Search

Rapid Arctic warming is expected to result in widespread permafrost degradation. However, observations show that site-specific conditions (vegetation and soils) may offset the reaction of permafrost to climate change. This paper summarizes 43 years of interannual seasonal thaw observations from tundra landscapes surrounding the Marre-Sale on the west coast of the Yamal Peninsula, northwest Siberia. This robust dataset includes landscape-specific climate, active layer thickness, soil moisture, and vegetation observations at multiple scales. Long-term trends from these hierarchically scaled observations indicate that drained landscapes exhibit the most pronounced responses to changing climatic conditions, while moist and wet tundra landscapes exhibit decreasing active layer thickness, and river floodplain landscapes do not show changes in the active layer. The slow increase in seasonal thaw depth despite significant warming observed over the last four decades on the Yamal Peninsula can be explained by thickening moss covers and ground surface subsidence as the transient layer (ice-rich upper permafrost soil horizon) thaws and compacts. The uneven proliferation of specific vegetation communities, primarily mosses, is significantly contributing to spatial variability observed in active layer dynamics. Based on these findings, we recommend that regional permafrost assessments employ a mean landscape-scale active layer thickness that weights the proportions of different landscape types.

Climate warming is occurring at an unprecedented rate in the Arctic due to regional amplification, potentially accelerating land cover change. Measuring and monitoring land cover change utilizing optical remote sensing in the Arctic has been challenging due to persistent cloud and snow cover issues and the spectrally similar land cover types. Google Earth Engine (GEE) represents a powerful tool to efficiently investigate these changes using a large repository of available optical imagery. This work examines land cover change in the Lower Yenisei River region of arctic central Siberia and exemplifies the application of GEE using the random forest classification algorithm for Landsat dense stacks spanning the 32-year period from 1985 to 2017, referencing 1641 images in total. The semiautomated methodology presented here classifies the study area on a per-pixel basis utilizing the complete Landsat record available for the region by only drawing from minimally cloud- and snow-affected pixels. Climatic changes observed within the study area’s natural environments show a statistically significant steady greening (~21,000 km2 transition from tundra to taiga) and a slight decrease (~700 km2) in the abundance of large lakes, indicative of substantial permafrost degradation. The results of this work provide an effective semiautomated classification strategy for remote sensing in permafrost regions and map products that can be applied to future regional environmental modeling of the Lower Yenisei River region.

Climate change has adverse impacts on Arctic natural ecosystems and threatens northern communities by disrupting subsistence practices, limiting accessibility, and putting built infrastructure at risk. In this paper, we analyze spatial patterns of permafrost degradation and associated risks to built infrastructure due to loss of bearing capacity and thaw subsidence in permafrost regions of the Arctic. Using a subset of three Coupled Model Intercomparison Project 6 models under SSP245 and 585 scenarios we estimated changes in permafrost bearing capacity and ground subsidence between two reference decades: 2015–2024 and 2055–2064. Using publicly available infrastructure databases we identified roads, railways, airport runways, and buildings at risk of permafrost degradation and estimated country-specific costs associated with damage to infrastructure. The results show that under the SSP245 scenario 29% of roads, 23% of railroads, and 11% of buildings will be affected by permafrost degradation, costing $182 billion to the Arctic states by mid-century. Under the SSP585 scenario, 44% of roads, 34% of railroads, and 17% of buildings will be affected with estimated cost of $276 billion, with airport runways adding an additional $0.5 billion. Russia is expected to have the highest burden of costs, ranging from $115 to $169 billion depending on the scenario. Limiting global greenhouse gas emissions has the potential to significantly decrease the costs of projected damages in Arctic countries, especially in Russia. The approach presented in this study underscores the substantial impacts of climate change on infrastructure and can assist to develop adaptation and mitigation strategies in Arctic states.

Russian regions containing permafrost play an important role in the Russian economy, containing vast reserves of natural resources and hosting large-scale infrastructure to facilitate these resources’ exploitation. Rapidly changing climatic conditions are a major concern for the future economic development of these regions. This study examines the extent to which infrastructure and housing are affected by permafrost in Russia and estimates the associated value of these assets. An ensemble of climate projections is used as a forcing to a permafrost-geotechnical model, in order to estimate the cost of buildings and infrastructure affected by permafrost degradation by mid-21st century under RCP 8.5 scenario. The total value of fixed assets on permafrost was estimated at 248.6 bln USD. Projected climatic changes will affect 20% of structures and 19% of infrastructure assets, costing 16.7 bln USD and 67.7 bln USD respectively to mitigate. The total cost of residential real estate on permafrost was estimated at 52.6 bln USD, with 54% buildings affected by significant permafrost degradation by the mid-21st century. The paper discusses the variability in climate-change projections and the ability of Russia’s administrative regions containing permafrost to cope with projected climate-change impacts. The study can be used in land use planning and to promote the development of adaptation and mitigation strategies for addressing the climate-change impacts of permafrost degradation on infrastructure and housing.

Role of changing climatic conditions on permafrost degradation and hydrology was investigated in the transition zone between the tundra and forest ecotones at the boundary of continuous and discontinuous permafrost of the lower Yenisei River. Three watersheds of various sizes were chosen to represent the characteristics of the regional landscape conditions. Samples of river flow, precipitation, snow cover, and permafrost ground ice were collected over the watersheds to determine isotopic composition of potential sources of water in a river flow over a two year period. Increases in air temperature over the last forty years have resulted in permafrost degradation and a decrease in the seasonal frost which is evident from soil temperature measurements, permafrost and active-layer monitoring, and analysis of satellite imagery. The lowering of the permafrost table has led to an increased storage capacity of permafrost affected soils and a higher contribution of ground water to river discharge during winter months. A progressive decrease in the thickness of the layer of seasonal freezing allows more water storage and pathways for water during the winter low period making winter discharge dependent on the timing and amount of late summer precipitation. There is a substantial seasonal variability of stable isotopic composition of river flow. Spring flooding corresponds to the isotopic composition of snow cover prior to the snowmelt. Isotopic composition of river flow during the summer period follows the variability of precipitation in smaller creeks, while the water flow of larger watersheds is influenced by the secondary evaporation of water temporarily stored in thermokarst lakes and bogs. Late summer precipitation determines the isotopic composition of texture ice within the active layer in tundra landscapes and the seasonal freezing layer in forested landscapes as well as the composition of the water flow during winter months.