we modelled the influence of the spatially and temporally heterogeneous snow cover on the surface energy balance and thus on rock temperatures in two rugged, steep rock walls on the Gemsstock ridge in the central Swiss Alps. The heterogeneous snow depth distribution in the rock walls was introduced to the distributed, process-based energy balance model Alpine3D with a precipitation scaling method based on snow depth data measured by terrestrial laser scanning. The influence of the snow cover on rock temperatures was investigated by comparing a snow-covered model scenario (precipitation input provided by precipitation scaling) with a snow-free (zero precipitation input) one. Model uncertainties are discussed and evaluated at both the point and spatial scales against 22 near-surface rock temperature measurements and high-resolution snow depth data from winter terrestrial laser scans.In the rough rock walls, the heterogeneously distributed snow cover was moderately well reproduced by Alpine3D with mean absolute errors ranging between 0.31 and 0.81 m. However, snow cover duration was reproduced well and, consequently, near-surface rock temperatures were modelled convincingly. Uncertainties in rock temperature modelling were found to be around 1.6 °C. Errors in snow cover modelling and hence in rock temperature simulations are explained by inadequate snow settlement due to linear precipitation scaling, missing lateral heat fluxes in the rock, and by errors caused by interpolation of shortwave radiation, wind and air temperature into the rock walls.Mean annual near-surface rock temperature increases were both measured and modelled in the steep rock walls as a consequence of a thick, long-lasting snow cover. Rock temperatures were 1.3–2.5 °C higher in the shaded and sunny rock walls, while comparing snow-covered to snow-free simulations. This helps to assess the potential error made in ground temperature modelling when neglecting snow in steep bedrock.

scholarly journals Snow Cover and Snow Persistence Changes in the Mocho-Choshuenco Volcano (Southern Chile) Derived From 35 Years of Landsat Satellite Images

2021 ◽  
Vol 9 ◽  
Author(s):  
Roberto O. Chávez ◽  
Verónica F. Briceño ◽  
José A. Lastra ◽  
Daniel Harris-Pascal ◽  
Sergio A. Estay
Keyword(s):  
Snow Cover ◽  
Satellite Images ◽  
Remote Sensing Data ◽  
Landsat Images ◽  
Microbial Composition ◽  
Mountain Areas ◽  
Pixel Resolution ◽  
Temperature Changes ◽  
Soil Microbial ◽  
Landsat Satellite

Mountain regions have experienced above-average warming in the 20th century and this trend is likely to continue. These accelerated temperature changes in alpine areas are causing reduced snowfall and changes in the timing of snowfall and melt. Snow is a critical component of alpine areas - it drives hibernation of animals, determines the length of the growing season for plants and the soil microbial composition. Thus, changes in snow patterns in mountain areas can have serious ecological consequences. Here we use 35 years of Landsat satellite images to study snow changes in the Mocho-Choshuenco Volcano in the Southern Andes of Chile. Landsat images have 30 m pixel resolution and a revisit period of 16 days. We calculated the total snow area in cloud-free Landsat scenes and the snow frequency per pixel, here called “snow persistence” for different periods and seasons. Permanent snow cover in summer was stable over a period of 30 years and decreased below 20 km2 from 2014 onward at middle elevations (1,530–2,000 m a.s.l.). This is confirmed by negative changes in snow persistence detected at the pixel level, concentrated in this altitudinal belt in summer and also in autumn. In winter and spring, negative changes in snow persistence are concentrated at lower elevations (1,200–1,530 m a.s.l.). Considering the snow persistence of the 1984–1990 period as a reference, the last period (2015–2019) is experiencing a −5.75 km2 reduction of permanent snow area (snow persistence > 95%) in summer, −8.75 km2 in autumn, −42.40 km2 in winter, and −18.23 km2 in spring. While permanent snow at the high elevational belt (>2,000 m a.s.l.) has not changed through the years, snow that used to be permanent in the middle elevational belt has become seasonal. In this study, we use a probabilistic snow persistence approach for identifying areas of snow reduction and potential changes in alpine vegetation. This approach permits a more efficient use of remote sensing data, increasing by three times the amount of usable scenes by including images with spatial gaps. Furthermore, we explore some ecological questions regarding alpine ecosystems that this method may help address in a global warming scenario.

scholarly journals Factors delaying spring runoff in the upper Ürümqi River basin, China

1992 ◽  
Vol 16 ◽  
pp. 225-230 ◽  
Author(s):  
Richard Kattelmann ◽  
Yang Daqing
Keyword(s):  
Snow Cover ◽  
River Basin ◽  
Early Spring ◽  
Ice Formation ◽  
Stream Channels ◽  
Spring Runoff ◽  
Basal Ice ◽  
Interface Growth ◽  
Streamflow Generation ◽  
Soil Interface

Although less than 100 mm of precipitation generally falls during the winter months in the upper Ürümqi River basin, an uneven snowpack of 20 to 100 cm depth is present in early spring. When the surface of this snow cover begins to melt in April, the meltwater is not immediately transformed into streamflow. Several processes are responsible for the five to 15 days of delay in streamflow generation: refreezing in the snow cover itself, creation of a basal ice layer at the snow-soil interface, growth of superimposed ice on the glaciers of the basin, ice formation in stream channels and restoration of high albedo by snowstorms that occur about once a week in spring.

scholarly journals Fast Warming Has Accelerated Snow Cover Loss during Spring and Summer across the Northern Hemisphere over the Past 52 Years (1967–2018)

Atmosphere ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 728
Author(s):  
Xuejiao Wu ◽  
Yongping Shen ◽  
Wei Zhang ◽  
Yinping Long
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Spatial Scales ◽  
Summer Precipitation ◽  
Temperature Changes ◽  
The Past ◽  
Four Seasons ◽  
Snow Cover Extent ◽  
Summer Temperatures ◽  
Substantial Decline

With snow cover changing worldwide in several worrisome ways, it is imperative to determine both the variability in snow cover in greater detail and its relationship with ongoing climate change. Here, we used the satellite-based snow cover extent (SCE) dataset of National Oceanic and Atmospheric Administration (NOAA) to detect SCE variability and its linkages to climate over the 1967–2018 periods across the Northern Hemisphere (NH). Interannually, the time series of SCE across the NH reveal a substantial decline in both spring and summer (−0.54 and −0.71 million km2/decade, respectively), and this decreasing trend corresponded with rising spring and summer temperatures over high-latitude NH regions. Among the four seasons, the temperature rise over the NH was the highest in winter (0.39 °C/decade, p < 0.01). More precipitation in winter was closely related to an increase of winter SCE in mid-latitude areas of NH. Summer precipitation over the NH increased at a significant rate (1.1 mm/decade, p < 0.01), which likely contribute to the accelerated reduction of summer’s SCE across the NH. However, seasonal sensitivity of SCE to temperature changes differed between the Eurasian and North American continents. Thus, this study provides a better understanding of seasonal SCE variability and climatic changes that occurred at regional and hemispheric spatial scales in the past 52 years.

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