The high-resolution permafrost distribution maps have a closer relationship with engineering applications in cold regions because they are more relative to the real situation compared with the traditional permafrost zoning mapping. A particle swarm optimization algorithm was used to obtain the index eta with 30 m resolution and to characterize the distribution probability of permafrost at the field scale. The index consists of five environmental variables: slope position, slope, deviation from mean elevation, topographic diversity, and soil bulk density. The downscaling process of the surface frost number from a resolution of 1000 m to 30 m is achieved by using the spatial weight decomposition method and index eta. We established the regression statistical relationship between the surface frost number after downscaling and the temperature at the freezing layer that is below the permafrost active layer base. We simulated permafrost temperature distribution maps with 30 m resolution in the four periods of 2003-2007, 2008-2012, 2013-2017, and 2018-2021, and the permafrost area is, respectively, 28.35 x 10(4) km(2), 35.14 x 10(4) km(2), 28.96 x 10(4) km(2), and 25.21 x 10(4) km(2). The proportion of extremely stable permafrost (< -5.0 degrees C), stable permafrost (-3.0 similar to -5.0 degrees C), sub-stable permafrost (-1.5 similar to -3.0 degrees C), transitional permafrost (-0.5 similar to -1.5 degrees C), and unstable permafrost (0 similar to -0.5 degrees C) is 0.50-1.27%, 6.77-12.45%, 29.08-33.94%, 34.52-39.50%, and 19.87-26.79%, respectively, with sub-stable, transitional, and unstable permafrost mainly distributed. Direct and indirect verification shows that the permafrost temperature distribution maps after downscaling still have high reliability, with 83.2% of the residual controlled within the range of +/- 1 degrees C and the consistency ranges from 83.17% to 96.47%, with the identification of permafrost sections in the highway engineering geological investigation reports of six highway projects. The maps are of fundamental importance for engineering planning and design, ecosystem management, and evaluation of the permafrost change in the future in Northeast China.

Against the background of global warming, environmental and ecological problems caused by frozen ground degradation have become a focus of attention for the scientific community. As the temperature rises, the permafrost is degrading significantly in the frozen ground region of northeast China (FGRN China). At present, research on FGRN China is based mainly on data from meteorological stations, and the research period has been short. In this study, we analyzed spatial and temporal variation in the ground surface freezing index (GFI) and ground surface thawing index (GTI) from 1900 to 2017 for FGRN China, with the air freezing index (AFI) and air thawing index (ATI) using the University of Delaware (UDEL) monthly gridded air temperature dataset. The turning point year for annual mean air temperature (AMAT) was identified as 1985, and the turning point years for GFI and GTI were 1977 and 1996. The air temperature increased by 0.01 degrees C per year during 1900-2017, and the GFI and GTI increased at rates of -0.4 and 0.5 degrees C d per year before the turning point year; after the turning point, these rates were -0.7 and -2.1 degrees C d per year. We utilized a surface frost number model to study the distribution of frozen ground in FGRN China from 1900 to 2017. When the empirical coefficient E value is 0.57, the simulated frozen ground distribution is basically consistent with the existing frozen ground maps. The total area of permafrost in FGRN China decreased by 22.66x10(4) km(2) from 1900 to 2017, and the permafrost boundary moved northward with obvious degradation. The results of this study demonstrate the trend in permafrost boundary degradation in FGRN China, and provide basic data for research on the hydrological, climate, and ecological changes caused by permafrost degradation.

Dynamics of the frozen ground are key to understand the changes of eco-environment in cold regions, especially for areas with limited field observations. In this study, we analyzed the spatial and temporal variations of the ground surface freezing and thawing indices from 1900 to 2017 for the upper Brahmaputra River (also called the Yarlung Zangbo River in China) Basin (UBRB), southwestern Tibetan Plateau, with the air freezing and thawing indices using the University of Delaware (UDEL) monthly gridded air temperature dataset. The abrupt change years for air freezing index (AFI) and ground surface freezing index (GFI) were detected in 1999 and 2002, respectively, and for both air thawing index (ATI) and ground surface thawing index (GTI) were 2009. With the air temperature rising at a rate of 0.006 degrees C per year over 1900-2017, the AFI and GFI decreased at a rate of -0.1 degrees C d per year, while the ATI and GTI increased at rates of 0.3 and 0.5 degrees C d per year before the abrupt change year, respectively; all changing trends of freezing/thawing indices increased after the abrupt year, which was -2.9, -0.8, 7.3, and 21.7 degrees C d per year for the AFI, GFI, ATI, and GTI, respectively. We utilized the surface frost number model to obtain the dynamics of the frozen ground over the UBRB. When the empirical coefficient of E was assigned to 1.2, the simulated frozen ground occupied about 53.2% of the whole UBRB in the 1990s, which agreed well with the existing permafrost map published in 1996. The area of frozen ground accounts for 51.5%-54.5% of the UBRB during 1900-2017. This result may facilitate further studies of the multi-interactions among the frozen ground and relevant eco-environment, such as the air-ground surface energy exchange, hydrological cycles, and changes of the active layer thickness over the UBRB.