Atmospheric conditions, topsoil properties and land cover conditions play essential roles in ground surface temperature (GST), surface air temperature (SAT) and their differences (GST-SAT). They determine the strength of the thermal forcing of the lower atmospheric boundary and the distributions of frozen ground in cold regions. However, the relative importance of these factors at various time scales and the underlying physical mechanisms remain less well understood. Here, we investigate the spatiotemporal patterns of GST-SAT and examine 11 potential factors in three categories in influencing the GST-SAT variations from 1983 to 2019 over the Tibetan Plateau (TP) using boosted regression tree models. The results show that the TP has experienced asynchronous warming in GST and SAT since 2001: a warming hiatus in SAT but continued warming in GST, resulting in a significantly increasing trend in GST-SAT. The relative importance of the three categories that influence the GSTSAT spatial variation was: atmospheric variables (56.1 %) > shallow soil properties (24.4 %) > interfacial land cover features (19.5 %). The importance of the factors also varied with the combinations of annual, seasonal, daily, day-time and night-time time scales, manifested by positive or negative effects. The interdecadal changes of net radiation, precipitation, wind speed and soil moisture amplified the asynchronous warming between air and shallow ground over the TP since the 2000s. These findings provide an in-depth understanding of the spatiotemporal variations of GST-SAT and the underlying mechanisms. This study will benefit the development of the Earth system models on the TP.

Surface air temperatures are significant indicators of environmental and climatic change that affect a diverse set of physical systems including permafrost. Most temperature products, such as gridded or reanalysis data, are still at a relatively low spatial resolution, limiting the ability to simulate heterogeneous permafrost changes and leading to large uncertainties. Here we apply a downscaling method based on elevation to obtain high-resolution surface air temperatures from the sixth Coupled Model Intercomparison Project in Northern Hemisphere permafrost regions. Root-mean-square errors and mean absolute errors after downscaling are reduced by 34 and 37%, respectively, relative to meteorological site data and gridded observations from the Climatic Research Unit. Compared to the downscaled surface air temperature data, non-downscaled model projections overestimate by 0.12-0.39 degrees C in the discontinuous, isolated, and sporadic permafrost regions and underestimate up to 0.18 degrees C in the continuous permafrost region under different emission scenarios. The warming rates in Northern Hemisphere permafrost regions were 0.093 degrees C/10 year during the historical (1850-2014) period and are projected to be 0.22 degrees C/10 year for SSP1-2.6, 0.48 degrees C/10 year for SSP2-4.5, 0.75 degrees C/10 year for SSP3-7.0, and 0.95 degrees C/10 year for SSP5-8.5 during 2015-2100, which is 1.4-1.6 times the warming of non-permafrost regions. Warming rates in high latitudes are 1.2-1.7 times higher than those in high-elevation regions. Continuous permafrost regions' warming will be 1.2-1.4 times higher than in other permafrost regions. For permafrost with high ground ice content, warming will be 1.1 times greater than in permafrost regions with medium or low ground ice content.

There are numerous studies on polar amplification and its influence on mid-latitude weather and climate. However, assessments on whether polar amplification occurs in Antarctica are rarely conducted. Based on the latest atmospheric reanalysis of ERA5 produced by European Centre for Medium-Range Weather Forecasts (ECMWF), we have defined the Antarctic amplification index, and calculated the trend of annual and seasonal Surface Air Temperature (SAT) mean during 1979-2019 for Antarctic Ice Sheet (AIS) and the trend mean of different meridional sectors of Antarctic sub regions including East Antarctic Ice Sheet (EAIS), West Antarctic Ice Sheet (WAIS) and Antarctic Peninsula (AP). Antarctic amplification shows regional differences and seasonal variations. Antarctica shows a slight warming with the largest magnitude in AP. The temperature anomalies indicate the least fluctuations in austral summer, and the more fluctuations in winter and spring. In austral summer, the warming trend domains EAIS and WAIS, while the cooling trend appears over AP. The zonal mean in Southern Hemisphere maintains a warming trend in the low latitudes, and fluctuates greatly in the middle and high latitudes. The strongest Antarctic amplification phenomenon occurs in spring, with the amplification index of 1.20. For AP, the amplification occurs in austral autumn, and the amplification index is 2.16. At South Pole and the surrounding regions, SAT for land only fluctuates largely and shows different trends in different seasons. The mechanism of Antarctic amplification is unclear till now, and its research suffers from the limitation of measured data. This suggests that future research needs progress in comprehensive ground observation network, remote sensing data accumulation, and high-resolution climate modeling with better representation of both atmospheric and cryospheric processes in Antarctica.

Surface temperature is critical for the simulation of climate change impacts on the ecology, environment, and particularly permafrost in the cryosphere. Virtually, surface temperatures are different in the near-surface air temperature (T-a) measured at a screen-height of 1.5-2 m, the land surface temperature (LST) on the top canopy layer, and the ground surface temperature (GST) 0-5 cm beneath the surface cover. However, not enough attention has been concentrated on the difference in these surface temperatures. This study aims at quantifying the distinction of surface temperatures by the comparisons and numerical simulations of observational field data collected in a discontinuous permafrost region on the northeastern Qinghai-Tibet Plateau (QTP). We compared the hourly, seasonal and yearly differences between T omega, IST, GST, and ground temperatures, as well as the freezing and thawing indices, the N-factors, and the surface and thermal offsets derived from these temperatures. The results showed that the peak hourly LST was reached earliest, closely followed by the hourly T-a. Mean annual LST (MALST) was moderately comparable to mean annual T-a (MAAT), and both were lower than mean annual GST (MAGST). Surface offsets (MAGST-MAAT) were all within 3.5 degrees C, which are somewhat consistent with other parts of the QTP but smaller than those in the Arctic and Subarctic regions with dense vegetation and thick, long-duration snow cover. Thermal offsets, the mean annual differences between the ground surface and the permafrost surface, were within -0.3 degrees C, and one site was even reversed, which may be relevant to equally thawed to frozen thermal conductivities of the soils. Even with identical T-a (comparable to MAAT of -3.27 and -3.17 degrees C), the freezing and thawing processes of the active layer were distinctly different, due to the complex influence of surface characteristics and soil, textures. Furthermore, we employed the Geophysical Institute Permafrost Lab (GIPL) model to numerically simulate the dynamics of ground temperature driven by T-a, LST, and GST, respectively. Simulated results demonstrated that GST was a reliable driving indicator for the thermal regime of frozen ground, even if no thermal effects of surface characteristics were taken into account. However, great biases of mean annual ground temperatures, being as large as 3 degrees C, were induced on the basis of simulations with LST and T-a when the thermal effect of surface characteristics was neglected. We conclude that quantitative calculation of the thermal effect of surface characteristics on GST is indispensable for the permafrost simulations based on the T-a datasets and the LST products-that derived from thermal infrared remote sensing.