Permafrost warming leads to greenhouse gas release to the atmosphere, resulting in a positive feedback to climate change. Earth system models indicate that more than 80% of the near‐surface permafrost is projected to disappear by the end of this century, but with a high degree of uncertainty. Here, we apply the Stefan solution to estimate permafrost degradation under future emission scenarios. We find that the most severe future scenario is likely to lead to only a 14% decrease in area extent of the near‐surface permafrost at 3.5 m depth, and an area extent decrease of 1.3% at a depth of 6.0 m. Relative to active layer thickness increases from historical simulations, we find a less than 30% deepening for most permafrost regions by the end of this century. These results imply that the Stefan solution provides near‐surface permafrost area extent degradation estimates that are substantially lower than directly projected by models.

Vegetation is closely tied to climate change, hydrological processes, the carbon cycle, and the energy balance. However, in cold regions, both climate and vegetation changes are also closely coupled to permafrost. The association between amplified warming and greening in Northern Hemisphere permafrost regions is not clearly understood. We therefore produce an extended 1982–2015 normalized difference vegetation index record based on concatenated Global Inventory Modeling and Mapping Studies and Moderate‐Resolution Imaging Spectroradiometer data to quantify the spatiotemporal patterns of vegetation variability. We also establish spatiotemporal permafrost warming patterns based on a thawing index, active layer thickness, soil temperature, the first thaw date, and thawing days. Next, we establish the association between vegetation and warming permafrost. We find that normalized difference vegetation index increases in approximately 70% of Northern Hemisphere permafrost regions during the growing season (April–October) and in 72% of the region during autumn. Warming permafrost shows a positive relationship with greening. A higher thawing index, greater active layer thickness, higher soil temperature, and also increased precipitation are linked with the observed greening. An earlier first thaw date and an increased number of thawing days also correlate with vegetation greening. These findings underscore the sensitivity of vegetation to warming permafrost. Continued permafrost warming will result in further greening of Northern Hemisphere cold regions (and vice versa), with important implications for the permafrost soil‐vegetation‐atmosphere carbon cycles, and the water, nutrient, and energy budgets.

Retrogressive thaw slumps (RTSs), formed by abrupt degradation of ice‐rich permafrost, are widely distributed on the Qinghai‐Tibet Plateau, causing infrastructure damage and enhancing soil carbon emissions. We compiled annual RTS inventories across the plateau from 2016 to 2022 using a deep‐learning‐aided method to quantify the spatial‐temporal variations. We found that RTS‐affected locations increased from 1,592 to 3,805 in 2016–2022, which increased affected areas by 2.8 times from 1,714 to 6,507 ha. The most active initiation and expansion periods were in 2016–2017 and 2018–2019. RTSs tend to be clustered, showing local heterogeneity among clusters characterized by various responses toward high temperatures and precipitation and tendencies to be on different topography and vegetation types. This research reveals the rapid development, wide distribution and regional heterogeneity of RTS activities, serving as a crucial step toward understanding how RTSs respond to climate change and regional environmental varieties.

Surface air temperatures affect a diverse set of physical and biological systems in many parts of the world. For regional‐scale studies, gridded surface air temperature data sets are frequently used as input variables. Here we evaluate 10 commonly used gridded air temperature products with spatial resolutions ranging from 0.1° × 0.1° to 5.0° × 5.0°, relative to observations from in situ weather stations on the Tibetan Plateau. Gridded temperatures are consistently lower, with mean annual air temperature biases ranging from −4.68 °C to −1.72 °C, and root mean square error (RMSE) from 3.24 °C to 6.11 °C. The mean biases of mean seasonal air temperatures for spring, summer, autumn, and winter are −3.21 °C, −2.98 °C, −2.89 °C, and −2.98 °C, respectively, and RMSEs of 4.81 °C, 4.39 °C, 4.3 °C, and 4.7 °C. Of all 10 products, the China meteorological forcing data set compares best with observations. Annual and season temperatures all increase significantly during 1980–2018 on the Tibetan Plateau, with winter dominating the warming rate.