scholarly journals Linking tundra vegetation, snow, soil temperature, and permafrost

2020 ◽  
Author(s):  
Inge Grünberg ◽  
Evan J. Wilcox ◽  
Simon Zwieback ◽  
Philip Marsh ◽  
Julia Boike
Keyword(s):  
Snow Cover ◽  
Layer Thickness ◽  
Active Layer ◽  
Large Degree ◽  
Small Scale ◽  
Active Layer Thickness ◽  
Snow Melt ◽  
Vegetation Types ◽  
Soil Temperatures ◽  
Temporal And Spatial Characteristics

Abstract. Soil temperatures in permafrost regions are highly heterogeneous on small scales, in part due to variable snow and vegetation cover. Moreover, the temperature distribution that results from the interplay of complex biophysical processes remains poorly constrained. Sixty-eight temperature loggers were installed to record the distribution of topsoil temperatures at the Trail Valley Creek study site in the Northwestern Canadian Arctic. The measurements were distributed across six different vegetation types characteristic for this landscape. Two years of topsoil temperature data were analysed statistically to identify temporal and spatial characteristics and their relationship to vegetation, snow cover and active layer thickness. The mean annual topsoil temperature varied between −3.7 °C and 0.1 °C within a 1.2 km distance, with an approximate average across the landscape of −2.3 °C in 2017 and −1.7 °C in 2018. The observed variation can, to a large degree, be explained by variation in snow cover. Differences in height between vegetation types cause spatially variable snow depth during winter, leading to spatially variable snow melt timing in spring, causing pronounced differences in topsoil mean temperature and temperature variability during those time periods. Summer topsoil temperatures were quite similar below most vegetation types, and not consistently related to active layer thickness at the end of August. The small-scale pattern of vegetation and its influence on snow cover height and snow melt governs the annual topsoil temperature in this permafrost-underlain landscape.

scholarly journals Linking tundra vegetation, snow, soil temperature, and permafrost

2020 ◽  
Vol 17 (16) ◽  
pp. 4261-4279
Author(s):  
Inge Grünberg ◽  
Evan J. Wilcox ◽  
Simon Zwieback ◽  
Philip Marsh ◽  
Julia Boike
Keyword(s):  
Soil Temperature ◽  
Snow Cover ◽  
Layer Thickness ◽  
Active Layer ◽  
Vegetation Change ◽  
Vegetation Type ◽  
Spatial Scales ◽  
Active Layer Thickness ◽  
Vegetation Types ◽  
Thermal Dynamics

Abstract. Connections between vegetation and soil thermal dynamics are critical for estimating the vulnerability of permafrost to thaw with continued climate warming and vegetation changes. The interplay of complex biophysical processes results in a highly heterogeneous soil temperature distribution on small spatial scales. Moreover, the link between topsoil temperature and active layer thickness remains poorly constrained. Sixty-eight temperature loggers were installed at 1–3 cm depth to record the distribution of topsoil temperatures at the Trail Valley Creek study site in the northwestern Canadian Arctic. The measurements were distributed across six different vegetation types characteristic for this landscape. Two years of topsoil temperature data were analysed statistically to identify temporal and spatial characteristics and their relationship to vegetation, snow cover, and active layer thickness. The mean annual topsoil temperature varied between −3.7 and 0.1 ∘C within 0.5 km2. The observed variation can, to a large degree, be explained by variation in snow cover. Differences in snow depth are strongly related with vegetation type and show complex associations with late-summer thaw depth. While cold winter soil temperature is associated with deep active layers in the following summer for lichen and dwarf shrub tundra, we observed the opposite beneath tall shrubs and tussocks. In contrast to winter observations, summer topsoil temperature is similar below all vegetation types with an average summer topsoil temperature difference of less than 1 ∘C. Moreover, there is no significant relationship between summer soil temperature or cumulative positive degree days and active layer thickness. Altogether, our results demonstrate the high spatial variability of topsoil temperature and active layer thickness even within specific vegetation types. Given that vegetation type defines the direction of the relationship between topsoil temperature and active layer thickness in winter and summer, estimates of permafrost vulnerability based on remote sensing or model results will need to incorporate complex local feedback mechanisms of vegetation change and permafrost thaw.

scholarly journals Warming permafrost and active layer variability at Cime Bianche, Western Alps

2014 ◽  
Vol 8 (4) ◽  
pp. 4033-4074
Author(s):  
P. Pogliotti ◽  
M. Guglielmin ◽  
E. Cremonese ◽  
U. Morra di Cella ◽  
G. Filippa ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Snow Cover ◽  
Layer Thickness ◽  
Active Layer ◽  
Ground Surface ◽  
Small Scale ◽  
Active Layer Thickness ◽  
Spatial And Temporal Variability ◽  
Monitoring Site ◽  
Surface Temperatures

Abstract. The objective of this paper is to provide a first synthesis on the state and recent evolution of permafrost at the monitoring site of Cime Bianche (3100 m a.s.l.). The analysis is based on seven years of ground temperatures observations in two boreholes and seven surface points. The analysis aims to quantify the spatial and temporal variability of ground surface temperatures in relation to snow cover, the small scale spatial variability of the active layer thickness and the warming trends on deep permafrost temperatures. Results show that the heterogeneity of snow cover thickness, both in space and time, is the main factor controlling ground surface temperatures and leads to a mean range of spatial variability (2.5±0.15°C) which far exceeds the mean range of observed inter-annual variability (1.6±0.12°C). The active layer thickness measured in two boreholes 30 m apart, shows a mean difference of 2.03±0.15 m with the active layer of one borehole consistently lower. As revealed by temperature analysis and geophysical soundings, such a difference is mainly driven by the ice/water content in the sub-surface and not by the snow cover regimes. The analysis of deep temperature time series reveals that permafrost is warming. The detected linear trends are statistically significant starting from depth below 8 m, span the range 0.1–0.01°C year−1 and decrease exponentially with depth. Our findings are discussed in the context of the existing literature.

scholarly journals Warming permafrost and active layer variability at Cime Bianche, Western European Alps

2015 ◽  
Vol 9 (2) ◽  
pp. 647-661 ◽  
Author(s):  
P. Pogliotti ◽  
M. Guglielmin ◽  
E. Cremonese ◽  
U. Morra di Cella ◽  
G. Filippa ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Snow Cover ◽  
Layer Thickness ◽  
Active Layer ◽  
Ground Surface ◽  
Small Scale ◽  
Active Layer Thickness ◽  
Spatial And Temporal Variability ◽  
Monitoring Site ◽  
European Alps

Abstract. The objective of this paper is to provide a first synthesis on the state and recent evolution of permafrost at the monitoring site of Cime Bianche (3100 m a.s.l.) on the Italian side of the Western Alps. The analysis is based on 7 years of ground temperature observations in two boreholes and seven surface points. The analysis aims to quantify the spatial and temporal variability of ground surface temperature in relation to snow cover, the small-scale spatial variability of the active layer thickness and current temperature trends in deep permafrost. Results show that the heterogeneity of snow cover thickness, both in space and time, is the main factor controlling ground surface temperatures and leads to a mean range of spatial variability (2.5 ± 0.1 °C) which far exceeds the mean range of observed inter-annual variability (1.6 ± 0.1 °C). The active layer thickness measured in two boreholes at a distance of 30 m shows a mean difference of 2.0 ± 0.1 m with the active layer of one borehole consistently deeper. As revealed by temperature analysis and geophysical soundings, such a difference is mainly driven by the ice/water content in the sub-surface and not by the snow cover regimes. The analysis of deep temperature time series reveals that permafrost is warming. The detected trends are statistically significant starting from a depth below 8 m with warming rates between 0.1 and 0.01 °C yr−1.

Mapping patterns of distribution and modern conditions of permafrost landscapes in Yakutia

2020 ◽  
pp. 52-62
Author(s):  
A.A. Shestakova ◽  
Keyword(s):  
Layer Thickness ◽  
Active Layer ◽  
Anthropogenic Impacts ◽  
Active Layer Thickness ◽  
Thematic Maps ◽  
Digital Maps ◽  
Soil Temperatures ◽  
Ice Content ◽  
Cryogenic Processes ◽  
Modern Condition

Digital thematic maps of the modern condition of permafrost landscapes of Yakutia on a scale of 1:1 500 000 have been compiled. A quantitative analysis of the patterns of their spatial distribution was carried out, the differentiation of permafrost landscapes by geocryological characteristics was made, and the areas that are most vulnerable to modern climate change and anthropogenic impacts were identified. The analysis of a series of digital thematic maps of the modern condition of permafrost landscapes in Yakutia showed that 34% of the total territory is occupied by landscapes with soil temperatures from −2 to −4 °C, the least common high-temperature permafrost landscapes (from 0 to −2 °C) – about 4% of the territory. Landscapes with active layer thickness values of about 1 m are spread over 36% of the territory, which is the highest indicator. Insignificant territories (up to 3%) are occupied by landscapes with active layer thickness of up to 3 and 3,5 m. The most widespread landscapes are those with low-ice deposits (less than 0,2) – 38,7%, and landscapes with heavy-ice deposits (more than 0,4) occupy 31%. The most dangerous process is thermokarst, which occurs in the interalassic and slightly drained types of terrain. Key words: permafrost landscape, temperature of soils, ice content of deposits, cryogenic processes, digital maps, GIS model.

scholarly journals A multisite dataset of near-surface soil temperature, active-layer thickness, and soil and vegetation conditions measured in northwestern Canada, 2016-2017

2021 ◽  
Author(s):  
Y Zhang ◽  
R Touzi ◽  
W Feng ◽  
G Hong ◽  
T C Lantz ◽  
...  
Keyword(s):  
Layer Thickness ◽  
Active Layer ◽  
Land Use Planning ◽  
Surface Soil ◽  
Active Layer Thickness ◽  
Data Set ◽  
Near Surface ◽  
Soil Temperatures ◽  
Surface Soil Temperature ◽  
Boreal Landscape

Quantifying and understanding spatial variation in permafrost conditions at the landscape-scale is important for land use planning and assessing the impacts of permafrost thaw. This report documents detailed field data observed at 110 sites in two areas in northwestern Canada from 2016 to 2017. One area is a northern boreal landscape near Inuvik and the other is a tundra landscape near Tuktoyaktuk. The observations include near-surface soil temperatures (Tnss) at 107 sites, and active-layer thickness, soil and vegetation conditions at 110 sites. The data set includes the original Tnss records, the calculated daily, monthly, and annual averages of Tnss, soil and vegetation conditions at these sites, and photographs taken in the field. This data set will be useful for understanding the spatial heterogeneity of permafrost and validating modelling and mapping products.

scholarly journals Active Layer Thickness Estimation from X-Band SAR Backscatter Intensity

2016 ◽  
Author(s):  
Barbara Widhalm ◽  
Annett Bartsch ◽  
Marina Leibman ◽  
Artem Khomutov
Keyword(s):  
Land Cover ◽  
Layer Thickness ◽  
Active Layer ◽  
Satellite Data ◽  
Active Layer Thickness ◽  
Vegetation Types ◽  
Backscatter Intensity ◽  
X Band ◽  
Spatial Coverage ◽  
The Relationship

Abstract. The active layer above the permafrost, which seasonally thaws during summer is an important parameter for monitoring the state of permafrost. Its thickness is typically measured locally. A range of methods, which utilize information from satellite data exist. Their applicability has been demonstrated mostly for shallow depths below 70 cm. Some permafrost areas including central Yamal are characterized by higher Active Layer Thickness (ALT). The relationship between ALT and X-Band SAR backscatter of TerraSAR-X has been investigated in order to explore the possibility of delineating ALT on a continuous and larger spatial coverage in this area. This study shows that the mutual dependency of ALT and TerraSAR-X backscatter on land cover types induces a connection of both parameters. A range of 5 dB can be observed for an ALT range of 100 cm (40–140 cm) and an R2 of 0.66 has been determined over the calibration sites. An increase of ALT with increasing backscatter can be especially determined for ALT > 70 cm. The RMSE over a comparably heterogeneous validation site with maximum ALT of > 150 cm is in the range of 20–22 cm. Deviations are larger for measurement locations with mixed vegetation types.

scholarly journals Analysis of Permafrost Thermal Dynamics and Response to Climate Change in the CMIP5 Earth System Models

2013 ◽  
Vol 26 (6) ◽  
pp. 1877-1900 ◽  
Author(s):  
Charles D. Koven ◽  
William J. Riley ◽  
Alex Stern
Keyword(s):  
Soil Temperature ◽  
Layer Thickness ◽  
Active Layer ◽  
Air Temperature ◽  
High Latitude ◽  
Cmip5 Models ◽  
Active Layer Thickness ◽  
Thermal Dynamics ◽  
Wide Range ◽  
Soil Temperatures

Abstract The authors analyze global climate model predictions of soil temperature [from the Coupled Model Intercomparison Project phase 5 (CMIP5) database] to assess the models’ representation of current-climate soil thermal dynamics and their predictions of permafrost thaw during the twenty-first century. The authors compare the models’ predictions with observations of active layer thickness, air temperature, and soil temperature and with theoretically expected relationships between active layer thickness and air temperature annual mean- and seasonal-cycle amplitude. Models show a wide range of current permafrost areas, active layer statistics (cumulative distributions, correlations with mean annual air temperature, and amplitude of seasonal air temperature cycle), and ability to accurately model the coupling between soil and air temperatures at high latitudes. Many of the between-model differences can be traced to differences in the coupling between either near-surface air and shallow soil temperatures or shallow and deeper (1 m) soil temperatures, which in turn reflect differences in snow physics and soil hydrology. The models are compared with observational datasets to benchmark several aspects of the permafrost-relevant physics of the models. The CMIP5 models following multiple representative concentration pathways (RCP) show a wide range of predictions for permafrost loss: 2%–66% for RCP2.6, 15%–87% for RCP4.5, and 30%–99% for RCP8.5. Normalizing the amount of permafrost loss by the amount of high-latitude warming in the RCP4.5 scenario, the models predict an absolute loss of 1.6 ± 0.7 million km2 permafrost per 1°C high-latitude warming, or a fractional loss of 6%–29% °C−1.

15 years of snow manipulation reveals huge impact on lowland permafrost and vegetation

2020 ◽  
Author(s):  
Margareta Johansson ◽  
Jonas Åkerman ◽  
Gesche Blume-Werry ◽  
Terry V. Callaghan ◽  
Torben R. Christensen ◽  
...  
Keyword(s):  
Snow Cover ◽  
Layer Thickness ◽  
Active Layer ◽  
Snow Depth ◽  
Bacterial Community Composition ◽  
Strong Increase ◽  
Past Century ◽  
Active Layer Thickness ◽  
Permafrost Degradation ◽  
Significant Difference

<p>Snow depth increases observed and predicted in the sub-arctic are of critical importance for the dynamics of lowland permafrost and vegetation. Snow acts as an insulator that protects vegetation but may lead to permafrost degradation. In the Abisko area, in northernmost Sweden, there has been an increasing trend in snow depth during the last Century. Downscaled climate scenarios predict an increase in precipitation by 1.5 - 2% per decade for the coming 60 years. The observed changes in snow cover have affected peat mires in this area as thawing of permafrost, increases in active layer thickness and associated vegetation changes have been reported during the last decades. An experimental manipulation was set up at one of these lowland permafrost sites in the Abisko area (68°20’48’’N, 18°58’16’’E) 15 years ago, to simulate projected future increases in winter precipitation and to study their effect on permafrost and vegetation. The snow cover has been more than twice as thick in manipulated plots compared to control plots and it has had a large impact on permafrost and vegetation. It resulted in statistically significant differences in mean winter and minimum ground temperatures between the control and the manipulated plots. Already after three years there was a statistically significant difference between active layer thickness in the manipulated plots compared to the control plots. In 2019, the active layer thickness in the control plots were around 70 cm whereas in the manipulated plots it was 110 cm. The increased active layer thickness has led to surface subsidence due to melting of ground ice in all the manipulated plots. The increased snow thickness has prolonged the duration of the snow cover in spring with up to 22 days. However, this loss in early season photosynthesis was well compensated for by the increased absorption of PAR and higher light use efficiency throughout the whole growing seasons in the manipulated plots. Eriophorum vaginatum is a species that has been especially favored in the manipulated plots. It has increased both in number and in size. Underneath the soil surface, the roots have also been affected. There has been a strong increase in total root length and growth in the active layer, and deep roots has invaded the newly thawed permafrost in the manipulated plots. The increased active layer thickness has also had an effect on the bacterial community composition in the newly thawed areas. According to past, century-long patterns of increasing snow depth and projections of continuing increases, it is very likely that the changes in permafrost and vegetation that have been demonstrated by this experimental treatment will occur in the future under natural conditions.</p>

scholarly journals Frozen ground and snow cover monitoring in Livingston and Deception islands, Antarctica: preliminary results of the 2015-2019 PERMASNOW project

2020 ◽  
Vol 46 (1) ◽  
pp. 187-222
Author(s):  
M.A. De Pablo ◽  
J.J. Jiménez ◽  
M. Ramos ◽  
M. Prieto ◽  
A. Molina ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Snow Cover ◽  
Layer Thickness ◽  
Active Layer ◽  
Remote Sensing Data ◽  
Active Layer Thickness ◽  
Frozen Ground ◽  
Snow Layer ◽  
Sensing Data ◽  
Monitoring Stations

Since 2006, our research team has been establishing in the islands of Livingston and Deception, (South Shetland archipelago, Antarctica) several monitoring stations of the active layer thickness within the international network Circumpolar Active Layer Monitoring (CALM), and the ground thermal regime for the Ground Terrestrial Network-Permafrost (GTN-P). Both networks were developed within the International Permafrost Association (IPA). In the GTN-P stations, in addition to the temperature of the air, soil, and terrain at different depths, the snow thickness is also monitored by snow poles. Since 2006, a delay in the disappearance of the snow layer has been observed, which could explain the variations we observed in the active layer thickness and permafrost temperatures. Therefore, in late 2015 our research group started the PERMASNOW project (2015-2019) to pay attention to the effect of snow cover on ground thermal This project had two different ways to study the snow cover. On the first hand, in early 2017 we deployed new instrumentation, including new time lapse cameras, snow poles with high number of sensors and a complete and complex set of instruments and sensors to configure a snow pack analyzer station providing 32 environmental and snow parameters. We used the data acquired along 2017 and 2018 years with the new instruments, together with the available from all our already existing sensors, to study in detail the snow cover. On the other hand, remote sensing data were used to try to map the snow cover, not only at our monitoring stations but the entire islands in order to map and study the snow cover distribution, as well as to start the way for future permafrost mapping in the entire islands. MODIS-derived surface temperatures and albedo products were used to detect the snow cover and to test the surface temperature. Since cloud presence limited the acquisition of valid observations of MODIS sensor, we also analyzed Terrasar X data to overcome this limitation. Remote sensing data validation required the acquirement of in situ ground-true data, consisting on data from our permanent instruments, as well as ad hoc measurements in the field (snow cover mapping, snow pits, albedo characterization, etc.). Although the project is finished, the data analysis is still ongoing. We present here the different research tasks we are developing as well as the most important results we already obtained about the snow cover. These results confirm how the snow cover duration has been changing in the last years, affecting the ground thermal behavior.

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