Climatic controls on active layer dynamics: Amsler Island, Antarctica

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.

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>


2006 ◽  
Vol 43 ◽  
pp. 285-291 ◽  
Author(s):  
V. Zagorodnov ◽  
O. Nagornov ◽  
L.G. Thompson

AbstractSeasonal temperature variations occur in the glacier layer about 15–20 m below the surface, while at greater depths the glacier temperature depends on the long-term surface conditions. It is generally accepted that for glaciers without surface melting the temperature at 10 m depth (T10) is close to the mean annual air temperature at standard screen level (Ta), i.e. T10 =Ta. We found that this relationship is not valid for Ta above –17˚C and below –55˚C. The goal of our investigation is to find a better temperature transfer function (TTF) between Ta and temperature at the boundary of the active layer in accumulation areas of polar and tropical glaciers. Low-precision T10 temperatures from boreholes, obtained at 41 sites, are compared with air temperatures (Ta) measured in the vicinity of these sites for at least a 1 year period. We determine that when Ta falls into the temperature range –60 to –7˚C, empirical values can be approximated as T10 = 1:2Ta + 6:7. Analysis of these data suggests that high T10 occurs in the areas of the glacier that collect meltwater.


2006 ◽  
Vol 19 (15) ◽  
pp. 3722-3731 ◽  
Author(s):  
Marshall G. Bartlett ◽  
David S. Chapman ◽  
Robert N. Harris

Abstract Observations of air and ground temperatures collected between 1993 and 2004 from Emigrant Pass Geothermal Climate Observatory in northwestern Utah are analyzed to understand the relationship between these two quantities. The influence of surface air temperature (SAT), incident solar radiation, and snow cover on surface ground temperature (SGT) variations are explored. SAT variations explain 94% of the variance in SGT. Incident solar radiation is the primary variable governing the remaining variance misfit and is significantly more important during summer months than winter months. A linear relationship between the ground–air temperature difference (ΔTsgt-sat) and solar radiation exists with a trend of 1.21 K/(100 W m−2); solar radiation accounts for 1.3% of the variance in SGT. The effects of incident solar radiation also account for the 2.47-K average offset in ΔTsgt-sat. During the winter, snow cover plays a role in governing SGT variability, but exerts only a minor influence on the annual tracking of ground and air temperatures at the site, accounting for 0.5% of the variance in SGT. These observations of the tracking of SGT and SAT confirm that borehole temperature changes mimic changes in SAT at frequencies appropriate for climatic reconstructions.


2016 ◽  
Vol 10 (3) ◽  
pp. 1201-1215 ◽  
Author(s):  
Kjersti Gisnås ◽  
Sebastian Westermann ◽  
Thomas Vikhamar Schuler ◽  
Kjetil Melvold ◽  
Bernd Etzelmüller

Abstract. The strong winds prevalent in high altitude and arctic environments heavily redistribute the snow cover, causing a small-scale pattern of highly variable snow depths. This has profound implications for the ground thermal regime, resulting in highly variable near-surface ground temperatures on the metre scale. Due to asymmetric snow distributions combined with the nonlinear insulating effect of snow, the spatial average ground temperature in a 1 km2 area cannot be determined based on the average snow cover for that area. Land surface or permafrost models employing a coarsely classified average snow depth will therefore not yield a realistic representation of ground temperatures. In this study we employ statistically derived snow distributions within 1 km2 grid cells as input to a regional permafrost model in order to represent sub-grid variability of ground temperatures. This improves the representation of both the average and the total range of ground temperatures. The model reproduces observed sub-grid ground temperature variations of up to 6 °C, and 98 % of borehole observations match the modelled temperature range. The mean modelled temperature of the grid cell reproduces the observations with an accuracy of 1.5 °C or better. The observed sub-grid variations in ground surface temperatures from two field sites are very well reproduced, with estimated fractions of sub-zero mean annual ground surface temperatures within ±10 %. We also find that snow distributions within areas of 1 km2 in Norwegian mountain environments are closer to a gamma than to a lognormal theoretical distribution. The modelled permafrost distribution seems to be more sensitive to the choice of distribution function than to the fine-tuning of the coefficient of variation. When incorporating the small-scale variation of snow, the modelled total permafrost area of mainland Norway is nearly twice as large compared to the area obtained with grid-cell average snow depths without a sub-grid approach.


2020 ◽  
Author(s):  
Hannes Hemmerle ◽  
Peter Bayer

<p>Surface temperature variations have been well shown to transfer their thermal signature into the subsurface. This continuous heat transfer manifests in altered thermal conditions in the subsurface where temperature variations over a long lapse of time are more pronounced than shorter ones. Hence, repeated temperature depth profiles allow to investigate the effects of recent climate change on the subsurface. In this study we present recent temperature trends in more than 40 observation wells in Bavaria, Germany. Temperature depth profiles have been quarterly measured for one year between 1992-1994 and measurements have been repeated two times in 2019. The quarterly measurements reveal that the periodic seasonal temperature signal dampens to around 0.1 K at a depth of 15 m below ground surface. This implies that temperature variations below this depth can be used as climate archives as they store the temperature history of multiple years. The measurements span a time period of almost 30 years which is the most common period of reference for deriving climate normals according to the World Meteorological Organization. Therefore, the findings of recent subsurface temperature variations are assessed versus and complemented by 22 air temperature stations. Preliminary results show, that the linear regression of the annual mean air temperature since 1990 yields a slope of 0.35 ± 0.11 K 10a<sup>-1</sup>. In the subsurface, median temperature differences of the respective baselines from 1992-94 period and 2019 are 0.26, 0.13 and 0.07 K 10a<sup>-1 </sup>at 20, 40 and 60 m depth below surface, accordingly. Despite the common magnitude and continuous downward decrease, subsurface temperature differences exhibit a much higher variance compared to air temperature changes. This is due to local effects, such as varying thermal conductivities of the subsurface, latent heat transport caused by evapotranspiration, lateral and vertical groundwater flow, and anthropogenic influences. Our contribution will feature a comparison of this temperature change in response to recent atmospheric climate change in Bavaria and link these results with perceptions gained by similar investigations on local scale in other European regions.</p>


2019 ◽  
Vol 9 (1) ◽  
pp. 20-36 ◽  
Author(s):  
Filip Hrbáček ◽  
Daniel Nývlt ◽  
Kamil Láska ◽  
Michaela Kňažková ◽  
Barbora Kampová ◽  
...  

This study summarizes the current state of the active layer and permafrost research on James Ross Island. The analysis of climate parameters covers the reference period 2011–2017. The mean annual air temperature at the AWS-JGM site was -6.9°C (ranged from -3.9°C to -8.2°C). The mean annual ground temperature at the depth of 5 cm was -5.5°C (ranged from -3.3°C to -6.7°C) and it also reached -5.6°C (ranged from -4.0 to -6.8°C) at the depth of 50 cm. The mean daily ground temperature at the depth of 5 cm correlated moderately up to strongly with the air temperature depending on the season of the year. Analysis of the snow effect on the ground thermal regime confirmed a low insulating effect of snow cover when snow thickness reached up to 50 cm. A thicker snow accumulation, reaching at least 70 cm, can develop around the hyaloclastite breccia boulders where a well pronounced insulation effect on the near-surface ground thermal regime was observed. The effect of lithology on the ground physical properties and the active layer thickness was also investigated. Laboratory analysis of ground thermal properties showed variation in thermal conductivity (0.3 to 0.9 W m-1 K-1). The thickest active layer (89 cm) was observed on the Berry Hill slopes site, where the lowest thawing degree days index (321 to 382°C·day) and the highest value of thermal conductivity (0.9 W m-1 K-1) was observed. The clearest influence of lithological conditions on active layer thickness was observed on the CALM-S grid. The site comprises a sandy Holocene marine terrace and muddy sand of the Whisky Bay Formation. Surveying using a manual probe, ground penetrating radar, and an electromagnetic conductivity meter clearly showed the effect of the lithological boundary on local variability of the active layer thickness.


2020 ◽  
Author(s):  
Runze Zhao ◽  
Kaicun Wang ◽  
Guocan Wu ◽  
Chunlue Zhou

<p>The change of its annual cycle is extremely important due to global warming. A widely used method to analyze the changes of temperature annual cycle is based on the decomposition to phase, amplitude and baseline terms. Solar radiation as the leading energy source of temperature changes can directly influence temperature annual cycle. In this study, we investigate the phase, amplitude and baseline of temperature and solar radiation annual cycle after Fourier transform during 1960-2016 in China. The results show that annual cycle of maximum, minimum and mean surface air temperature are advancing in time (-0.08, -0.27 and -0.33 days per ten years), decreasing in range (-0.07, -0.25 and -0.18 degrees per ten years) and rising in baseline (0.20, 0.34 and 0.25 degrees per ten years). To further quantify the effect of surface solar radiation to temperature, we remove the effect from its original time series of maximum and mean temperature, based on a linear regression. The compare of raw and adjusted temperature shows that surface solar radiation advancing the time by 0.19 and 0.19 days per ten years, reduces the range by 0.14 and 0.13 degrees per ten years, and reduces the baseline by 0.08 and 0.04 degrees per ten years, for surface maximum and mean daily air temperature. The result can explain parts of seasonal temperature variation. Effect of surface solar radiation is most obvious Yunnan-Guizhou Plateau for maximum phase. The low phase value in this area is corrected and well-match with other same latitude area after adjusted.</p>


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.


2006 ◽  
Vol 37 (1) ◽  
pp. 1-19 ◽  
Author(s):  
S. Pohl ◽  
P. Marsh ◽  
A. Pietroniro

Much of the spring landscape of arctic regions is dominated by a patchy snow cover with implications for both spring melt runoff and atmospheric fluxes. In addition to a variable end-of-winter snowpack, spatial differences in snowmelt energy terms play an important role in the development of this patchy snow cover. This paper focuses specifically on the influence of solar radiation on snowmelt by using a model to simulate the small-scale variability of solar radiation incident on the ground surface due to topographic influences over a small arctic catchment. The model only requires a digital elevation model (DEM) and measured global radiation. Despite the relatively low relief (average slope 3°) of the study area, the results showed solar radiation differences of up to 10% of the area-wide mean over the melt period. This would result in differences in snowmelt amounts of up to 50 mm, a value similar in magnitude to the overall mean end-of-winter snow water equivalent in the study region. An analysis of the effects of changing model scale showed that the simulated variability decreased substantially for larger grid sizes. The results show that the small-scale variability of solar radiation contributes greatly to the mosaic patterns in melting snow covers of arctic regions, affects the timing and amount of meltwater release and influences the surface energy balance of these areas considerably.


1993 ◽  
Vol 18 ◽  
pp. 79-84
Author(s):  
Nobuo Ono ◽  
Maxim S. Krass

As the greater part of sea-ice area is covered with snow, the thermal regime of sea ice is characterized by the thermal behavior of snow-covered sea ice. In this paper the thermal regime of snow-covered sea ice is quantitatively investigated with a one-dimensional non-linear boundary model which contains: compaction of snow cover; internal absorption of solar radiation; evaporation–condensation within snow cover; equilibrium phase change of brine within sea ice; and vertical oceanic heat flux from seawater to ice. Penetration of air temperature oscillations into the snow-covered sea ice increases remarkably with increasing snow density. As internal melting within the snow-covered sea ice appears with increasing solar radiation, the rise in air temperature and increase of solar radiation in the springtime produce a corresponding change in the thermal state of sea ice, causing a drastic retreat of sea-ice cover. A case study for warm sea ice is presented describing the thermal state during the melting season.


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