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The active layer over permafrost plays a significant role in surface energy balance, hydrologic cycle, carbon fluxes, ecosystem, and landscape processes and on the human infrastructure in cold regions. Over a period from 1995 to 2007, a systematic soil temperature measurement network of 10 sites was established along the Qinghai‐Tibetan Highway. Soil temperatures up to 12 m depth were continuously measured semimonthly. In this study, we investigate spatial variations of active layer thickness (ALT) and its change over the period of record. We found that ALT can be estimated with confidence using semimonthly soil temperature profiles compared to those determined from available daily soil temperature profiles over the Qinghai‐Tibetan Plateau. The primary results demonstrate that long‐term and spatially averaged ALT is ∼2.41 m with a range of 1.32–4.57 m along the Qinghai‐Tibetan Highway. All monitoring sites show an increase in ALT over the period of their records. The mean increasing rate of ALT is ∼7.5 cm/yr. ALT shows a closely positive correlation with the thawing index of air temperature on the plateau. We estimated ALT using the thawing index over a period from 1956 to 2005 near the Wudaoliang Meteorological Station in the northern plateau. ALT had no or very limited change from 1956 to 1983 and a sharp increase of ∼39 cm from 1983 to 2005. The magnitude of ALT increase is greater in the warm permafrost region than in the cold permafrost region. The primary control of increase in ALT is caused by an increase in summer air temperature, whereas changes in the winter air temperature and snow cover condition play no or a very limited role.

An integrated perspective of permafrost dynamics is a key bridge between permafrost and global socioeconomic assessments. This study investigated the air temperature changes (1976–2020) among permafrost zones in the Northern Hemisphere and their potential impacts on permafrost. We found that continuous permafrost zones experienced faster warming than other regions. The freezing index declined 724°C‐day while the thawing index increased only 166°C‐day over continuous permafrost zones. This may explain why the temperature of cold permafrost increased rapidly but the active layer thickness changed only slightly. Assuming permafrost carbon emissions arise only from thaw processes may miss a significant source of the emissions. An often‐neglected factor is that cold‐season snow amplifies permafrost warming caused by summertime air temperature changes. Due to seasonal effects, using mean‐annual air temperature to depict permafrost evolution under integrated assessment frameworks may lead to significant errors. Plain Language Summary Permafrost dynamics remains a core aspect of what people are concerned about. Some researchers are making efforts to couple permafrost to socioeconomic processes. Challenges include mismatched spatiotemporal scales and developing mathematical descriptions that are not too complex. To address these challenges, we attempt to capture the fundamental features of permafrost dynamics from an integral perspective in this study. We found that permafrost temperature changes during 1976–2020 were largely controlled by rapid changes in the air temperature during the cold seasons. We also realized that similar warming magnitudes during cold season and warm season may play an equivalent role in permafrost temperature evolution because seasonal snow cover can amplify the warming that occurred during the previous summer. The asymmetrical responses of cold and warm permafrost are critical for assessing permafrost carbon cycles and feedbacks. This is particularly true for cold continuous permafrost because about half of permafrost carbon is stored in the upper 1 m of soils and the carbon density in continuous permafrost is generally higher than other permafrost zones. Key Points Rapid changes in cold permafrost during 1976–2020 may be explained by a strong air temperature increase during the cold season Unchanging snow cover is still able to enhance the effect of climate warming on permafrost The asymmetric seasonal responses in cold and warm permafrost are critical for assessing permafrost carbon cycles and feedbacks

Ground‐based measurements of active layer thickness provide useful data for validating/calibrating remote sensing and modeling results. However, these in situ measurements are usually site‐specific with limited spatial coverage. Here we apply interferometric synthetic aperture radar (InSAR) to measure surface deformation over permafrost on the North Slope of Alaska during the 1992–2000 thawing seasons. We find significantly systematic differences in surface deformation between floodplain areas and the tundra‐covered areas away from the rivers. Using floodplain areas as the reference for InSAR's relative deformation measurements, we find seasonally varying vertical displacements of 1–4 cm with subsidence occurring during the thawing season and a secular subsidence of 1–4 cm/decade. We hypothesize that the seasonal subsidence is caused by thaw settlement of the active layer and that the secular subsidence is probably due to thawing of ice‐rich permafrost near the permafrost table. These mechanisms could explain why in situ measurements on Alaskan North Slope reveal negligible trends in active layer thickness during the 1990s, despite the fact that atmospheric and permafrost temperatures in this region increased during that time. This study demonstrates that surface deformation measurements from InSAR are complementary to more traditional in situ measurements of active layer thickness, and can provide new insights into the dynamics of permafrost systems and changes in permafrost conditions.

Ferroelectric domain wall memories have been proposed as a promising candidate for nonvolatile memories, given their intriguing advantages including low energy consumption and high-density integration. Perovskite oxides possess superior ferroelectric prosperities but perovskite-based domain wall memory integrated on silicon has rarely been reported due to the technical challenges in the sample preparation. Here, we demonstrate a domain wall memory prototype utilizing freestanding BaTiO 3 membranes transferred onto silicon. While as-grown BaTiO 3 films on (001) SrTiO 3 substrate are purely c -axis polarized, we find they exhibit distinct in-plane multidomain structures after released from the substrate and integrated onto silicon due to the collective effects from depolarizing field and strain relaxation. Based on the strong in-plane ferroelectricity, conductive domain walls with reading currents up to nanoampere are observed and can be both created and erased artificially, highlighting the great potential of the integration of perovskite oxides with silicon for ferroelectric domain wall memories. Integrating ferroelectric perovskite oxides on Si is highly desired for electronic applications but challenging. Here, the authors show emergent in-plane ferroelectricity and promising nonvolatile memories based on resistive domain wall in BaTiO 3 /Si.

Thawing of ice-rich permafrost causes thermokarst landforms on the ground surface. Obtaining the distribution of thermokarst landforms is a prerequisite for understanding permafrost degradation and carbon exchange at local and regional scales. However, because of their diverse types and characteristics, it is challenging to map thermokarst landforms from remote sensing images. We conducted a case study towards automatically mapping a type of thermokarst landforms (i.e., thermo-erosion gullies) in a local area in the northeastern Tibetan Plateau from high-resolution images by the use of deep learning. In particular, we applied the DeepLab algorithm (based on Convolutional Neural Networks) to a 0.15-m-resolution Digital Orthophoto Map (created using aerial photographs taken by an Unmanned Aerial Vehicle). Here, we document the detailed processing flow with key steps including preparing training data, fine-tuning, inference, and post-processing. Validating against the field measurements and manual digitizing results, we obtained an F1 score of 0.74 (precision is 0.59 and recall is 1.0), showing that the proposed method can effectively map small and irregular thermokarst landforms. It is potentially viable to apply the designed method to mapping diverse thermokarst landforms in a larger area where high-resolution images and training data are available.

The measurement of temporal changes in active layer thickness (ALT) is crucial to monitoring permafrost degradation in the Arctic. We develop a retrieval algorithm to estimate long‐term average ALT using thaw‐season surface subsidence derived from spaceborne interferometric synthetic aperture radar (InSAR) measurements. Our algorithm uses a model of vertical distribution of water content within the active layer accounting for soil texture, organic matter, and moisture. We determine the 1992–2000 average ALT for an 80 × 100 km study area of continuous permafrost on the North Slope of Alaska near Prudhoe Bay. We obtain an ALT of 30–50 cm over moist tundra areas, and a larger ALT of 50–80 cm over wet tundra areas. Our estimated ALT values match in situ measurements at Circumpolar Active Layer Monitoring (CALM) sites within uncertainties. Our results demonstrate that InSAR can provide ALT estimates over large areas at high spatial resolution. Key Points Thawing of active layer causes surface subsidence Surface subsidence from InSAR can be used to estimate active layer thickness Our active layer thickness estimates closely match ground measurements

A comprehensive and hemispheric-scale snow cover and snow depth analysis is a prerequisite for all related processes and interactions investigation on regional and global surface energy and water balance, weather and climate, hydrological processes, and water resources. However, such studies were limited by the lack of data products and/or valid snow retrieval algorithms. The overall objective of this study is to investigate the variation characteristics of snow depth across the Northern Hemisphere from 1992 to 2016. We developed long-term Northern Hemisphere daily snow depth (NHSnow) datasets from passive microwave remote sensing data using the support vector regression (SVR) snow depth retrieval algorithm. NHSnow is evaluated, along with GlobSnow and ERA-Interim/Land, for its accuracy across the Northern Hemisphere against meteorological station snow depth measurements. The results show that NHSnow performs comparably well with a relatively high accuracy for snow depth with a bias of −0.6 cm, mean absolute error of 16 cm, and root mean square error of 20 cm when benchmarked against the station snow depth measurements. The analysis results show that annual average snow depth decreased by 0.06 cm per year from 1992 to 2016. In the three seasons (autumn, winter, and spring), the areas with a significant decreasing trend of seasonal maximum snow depth are larger than those with a significant increasing trend. Additionally, snow cover days decreased at the rate of 0.99 day per year during 1992–2016. This study presents that the variation trends of snow cover days are, in part, not consistent with the variation trends of the annual average snow depth, of which approximately 20% of the snow cover areas show the completely opposite variation trends for these two indexes over the study period. This study provides a new perspective in snow depth variation analysis, and shows that rapid changes in snow depth have been occurring since the beginning of the 21st century, accompanied by dramatic climate warming.

Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) products are widely used in ecology, hydrology, vegetation monitoring, and global circulation models. Compared to the collection-5 (C5) LST products, the newly released collection-6 (C6) LST products have been refined over bare soil pixels. This study aims to evaluate the C6 MODIS 1-km LST product using multi-year in situ data covering barren surfaces. Evaluation using all in situ data shows that the MODIS C6 LSTs are underestimated with a root-mean-square error (RMSE) of 2.59 K for the site in the Gobi area, 3.05 K for the site in the sand desert area, and 2.86 K for the site in the desert steppe area at daytime. For nighttime LSTs, the RMSEs are 2.01 K, 2.88 K, and 1.80 K for the three sites, respectively. Both biases and RMSEs also show strong seasonal signals. Compared to the error of C5 1-km LSTs, the RMSE of C6 1-km LST product is smaller, especially for daytime LSTs, with a value of 2.24 K compared to 3.51 K. The large errors in the sand desert region are presumably due to the lack of global representativeness of the magnitude of emissivity adjustment and misclassification for the barren surface causing error in emissivities. It indicates that the accuracy of the MODIS C6 LST product might be further improved through emissivity adjustment with globally representative magnitude and accurate land cover classification. From this study, the MODIS C6 1-km LST product is recommended for applications.

Permafrost collapse can rapidly change regional soil-thermal and hydrological conditions, potentially stimulating production of climate-warming gases. Here, we report on rate and extent of permafrost collapse on the extensive Tibetan Plateau, also known as the Asian Water Tower and the Third Pole. Combined data from in situ measurements, unmanned aerial vehicles (UAV), manned aerial photographs, and satellite images suggest that permafrost collapse was accelerating across the Eastern Tibetan Plateau. From 1969 to 2017, the area of collapsed permafrost has increased by approximately a factor of 40, with 70% of the collapsed area forming since 2004. These widespread perturbations to the Tibetan Plateau permafrost could trigger changes in local ecosystem state and amplify large-scale permafrost climate feedbacks.

Frozen ground has an important role in regional hydrological cycles and ecosystems, particularly on the Qinghai–Tibetan Plateau (QTP), which is characterized by high elevations and a dry climate. This study modified a distributed, physically based hydrological model and applied it to simulate long-term (1971–2013) changes in frozen ground its the effects on hydrology in the upper Heihe basin, northeastern QTP. The model was validated against data obtained from multiple ground-based observations. Based on model simulations, we analyzed spatio-temporal changes in frozen soils and their effects on hydrology. Our results show that the area with permafrost shrank by 8.8 % (approximately 500 km2), predominantly in areas with elevations between 3500 and 3900 m. The maximum depth of seasonally frozen ground decreased at a rate of approximately 0.032 m decade−1, and the active layer thickness over the permafrost increased by approximately 0.043 m decade−1. Runoff increased significantly during the cold season (November–March) due to an increase in liquid soil moisture caused by rising soil temperatures. Areas in which permafrost changed into seasonally frozen ground at high elevations showed especially large increases in runoff. Annual runoff increased due to increased precipitation, the base flow increased due to changes in frozen soils, and the actual evapotranspiration increased significantly due to increased precipitation and soil warming. The groundwater storage showed an increasing trend, indicating that a reduction in permafrost extent enhanced the groundwater recharge.