scholarly journals Glacier albedo reduction and drought effects in the extratropical Andes, 1986–2020

2020 ◽  
pp. 1-12
Author(s):  
Thomas E. Shaw ◽  
Genesis Ulloa ◽  
David Farías-Barahona ◽  
Rodrigo Fernandez ◽  
Jose M. Lattus ◽  
...  
Keyword(s):  
Water Security ◽  
Late Summer ◽  
Severe Drought ◽  
Drought Period ◽  
Ice Melt ◽  
Mountain Glaciers ◽  
Snow Covered Area ◽  
Covered Area ◽  
Glacier Ice ◽  
Long Term Trends

Abstract Surface albedo typically dominates the mass balance of mountain glaciers, though long-term trends and patterns of glacier albedo are seldom explored. We calculated broadband shortwave albedo for glaciers in the central Chilean Andes (33–34°S) using end-of-summer Landsat scenes between 1986 and 2020. We found a high inter-annual variability of glacier-wide albedo that is largely a function of the glacier fractional snow-covered area and the total precipitation of the preceding hydrological year (up to 69% of the inter-annual variance explained). Under the 2010–2020 ‘Mega Drought’ period, the mean albedo, regionally averaged ranging from ~0.25–0.5, decreased by −0.05 on average relative to 1986–2009, with the greatest reduction occurring 3500–5000 m a.s.l. In 2020, differences relative to 1986–2009 were −0.14 on average as a result of near-complete absence of late summer snow cover and the driest hydrological year since the Landsat observation period began (~90% reduction of annual precipitation relative to the 1986–2009 period). We found statistically significant, negative trends in glacier ice albedo of up to −0.03 per decade, a trend that would have serious implications for the future water security of the region, because glacier ice melt acts to buffer streamflow shortages under severe drought conditions.

scholarly journals On the effect of short-term climate variability on mountain glaciers: insights from a case study

2013 ◽  
Vol 59 (217) ◽  
pp. 992-1006 ◽  
Author(s):  
Daniel Farinotti
Keyword(s):  
Climatic Variability ◽  
Swiss Alps ◽  
Ice Dynamics ◽  
Mountain Glaciers ◽  
Temperature And Precipitation ◽  
Glacier Ice ◽  
Long Term Trends ◽  
Model Set ◽  
Set Up

AbstractStudies addressing the response of glaciers to climate change have so far analyzed the effect of long-term trends in a particular set of meteorological variables only, implicitly assuming an unaltered climatic variability. Here a framework for distinguishing between year-to-year, month-to-month and day-to-day variability is proposed. Synthetically generated temperature and precipitation time series following the same long-term trend but with altered variability are then used to force an ice-dynamics model set up for Rhonegletscher, Swiss Alps. In the case of temperature, variations in the day-to-day variability are shown to have a larger effect than changes at the yearly scale, while in the case of precipitation, variability changes are assessed as having negligible impact. A first set of scenarios is used to show that compared to reference, doubling the temperature variability can reduce glacier ice volume by up to 64% within half a decade. A second set derived from the results of the European ENSEMBLES project, however, shows that such changes are expected to remain below 8% even for extreme scenarios. Although the latter results relativize the importance of the effect in the near future, the analyses indicate that at least caution is required when assuming ‘unchanged variability’.

scholarly journals Estimation of glacial melt contributions to the Bow River, Alberta, Canada, using a radiation-temperature melt model

2014 ◽  
Vol 55 (66) ◽  
pp. 138-152 ◽  
Author(s):  
Eleanor A. Bash ◽  
Shawn J. Marshall
Keyword(s):  
River Basin ◽  
Surface Air Temperature ◽  
Late Summer ◽  
Radiation Temperature ◽  
Glacier Mass Balance ◽  
Near Surface ◽  
Ice Melt ◽  
Southern Alberta ◽  
Glacier Runoff ◽  
Glacier Ice

AbstractAlberta’s Bow River has its headwaters in the glaciated eastern slopes of the Canadian Rockies and is a major source of water in southern Alberta. Glacial retreat, declining snowpacks and increased water demand are all expected in the coming century, yet there are relatively few studies focusing on quantifying glacial meltwater in the Bow River. We develop a new radiation-temperature melt model for modelling distributed glacier mass balance and runoff in the Bow River basin. The model reflects physical processes through the incorporation of near-surface air temperature and absorbed radiation, while avoiding problems of collinearity through the use of a radiation-decorrelated temperature index. The model is calibrated at Haig Glacier in the southern portion of the basin and validated at Haig and Peyto Glaciers. Application of the model to the entire Bow River basin for 2000-09 shows glacier ice melt is equivalent to 3% of annual discharge in Calgary on average. Modelled ice melt in August is equal to 8-20% of the August Bow River discharge in Calgary. This emphasizes the importance of glacier runoff to late-summer streamflow in the region, particularly in warm, dry years.

Rock glacier impact on high-alpine freshwater chemistry

2020 ◽  
Author(s):  
Ulrike Nickus ◽  
Hansjoerg Thies ◽  
Karl Krainer ◽  
Richard Tessadri
Keyword(s):  
Major Ions ◽  
Stream Water ◽  
Summer Precipitation ◽  
Late Summer ◽  
European Alps ◽  
Rock Glacier ◽  
Ice Melt ◽  
Bedrock Weathering ◽  
Glacier Ice ◽  
Rock Glaciers

<p>Borehole soundings have revealed a warming of mountain permafrost of up to 1°C during recent decades. There is evidence that the increase in air temperature has favored the solute release from active rock glaciers, and pronounced changes in water quality of headwaters in the Alps have been described. Here, we report on solute concentrations of selected streams and springs in the vicinity of an active rock glacier in the Central European Alps (Lazaun, Italy). Stream water sampling started in 2007, and samples were analysed for major ions and heavy metals. We compare surface freshwaters of different origin and chemical characteristics, i.e. outflows of active and fossil rock glaciers, a spring emerging from a moraine and an ice glacier fed stream. Substance concentrations were highest in springs impacted by active rock glaciers, and dissolved ions increased up to a factor of 3 through the summer season. This pattern reflects a seasonally varying contribution to runoff by the melting winter snow pack, summer precipitation, baseflow and ice melt. Intense geochemical bedrock weathering of freshly exposed mineral surfaces, which are due to the downhill movement of the active rock glacier, is considered as a major reason for the high ion and metal concentrations in late summer runoff. In addition, solutes contained in the ice matrix of the rock glacier are released due to enhanced melting of rock glacier ice. On the contrary, minimum substance concentrations without any seasonal variability were found in the moraine spring.</p>

scholarly journals Modelling runoff from a Himalayan debris-covered glacier

2014 ◽  
Vol 11 (2) ◽  
pp. 2441-2482 ◽  
Author(s):  
K. Fujita ◽  
A. Sakai
Keyword(s):  
Thermal Properties ◽  
Air Temperature ◽  
Field Experiments ◽  
Melting Rate ◽  
Ice Melt ◽  
Total Runoff ◽  
Temperature And Precipitation ◽  
Covered Area ◽  
Glacier Ice ◽  
The Impact

Abstract. Although the processes by which glacial debris-mantles alter the melting of glacier ice have been well studied, the mass balance and runoff patterns of Himalayan debris-covered glaciers and the response of these factors to climate change are not well understood. Many previous studies have addressed mechanisms of ice melt under debris mantles by applying multiplicative parameters derived from field experiments, and other studies have calculated the details of heat conduction through the debris layer. However, those approaches cannot be applied at catchment scales because debris distributions are heterogeneous and difficult to measure. Here, we establish a runoff model for a Himalayan debris-covered glacier in which the spatial distribution of the thermal properties of the debris mantle is estimated from remotely sensed multi-temporal data. We validated the model for the Tsho Rolpa Glacial Lake–Trambau Glacier basin in the Nepal Himalaya, using hydro-meteorological observations obtained for a 3.5 yr period (1993–1996). We calculated long-term averages of runoff components for the period 1980–2007 using gridded reanalysis datasets. Our calculations suggest that excess meltwater from the debris-covered area contributes significantly to the total runoff, mainly because of its location at lower elevations. Uncertainties in runoff values due to estimations of the thermal properties and albedo of the debris-covered surface were assessed to be approximately 8% of the runoff from the debris-covered area. We evaluated the sensitivities of runoff components to changes in air temperature and precipitation. As expected, warmer air temperatures increase the total runoff by increasing the melting rate; however, increased precipitation slightly reduces the total runoff, as ice melting is suppressed by the increased snow cover and associated high albedo. The response of total runoff to changing precipitation is complex because of the different responses of individual components (glacier, debris, and ice-free terrain) to precipitation levels. The impact of air temperature on inter-annual variability is 23 times greater than that of precipitation.

scholarly journals Mapping Fluctuations of Hispar Glacier, Karakoram, using Normalized Difference Snow Index (NDSI) and Normalized Difference Principal Component Snow Index (NDSPCSI)

2021 ◽  
Vol 11 (4) ◽  
pp. 48-55
Author(s):  
Nausheen Mazhar ◽  
Dania Amjad ◽  
Kanwal Javid ◽  
Rumana Siddiqui ◽  
Muhammad Ameer Nawaz ◽  
...  
Keyword(s):  
Water Resource Management ◽  
Principal Component ◽  
Maximum Temperature ◽  
Mountain Range ◽  
Snow Covered Area ◽  
Covered Area ◽  
Hazard Zone ◽  
Glacier Ice ◽  
Normalized Difference Snow Index ◽  
Hunza River

Investigation of the fluctuations in the snow-covered area of the major glaciers of the Karakoram range is essential for proper water resource management in Pakistan, since its glaciers are responding differently to the rising temperatures. The objective of this paper is to map snow covered area of Hispar glacier in Hunza river basin for the years 1990, 2010 and 2018. Two techniques, (NDPCSI) Normalized Difference Principal Component Snow Index and (NDSI) Normalized Difference Snow Index were used. Hispar glacier of the Hunza basin has lost 114 km2 of its ice cover area, during the last 28 years, with an alarming annual retreat rate of 1.67 km2 of glacier ice from 1990 to 2018. Hunza basin experienced a +1°C rise in both mean minimum and mean maximum temperature during 2007 to 2018.as a result, Karakorum ice reserves have been affected by rising temperature of the region. Due to temperature rise, retreat of snowcovered area of Hispar, Karakoram mountain range shows a shift in the cryospheric hazard zone.

Improving Runoff Simulations using Satellite-observed Time-series of Snow Covered Area

2003 ◽  
Vol 34 (4) ◽  
pp. 281-294 ◽  
Author(s):  
R.V. Engeset ◽  
H-C. Udnæs ◽  
T. Guneriussen ◽  
H. Koren ◽  
E. Malnes ◽  
...  
Keyword(s):  
Time Series ◽  
Radar Sensors ◽  
Noaa Avhrr ◽  
Runoff Forecasting ◽  
Snow Covered Area ◽  
Covered Area ◽  
Satellite Sensors ◽  
Major Floods ◽  
Using Data ◽  
Southern Norway

Snowmelt can be a significant contributor to major floods, and hence updated snow information is very important to flood forecasting services. This study assesses whether operational runoff simulations could be improved by applying satellite-derived snow covered area (SCA) from both optical and radar sensors. Currently the HBV model is used for runoff forecasting in Norway, and satellite-observed SCA is used qualitatively but not directly in the model. Three catchments in southern Norway are studied using data from 1995 to 2002. The results show that satellite-observed SCA can be used to detect when the models do not simulate the snow reservoir correctly. Detecting errors early in the snowmelt season will help the forecasting services to update and correct the models before possible damaging floods. The method requires model calibration against SCA as well as runoff. Time-series from the satellite sensors NOAA AVHRR and ERS SAR are used. Of these, AVHRR shows good correlation with the simulated SCA, and SAR less so. Comparison of simultaneous data from AVHRR, SAR and Landsat ETM+ for May 2000 shows good inter-correlation. Of a total satellite-observed area of 1,088 km2, AVHRR observed a SCA of 823 km2 and SAR 720 km2, as compared to 889 km2 using ETM+.

scholarly journals Assessment of MERRA-2 and ERA5 to Model the Snow Water Equivalent in the High Atlas (1981–2019)

Water ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 890
Author(s):  
Mohamed Wassim Baba ◽  
Abdelghani Boudhar ◽  
Simon Gascoin ◽  
Lahoucine Hanich ◽  
Ahmed Marchane ◽  
...  
Keyword(s):  
River Discharge ◽  
Snow Water Equivalent ◽  
High Elevation ◽  
Water Runoff ◽  
High Atlas ◽  
Seasonal Snow ◽  
Snow Covered Area ◽  
Covered Area ◽  
Snow Water

Melt water runoff from seasonal snow in the High Atlas range is an essential water resource in Morocco. However, there are only few meteorological stations in the high elevation areas and therefore it is challenging to estimate the distribution of snow water equivalent (SWE) based only on in situ measurements. In this work we assessed the performance of ERA5 and MERRA-2 climate reanalysis to compute the spatial distribution of SWE in the High Atlas. We forced a distributed snowpack evolution model (SnowModel) with downscaled ERA5 and MERRA-2 data at 200 m spatial resolution. The model was run over the period 1981 to 2019 (37 water years). Model outputs were assessed using observations of river discharge, snow height and MODIS snow-covered area. The results show a good performance for both MERRA-2 and ERA5 in terms of reproducing the snowpack state for the majority of water years, with a lower bias using ERA5 forcing.

Improved linear interpolation method for the estimation of snow-covered area from optical data

2002 ◽  
Vol 82 (1) ◽  
pp. 64-78 ◽  
Author(s):  
Sari Metsämäki ◽  
Jenni Vepsäläinen ◽  
Jouni Pulliainen ◽  
Yrjö Sucksdorff
Keyword(s):  
Interpolation Method ◽  
Linear Interpolation ◽  
Optical Data ◽  
Snow Covered Area ◽  
Covered Area ◽  
Linear Interpolation Method

Snow-Covered Area Utilization in Runoff Forecasts

1979 ◽  
Vol 105 (1) ◽  
pp. 53-66
Author(s):  
Albert Rango ◽  
A. Jean Brown ◽  
Michael Rosenzweig ◽  
Jack F. Hannaford ◽  
Roderick L. Hall
Keyword(s):  
Snow Covered Area ◽  
Covered Area

scholarly journals Nimbus-7 SMMR Derived Global Snow Cover Parameters

1987 ◽  
Vol 9 ◽  
pp. 39-44 ◽  
Author(s):  
A.T.C. Chang ◽  
J.L. Foster ◽  
D.K. Hall
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Snow Water Equivalent ◽  
Theoretical Calculations ◽  
Winter Season ◽  
Western China ◽  
High Plains ◽  
Snow Covered Area ◽  
Covered Area ◽  
Snow Water

Snow covers about 40 million km2of the land area of the Northern Hemisphere during the winter season. The accumulation and depletion of snow is dynamically coupled with global hydrological and climatological processes. Snow covered area and snow water equivalent are two essential measurements. Snow cover maps are produced routinely by the National Environmental Satellite Data and Information Service of the National Oceanic and Atmospheric Administration (NOAA/NESDIS) and by the US Air Force Global Weather Center (USAFGWC). The snow covered area reported by these two groups sometimes differs by several million km2, Preliminary analysis is performed to evaluate the accuracy of these products.Microwave radiation penetrating through clouds and snowpacks could provide depth and water equivalent information about snow fields. Based on theoretical calculations, snow covered area and snow water equivalent retrieval algorithms have been developed. Snow cover maps for the Northern Hemisphere have been derived from Nimbus-7 SMMR data for a period of six years (1978–1984). Intercomparisons of SMMR, NOAA/NESDIS and USAFGWC snow maps have been conducted to evaluate and assess the accuracy of SMMR derived snow maps. The total snow covered area derived from SMMR is usually about 10% less than the other two products. This is because passive microwave sensors cannot detect shallow, dry snow which is less than 5 cm in depth. The major geographic regions in which the differences among these three products are the greatest are in central Asia and western China. Future study is required to determine the absolute accuracy of each product.Preliminary snow water equivalent maps have also been produced. Comparisons are made between retrieved snow water equivalent over large area and available snow depth measurements. The results of the comparisons are good for uniform snow covered areas, such as the Canadian high plains and the Russian steppes. Heavily forested and mountainous areas tend to mask out the microwave snow signatures and thus comparisons with measured water equivalent are poorer in those areas.

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