scholarly journals Numerical Mapping and Modeling Permafrost Thermal Dynamics across the Qinghai-Tibet Engineering Corridor, China Integrated with Remote Sensing

2018 ◽  
Vol 10 (12) ◽  
pp. 2069 ◽  
Author(s):  
Guoan Yin ◽  
Hao Zheng ◽  
Fujun Niu ◽  
Jing Luo ◽  
Zhanju Lin ◽  
...  
Keyword(s):  
Air Temperature ◽  
Field Measurements ◽  
Active Layer Thickness ◽  
Climate Projections ◽  
Permafrost Region ◽  
Infrastructure Development ◽  
High Mountains ◽  
Thermal Dynamics ◽  
Near Surface ◽  
Discontinuous Permafrost

Permafrost thermal conditions across the Qinghai–Tibet Engineering Corridor (QTEC) is of growing interest due to infrastructure development. Most modeling of the permafrost thermal regime has been conducted at coarser spatial resolution, which is not suitable for engineering construction in a warming climate. Here we model the spatial permafrost thermal dynamics across the QTEC from the 2010 to the 2060 using the ground thermal model. Soil properties are defined based on field measurements and ecosystem types. The climate forcing datasets are synthesized from MODIS-LST products and the reanalysis product of near-surface air temperature. The climate projections are based on long-term observations of air temperature across the QTEC. The comparison of model results to field measurements demonstrates a satisfactory agreement for the purpose of permafrost thermal modeling. The results indicate a discontinuous permafrost distribution in the QTEC. Mean annual ground temperatures (MAGT) are lowest (<−2.0 °C) for the high mountains. In most upland plains, MAGTs range from −2.0 °C to 0 °C. For high mountains, the average active-layer thickness (ALT) is less than 2.0 m, while the river valley features ALT of more than 4.0 m. For upland plains, the modeled ALTs generally range from 3.0 m to 4.0 m. The simulated results for the future 50 years suggest that 12.0%~20.2% of the permafrost region will be involved in degradation, with an MAGT increase of 0.4 °C~2.3 °C, and the ALT increasing by 0.4 m~7.3 m. The results of this study are useful for the infrastructure development, although there are still several improvements in detailed forcing datasets and a locally realistic model.

scholarly journals Using MODIS Land Surface Temperatures for Permafrost Thermal Modeling in Beiluhe Basin on the Qinghai-Tibet Plateau

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4200 ◽  
Author(s):  
Anyuan Li ◽  
Caichu Xia ◽  
Chunyan Bao ◽  
Guoan Yin
Keyword(s):  
Surface Temperature ◽  
Land Surface ◽  
Ground Surface ◽  
Tibet Plateau ◽  
Active Layer Thickness ◽  
Permafrost Region ◽  
Thermal Dynamics ◽  
Near Surface ◽  
Warm Bias ◽  
Qinghai Tibet Plateau

It is essential to monitor the ground temperature over large areas to understand and predict the effects of climate change on permafrost due to its rapid warming on the Qinghai-Tibet Plateau (QTP). Land surface temperature (LST) is an important parameter for the energy budget of permafrost environments. Moderate Resolution Imaging Spectroradiometer (MODIS) LST products are especially valuable for detecting permafrost thermal dynamics across the QTP. This study presents a comparison of MODIS-LST values with in situ near-surface air temperature (Ta), and ground surface temperature (GST) obtained from 2014 to 2016 at five sites in Beiluhe basin, a representative permafrost region on the QTP. Furthermore, the performance of the thermal permafrost model forced by MODIS-LSTs was studied. Averaged LSTs are found to strongly correlated with Ta and GST with R2 values being around 0.9. There is a significant warm bias (4.43–4.67 °C) between averaged LST and Ta, and a slight warm bias (0.67–2.66 °C) between averaged LST and GST. This study indicates that averaged MODIS-LST is supposed to be a useful data source for permafrost monitoring. The modeled ground temperatures and active-layer thickness have a good agreement with the measurements, with a difference of less than 1.0 °C and 0.4 m, respectively.

scholarly journals High Spatial Resolution Modeling of Climate Change Impacts on Permafrost Thermal Conditions for the Beiluhe Basin, Qinghai-Tibet Plateau

2019 ◽  
Vol 11 (11) ◽  
pp. 1294 ◽  
Author(s):  
Jing Luo ◽  
Guoan Yin ◽  
Fujun Niu ◽  
Zhanju Lin ◽  
Minghao Liu
Keyword(s):  
Climate Change ◽  
Climate Change Impacts ◽  
Tibet Plateau ◽  
Ecosystem Change ◽  
Active Layer Thickness ◽  
Climate Projections ◽  
Permafrost Degradation ◽  
Thermal Dynamics ◽  
Discontinuous Permafrost ◽  
Qinghai Tibet Plateau

Permafrost is degrading on the Qinghai-Tibet Plateau (QTP) due to climate change. Permafrost degradation can result in ecosystem changes and damage to infrastructure. However, we lack baseline data related to permafrost thermal dynamics at a local scale. Here, we model climate change impacts on permafrost from 1986 to 2075 at a high resolution using a numerical model for the Beiluhe basin, which includes representative permafrost environments of the QTP. Ground surface temperatures are derived from air temperature using an n-factor vs Normalized Differential Vegetation Index (NDVI) relationship. Soil properties are defined by field measurements and ecosystem types. The climate projections are based on long-term observations. The modelled ground temperature (MAGT) and active-layer thickness (ALT) are close to in situ observations. The results show a discontinuous permafrost distribution (61.4%) in the Beiluhe basin at present. For the past 30 years, the permafrost area has decreased rapidly, by a total of 26%. The mean ALT has increased by 0.46 m. For the next 60 years, 8.5–35% of the permafrost area is likely to degrade under different trends of climate warming. The ALT will probably increase by 0.38–0.86 m. The results of this study are useful for developing a deeper understanding of ecosystem change, permafrost development, and infrastructure development on the QTP.

Permafrost and active layer research on James Ross Island: An overview

2019 ◽  
Vol 9 (1) ◽  
pp. 20-36 ◽  
Author(s):  
Filip Hrbáček ◽  
Daniel Nývlt ◽  
Kamil Láska ◽  
Michaela Kňažková ◽  
Barbora Kampová ◽  
...  
Keyword(s):  
Thermal Conductivity ◽  
Layer Thickness ◽  
Active Layer ◽  
Air Temperature ◽  
Thermal Regime ◽  
Ground Temperature ◽  
Active Layer Thickness ◽  
Near Surface ◽  
James Ross Island ◽  
The Mean

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.

scholarly journals Simulated high-latitude soil thermal dynamics during the past four decades

2015 ◽  
Vol 9 (2) ◽  
pp. 2301-2337 ◽  
Author(s):  
S. Peng ◽  
P. Ciais ◽  
G. Krinner ◽  
T. Wang ◽  
I. Gouttevin ◽  
...  
Keyword(s):  
Active Layer ◽  
Loss Rate ◽  
Rate Of Change ◽  
Climate Forcing ◽  
Active Layer Thickness ◽  
Thermal Dynamics ◽  
Near Surface ◽  
Key Indicator ◽  
Decadal Scale ◽  
Downward Radiation

Abstract. Soil temperature (Ts) change is a key indicator of the dynamics of permafrost. On seasonal and inter-annual time scales, the variability of Ts determines the active layer depth, which regulates hydrological soil properties and biogeochemical processes. On the multi-decadal scale, increasing Ts not only drives permafrost thaw/retreat, but can also trigger and accelerate the decomposition of soil organic carbon. The magnitude of permafrost carbon feedbacks is thus closely linked to the rate of change of soil thermal regimes. In this study, we used nine process-based ecosystem models with permafrost processes, all forced by different observation-based climate forcing during the period 1960–2000, to characterize the warming rate of Ts in permafrost regions. There is a large spread of Ts trends at 20 cm depth across the models, with trend values ranging from 0.010 ± 0.003 to 0.031 ± 0.005 °C yr−1. Most models show smaller increase in Ts with increasing depth. Air temperature (Ta) and longwave downward radiation (LWDR) are the main drivers of Ts trends, but their relative contributions differ amongst the models. Different trends of LWDR used in the forcing of models can explain 61% of their differences in Ts trends, while trends of Ta only explain 5% of the differences in Ts trends. Uncertain climate forcing contributes a larger uncertainty in Ts trends (0.021 ± 0.008 °C yr−1, mean ± SD) than the uncertainty of model structure (0.012 ± 0.001 °C yr−1), diagnosed from the range of response between different models, normalized to the same forcing. In addition, the loss rate of near-surface permafrost area, defined as total area where the maximum seasonal active layer thickness (ALT) is less than 3 m loss rate is found to be significantly correlated with the magnitude of the trends of Ts at 1 m depth across the models (R = −0.85, P = 0.003), but not with the initial total near-surface permafrost area (R = −0.30, P = 0.438). The sensitivity of the total boreal near-surface permafrost area to Ts at 1 m, is estimated to be of −2.80 ± 0.67 million km2 °C−1. Finally, by using two long-term LWDR datasets and relationships between trends of LWDR and Ts across models, we infer an observation-constrained total boreal near-surface permafrost area decrease comprised between 39 ± 14 × 103 and 75 ± 14 × 103 km2 yr−1 from 1960 to 2000. This corresponds to 9–18% degradation of the current permafrost area.

scholarly journals Simulated high-latitude soil thermal dynamics during the past 4 decades

2016 ◽  
Vol 10 (1) ◽  
pp. 179-192 ◽  
Author(s):  
S. Peng ◽  
P. Ciais ◽  
G. Krinner ◽  
T. Wang ◽  
I. Gouttevin ◽  
...  
Keyword(s):  
Active Layer ◽  
Loss Rate ◽  
Rate Of Change ◽  
Climate Forcing ◽  
Active Layer Thickness ◽  
Data Sets ◽  
Thermal Dynamics ◽  
Near Surface ◽  
Decadal Scale ◽  
Downward Radiation

Abstract. Soil temperature (Ts) change is a key indicator of the dynamics of permafrost. On seasonal and interannual timescales, the variability of Ts determines the active-layer depth, which regulates hydrological soil properties and biogeochemical processes. On the multi-decadal scale, increasing Ts not only drives permafrost thaw/retreat but can also trigger and accelerate the decomposition of soil organic carbon. The magnitude of permafrost carbon feedbacks is thus closely linked to the rate of change of soil thermal regimes. In this study, we used nine process-based ecosystem models with permafrost processes, all forced by different observation-based climate forcing during the period 1960–2000, to characterize the warming rate of Ts in permafrost regions. There is a large spread of Ts trends at 20 cm depth across the models, with trend values ranging from 0.010 ± 0.003 to 0.031 ± 0.005 °C yr−1. Most models show smaller increase in Ts with increasing depth. Air temperature (Tsub>a) and longwave downward radiation (LWDR) are the main drivers of Ts trends, but their relative contributions differ amongst the models. Different trends of LWDR used in the forcing of models can explain 61 % of their differences in Ts trends, while trends of Ta only explain 5 % of the differences in Ts trends. Uncertain climate forcing contributes a larger uncertainty in Ts trends (0.021 ± 0.008 °C yr−1, mean ± standard deviation) than the uncertainty of model structure (0.012 ± 0.001 °C yr−1), diagnosed from the range of response between different models, normalized to the same forcing. In addition, the loss rate of near-surface permafrost area, defined as total area where the maximum seasonal active-layer thickness (ALT) is less than 3 m loss rate, is found to be significantly correlated with the magnitude of the trends of Ts at 1 m depth across the models (R = −0.85, P = 0.003), but not with the initial total near-surface permafrost area (R = −0.30, P = 0.438). The sensitivity of the total boreal near-surface permafrost area to Ts at 1 m is estimated to be of −2.80 ± 0.67 million km2 °C−1. Finally, by using two long-term LWDR data sets and relationships between trends of LWDR and Ts across models, we infer an observation-constrained total boreal near-surface permafrost area decrease comprising between 39 ± 14  ×  103 and 75 ± 14  ×  103 km2 yr−1 from 1960 to 2000. This corresponds to 9–18 % degradation of the current permafrost area.

scholarly journals Permafrost thaw and ground settlement considering long-term climate impact in northern Alaska

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Zhaohui Joey Yang ◽  
Kannon C. Lee ◽  
Haibo Liu
Keyword(s):  
Layer Thickness ◽  
Active Layer ◽  
Air Temperature ◽  
Climate Model ◽  
Ground Surface ◽  
Active Layer Thickness ◽  
Near Surface ◽  
Surface Conditions ◽  
Ice Content ◽  
Northern Alaska

AbstractAlaska’s North Slope is predicted to experience twice the warming expected globally. When summers are longer and winters are shortened, ground surface conditions in the Arctic are expected to change considerably. This is significant for Arctic Alaska, a region that supports surface infrastructure such as energy extraction and transport assets (pipelines), buildings, roadways, and bridges. Climatic change at the ground surface has been shown to impact soil layers beneath through the harmonic fluctuation of the active layer, and warmer air temperature can result in progressive permafrost thaw, leading to a deeper active layer. This study attempts to assess climate change based on the climate model data from the fifth phase of the Coupled Model Intercomparison Project and its impact on a permafrost environment in Northern Alaska. The predicted air temperature data are analyzed to evaluate how the freezing and thawing indices will change due to climate warming. A thermal model was developed that incorporated a ground surface condition defined by either undisturbed intact tundra or a gravel fill surface and applied climate model predicted air temperatures. Results indicate similar fluctuation in active layer thickness and values that fall within the range of minimum and maximum readings for the last quarter-century. It is found that the active layer thickness increases, with the amount depending on climate model predictions and ground surface conditions. These variations in active layer thickness are then analyzed by considering the near-surface frozen soil ice content. Analysis of results indicates that thaw strain is most significant in the near-surface layers, indicating that settlement would be concurrent with annual thaw penetration. Moreover, ice content is a major factor in the settlement prediction. This assessment methodology, after improvement, and the results can help enhance the resilience of the existing and future new infrastructure in a changing Arctic environment.

scholarly journals Permafrost Thaw and Ground Settlement Considering Long-Term Climate Impact in Northern Alaska

2021 ◽  
Author(s):  
Joey Yang ◽  
Kannon C. Lee ◽  
Haibo Liu
Keyword(s):  
Active Layer ◽  
Air Temperature ◽  
Climate Model ◽  
Ground Surface ◽  
North Slope ◽  
Active Layer Thickness ◽  
Near Surface ◽  
Surface Conditions ◽  
Air Temperatures ◽  
Ice Content

Abstract Alaska’s North Slope is predicted to experience twice the warming expected globally. When summers are longer and winters are shortened, ground surface conditions in the Arctic are expected to change considerably. This is significant for Arctic Alaska, a region that supports surface infrastructure such as energy extraction and transport assets (pipelines), buildings, roadways, and bridges. Climatic change at the ground surface has been shown to infiltrate soil layers beneath through the harmonic fluctuation of the active layer. Past studies found that warmer air temperature resulted in increasingly deeper thaw, leading to a deeper active layer. This study attempts to assess climate change based on the climate model data from the fifth phase of the Coupled Model Intercomparison Project and its impact on a study site on the North Slope. The predicted air temperature data are analyzed to evaluate how the freezing and thawing indices will change due to climate warming. A thermal model was developed that incorporated a ground surface condition defined by either undisturbed intact tundra or a gravel fill surface and applied climate model predicted air temperatures. Results indicate similar fluctuation in active layer thickness and values that fall within the range of minimum and maximum readings. It is found that the active layer thickens when the ground surface is either gravel fill or undisturbed tundra, but its thickness varies based on climate model predictions. These variations in active layer thickness are then analyzed by considering the near-surface frozen soil ice content. Analysis of results indicates that strain is most significant in the near-surface layers during thaw, indicating that settlement would be concurrent with annual thaw penetration. From this study, the climate model predicted air temperatures for a warming Arctic suggest that the thaw of near-surface frozen ground is largely dependent on ground surface conditions and the thermal properties of soil. Moreover, ice content is a major factor in the settlement predictions on Alaska’s North Slope. This study's results can help enhance the resilience of the existing and future new infrastructure in a changing Arctic environment.

Climate extremes relevant for permafrost degradation

2020 ◽  
Author(s):  
Goran Georgievski ◽  
Stefan Hagemann ◽  
Dmitry Sein ◽  
Dmitry Drozdov ◽  
Andrew Gravis ◽  
...  
Keyword(s):  
Air Temperature ◽  
Snow Depth ◽  
Thermal State ◽  
Numerical Models ◽  
Soil Layer ◽  
Active Layer Thickness ◽  
Climate Projections ◽  
Permafrost Degradation ◽  
Climate Conditions ◽  
Extreme Climate

&lt;p&gt;During the past several decades, Arctic regions warmed almost twice as much as the global average temperature. Simultaneously in the high northern latitudes, observations indicate a decline in permafrost extend and landscape modifications due to permafrost degradation. Climate projections suggest an accelerated soil warming, and consequently deepening of the active layer thickness in the near future. Except air temperature, two other parameters i.e. precipitation and snow depth are the most important climatic parameters affecting the thermal state and extend of the permafrost. The key research question of this study is whether or not certain climatic conditions can be identified that can be considered as an extreme event relevant for permafrost degradation. Here we apply data mining techniques on meteorological re-analysis to develop a coherent framework for the identification of extreme climate conditions relevant for active soil layer deepening and a decline of permafrost extend. &lt;br&gt;Several key types of events have been classified based on various combinations of temperature, precipitation and snow depth statistics. Then, the respective events have been identified in ERA-Interim reanalysis and evaluated against in situ observations in West Siberia region. The evaluation proved that the developed algorithm could successfully detect relevant extreme climate conditions in meteorological re-analysis dataset. It also indicated possibilities to improve the algorithm by refining definitions of extreme events. Refinement of algorithm is currently work in progress as well as the evaluation against satellite observations and a hierarchy of numerical models. Nevertheless, the method is applicable for all kinds of gridded climatological datasets that contain air temperature, precipitation and snow depth.&lt;/p&gt;&lt;p&gt;A&lt;span&gt;cknowledgement&lt;/span&gt;&lt;br&gt;This work is funded in the frame of ERA-Net plus Russia. TSU is supported by MOSC RF # 14.587.21.0048 (RFMEFI58718X0048), AWI and HZG are supported by BMBF (Grant no. 01DJ18016A and 01DJ18016B), and WUT by a grant of the Romanian National Authority for Scientific Research and Innovation, CCDI-UEFISCDI, project number ERANET-RUS-PLUS-SODEEP, within PNCD III&lt;/p&gt;

scholarly journals A distributed temperature profiling method for assessing spatial variability in ground temperatures in a discontinuous permafrost region of Alaska

2019 ◽  
Vol 13 (11) ◽  
pp. 2853-2867 ◽  
Author(s):  
Emmanuel Léger ◽  
Baptiste Dafflon ◽  
Yves Robert ◽  
Craig Ulrich ◽  
John E. Peterson ◽  
...  
Keyword(s):  
Soil Temperature ◽  
Thermal Flux ◽  
Temperature Sensing ◽  
Permafrost Region ◽  
Distributed Temperature Sensing ◽  
Near Surface ◽  
Ground Temperatures ◽  
Discontinuous Permafrost ◽  
New Strategy ◽  
Over The Top

Abstract. Soil temperature has been recognized as a property that strongly influences a myriad of hydro-biogeochemical processes and reflects how various properties modulate the soil thermal flux. In spite of its importance, our ability to acquire soil temperature data with high spatial and temporal resolution and coverage is limited because of the high cost of equipment, the difficulties of deployment, and the complexities of data management. Here we propose a new strategy that we call distributed temperature profiling (DTP) for improving the characterization and monitoring near-surface thermal properties through the use of an unprecedented number of laterally and vertically distributed temperature measurements. We developed a prototype DTP system, which consists of inexpensive, low-impact, low-power, and vertically resolved temperature probes that independently and autonomously record soil temperature. The DTP system concept was tested by moving sequentially the system across the landscape to identify near-surface permafrost distribution in a discontinuous permafrost environment near Nome, Alaska, during the summertime. Results show that the DTP system enabled successful acquisition of vertically resolved profiles of summer soil temperature over the top 0.8 m at numerous locations. DTP also enabled high-resolution identification and lateral delineation of near-surface permafrost locations from surrounding zones with no permafrost or deep permafrost table locations overlain by a perennially thawed layer. The DTP strategy overcomes some of the limitations associated with – and complements the strengths of – borehole-based soil temperature sensing as well as fiber-optic distributed temperature sensing (FO-DTS) approaches. Combining DTP data with co-located topographic and vegetation maps obtained using unmanned aerial vehicle (UAV) and electrical resistivity tomography (ERT) data allowed us to identify correspondences between surface and subsurface property distribution and in particular between topography, vegetation, shallow soil properties, and near-surface permafrost. Finally, the results highlight the considerable value of the newly developed DTP strategy for investigating the significant variability in and complexity of subsurface thermal and hydrological regimes in discontinuous permafrost regions.

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