Accurate estimate of active layer thickness (ALT) is crucial for understanding permafrost and ecosystem responses to climate change. Interferometric Synthetic Aperture SAR (InSAR) technology can detect active layer freeze-thaw induced surface deformation with high accuracy, facilitating more accurate ALT estimation at the regional scale. Previous studies revealed a positive relationship between ALT and seasonal deformation in poorly drained Arctic soils. However, whether such relationship still holds in arid permafrost regions such as the Qinghai-Tibet Plateau (QTP) remains uncertain. Through synthesizing extensive field observations and remote sensing data, we find an overall negative correlation (r = -0.53, p < 0.01) between ALT and seasonal deformation in QTP, which tends to become more negative with sparser vegetation and drier soils, in contrast to the Arctic. After normalizing the climatic effect on ALT, we observe a decreasing sensitivity of seasonal deformation to active-layer changes with drier soils. Our study reveals a non-linear relationship between ALT and seasonal deformation across different permafrost regions, which helps to inform future development of InSAR-based permafrost applications.

Hoh Xil is an uninhabited extremity secluded on the Tibetan Plateau hinterland. A complete mapping of ground motion variation in Hoh Xil is essential for in-depth understanding of terrain’s responses to climate change on the Tibetan Plateau. However, the inaccessibility and extremely harsh environment impeded extensive field investigations on landform alteration and its formative process. Such difficulty can be resolved by Interferometric Synthetic Aperture Radar (InSAR), which enables a broad detection of subtle permafrost motions at millimeter precision. This study, for the first time, accomplished a Multi-temporal InSAR (MT-InSAR) deformation mapping from 2015 to 2020 in Hoh Xil, with a wide coverage of about 200,000 km ² . 1,592 Sentinel-1 images were processed based on the small baseline subset (SBAS) technique. The results show that Hoh Xil was experiencing dynamic permafrost disturbances. Thawing permafrost with both the linear subsidence rate higher than 2 mm/yr and the periodic amplitude over 2 mm was primarily detected in areas of flat or gentle slopes. The InSAR cumulative deformation is highly correlated with permafrost thawing depth. Significant lag times were identified between seasonal oscillation of InSAR deformation and land surface temperature (LST). Thermokarst landforms of retrogressive thaw slumps and thermokarst lakes broadly formed and dynamically evolved as a consequence of permafrost degradation. Particularly, widespread thawing permafrost characterized by the spatial clustering of thermokarst lakes appeared to occur in areas adjacent to large lakes. The discovered dynamic permafrost disturbances in Hoh Xil manifested even the secluded Tibetan Plateau hinterland was facing the threat of climate change.

We used full polarimetric L-band and P-band synthetic aperture radar (SAR) data collected from the recent NASA Arctic Boreal Vulnerability Experiment (ABoVE) airborne campaign and Sentinel-1 C-band dual-polarization data to understand the sensitivity of radar backscatter intensity and phase to fire-induced changes in the surface and subsurface soil processes in Arctic tundra underlain by permafrost. The 2007 Anaktuvuk River fire on the Alaska North Slope was used as a case study. At ~10-year post-fire, we observed strong increases (> ~3-4 dB) in the low frequency radar backscatter in severely burned areas during the thaw season, in contrast to limited (< ~0.5 dB) C-band backscatter differences (VV, VH) between burned and unburned areas. However, C-band winter backscatter is generally higher (>1 dB) in burned areas than adjacent unburned areas. Polarimetric decomposition analysis indicated a general trend towards more random surface scattering, and strong increases in double-bounce and volume scattering power at both P- and L-band in the burned areas. The ice-rich yedoma region shows largest backscatter increases in burned areas, and the highest correlation with burn severity and microtopography changes. The above backscatter changes are attributed to increasing surface roughness and microtopography due to ice wedge degradation and thermokarst development, and increasing subsurface scattering due to an overall drier and deeper active layer in burned areas. Among all frequencies, P-band shows consistently larger contrast in backscatter power and phase between burned and unburned areas, which makes it potentially more useful to study fire-permafrost interactions in the Arctic over decadal time scales.

Global climate zones are experiencing widespread shifts with ongoing rise in atmospheric CO₂, influencing vegetation growth and shifting its distributions to challenge ecosystem structure and function, posing threats on ecological and societal safety. However, how rising atmospheric CO₂ affects the pace of global climate zone shifts is highly uncertain. More attentions are urgently required to understand the underlying mechanisms and quantifications of regional climate vulnerability in response to rising CO₂. In this study, we employ nine Earth system models from CMIP6 to investigate global climate zone shifts with rising CO₂, unravel the effects of vegetation physiological response (PHY), and categorize climate vulnerable regions depending on the extent of climate zone shifts. We find that climate zone shifts over half of the global land area, 16.8% of which is contributed by PHY at 4 × CO₂. Intriguingly, besides warming, PHY-induced precipitation changes and their interactions with warming dominate about two-fifths of PHY-forced shifts, providing potential direction for model improvement in future predictions of climate zone shifts. Aided with PHY effects, 4 × CO₂ imposes substantial climate zone shifts over about one-fifth of the global land area, suggesting substantial changes in local climate and ecosystem structure and functions. Hence, those regions would experience strong climate vulnerability, and face high risk of climate extremes, water scarcity and food production. Our results quantitatively identify the vulnerable regions and unravel the underlying drivers, providing scientific insights to prioritize conservation and restoration efforts to ensure ecological and social safety globally.