scholarly journals Tundra shrub expansion may amplify permafrost thaw by advancing snowmelt timing

2019 ◽  
Vol 5 (4) ◽  
pp. 202-217 ◽  
Author(s):  
Evan J. Wilcox ◽  
Dawn Keim ◽  
Tyler de Jong ◽  
Branden Walker ◽  
Oliver Sonnentag ◽  
...  
Keyword(s):  
Active Layer ◽  
Snow Depth ◽  
Structural Equation ◽  
The Arctic ◽  
Equation Modeling ◽  
Active Layer Thickness ◽  
Snow Surface ◽  
Shrub Expansion ◽  
Shrub Tundra ◽  
Temporal Influence

The overall spatial and temporal influence of shrub expansion on permafrost is largely unknown due to uncertainty in estimating the magnitude of many counteracting processes. For example, shrubs shade the ground during the snow-free season, which can reduce active layer thickness. At the same time, shrubs advance the timing of snowmelt when they protrude through the snow surface, thereby exposing the active layer to thawing earlier in spring. Here, we compare 3056 in situ frost table depth measurements split between mineral earth hummocks and organic inter-hummock zones across four dominant shrub–tundra vegetation types. Snow-free date, snow depth, hummock development, topography, and vegetation cover were compared to frost table depth measurements using a structural equation modeling approach that quantifies the direct and combined interacting influence of these variables. Areas of birch shrubs became snow free earlier regardless of snow depth or hillslope aspect because they protruded through the snow surface, leading to deeper hummock frost table depths. Projected increases in shrub height and extent combined with projected decreases in snowfall would lead to increased shrub protrusion across the Arctic, potentially deepening the active layer in areas where shrub protrusion advances the snow-free date.

scholarly journals The influence of climate and hydrological variables on opposite anomaly in active-layer thickness between Eurasian and North American watersheds

2013 ◽  
Vol 7 (2) ◽  
pp. 631-645 ◽  
Author(s):  
H. Park ◽  
J. Walsh ◽  
A. N. Fedorov ◽  
A. B. Sherstiukov ◽  
Y. Iijima ◽  
...  
Keyword(s):  
Layer Thickness ◽  
Active Layer ◽  
North American ◽  
Land Surface ◽  
Snow Depth ◽  
The Arctic ◽  
Surface Model ◽  
Active Layer Thickness ◽  
Hydrological Variables ◽  
Permafrost Regions

Abstract. This study not only examined the spatiotemporal variations of active-layer thickness (ALT) in permafrost regions during 1948–2006 over the terrestrial Arctic regions experiencing climate changes, but also identified the associated drivers based on observational data and a simulation conducted by a land surface model (CHANGE). The focus on the ALT extends previous studies that have emphasized ground temperatures in permafrost regions. The Ob, Yenisey, Lena, Yukon, and Mackenzie watersheds are foci of the study. Time series of ALT in Eurasian watersheds showed generally increasing trends, while the increase in ALT in North American watersheds was not significant. However, ALT in the North American watersheds has been negatively anomalous since 1990 when the Arctic air temperature entered into a warming phase. The warming temperatures were not simply expressed to increases in ALT. Since 1990 when the warming increased, the forcing of the ALT by the higher annual thawing index (ATI) in the Mackenzie and Yukon basins has been offset by the combined effects of less insulation caused by thinner snow depth and drier soil during summer. In contrast, the increasing ATI together with thicker snow depth and higher summer soil moisture in the Lena contributed to the increase in ALT. The results imply that the soil thermal and moisture regimes formed in the pre-thaw season(s) provide memory that manifests itself during the summer. The different ALT anomalies between Eurasian and North American watersheds highlight increased importance of the variability of hydrological variables.

Contrasting thermal responses of permafrost to winter warming events under different snow regimes in the subarctic

2021 ◽  
Author(s):  
Didac Pascual Descarrega ◽  
Margareta Johansson
Keyword(s):  
Layer Thickness ◽  
Active Layer ◽  
Snow Depth ◽  
Thermal Response ◽  
Winter Precipitation ◽  
The Arctic ◽  
Active Layer Thickness ◽  
Thermal Dynamics ◽  
Winter Warming

<p>Winter warming events (WWE) in the Swedish subarctic are abrupt and short-lasting (hours-to-days) events of positive air temperature that occur during wintertime, sometimes accompanied by rainfall (rain on snow; ROS). These events cause changes in snow properties, which affect the below-ground thermal regime that, in turn, controls a suite of ecosystem processes ranging from microbial activity to permafrost and vegetation dynamics. For instance, winter melting can cause ground warming due to the shortening of the snow cover season, or ground cooling as the reduced snow depth and the formation of refrozen layers of high thermal conductivity at the base of the snowpack facilitate the release of soil heat. Apart from these interacting processes, the overall impacts of WWE on ground temperatures may also depend on the timing of the events and the preceding snowpack characteristics. The frequency and intensity of these events in the Arctic, including the Swedish subarctic, has increased remarkably during the recent decades, and is expected to increase even further during the 21st Century. In addition, snow depth (not necessarily snow duration) is projected to increase in many parts of the Arctic, including the Swedish subarctic. In 2005, a manipulation experiment was set up on a lowland permafrost mire in the Swedish subarctic, to simulate projected future increases in winter precipitation. In this study, we analyse this 15-year record of ground temperature, active layer thickness, and meteorological variables, to evaluate the short- (days to weeks) and long-term (up to 1 year) impacts of WWE on the thermal dynamics of lowland permafrost, and provide new insights into the influence of the timing of WWE and the underlying snowpack conditions on the thermal response of permafrost. On the short-term, the thermal responses to WWE are faster and stronger in areas with a shallow snowpack (5-10 cm), although these responses are more persistent in areas with a thicker snowpack (>25 cm), especially after ROS events. On the long term, permafrost in areas with a thicker snowpack exhibit a more durable warming response to WWE that results in thicker active layers at the end of the season. On the contrary, we do not observe a correlation between WWE and end of season active layer thickness in areas with a shallow snowpack. </p>

scholarly journals The influence of climate and hydrological variables on opposite anomaly in active layer thickness between Eurasian and North American watersheds

2012 ◽  
Vol 6 (4) ◽  
pp. 2537-2574 ◽  
Author(s):  
H. Park ◽  
J. Walsh ◽  
A. N. Fedorov ◽  
A. B. Sherstiukov ◽  
Y. Iijima ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Layer Thickness ◽  
Active Layer ◽  
Air Temperature ◽  
North American ◽  
Snow Depth ◽  
The Arctic ◽  
Surface Model ◽  
Active Layer Thickness ◽  
Hydrological Variables

Abstract. This study not only examined the spatiotemporal variations of permafrost active layer thickness (ALT) during 1948–2006 over the terrestrial Arctic regions experiencing climate changes, but also identified the associated drivers based on observational data and a simulation conducted by a land surface model (CHANGE). The focus on the ALT extends previous studies that have emphasized ground temperatures in permafrost regions. The Ob, Yenisey, Lena, Yukon, and Mackenzie watersheds are foci of the study. Time series of ALT in Eurasian watersheds showed generally increasing trends, while ALT in North American watersheds showed decreases. An opposition of ALT variations implicated with climate and hydrological variables was most significant when the Arctic air temperature entered into a warming phase. The warming temperatures were not simply expressed to increases in ALT. Since 1990 when the warming increased, the forcing of the ALT by the higher Annual Thawing Index in the Mackenzie and Yukon Basins was offset by the combined effects of less insulation caused by thinner snow depth and drier soil during summer. In contrast, the increasing Annual Thawing Index together with thicker snow depth and higher summer soil moisture in the Lena contributed to the increase in ALT. The results imply that the soil thermal and moisture regimes formed in the pre-thaw season(s) provide memory that manifests itself during the summer. While it is widely believed that ALT will increase with global warming, this hypothesis may need modification because the ALT also shows responses to variations in snow depth and soil moisture that can over-ride the effect of air temperature. The dependence of the hydrological variables driven by the atmosphere further increases the uncertainty in future changes of the permafrost active layer.

scholarly journals A SPATIO-TEMPORAL FRAMEWORK FOR MODELING ACTIVE LAYER THICKNESS

2015 ◽  
Vol II-4/W2 ◽  
pp. 199-206
Author(s):  
J. Touyz ◽  
D. A. Streletskiy ◽  
F. E. Nelson ◽  
T. V. Apanasovich
Keyword(s):  
Layer Thickness ◽  
Active Layer ◽  
Environmental Changes ◽  
Predictive Accuracy ◽  
The Arctic ◽  
Active Layer Thickness ◽  
Error Statistics ◽  
Stochastic Component ◽  
Spatio Temporal ◽  
Naive Model

The Arctic is experiencing an unprecedented rate of environmental and climate change. The active layer (the uppermost layer of soil between the atmosphere and permafrost that freezes in winter and thaws in summer) is sensitive to both climatic and environmental changes, and plays an important role in the functioning, planning, and economic activities of Arctic human and natural ecosystems. This study develops a methodology for modeling and estimating spatial-temporal variations in active layer thickness (ALT) using data from several sites of the Circumpolar Active Layer Monitoring network, and demonstrates its use in spatial-temporal interpolation. The simplest model’s stochastic component exhibits no spatial or spatio-temporal dependency and is referred to as the naïve model, against which we evaluate the performance of the other models, which assume that the stochastic component exhibits either spatial or spatio-temporal dependency. The methods used to fit the models are then discussed, along with point forecasting. We compare the predicted fit of the various models at key study sites located in the North Slope of Alaska and demonstrate the advantages of space-time models through a series of error statistics such as mean squared error, mean absolute and percent deviance from observed data. We find the difference in performance between the spatio-temporal and remaining models is significant for all three error statistics. The best stochastic spatio-temporal model increases predictive accuracy, compared to the naïve model, of 33.3%, 36.2% and 32.5% on average across the three error metrics at the key sites for a one-year hold out period.

scholarly journals Thermal state of the active layer and permafrost along the Qinghai-Xizang (Tibet) railway from 2006 to 2010

2011 ◽  
Vol 5 (5) ◽  
pp. 2465-2481 ◽  
Author(s):  
Q. Wu ◽  
T. Zhang ◽  
Y. Liu
Keyword(s):  
Linear Regression ◽  
Layer Thickness ◽  
Active Layer ◽  
Thermal State ◽  
Monitoring Network ◽  
The Arctic ◽  
Active Layer Thickness ◽  
Different Depths ◽  
The Mean ◽  
Using Data

Abstract. In this study, we investigated changes in active layer thickness (ALT) and permafrost temperatures at different depths using data from permafrost monitoring network along the Qinghai-Xizang (Tibet) Railway since 2005. Among sites, average ALT is about 3.1 m with a range from about 1.1 m to 4.9 m. From 2006 through 2010, ALT has increased at a rate of about 6.3 cm a−1. The mean rising rate of permafrost temperature at the depth of 6.0 m is about 0.02 °C a−1 estimated by linear regression using five years of data, and the mean rising rate of mean annual ground temperature (MAGT) at depth of zero amplitude is about 0.012 °C a−1. Changes for colder permafrost (MAGT < −1.0 °C) is greater than that for relatively warmer permafrost (MAGT > −1.0 °C). This is consistent with results observed in the Arctic and Subarctic.

scholarly journals Numerical modeling of permafrost dynamics in Alaska using a high spatial resolution dataset

2012 ◽  
Vol 6 (3) ◽  
pp. 613-624 ◽  
Author(s):  
E. E. Jafarov ◽  
S. S. Marchenko ◽  
V. E. Romanovsky
Keyword(s):  
Spatial Resolution ◽  
Active Layer ◽  
21St Century ◽  
Soil Column ◽  
The Arctic ◽  
Quality Data ◽  
Active Layer Thickness ◽  
Climate Projections ◽  
Permafrost Degradation ◽  
Model Composite

Abstract. Climate projections for the 21st century indicate that there could be a pronounced warming and permafrost degradation in the Arctic and sub-Arctic regions. Climate warming is likely to cause permafrost thawing with subsequent effects on surface albedo, hydrology, soil organic matter storage and greenhouse gas emissions. To assess possible changes in the permafrost thermal state and active layer thickness, we implemented the GIPL2-MPI transient numerical model for the entire Alaska permafrost domain. The model input parameters are spatial datasets of mean monthly air temperature and precipitation, prescribed thermal properties of the multilayered soil column, and water content that are specific for each soil class and geographical location. As a climate forcing, we used the composite of five IPCC Global Circulation Models that has been downscaled to 2 by 2 km spatial resolution by Scenarios Network for Alaska Planning (SNAP) group. In this paper, we present the modeling results based on input of a five-model composite with A1B carbon emission scenario. The model has been calibrated according to the annual borehole temperature measurements for the State of Alaska. We also performed more detailed calibration for fifteen shallow borehole stations where high quality data are available on daily basis. To validate the model performance, we compared simulated active layer thicknesses with observed data from Circumpolar Active Layer Monitoring (CALM) stations. The calibrated model was used to address possible ground temperature changes for the 21st century. The model simulation results show widespread permafrost degradation in Alaska could begin between 2040–2099 within the vast area southward from the Brooks Range, except for the high altitude regions of the Alaska Range and Wrangell Mountains.

scholarly journals Snow Depth Variations in Svalbard Derived from GNSS Interferometric Reflectometry

2020 ◽  
Vol 12 (20) ◽  
pp. 3352
Author(s):  
Jiachun An ◽  
Pan Deng ◽  
Baojun Zhang ◽  
Jingbin Liu ◽  
Songtao Ai ◽  
...  
Keyword(s):  
Snow Depth ◽  
Depth Estimation ◽  
Snow Accumulation ◽  
The Arctic ◽  
Noise Power ◽  
Snow Surface ◽  
Depth Sensing ◽  
Three Stages ◽  
The Impact ◽  
Mean Square Errors

Snow plays a critical role in hydrological monitoring and global climate change, especially in the Arctic region. As a novel remote sensing technique, global navigation satellite system interferometric reflectometry (GNSS-IR) has shown great potential for detecting reflector characteristics. In this study, a field experiment of snow depth sensing with GNSS-IR was conducted in Ny-Alesund, Svalbard, and snow depth variations over the 2014–2018 period were retrieved. First, an improved approach was proposed to estimate snow depth with GNSS observations by introducing wavelet decomposition before spectral analysis, and this approach was validated by in situ snow depths obtained from a meteorological station. The proposed approach can effectively separate the noise power from the signal power without changing the frequency composition of the original signal, particularly when the snow depth changes sharply. Second, snow depth variations were analyzed at three stages including snow accumulation, snow ablation and snow stabilization, which correspond to different snow-surface-reflection characteristics. For these three stages of snow depth variations, the mean absolute errors (MAE) were 4.77, 5.11 and 3.51 cm, respectively, and the root mean square errors (RMSE) were 6.00, 6.34 and 3.78 cm, respectively, which means that GNSS-IR can be affected by different snow surface characteristics. Finally, the impact of rainfall on snow depth estimation was analyzed for the first time. The results show that the MAE and RMSE were 2.19 and 2.08 cm, respectively, when there was no rainfall but 5.63 and 5.46 cm, respectively, when it was rainy, which indicates that rainfall reduces the accuracy of snow depth estimation by GNSS-IR.

scholarly journals Numerical modeling of permafrost dynamics in Alaska using a high spatial resolution dataset

2012 ◽  
Vol 6 (1) ◽  
pp. 89-124 ◽  
Author(s):  
E. E. Jafarov ◽  
S. S. Marchenko ◽  
V. E. Romanovsky
Keyword(s):  
Spatial Resolution ◽  
Active Layer ◽  
21St Century ◽  
Soil Column ◽  
The Arctic ◽  
Quality Data ◽  
Active Layer Thickness ◽  
Climate Projections ◽  
Permafrost Degradation ◽  
Model Composite

Abstract. Climate projections for the 21st century indicate that there could be a pronounced warming and permafrost degradation in the Arctic and sub-Arctic regions. Climate warming is likely to cause permafrost thawing with subsequent effects on surface albedo, hydrology, soil organic matter storage and greenhouse gas emissions. To assess possible changes in the permafrost thermal state and active layer thickness, we implemented the GIPL2-MPI transient numerical model for the entire Alaska permafrost domain. Input parameters to the model are spatial datasets of mean monthly air temperature and precipitation, prescribed thermal properties of the multilayered soil column, and water content which are specific for each soil class and geographical location. As a climate forcing we used the composite of five IPCC Global Circulation Models that has been downscaled to 2 by 2 km spatial resolution by Scenarios Network for Alaska Planning (SNAP) group. In this paper we present the preliminary modeling results based on input of five-model composite with A1B carbon emission scenario. The model has been calibrated according to the annual borehole temperature measurements for the State of Alaska. We also performed more detailed calibration for fifteen shallow borehole stations where high quality data are available on daily basis. To validate the model performance we compared simulated active layer thicknesses with observed data from CALM active layer monitoring stations. Calibrated model was used to address possible ground temperature changes for the 21st century. The model simulation results show the widespread permafrost degradation in Alaska could begin in 2040–2099 time frame within the vast area southward from the Brooks Range except for the high altitudes of the Alaska Range and Wrangell Mountains.

scholarly journals Characterizing permafrost soil active layer dynamics and sensitivity to landscape spatial heterogeneity in Alaska

2017 ◽  
Author(s):  
Yonghong Yi ◽  
John S. Kimball ◽  
Richard Chen ◽  
Mahta Moghaddam ◽  
Rolf H. Reichle ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Spatial Heterogeneity ◽  
Active Layer ◽  
Landscape Heterogeneity ◽  
The Arctic ◽  
Integrated Modelling ◽  
Permafrost Soil ◽  
Soil Conditions ◽  
Active Layer Thickness ◽  
Recent Climate

Abstract. An important feature of the Arctic is large spatial heterogeneity in active layer conditions, which is generally poorly represented by global models. In this study, we developed a spatially integrated modelling and analysis framework combining field observations, local scale (~ 50 m) active layer thickness (ALT) and soil moisture maps derived from airborne low frequency (L + P-band) radar measurements, and global satellite environmental observations to investigate the ALT sensitivity to recent climate trends and landscape heterogeneity in Alaska. Model simulated ALT results show good correspondence with in-situ measurements in higher permafrost probability (PP ≥ 70 %) areas (n = 33, R = 0.60, mean bias = 1.58 cm, RMSE = 20.32 cm). The model results also reveal widespread ALT deepening since 2001, with smaller ALT increases in northern Alaska (mean trend = 0.32 ± 1.18 cm yr-1) and much larger increases (> 3 cm yr-1) across interior and southern Alaska. The positive ALT trend coincides with regional warming and a longer snow-free season (R = 0.60 ± 0.32). Uncertainty in the spatial and vertical distribution of soil organic carbon (SOC) was found to be the most important factor affecting model ALT accuracy. Potential improvements in characterizing SOC heterogeneity, including better spatial sampling of soil conditions and advances in remote sensing of SOC and soil moisture, will enable more accurate predictions of permafrost active layer conditions.

scholarly journals Geoelectrical Survey of Active Layer Depth in Urban and Mature Environments of Yamal Region

2018 ◽  
Vol 170 ◽  
pp. 02024
Author(s):  
Ivan Alekseev ◽  
Evgeny Abakumov ◽  
Luka Akimov ◽  
Lubov Vorona-Slivinskaya
Keyword(s):  
Electrical Resistivity ◽  
Active Layer ◽  
Soil Cover ◽  
Urban Ecosystems ◽  
Arctic Region ◽  
The Arctic ◽  
Soil Profiles ◽  
Active Layer Thickness ◽  
Natural Environments ◽  
Mechanical Pressure

Active layer thickness and the depth of the permafrost are the basic features of the soil cover of the Arctic region. Urban ecosystems are characterized by disjunctive character of soil cover. Identification of separate soil bodies within the urban ecosystems, their spatial limitation and vertical stratification should be performed for adequate ecological assessment of urban territories. Methods of field electrophysics, which do not lead to any mechanical disturbances of soil cover, should be preferably used for both urban and natural environments. Studied soil profiles revealed significant differences in profile distribution of electrical resistivity values and active layer depths. Predominance of sand fraction in soil of Salekhard site (Spodic Cryosol) determines higher rates of thawing process compared to soil from natural site (Aquiturbic Cryosol), where clay is predominant fraction. Both soil profiles and their electrical resistivity curves are significantly affected by natural cryoturbation processes. However, vertical profile of electrical resistivity value in urban soil is more complicated and has a number of fluctuations due to higher rates of ground mixing, mechanical pressure and high amount of artefacts.

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