scholarly journals Sensitivities and uncertainties of modeled ground temperatures in mountain environments

2013 ◽  
Vol 6 (1) ◽  
pp. 791-840 ◽  
Author(s):  
S. Gubler ◽  
S. Endrizzi ◽  
S. Gruber ◽  
R. S. Purves

Abstract. Before operational use or for decision making, models must be validated, and the degree of trust in model outputs should be quantified. Often, model validation is performed at single locations due to the lack of spatially-distributed data. Since the analysis of parametric model uncertainties can be performed independently of observations, it is a suitable method to test the influence of environmental variability on model evaluation. In this study, the sensitivities and uncertainty of a physically-based mountain permafrost model are quantified within an artificial topography consisting of different elevations and exposures combined with six ground types characterized by their hydraulic properties. The analyses performed for all combinations of topographic factors and ground types allowed to quantify the variability of model sensitivity and uncertainty within mountain regions. We found that modeled snow duration considerably influences the mean annual ground temperature (MAGT). The melt-out day of snow (MD) is determined by processes determining snow accumulation and melting. Parameters such as the temperature and precipitation lapse rate and the snow correction factor have therefore a great impact on modeled MAGT. Ground albedo changes MAGT from 0.5 to 4°C in dependence of the elevation, the aspect and the ground type. South-exposed inclined locations are more sensitive to changes in ground albedo than north-exposed slopes since they receive more solar radiation. The sensitivity to ground albedo increases with decreasing elevation due to shorter snow cover. Snow albedo and other parameters determining the amount of reflected solar radiation are important, changing MAGT at different depths by more than 1°C. Parameters influencing the turbulent fluxes as the roughness length or the dew temperature are more sensitive at low elevation sites due to higher air temperatures and decreased solar radiation. Modeling the individual terms of the energy balance correctly is hence crucial in any physically-based permafrost model, and a separate evaluation of the energy fluxes could substantially improve the results of permafrost models. The sensitivity in the hydraulic properties change considerably for different ground types: rock or clay for instance are not sensitive while gravel or peat, accurate measurements of the hydraulic properties could significantly improve modeled ground temperatures. Further, the discretization of ground, snow and time have an impact on modeled MAGT that cannot be neglected (more than 1°C for several discretization parameters). We show that the temporal resolution should be at least one hour to ensure errors less than 0.2°C in modeled MAGT, and the uppermost ground layer should at most be 20 mm thick. Within the topographic setting, the total parametric output uncertainties expressed as the standard deviation of the Monte Carlo model simulations range from 0.1 to 0.5°C for clay, silt and rock, and from 0.1 to 0.8°C for peat, sand and gravel. These uncertainties are comparable to the variability of ground surface temperatures measured within 10 m × 10 m grids in Switzerland. The increased uncertainties for sand, peat and gravel is largely due to the high hydraulic conductivity.

2013 ◽  
Vol 6 (4) ◽  
pp. 1319-1336 ◽  
Author(s):  
S. Gubler ◽  
S. Endrizzi ◽  
S. Gruber ◽  
R. S. Purves

Abstract. Model evaluation is often performed at few locations due to the lack of spatially distributed data. Since the quantification of model sensitivities and uncertainties can be performed independently from ground truth measurements, these analyses are suitable to test the influence of environmental variability on model evaluation. In this study, the sensitivities and uncertainties of a physically based mountain permafrost model are quantified within an artificial topography. The setting consists of different elevations and exposures combined with six ground types characterized by porosity and hydraulic properties. The analyses are performed for a combination of all factors, that allows for quantification of the variability of model sensitivities and uncertainties within a whole modeling domain. We found that model sensitivities and uncertainties vary strongly depending on different input factors such as topography or different soil types. The analysis shows that model evaluation performed at single locations may not be representative for the whole modeling domain. For example, the sensitivity of modeled mean annual ground temperature to ground albedo ranges between 0.5 and 4 °C depending on elevation, aspect and the ground type. South-exposed inclined locations are more sensitive to changes in ground albedo than north-exposed slopes since they receive more solar radiation. The sensitivity to ground albedo increases with decreasing elevation due to shorter duration of the snow cover. The sensitivity in the hydraulic properties changes considerably for different ground types: rock or clay, for instance, are not sensitive to uncertainties in the hydraulic properties, while for gravel or peat, accurate estimates of the hydraulic properties significantly improve modeled ground temperatures. The discretization of ground, snow and time have an impact on modeled mean annual ground temperature (MAGT) that cannot be neglected (more than 1 °C for several discretization parameters). We show that the temporal resolution should be at least 1 h to ensure errors less than 0.2 °C in modeled MAGT, and the uppermost ground layer should at most be 20 mm thick. Within the topographic setting, the total parametric output uncertainties expressed as the length of the 95% uncertainty interval of the Monte Carlo simulations range from 0.5 to 1.5 °C for clay and silt, and ranges from 0.5 to around 2.4 °C for peat, sand, gravel and rock. These uncertainties are comparable to the variability of ground surface temperatures measured within 10 m × 10 m grids in Switzerland. The increased uncertainties for sand, peat and gravel are largely due to their sensitivity to the hydraulic conductivity.


2009 ◽  
Vol 10 (6) ◽  
pp. 1430-1446 ◽  
Author(s):  
Ryan J. MacDonald ◽  
James M. Byrne ◽  
Stefan W. Kienzle

Abstract This paper describes the continued development of the physically based hydrometeorological model Generate Earth Systems Science input (GENESYS) and its application in simulating snowpack in the St. Mary (STM) River watershed, Montana. GENESYS is designed to operate a high spatial and temporal resolution over complex mountainous terrain. The intent of this paper is to assess the performance of the model in simulating daily snowpack and the spatial extent of snow cover over the St. Mary River watershed. A new precipitation estimation method that uses snowpack telemetry (SNOTEL) and snow survey data is presented and compared with two other methods, including Parameter-elevation Regressions on Independent Slopes Model (PRISM) precipitation data. A method for determining daily temperature lapse rates from NCEP reanalysis data is also presented and the effect of temperature lapse rate on snowpack simulations is determined. Simulated daily snowpack values compare well with observed values at the Many Glacier SNOTEL site, with varying degrees of accuracy, dependent on the method used to estimate precipitation. The spatial snow cover extent compares well with Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover products for three dates selected to represent snow accumulation and ablation periods.


1975 ◽  
Vol 12 (8) ◽  
pp. 1421-1438 ◽  
Author(s):  
M. W. Smith

Variations in ground thermal regime were studied over a small area in the east-central part of the Mackenzie Delta, Northwest Territories, about 50 km northwest of Inuvik. Vegetation shows a successional sequence related to river migration and there is a complex interaction between vegetation, topography, and microclimate.Measurements from five sites show that significant differences in thermal regime exist beneath various types of vegetation. There is a general decrease in mean annual ground temperatures with increasing vegetation. The mean annual air temperature in this area is −9 °to −10 °C, but microclimatic factors lead to mean surface temperatures of between 0 °C and −4.2 °C.In summer, variations in net radiation account for the differences in ground thermal regime at the three sites on the slip-off slope. At the other two sites a surface layer of moss and peat leads to small values in ground heat flux and is instrumental in maintaining lower temperatures there. Removal of 10 cm of organic material at one site led to an increase of 3 °C in the mean daily 10 cm temperature.In winter, on the slip-off slope, variations in snow accumulation lead to ground temperature variations greater than those due to vegetation per se. Spatial variation of about 20 °C in ground surface temperature was measured in March 1970; during July and August 1970 the maximum spatial variation observed was only 10 °C. Differences of up to 6 °C in 1 m temperatures were measured over a distance of only 12 m. Snow cover is a permafrost-controlling factor in this area; where accumulations are greatest a talik has formed due to the insulating effect of deep snow.


2016 ◽  
Vol 29 (2) ◽  
pp. 173-182 ◽  
Author(s):  
Kelly R. Wilhelm ◽  
James G. Bockheim

AbstractVariations in atmospheric conditions can be important factors influencing temperature dynamics within the active layer of a soil. Solar radiation and air temperature can directly alter ground surface temperatures, while variations in wind and precipitation can control how quickly heat is carried through soil pores. The presence of seasonal snow cover can also create a thermal barrier between the atmosphere and ground surface. This study examines the relation between atmospheric conditions and ground temperature variations on a deglaciated island along the Western Antarctic Peninsula. Ground temperatures were most significantly influenced by incoming solar radiation, followed by air temperature variations. When winter months were included in the comparison, the influence of air temperature increased while solar radiation became less influential, indicating that snow cover reflected solar radiation inputs, but was not thick enough to insulate the ground. When ground temperatures were compared to atmospheric conditions of preceding weeks, seasonal temperature peaks 1.6 m below ground were best related to seasonal air temperature peaks from the previous two weeks. The same ground temperature peaks were best related to seasonal solar radiation peaks of seven weeks prior. This difference was a result of temperature lags within the atmosphere.


Geophysics ◽  
2016 ◽  
Vol 81 (1) ◽  
pp. WA183-WA193 ◽  
Author(s):  
W. Steven Holbrook ◽  
Scott N. Miller ◽  
Matthew A. Provart

The water balance in alpine watersheds is dominated by snowmelt, which provides infiltration, recharges aquifers, controls peak runoff, and is responsible for most of the annual water flow downstream. Accurate estimation of snow water equivalent (SWE) is necessary for runoff and flood estimation, but acquiring enough measurements is challenging due to the variability of snow accumulation, ablation, and redistribution at a range of scales in mountainous terrain. We have developed a method for imaging snow stratigraphy and estimating SWE over large distances from a ground-penetrating radar (GPR) system mounted on a snowmobile. We mounted commercial GPR systems (500 and 800 MHz) to the front of the snowmobile to provide maximum mobility and ensure that measurements were taken on pristine snow. Images showed detailed snow stratigraphy down to the ground surface over snow depths up to at least 8 m, enabling the elucidation of snow accumulation and redistribution processes. We estimated snow density (and thus SWE, assuming no liquid water) by measuring radar velocity of the snowpack through migration focusing analysis. Results from the Medicine Bow Mountains of southeast Wyoming showed that estimates of snow density from GPR ([Formula: see text]) were in good agreement with those from coincident snow cores ([Formula: see text]). Using this method, snow thickness, snow density, and SWE can be measured over large areas solely from rapidly acquired common-offset GPR profiles, without the need for common-midpoint acquisition or snow cores.


2010 ◽  
Vol 7 (1) ◽  
pp. 1103-1141 ◽  
Author(s):  
X. Fang ◽  
J. W. Pomeroy ◽  
C. J. Westbrook ◽  
X. Guo ◽  
A. G. Minke ◽  
...  

Abstract. The eastern Canadian Prairies are dominated by cropland, pasture, woodland and wetland areas. The region is characterized by many poor and internal drainage systems and large amounts of surface water storage. Consequently, basins here have proven challenging to hydrological model predictions which assume good drainage to stream channels. The Cold Regions Hydrological Modelling platform (CRHM) is an assembly system that can be used to set up physically based, flexible, object oriented models. CRHM was used to create a prairie hydrological model for the externally drained Smith Creek Research Basin (~400 km2), east-central Saskatchewan. Physically based modules were sequentially linked in CRHM to simulate snow processes, frozen soils, variable contributing area and wetland storage and runoff generation. Five "representative basins" (RBs) were used and each was divided into seven hydrological response units (HRUs): fallow, stubble, grassland, river channel, open water, woodland, and wetland as derived from a supervised classification of SPOT 5 imagery. Two types of modelling approaches calibrated and uncalibrated, were set up for 2007/08 and 2008/09 simulation periods. For the calibrated modelling, only the surface depression capacity of upland area was calibrated in the 2007/08 simulation period by comparing simulated and observed hydrographs; while other model parameters and all parameters in the uncalibrated modelling were estimated from field observations of soils and vegetation cover, SPOT 5 imagery, and analysis of drainage network and wetland GIS datasets as well as topographic map based and LiDAR DEMs. All the parameters except for the initial soil properties and antecedent wetland storage were kept the same in the 2008/09 simulation period. The model performance in predicting snowpack, soil moisture and streamflow was evaluated and comparisons were made between the calibrated and uncalibrated modelling for both simulation periods. Calibrated and uncalibrated predictions of snow accumulation were very similar and compared fairly well with the distributed field observations for the 2007/08 period with slightly poorer results for the 2008/09 period. Soil moisture content at a point during the early spring was adequately simulated and very comparable between calibrated and uncalibrated results for both simulation periods. The calibrated modelling had somewhat better performance in simulating spring streamflow in both simulation periods, whereas the uncalibrated modelling was still able to capture the streamflow hydrographs with good accuracy. This suggests that prediction of prairie basins without calibration is possible if sufficient data on meteorology, basin landcover and physiography are available.


2018 ◽  
Author(s):  
Isabelle Gouttevin ◽  
Moritz Langer ◽  
Henning Löwe ◽  
Julia Boike ◽  
Martin Proksch ◽  
...  

Abstract. The shortage of information on snow properties in high latitudes places a major limitation on permafrost and more generally climate modelling. A dedicated field program was therefore carried out to investigate snow properties and their spatial variability at a polygonal tundra permafrost site. Notably, snow samples were analysed for surface-normal thermal conductivity (Keff-z) based on X-ray microtomography. Also, the detailed snow model SNOWPACK was adapted to these Arctic conditions to enable relevant simulations of the ground thermal regime. Finally, the sensitivity of soil temperatures to snow spatial variability was analysed. Our depth hoar samples were found more conductive (Keff-z = 0.22 ± 0.05 W m−1 K−1) than in most previously published studies, which could be explained by their high density and anisotropy. Spatial variations in the thermal properties of the snowpack were well explained the micro-topography and ground surface conditions of the polygonal tundra, which control depth hoar growth and snow accumulation. Our adaptations to SNOWPACK, phenomenologically taking into account the effects of wind compaction, basal vegetation and water vapour flux, yielded realistic density and Keff-z profiles that greatly improved simulations of the ground thermal regime. The potential of an anisotropy and density-based formulation of Keff-z in snow models was shown. Soil temperatures were found to be particularly sensitive to snow conditions during the dark part of winter, highlighting the need for improved snow characterization and modelling over this period.


2021 ◽  
Author(s):  
Andreas Kellerer-Pirklbauer ◽  
Gerhard Karl Lieb

<p>Ground temperatures in alpine environments are severely influenced by slope orientation (aspect), slope inclination, local topoclimatic conditions, and thermal properties of the rock material. Small differences in one of these factors may substantially impact the ground thermal regime, weathering by freeze-thaw action or the occurrence of permafrost. To improve the understanding of differences, variations, and ranges of ground temperatures at single mountain summits, we studied the ground thermal conditions at a triangle-shaped (plan view), moderately steep pyramidal peak over a two-year period (2018-2020).</p><p>We installed 18 monitoring sites with 23 sensors near the summit of Innerer Knorrkogel (2882m asl), in summer 2018 with one- and multi-channel datalogger (Geoprecision). All three mountain ridges (east-, northwest-, and southwest-facing) and flanks (northeast-, west-, and south-facing) were instrumented with one-channel dataloggers at two different elevations (2840 and 2860m asl) at each ridge/flank to monitor ground surface temperatures. Three bedrock temperature monitoring sites with shallow boreholes (40cm) equipped with three sensors per site at each of the three mountain flanks (2870m asl) were established. Additionally, two ground surface temperature monitoring sites were installed at the summit.</p><p>Results show remarkable differences in mean annual ground temperatures (MAGT) between the 23 different sensors and the two years despite the small spatial extent (0.023 km²) and elevation differences (46m). Intersite variability at the entire mountain pyramid was 3.74°C in 2018/19 (mean MAGT: -0.40°C; minimum: -1.78°C; maximum: 1.96°C;) and 3.27°C in 2019/20 (mean MAGT: 0.08°C; minimum: -1.54°C; maximum: 1,73°C;). Minimum was in both years at the northeast-facing flank, maximum at the south-facing flank. In all but three sites, the second monitoring year was warmer than the first one (mean +0.48°C) related to atmospheric differences and site-specific snow conditions. The comparison of the MAGT-values of the two years (MAGT-2018/19 minus MAGT-2019/20) revealed large thermal inhomogeneities in the mountain summit ranging from +0.65° (2018/19 warmer than 2019/20) to -1.76°C (2018/19 colder than 2019/20) at identical sensors. Temperature ranges at the three different aspects but at equal elevations were 1.7-2.2°C at ridges and 1.8-3.7°C at flanks for single years. The higher temperature range for flank-sites is related to seasonal snow cover effects combined with higher radiation at sun-exposed sites. Although the ground temperature was substantially higher in the second year, the snow cover difference between the two years was variable. Some sites experienced longer snow cover periods in the second year 2019/20 (up to +85 days) whereas at other sites the opposite was observed (up to -85 days). Other frost weathering-related indicators (diurnal freeze-thaw cycles, frost-cracking window) show also large intersite and interannual differences.</p><p>Our study shows that the thermal regime at a triangle-shaped moderately steep pyramidal peak is very heterogeneous between different aspects and landforms (ridge/flank/summit) and between two monitoring years confirming earlier monitoring and modelling results. Due to high intersite and interannual variabilities, temperature-related processes such as frost-weathering can vary largely between neighbouring sites. Our study highlights the need for systematic and long-term ground temperature monitoring in alpine terrain to improve the understanding of small- to medium-scale temperature variabilities.</p>


1971 ◽  
Vol 103 (4) ◽  
pp. 605-609 ◽  
Author(s):  
J. A. Odera

AbstractInternal cone temperatures recorded in the mornings and in the afternoons demonstrated marked differences between sunny and shaded sites. Analysis of variance confirmed differences between treatment as highly significant. High and low cone temperatures coincided with high and low ground temperatures. The average correlation coefficient relating cone and ground temperatures was highly significant, while that for cone temperatures and cone size was non-significant.Heavy insect mortality occurred in cones exposed to direct solar radiation but mortality remained relatively low in the cones left in the shade. The greatest high-temperature mortality occurred during summer between late June and early August.


2019 ◽  
Vol 13 (7) ◽  
pp. 1925-1941 ◽  
Author(s):  
Robert Kenner ◽  
Jeannette Noetzli ◽  
Martin Hoelzle ◽  
Hugo Raetzo ◽  
Marcia Phillips

Abstract. Mountain permafrost is invisible, and mapping it is still a challenge. Available permafrost distribution maps often overestimate the permafrost extent and include large permafrost-free areas in their permafrost zonation. In addition, the representation of the lower belt of permafrost consisting of ice-rich features such as rock glaciers or ice-rich talus slopes can be challenging. These problems are caused by considerable differences in genesis and thermal characteristics between ice-poor permafrost, occurring for example in rock walls, and ice-rich permafrost. While ice-poor permafrost shows a strong correlation of ground temperature with elevation and potential incoming solar radiation, ice-rich ground does not show such a correlation. Instead, the distribution of ice-rich ground is controlled by gravitational processes such as the relocation of ground ice by permafrost creep or by ground ice genesis from avalanche deposits or glacierets covered with talus. We therefore developed a mapping method which distinguishes between ice-poor and ice-rich permafrost and tested it for the entire Swiss Alps. For ice-poor ground we found a linear regression formula based on elevation and potential incoming solar radiation which predicts borehole ground temperatures at multiple depths with an accuracy higher than 0.6 ∘C. The zone of ice-rich permafrost was defined by modelling the deposition zones of alpine mass wasting processes. This dual approach allows the cartographic representation of permafrost-free belts, which are bounded above and below by permafrost. This enables a high quality of permafrost modelling, as is shown by the validation of our map. The dominating influence of the two rather simple connected factors, elevation (as a proxy for mean annual air temperature) and solar radiation, on the distribution of ice-poor permafrost is significant for permafrost modelling in different climate conditions and regions. Indicating temperatures of ice-poor permafrost and distinguishing between ice-poor and ice-rich permafrost on a national permafrost map provides new information for users.


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