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The high latitudes are a hotspot for past and future climate change as forced climate signals have begun to emerge from internal variability in recent decades. New tools, such as initial condition large ensembles, provide a simulated range of possible climate realities that allow for separating the externally forced and internally variable components of the climate system. In addition, interactions between environmental variables and atmospheric circulation patterns can be detected in an unforced climate scenario and removed to isolate thermodynamic influences on the climate system. In the Arctic, this separation between dynamic and thermodynamic influences can be used to examine the impact of permafrost degradation on surface air temperatures (SAT). While impacts from permafrost degradation and subsequent carbon release have been thoroughly studied, geophysical influences have not received as much attention. This study employs the Community Earth System Model’s Large Ensemble to simulate and analyze these geophysical impacts over three time periods: 1976–2005, 2021–2050, and 2071–2100. As soil is thawing earlier and freezing later, we focus on spring and autumn to determine permafrost’s thermodynamic influence on SAT across Eurasia. We find that large internal variability, primarily due to atmospheric dynamics, affects spring SATs through 2100 while variability in autumn SATs will decrease over time due to increasing thermodynamic surface factors. These thermodynamic surface influences are most prominent in areas of continuous and discontinuous permafrost and lesser in non-permafrost regions, likely the result of a changing seasonal surface energy budget resulting from degradation and loss of permafrost.

As Arctic sea ice declines in response to climate change, a shift from thick multiyear ice to a thinner ice cover is occurring. With this transition, ice thicknesses approach a threshold below which ice no longer insulates the atmosphere from oceanic surface fluxes. While this is well known, there are no estimates of the magnitude of this threshold, nor of the proportion of sea ice area that is below this threshold as ice thins. We determine this threshold by simulating the atmospheric response to varying thicknesses, ranging from 0.0 to 2.0 m and determine that threshold to be 0.40–0.50 m. The resulting “effective” ice area is 4–14% lower than reported total ice area, as 0.39–0.97 × 106 km2 of the total ice area falls below the threshold throughout the twentieth century, including during notable ice minima. The atmosphere above large non-insulating ice-covered regions is susceptible to more than 2 °C of warming despite ice presence. Observed mean Arctic Ocean ice thickness is projected to fall below this threshold as early as the mid-2020s. Studies on ocean–atmosphere interactions in relation to sea ice area should focus on this insulating sea ice area, where ice is at least 0.40–0.50 m thick, and treat ice regions below 0.40–0.50 m thickness with caution.

Soil freeze depth (SFD) is an important indicator of cryospheric and climate change. Changes in SFD have important effects on hydrology, the energy balance, carbon exchange, and ecosystem diversity. However, quantifying and predicting SFD at large scales remains a challenge due to sparse long-term observations. This study employs the Stefan solution combined with 16 of the coupled model inter-comparison project phase 5 (CMIP5) models over the historical period (1850–2005) and three representative concentration pathways (RCP 2.6, 4.5, and 8.5) for 2006–2100, the Climatic Research Unit dataset (1901–2013), and hundreds of soil temperature, air temperature, precipitation, and snow depth sites to analyze the spatiotemporal variability of SFD in Eurasia under historical and projected climate change. During 1850–2005, a statistically significant SFD decrease of 0.49 ± 0.04 cm/decade is observed. Spatially, the biggest decreases are generally in Siberia and on the Tibetan Plateau. There is a projected decrease in 2006–2100 SFD of 4.58 ± 0.26, 1.85 ± 0.21, and 0.45 ± 0.18 cm/decade for RCP 8.5, 4.5, 2.6, respectively. These variations in SFD provide key insights into spatiotemporal changes in climate, and facilitate improved understanding of variation in frozen ground across Eurasia.

Urbanization plays an important role in human-induced climate change at the regional scale through altered land-atmosphere interactions over urban areas. In this study, the impacts of future urbanization in China on climate are investigated. The Weather Research and Forecasting model is used to downscale future projections using Representative Concentration Pathways (RCP) 4.5 simulations from the Community Earth System Model. Results for 2050 show decreased latent and increased sensible heat fluxes over the urban area, therefore leading to higher surface temperatures and less humidity. Future climate projections reveal that urbanization produces strong warming effects, up to 1.9 °C at regional and local/urban scales, which is comparable to the magnitude of greenhouse gas forcing under the RCP 4.5 scenario. Greater urban warming effects are projected during night and summer, which can be attributed to the high heat capacity of built-up areas. The impacts of urbanization on precipitation show varying effects primarily in summer—both increases and decreases depending on spatial scale—related to both local moisture deficits and large-scale circulation changes. Urbanization could strengthen the East Asian summer monsoon in southern China in summer, and slightly weaken it in eastern China in winter. Due to these significant impacts, we suggest that urbanization should be included in model projections to provide a more realistic and complete depiction of future climate.

Climate models simulate an intensifying Arctic hydrologic cycle in response to climatic warming, however the role of surface-atmosphere interactions from degrading frozen ground is unclear in these projections. Using Modern-Era Retrospective Analysis for Research and Applications (MERRA) data in high-latitude Eurasia, we examine long-term variability in surface-atmosphere coupling as represented by the statistical relationship between surface evaporative fraction (EF) and afternoon precipitation. Changes in EF, precipitation and their statistical association are then related to underlying permafrost type and snow cover. Results indicate significant positive trends in July EF in the Central Siberian Plateau, corresponding to significant increases in afternoon precipitation. The positive trends are only significant over continuous permafrost, with non-significant or negative EF and precipitation trends over isolated, sporadic and discontinuous permafrost areas. Concurrently, increasing EF and subsequent precipitation are found to coincide with significant trends in May and June snowmelt, which potentially provides the moisture source for the observed enhanced latent heating and moisture recycling in the region. As climate change causes continuous permafrost to transition to discontinuous, discontinuous to sporadic, sporadic to isolated and isolated permafrost disappears, this will also alter patterns of atmospheric convection, moisture recycling and hence the hydrologic cycle in high-latitude land areas.