Changes in permafrost extent and active layer thickness in the Northern Hemisphere from 1969 to 2018

Degradation of ice-wedge polygons leads to increased fluxes of water and DOC

Ice-wedge polygon landscapes make up a substantial part of high-latitude permafrost landscapes. The hydrological conditions shape how these landscapes store and release organic carbon. However, their coupled water‑carbon dynamics are poorly understood as field measurements are sparse in smaller catchments and coupled hydrology-dissolved organic carbon (DOC) models are not tailored for these landscapes. Here we present a model that simulates the hydrology and associated DOC export of high-centered and low-centered ice-wedge polygons and apply the model to a small catchment with abundant polygon coverage along the Yukon Coast, Canada. The modeled seasonal pattern of water and carbon fluxes aligns with sparse field data. These modeled seasonal patterns indicate that early-season runoff is mostly surficial and generated by low-centered polygons and snow trapped in troughs of high-centered polygons. High-centered polygons show potential for deeper subsurface flow under future climate conditions. This suggests that high-centered polygons will be responsible for an increasing proportion of annual DOC export compared to low-centered polygons. Warming likely shifts low-centered polygons to high-centered polygons, and our model shows that this shift will cause a deepening of the active layer and a lengthening of the thawing season. This, in turn, intensifies seasonal runoff and DOC flux, mainly through its duration. Our model provides a physical hypothesis that can be used to further quantify and refine our understanding of hydrology and DOC export of arctic ice-wedge polygon terrain.

Significant role of permafrost in regional hydrology of the Upper Indus Basin, India

Upper Indus Basin (UIB), being climatologically sensitive and socio-economically important, has emerged as a hotspot for eco-hydrological studies. Permafrost, one of the essential components of the regional hydrological cycle with a critical role in microclimate, is also an important water resource in the UIB. Despite being an important component of the cryospheric system, permafrost is least studied in the UIB. In present study, we used stable oxygen and hydrogen isotopic composition in supra-permafrost water (SPFW) and aufeis along with precipitation, snowpack, glacier and other groundwaters to assess their variability and estimate their contribution to regional hydrology. The sources are evolving isotopically, depending on physiographic and hydrometeorological factors, with each source attaining different (if not distinct) isotopic signatures. The isotopic signatures (with different ranges) of sources help in estimating the contribution from these sources. A significant altitude gradient of δ18O is observed in stream water, SPFW and other groundwaters. Isotopic composition in SPFW is differentially modulated by fractionation, resulting in isotopic variability from the source waters. The results suggest snowmelt and/or glacier melt as the source of SPFW. To stream flow, SPFW is the dominant contributor (43 ± 18 %) at higher elevations (> 4300 m a.m.s.l.) in July, followed by snowmelt (26 ± 10 %). In September, SPFW contribution decreases (14 ± 8 %), but the contribution from other groundwaters becomes dominant (39 ± 11 %) to stream flow. The results indicate the significant role of seasonal thawing and freezing of active layer on the contribution from SPFW. This study highlights the significant role of permafrost in the hydrological system of the basin. The study also emphasizes the need to understand the dynamics of permafrost, taliks of various types (e.g., supra-permafrost subaerial talik) and active layer under changing climate to define the subsequent implications to regional hydrology, eco-hydrological systems and micro-climate of permafrost regions.

Soil freeze-thaw cycles affect spring phenology by changing phenological sensitivity in the Northern Hemisphere

The use of frozen soil-vegetation feedback for predictive models is undergoing enormous changes under rapid climate warming. However, the influence of soil freeze-thaw (SFT) cycles on vegetation phenology and the underlying mechanisms remain poorly understood. By synthesizing a variety of satellite-derived data from 2002 to 2021 in the Northern Hemisphere (NH), we demonstrated a widespread positive correlation between soil thawing and the start of the growing season (SOS). Our results also showed that the SFT cycles had a significant impact on vegetation phenology mainly by altering the phenological sensitivities to daytime and nighttime temperatures, solar radiation and precipitation. Moreover, the effects of SFT cycles on the sensitivity of the SOS were more pronounced than those on the sensitivity of the end of the growing season (EOS) and the length of growing season (LOS). Furthermore, due to the degradation of frozen soil, the changes in phenological sensitivity in the grassland and tundra biomes were significantly larger than those in the forest. These findings highlighted the importance of incorporating the SFT as an intermediate process into process-based phenological models.

Permafrost table temperature and active layer thickness variability on James Ross Island, Antarctic Peninsula, in 2004-2021

Climate change and its impacts on sensitive polar ecosystems are relatively little studied in Antarctic regions. Permafrost and active layer changes over time in periglacial regions of the world are important indicators of climate variability. These changes (e. g. permafrost degradation, increasing of the active layer thickness) can have a significant impact on Antarctic terrestrial ecosystems. The study site (AWS-JGM) is located on the Ulu Peninsula in the north of James Ross Island. Ground temperatures at depths of 5, 50, and 75 cm have been measured at the site since 2011, while air temperature began to be measured in 2004. The main objective is to evaluate the year-to-year variability of the reconstructed temperature of the top of the permafrost table and the active layer thickness (ALT) since 2004 based on air temperature data using TTOP and Stefan models, respectively. The models were verified against direct observations from a reference period 2011/12-2020/21 showing a strong correlation of 0.95 (RMSE = 0.52) and 0.84 (RMSE = 3.54) for TTOP and Stefan models, respectively. The reconstructed average temperature of the permafrost table for the period 2004/05-2020/21 was -5.8 °C with a trend of -0.1 °C/decade, while the average air temperature reached -6.6 °C with a trend of 0.6 °C/decade. Air temperatures did not have an increasing trend throughout the period, but in the first part of the period (2004/05-2010/11) showed a decreasing tendency (-1.3 °C/decade). In the period 2011/12-2020/21, it was a warming of 1.9 °C/decade. The average modelled ALT for the period 2004/05-2020/21 reached a value of 60cm with a trend of -1.6 cm/decade. Both models were found to provide reliable results, and thus they significantly expand the information about the permafrost and ALT, which is necessary for a better understanding of their spatiotemporal variability and the impact of climate change on the cryosphere.

Characteristics of the Northern Hemisphere cold regions changes from 1901 to 2019

The accurate delineation of the spatial extent of cold regions provides the basis for the study of global environmental change. However, attention has been lacking on the temperature-sensitive spatial changes in the cold regions of the Earth in the context of climate warming. In this study, the mean temperature in the coldest month lower than - 3 °C, no more than 5 months over 10 °C, and an annual mean temperature no higher than 5 °C were selected to define cold regions. Based on the Climate Research Unit land surface air temperature (CRUTEM) of monthly mean surface climate elements, the spatiotemporal distribution and variation characteristics of the Northern Hemisphere (NH) continental cold regions from 1901 to 2019 are analyzed in this study, by adopting time trend and correlation analyses. The results show: (1) In the past 119 years, the cold regions of the NH covered on average about 4.074 × 10⁷ km², accounting for 37.82% of the total land area of the NH. The cold regions can be divided into the Mid-to-High latitude cold regions and the Qinghai-Tibetan Plateau cold regions, with spatial extents of 3.755 × 10⁷ km² and 3.127 × 10⁶ km², respectively. The Mid-to-High latitude cold regions in the NH are mainly distributed in northern North America, most of Iceland, the Alps, northern Eurasia, and the Great Caucasus with a mean southern boundary of 49.48° N. Except for the southwest, the entire region of the Qinghai-Tibetan Plateau, northern Pakistan, and most of Kyrgyzstan are cold regions. (2) In the past 119 years, the rates of change in the spatial extent of the cold regions in the NH, the Mid-to-High latitude, and the Qinghai-Tibetan Plateau were - 0.030 × 10⁷ km²/10 a, - 0.028 × 10⁷ km²/10 a, and - 0.013 × 10⁶ km²/10 a, respectively, showing an extremely significant decreasing trend. In the past 119 years, the mean southern boundary of the Mid-to-High latitude cold regions has been retreating northward at all longitudes. For instance, the mean southern boundary of the Eurasian cold regions moved 1.82° to the north and that of North America moved 0.98° to the north. The main contribution of the study lies in the accurate definition of the cold regions and documentation of the spatial variation of the cold regions in the NH, revealing the response trends of the cold regions to climate warming, and deepening the study of global change from a new perspective.

Changes in permafrost spatial distribution and active layer thickness from 1980 to 2020 on the Tibet Plateau

The Tibetan Plateau (TP) is experiencing extensive permafrost degradation due to climate change, which seriously threatens sustainable water and ecosystem management in the TP and its downstream areas. Understanding the evolution of permafrost is critical for studying changes in the water cycle, carbon flux, and ecology of the TP. In this study, we mapped the spatial distribution of permafrost and active layer thickness (ALT) at 1 km resolution for each decade using empirical models and machine learning methods validated with borehole data. A comprehensive comparison of model results and validation accuracy shows that the machine learning method is more advantageous in simulating the permafrost distribution, while the ALT simulated by the empirical model (i.e., Stefan model) better reflects the actual ALT distribution. We further evaluated the dynamics of permafrost distribution and ALT from 1980 to 2020 based on the results of the better-performing models, and analyzed the patterns and influencing factors of the changes in permafrost distribution and ALT. The results show that the permafrost area on the TP has decreased by 15.5 %, and the regionally average ALT has increased by 18.94 cm in the 2010s compared to the 1980s. The average decreasing rate of permafrost area is 6.33 × 10⁴ km² decade^-1, and the average increasing rate of ALT is 6.31 cm decade^-1. Permafrost degradation includes the decreasing permafrost area and the thickening active layer mainly related to the warming of the TP. Spatially, permafrost area decrease is more susceptible to occur at lower latitudes and lower altitudes, while ALT increases more dramatically at lower latitudes and higher altitudes. In addition, permafrost is more likely to degrade to seasonally frozen ground in areas with deeper ALT.

Underestimated permafrost degradation: Improving the TTOP model based on soil thermal conductivity

Under the continuing influence of global warming, resolving the inconsistency of permafrost degradation rates and quantifying the spatial distribution characteristics are critical for high-altitude water cycle processes. The dynamics of permafrost degradation are mainly manifested in soil temperature, which can be measured with high accuracy and high temporal resolution. This study considered the influence of soil thermal conductivity (K) by periodic land surface temperature (LST), improved the static output of the temperature at the top of permafrost (TTOP) model, and verified the reliability of the TTOP model improvement by the Kappa coefficient. The results showed that from 2000 to 2020, the extent of dynamically simulated permafrost was 5.42 × 105 km2 less than that of static simulated permafrost, and the linear degradation rate doubled. The degraded permafrost showed an increasing degradation from southeast to northwest. Among them, the degradation in the Nujiang River and the Changjiang River north of the Nyainqentanglha Mountain has exacerbated the permafrost degradation in the hinterland of the Qiangtang Plateau. Based on the AWI-CM-1-1-MR LST from CMIP6, SSP126 to SSP585 dynamic simulation results of permafrost indicate that the extent will decrease by 11.35 % by 2100. Overall, the extent and rate of permafrost degradation, considering high spatiotemporal resolution, were twice as fast as expected. Our results will inform policymakers with a more accurate spatiotemporal distribution of frozen soil types in high-altitude regions and characteristics of permafrost degradation within the watershed.

Impacts of permafrost thaw on streamflow recession in a discontinuous permafrost watershed of northeastern China

Permafrost thaw due to climate change is altering terrestrial hydrological processes by increasing ground hydraulic conductivity and surface and subsurface hydrologic connectivity across the pan-Arctic. Understanding how runoff responds to changes in hydrologic processes and conditions induced by permafrost thaw is critical for water resources management in high-latitude and high-altitude regions. In this study, we analyzed streamflow recession characteristics for 1964-2016 for the Tahe watershed located at the southern margin of the permafrost region in Eurasia. Results reveal a link between streamflow recession and permafrost degradation as indicated by the statistical analyses of streamflow and the modeled ground warming and active layer thickening. The recession constant and the active layer temperatures at depths of 5, 40, 100, and 200 cm simulated by the backpropagation neural network model significantly increased during the study period from 1972 to 2020 due to intensified climate warming in northeastern China. The onset of seasonal active layer thaw was advanced by 10 days, and the modeled active layer thickness increased by 54 cm in this period. The average annual streamflow recession time increased by 11.5 days (+53 %) from the warming period (1972-1988) to the thawing period (1989-2016), with these periods determined from breakpoint analysis. These hydrologic changes arose from increased catchment storage and were correlated to increased active layer thickness and longer seasonal thawing periods. These results highlight that permafrost degradation can significantly extend the recession flow duration in a watershed underlain by discontinuous, sporadic, and isolated permafrost, and thereby alter flooding dynamics and water resources in the southern margin of the Eurasian permafrost region.

Catastrophic PM2.5 emissions from Siberian forest fires: Impacting factors analysis

With increased forest fires due to climate change, PM_2.5 emissions also intensified. Record PM_2.5 emissions according to Copernicus Atmosphere Monitoring Service in Russia amounted to 8 megatons (Mt) in 2021, which is 78% higher than the average level of 2004-2021 (4.5 Mt). Seven federal subjects (the constituent entities) with vast forest areas without fire protection produced 86% of emissions (6.8 Mt) in 2021, the major losses (6.1 Mt) in Yakutia (Sakha Republic). The ambient temperature in Eastern Siberia is increasing, especially in months of winter and spring seasons (up to +3.6 °C) in 1990-2020 compared to 1901-2020 (CEDA Archive); climate change has affected meteorological conditions leading to increased forest fires. The results of the SARIMAX model study for PM_2.5 emissions considering meteorological factors using ERA5 and burnt forest area using MODIS (MCD64A1), establishing a significant dependence of PM_2.5 emissions on the lack of precipitation and the associated parameters of complete and potential evaporation. This influence long before the fire season (up to 9 months), as it affects the snow cover and the dryness of the fuel by the beginning of forest fires. In turn, high PM_2.5 emission values are accompanied by a drop in 2 m air temperature and surface solar radiation downwards due to the aerosol saturation with suspended particles. The average COR for seven federal subjects was 0.79, with the highest forecast result in Yakutia (0.95), indicating the maximum propensity for record emissions due to weather conditions. In combination with forest management without fire protection, meteorological parameters have caused an increase in PM_2.5 emissions in recent years in Siberia. The forest needs other ways to manage under the pressures of climate change to reduce environmental pollution associated with PM_2.5 emissions from vast Siberian fires.