A scenario-based approach was used to test air and ground response to warming with and without changes to inverted surface lapse rates in four Yukon valleys. Generally, climate warming coupled with weakening of temperature inversions resulted in the greatest increase in air temperature at low elevations. However, ground temperatures at high elevations showed the greatest response to warming and variability between scenarios due to increased connectivity between air and ground. Low elevations showed less of a response to warming and permafrost was largely preserved in these locations. Local models also predicted higher permafrost occurrence compared to a regional permafrost probability model, due to the inclusion of differential surface and thermal offsets. Results show that the spatial warming patterns in these mountains may not follow those predicted in other mountain environments following elevation-dependent warming (EDW). As a result, the concept of EDW should be expanded to become more inclusive of a wider range of possible spatial warming distributions. The purpose of this paper is not to provide exact estimations of warming, but rather to provide hypothetical spatial warming patterns, based on logical predictions of changes to temperature inversion strength, which may not directly follow the distribution projected through EDW.

Current permafrost models in Canadian boreal forests are generally of low spatial resolution as they cover regional or continental scales. This study aims to understand the viability of creating a temperature at the top of permafrost (TTOP) model on a local scale in the boreal wetland environment of What & igrave;, Northwest Territories from short-term field-collected temperature data. The model utilizes independent variables of vegetation, topographic position index, and elevation, with the dependent variables being ground surface temperature collected from 60 ground temperature nodes and 1.5 m air temperature collected from 10 temperature stations. In doing this, the study investigates the relationship vegetation and disturbance have on ground temperature and permafrost distribution. The model predicts that 31% of the ground is underlain by permafrost, based on a mean annual temperature at TTOP of <0 degrees C. This model shows an accuracy of 62.5% when compared to cryotic assessment sites (CAS). Most inaccuracies, showing the limitations of the TTOP model, came from peat plateaus that had been burned in the most recent forest fire in 2014. These resulted in out-of-equilibrium permafrost and climatic conditions that TTOP cannot handle well. Commonly, permafrost mapping places What & igrave; in the extensive discontinuous zone, estimating that between 50% and 90% of the ground is underlain by permafrost. The study shows that a climatically driven TTOP model calibrated with CAS can be used to illustrate ground temperature heterogeneity from short-term data in boreal forest wetland environments. However, this approach likely underestimates permafrost extent and is perhaps not the best-suited modelling choice for nearsurface permafrost, which is currently out of equilibrium with the current climate.

Climate change and its impacts on sensitive polar ecosystems are relatively little studied in Antarctic regions. Permafrost and active layer changes over time in periglacial regions of the world are important indicators of climate variability. These changes (e. g. permafrost degradation, increasing of the active layer thickness) can have a significant impact on Antarctic terrestrial ecosystems. The study site (AWS-JGM) is located on the Ulu Peninsula in the north of James Ross Island. Ground temperatures at depths of 5, 50, and 75 cm have been measured at the site since 2011, while air temperature began to be measured in 2004. The main objective is to evaluate the year-to-year variability of the reconstructed temperature of the top of the permafrost table and the active layer thickness (ALT) since 2004 based on air temperature data using TTOP and Stefan models, respectively. The models were verified against direct observations from a reference period 2011/12-2020/21 showing a strong correlation of 0.95 (RMSE = 0.52) and 0.84 (RMSE = 3.54) for TTOP and Stefan models, respectively. The reconstructed average temperature of the permafrost table for the period 2004/05-2020/21 was -5.8 degrees C with a trend of -0.1 degrees C/decade, while the average air temperature reached -6.6 degrees C with a trend of 0.6 degrees C/decade. Air temperatures did not have an increasing trend throughout the period, but in the first part of the period (2004/05-2010/11) showed a decreasing tendency (-1.3 degrees C/decade). In the period 2011/ 12-2020/21, it was a warming of 1.9 degrees C/decade. The average modelled ALT for the period 2004/05-2020/21 reached a value of 60cm with a trend of -1.6 cm/decade. Both models were found to provide reliable results, and thus they significantly expand the information about the permafrost and ALT, which is necessary for a better understanding of their spatiotemporal variability and the impact of climate change on the cryosphere.

Permafrost and its spatiotemporal variation considerably influence the surface and sub-surface hydrological processes, biogeochemical cycles, fauna and flora growth and cold region engineering projects in the Three-River Source Region (TRSR), Qinghai-Tibet Plateau. However, the dynamics of permafrost over a relatively long term duration (e.g. >100 years) in the TRSR is not well quantified. Thus, the spatial and temporal variations of the temperature at the top of the perennially frozen/unfrozen ground (TTOP), active layer thickness (ALT) in permafrost regions and the maximum depth of frost penetration (MDFP) in the seasonally frozen ground of the TRSR during 1901-2020 were simulated using the TTOP model and Stefan equation driven by the widely used reanalysis Climatic Research Unit 4.05 dataset. Results revealed that the permafrost in the TRSR over the past 120 years did not degrade monotonically but experienced considerable fluctuations in area with the decadal oscillations of climate warming and cooling: shrinking from 263.9 x 103 km2 in the 1900s to 233.3 x 103 km2 in the 1930s, expanding from 232.3 x 103 km2 in the 1940s to 260.9 x 103 km2 in the 1970s and shrinking again from 254.1 x 103 km2 in the 1980s to 228.9 x 103 km2 in the 2010s. The regional average TTOP increased from -1.34 & PLUSMN; 2.74 & DEG;C in the 1910s to -0.48 & PLUSMN; 2.69 & DEG;C in the 2010s, demonstrating the most noticeable change for the extremely stable permafrost (TTOP 3.0 m by 12% from 1901 to 2020. Notably, minor changes were observed for the regional average MDFP, probably due to the increase in the area proportion of MDFP 3.5 m (owing to the transformation of permafrost to seasonally frozen ground) by 7.39% and 4.77%, respectively. These findings can facilitate an in-depth understanding of permafrost dynamics and thus provide a scientific reference for eco-environment protection and sustainable development under climate change in the TRSR

The monitoring of permafrost is important for assessing the effects of global environmental changes and maintaining and managing social infrastructure, and remote sensing is increasingly being used for this wide-area monitoring. However, the accuracy of the conventional method in terms of temperature factor and soil factor needs to be improved. To address these two issues, in this study, we propose a new model to evaluate permafrost with a higher accuracy than the conventional methods. In this model, the land surface temperature (LST) is used as the upper temperature of the active layer of permafrost, and the temperature at the top of permafrost (TTOP) is used as the lower temperature. The TTOP value is then calculated by a modified equation using precipitation-evapotranspiration (PE) factors to account for the effect of soil moisture. This model, referred to as the TTOP-LST zero-curtain (TLZ) model, allows us to analyze subsurface temperatures for each layer of the active layer, and to evaluate the presence or absence of the zero-curtain effect through a time series analysis of stratified subsurface temperatures. The model was applied to the Qinghai-Tibetan Plateau and permafrost was classified into seven classes based on aspects such as stability and seasonality. As a result, it was possible to map the recent deterioration of permafrost in this region, which is thought to be caused by global warming. A comparison with the mean annual ground temperature (MAGT) model using local subsurface temperature data showed that the average root mean square error (RMSE) value of subsurface temperatures at different depths was 0.19 degrees C, indicating the validity of the TLZ model. A similar analysis based on the TLZ model is expected to enable detailed permafrost analysis in other areas.

Permafrost is a key element of the cryosphere and sensitive to climate change. High-resolution permafrost map is important to environmental assessment, climate modeling, and engineering application. In this study, to estimate high-resolution Xing'an permafrost map (up to 1 km(2)), we employed the surface frost number (SFN) model and ground temperature at the top of permafrost (TTOP) model for the 2001-2018 period, driven by remote sensing data sets (land surface temperature and land cover). Based on the comparison of the modeling results, it was found that there was no significant difference between the two models. The performances of the SFN model and TTOP model were evaluated by using a published permafrost map. Based on statistical analysis, both the SFN model and TTOP model efficiently estimated the permafrost distribution in Northeast China. The extent of Xing'an permafrost distribution simulated by the SFN model and TTOP model were 6.88 x 10(5) km(2) and 6.81 x 10(5) km(2), respectively. Ground-surface characteristics were introduced into the permafrost models to improve the performance of models. The results provided a basic reference for permafrost distribution research at the regional scale.

冻土的冻融变化对寒区道路路基和路面等的修建具有重要影响。由于寒区地面观测数据较少,因此需发展基于遥感的高分辨率冻土分布估算模型。中国新一代高分五号卫星（GF-5）搭载的全谱段成像光谱仪有4个40m空间分辨率的热红外波段,为高空间分辨率的地表温度反演提供了可能。以青藏公路典型路段作为研究区,采用劈窗算法,利用GF-5热红外数据反演地表温度,并将结果与同期的MODIS地表温度产品和站点实测数据进行了比较。结果表明,该方法反演出的地表温度与实测结果的平均误差为-2.34℃,相关系数为0.86,表明结果具有较好的精度。以遥感地表温度作为输入,基于TTOP模型计算出了研究区的冻土分布图,得出研究区现状多年冻土面积为0.963×10～4 km2、季节性冻土面积为2.543×10～4 km2,与已有研究给出的研究区冻土分布图结果较为接近,表明建立的冻土分布反演模型具有可靠性和进一步应用的潜力。此外,还基于Stefan公式计算了研究区2018年～2019年的季节性冻土最大冻结深度和多年冻土活动层厚度,结果表明研究区内多年冻土活动层厚度在11cm～260cm之...

Ground surface and permafrost temperatures in the High Arctic are often considered homogeneous especially when viewed at the scale of climate and environmental models. However, this is generally incorrect due to highly variable, topographically redistributed snow cover, which generates a substantial degree of ground thermal heterogeneity. The objective of this study is to describe and spatially model the variability in the ground thermal regime within the Cape Bounty Arctic Watershed Observatory (CBAWO), Nunavut, Canada, using the TTOP model, for current conditions in addition to a series of future climate change scenarios. While observed air temperature was mostly uniform, annual mean ground surface and permafrost temperatures across the paired watersheds were estimated to range between -3.8 to -13.8 degrees C and -3.9 to -14 degrees C, respectively, similar to the -5 to -15 degrees C magnitude and range identified from boreholes across the High Arctic. The spatial models showed higher ground surface temperatures in topographic hollows (slope bases and stream channels), and lower temperatures in areas of topographic prominence (hilltops and plateaus) following the spatial pattern of snow accumulation and redistribution. Under projected climate change, the models predicted areas with the coldest permafrost to have the largest magnitude of warming (about 9 degrees C), while areas of warm permafrost became closer to 0 degrees C (warming 4-7 degrees C). This thermal heterogeneity may have implications for ground instability such as permafrost-related mass movements, hydrological connectivity, biogeochemical cycling, and microbial activity, which influence water quality and contaminant mobility.

The permafrost in the Qilian Mountains (QLMs), the northeastern margin of the Qinghai-Tibet Plateau, changed dramatically in the context of climate warming and increasing anthropogenic activities, which poses significant influences on the stability of the ecosystem, water resources, and greenhouse gas cycles. Yet, the characteristics of the frozen ground in the QLMs are largely unclear regarding the spatial distribution of active layer thickness (ALT), the maximum frozen soil depth (MFSD), and the temperature at the top of the permafrost or the bottom of the MFSD (TTOP). In this study, we simulated the dynamics of the ALT, TTOP, and MFSD in the QLMs in 2004-2019 in the Google Earth Engine (GEE) platform. The widely-adopted Stefan Equation and TTOP model were modified to integrate with the moderate-resolution imaging spectroradiometer (MODIS) land surface temperature (LST) in GEE. The N-factors, the ratio of near-surface air to ground surface freezing and thawing indices, were assigned to the freezing and thawing indices derived with MODIS LST in considerations of the fractional vegetation cover derived from MODIS normalized difference vegetation index (NDVI). The results showed that the GEE platform and remote sensing imagery stored in Google cloud could be quickly and effectively applied to obtain the spatial and temporal variation of permafrost distribution. The area with TTOP < 0 degrees C is 8.4 x 10(4) km(2) (excluding glaciers and lakes) and accounts for 46.6% of the whole QLMs, the regional mean ALT is 2.43 +/- 0.44 m, while the regional mean MFSD is 2.54 +/- 0.45 m. The TTOP and ALT increase with the decrease of elevation from the sources of the sub-watersheds to middle and lower reaches. There is a strong correlation between TTOP and elevation (slope = -1.76 degrees C km(-1), p < 0.001). During 2004-2019, the area of permafrost decreased by 20% at an average rate of 0.074 x 10(4) km(2)center dot yr(-1). The regional mean MFSD decreased by 0.1 m at a rate of 0.63 cm center dot yr(-1), while the regional mean ALT showed an exception of a decreasing trend from 2.61 +/- 0.45 m during 2004-2005 to 2.49 +/- 0.4 m during 2011-2015. Permafrost loss in the QLMs in 2004-2019 was accelerated in comparison with that in the past several decades. Compared with published permafrost maps, this study shows better calculation results of frozen ground in the QLMs.

青藏高原作为世界上中低纬度海拔最高、面积最大的多年冻土区域,其冻土环境变化会对中国东部乃至东亚气候的形成、变化和发展造成重大影响。RS技术对于冻土环境动态监测具有特别优势。针对青藏高原冻土的特点,提出一种基于多源RS监测数据的融合技术反演地表温度,实现不同空间尺度条件下冻土分类的自动提取方法。该技术方法先利用MODIS全年温度产品数据集,结合地表覆盖类型数据,使用TTOP模型反演得到1 km空间分辨率的冻土分布;然后对Landsat数据源采取PSC反演算法获得30 m空间分辨率的地表温度数据;最后利用多项式拟合技术,将Landsat反演地表温度与MODIS温度数据相互融合,以提高Landsat反演地表温度的准确度,并据此数据利用TTOP模型提取30 m空间分辨率的冻土分布,实现了小尺度精细化的冻土分类与制图。结果验证分析表明:本文的技术方法具有较好的可信度。