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The anthropogenic climate change threatens northern permafrost environments. This compromises the existence of permafrost landforms, such as palsas and peat plateaus, which have been assessed to be critically endangered habitats. In this study, for the first time we integrated geospatial datasets and statistical methods, to model the distribution of palsas and peat plateaus across the Northern Hemisphere permafrost region. The models were calibrated using data from years 1950–2000. The effects of climate change on the future distribution of palsas were assessed by using moderate and high emission scenarios (Representative Concentration Pathways; RCP4.5 and RCP8.5, respectively) for two periods (2041–2060 and 2061–2080). Hotspots for palsas and peat plateaus occurred in Northern Europe, Western Siberia, and subarctic Canada. Climate change was predicted to cause an almost complete loss (˗98.2 %) of suitable environmental spaces under a high emissions scenario by 2061–2080, while under a moderate emissions scenario 89.3 % were predicted to disappear. The comparison with previously published thermokarst data supported our findings regarding the recent degradation of palsa and peat plateau environments. Our results fill the knowledge gaps in the distribution of the permafrost landforms in less studied areas such as Central and Eastern Siberia. In addition, the projections provide insights into the changing geoecological conditions of the circumpolar region with important implications for greenhouse gas emissions.

The thermal state of permafrost affects Earth surface systems and human activity in the Arctic and has implications for global climate. Improved understanding of the local-scale variability in the global ground thermal regime is required to account for its sensitivity to changing climatic and geoecological conditions. Here, we statistically related observations of mean annual ground temperature (MAGT) and active-layer thickness (ALT) to high-resolution (∼1 km2) geospatial data of climatic and local environmental conditions across the Northern Hemisphere. The aim was to characterize the relative importance of key environmental factors and the magnitude and shape of their effects on MAGT and ALT. The multivariate models fitted well to both response variables with average R2 values being ∼0.94 and 0.78. Corresponding predictive performances in terms of root-mean-square error were ∼1.31 ∘C and 87 cm. Freezing (FDD) and thawing (TDD) degree days were key factors for MAGT inside and outside the permafrost domain with average effect sizes of 6.7 and 13.6 ∘C, respectively. Soil properties had marginal effects on MAGT (effect size =0.4–0.7 ∘C). For ALT, rainfall (effect size =181 cm) and solar radiation (161 cm) were most influential. Analysis of variable importance further underlined the dominance of climate for MAGT and highlighted the role of solar radiation for ALT. Most response shapes for MAGT ≤0 ∘C and ALT were non-linear and indicated thresholds for covariation. Most importantly, permafrost temperatures had a more complex relationship with air temperatures than non-frozen ground. Moreover, the observed warming effect of rainfall on MAGT≤0∘C reverted after reaching an optimum at ∼250 mm, and that of snowfall started to level off at ∼300–400 mm. It is suggested that the factors of large global variation (i.e. climate) suppressed the effects of local-scale factors (i.e. soil properties and vegetation) owing to the extensive study area and limited representation of soil organic matter. Our new insights into the factors affecting the ground thermal regime at a 1 km scale should improve future hemispheric-scale studies.

Monitoring the thermal state of permafrost (TSP) is important in many environmental science and engineering applications. However, such data are generally unavailable, mainly due to the lack of ground observations and the uncertainty of traditional physical models. This study produces novel permafrost datasets for the Northern Hemisphere (NH), including predictions of the mean annual ground temperature (MAGT) at the depth of zero annual amplitude (DZAA) (approximately 3 to 25 m) and active layer thickness (ALT) with 1 km resolution for the period of 2000–2016, as well as estimates of the probability of permafrost occurrence and permafrost zonation based on hydrothermal conditions. These datasets integrate unprecedentedly large amounts of field data (1002 boreholes for MAGT and 452 sites for ALT) and multisource geospatial data, especially remote sensing data, using statistical learning modeling with an ensemble strategy. Thus, the resulting data are more accurate than those of previous circumpolar maps (bias = 0.02±0.16 ∘C and RMSE = 1.32±0.13 ∘C for MAGT; bias = 2.71±16.46 cm and RMSE = 86.93±19.61 cm for ALT). The datasets suggest that the areal extent of permafrost (MAGT ≤0 ∘C) in the NH, excluding glaciers and lakes, is approximately 14.77 (13.60–18.97) × 106 km2 and that the areal extent of permafrost regions (permafrost probability >0) is approximately 19.82×106 km2. The areal fractions of humid, semiarid/subhumid, and arid permafrost regions are 51.56 %, 45.07 %, and 3.37 %, respectively. The areal fractions of cold (≤-3.0 ∘C), cool (−3.0 ∘C to −1.5 ∘C), and warm (>-1.5 ∘C) permafrost regions are 37.80 %, 14.30 %, and 47.90 %, respectively. These new datasets based on the most comprehensive field data to date contribute to an updated understanding of the thermal state and zonation of permafrost in the NH. The datasets are potentially useful for various fields, such as climatology, hydrology, ecology, agriculture, public health, and engineering planning. All of the datasets are published through the National Tibetan Plateau Data Center (TPDC), and the link is https://doi.org/10.11888/Geocry.tpdc.271190 (Ran et al., 2021a).

The climate in the Boreal area is warming at a pace that is exceeding the global average. Both temperature and precipitation is projected to increase due to climate change. The gross primary production in the forested area is also projected to increase, as well as the soil respiration. The burned area is sensitive to the meteorological forcing and the risk of ignition depends on the amount and properties of the litter. Overall climate change has a potential to increase the fire risk in the Boreal forests.The effects of projected climate change on forest fires in Fennoscandia, and in parts of Russia adjacent to Finland, were simulated with the JSBACH-SPITFIRE. JSBACH is the land model in the Earth system models of the Max-Planck Institute for Meteorology. SPITFIRE is a mechanistic fire model, driven by meteorology, vegetation cover, fuel load and fuel properties. The model simulates fire risk, number of fires and burned area fraction. SPITFIRE uses ignition rates and distinguishes between ignition events caused by lightning and humans. Ignition events result in fire only when enough fuel is present, and the fuel is sufficiently dry. The JSBACH-SPITFIRE model was driven by downscaled and bias corrected meteorological data from the EURO-CORDEX initiative, for the period from 1951 to 2100. The model domain was the land area within 55-71°N and 5-38°E. A subset of the EUR-44 domain was regridded to 0.5° resolution for our model domain. The global driving models used for producing the EURO-CORDEX data used here were CanESM2, CNRM-CM5, MIROC5. We selected driver models that represent mid-range regarding the projected change in temperature and precipitation for Finland under RCP4.5 and RCP8.5. We used daily bias corrected data of precipitation and temperature from 1951 to 2100 for both RCP4.5 and RCP8.5 climate change projections. In addition, daily data of relative humidity, wind speed, longwave and shortwave radiation were used for the historical (1951-2005) and scenario period (2006-2100).Preliminary results indicate that the increase in temperature, which affects the drying rate of the fuel, is the major factor for driving the changes in forest fires in the simulations.

Arctic earth surface systems are undergoing unprecedented changes, with permafrost thaw as one of the most striking examples. Permafrost is critical because it controls ecosystem processes, human activities, and landscape dynamics in the north. Degradation (i.e. warming and thawing) of permafrost is related to several hazards, which may pose a serious risk to humans and the environment. Thaw of ice-rich permafrost increases ground instability, landslides, and infrastructure damages. Degrading permafrost may lead to the release of significant amounts of greenhouse gases to the atmosphere and threatens also biodiversity, geodiversity and ecosystem services. Thawing permafrost may even jeopardize human health. Consequently, a deeper understanding of the hazards and risks related to the degradation of permafrost is fundamental for science and society.To address climate change effects on infrastructure and human activities, we (i) mapped circumpolar permafrost hazard areas and (ii) quantified critical engineering structures and population at risk by mid-century. We used observations of ground thermal regime, geospatial environmental data, and statistically-based ensemble methods to model the current and future near-surface permafrost extent at ca. 1 km resolution. Using the forecasts of ground temperatures, a consensus of three geohazard indices, and geospatial data we quantified the amount and proportion of infrastructure elements and population at risk owing to climate change. We show that ca. 70% of current infrastructure and population in the permafrost domain are in areas with high potential for thaw of near-surface permafrost by 2050. One-third of fundamental infrastructure is located in high hazard regions where the ground is susceptible to thaw-related ground instability. Owing to the observed data-related and methodological limitations we call for improvements in the circumpolar hazard mappings and infrastructure risk assessments.To successfully manage climate change impacts and support sustainable development in the Arctic, it is critical to (i) produce high-resolution geospatial datasets of ground conditions (e.g., content of organic material and ground ice), (ii) develop further high-resolution permafrost modelling, (iii) comprehensively map permafrost degradation-related hazards, and (iv) quantify the amount and economic value of infrastructure and natural resources at risk across the circumpolar permafrost area.

In recent years, large forest fires in Fennoscandia have shown that wildfires can have a strong impact on society also in northern Europe. In the future, meteorological conditions are expected to become increasingly favorable for wildfires due to climate change. An important aspect in fire management are the national forest management strategies that play a crucial role in controlling e.g. fuel availability in forests, and further areal coverage of burned area. In addition, the effectiveness of rescue services is crucial. Thus, the development of fire risk prediction and fire detection systems, as well as, modeling of spread of fires and emissions of harmful ingredients, such as black carbon are urgently required to improve the societies preparedness to the increasing thread. In this presentation we synthetize the current state-of-the-art understanding of wildfires in Fennoscandia from a wide range of key perspectives: historical fire regimes, monitoring using in-situ and remote-sensing technologies, integrated modeling (e.g. climate models, spatial fire propagation models forced with operational weather forecast model) and fire suppression. In addition, we assess the amount of black carbon emissions released from recent wildfires in Fennoscandia. These results will help northern societies to tackle against the negative impacts of climate change and to support the development of efficient mitigation strategies. In the upcoming decades the effective management of wildfires is especially relevant, as wildfires greatly affect regional carbon budgets and mitigation efforts.

Ground thermal regime in cold environments is key to understanding the effects of climate change on surface–atmosphere feedbacks. The northern Eurasia, covering over half of terrestrial areas north of 40°N, is sensitive to the ongoing climate change due to underlain permafrost and seasonal frost. Here, we quantify the recent ground thermal dynamics and variations over northern Eurasia by compiling measurements of soil temperature data over 457 sites at multiple depths from 1975-2016. Our analysis shows that the mean annual ground temperature has significant warming trends by 0.30–0.31 °C/decade at depths of 0.8, 1.6, and 3.2 m. We found that the changes in annual maximum ground temperatures were more pronounced than mean annual ground temperatures with a weakened warming magnitude (0.40 to 0.31°C/decade) from upper to lower ground. Our results also suggest the substantial differences in warming magnitudes through parameters and depths over different frost-related areas. The ground over continuous permafrost area warmed faster than non-continuous permafrost and seasonal frost areas in shallow ground (0.8 and 1.6 m depth) but slower in deeper ground (3.2 m). Our study highlights the varied ground temperature evolutions at multiple depths and different frost-related ground, suggesting the importance of separated discussions on different frost-affected ground in application and future research. Noteworthy, the results indicate that the significant ground warming can promote greenhouse gas emissions from soil to atmosphere, further accelerating climate change.

The thermal dynamics of permafrost shape Earth surface systems and human activity in the Arctic and have implications to global climate. Improved understanding of the fine-scale variability in the circumpolar ground thermal regime is required to account for its sensitivity to changing climatic and geoecological conditions. Here, we statistically related circumpolar observations of mean annual ground temperature (MAGT) and active-layer thickness (ALT) to high-resolution (~1 km2) geospatial data to identify their key environmental drivers. The multivariate models fitted well to MAGT and ALT observations with average R2 values being ~0.94 and 0.78, respectively. Corresponding predictive performances in terms of root mean square error were ~1.31 °C and 87 cm. Freezing air temperatures were the main driver of MAGT in permafrost conditions while thawing temperatures dominated when permafrost was not present. ALT was most strongly related to solar radiation and precipitation with an important influence from soil properties. Our findings suggest that in addition to climatic factors, initial ground thermal conditions and local-scale topography-soil-driven variability need to be considered in order to realistically assess the impacts of climate change on cold-climate geoecosystems.