Permafrost in High Mountain Asia (HMA) is becoming increasingly vulnerable to thaw due to climate change. However, the lack of either in situ ground surface or borehole temperature data beyond the Tibetan Plateau prevents comprehensive assessments of its impact on the regional hydrologic cycle and local cascading hazards. Although past studies have generated estimates of permafrost extent in Central Asia, many are limited to the Tibetan Plateau, excluding the more remote reaches of the Tien Shan, Pamirs, and Himalayas. By leveraging surface temperatures from both the Moderate Resolution Imaging Spectroradiometer (MODIS) and Atmospheric Infra-Red Sounder (AIRS), this study advances further understanding of remotely sensed permafrost occurrence at high altitudes, which are prone to error due to frequent cloud cover. We demonstrate that the fusion of MODIS and AIRS products can accurately estimate long-term thermal regimes of the subsurface, with reported correlation coefficients of 0.773 and 0.560, RMSEs of 0.890 degree celsius and 0.680 degree celsius, and biases of 0.003 degree celsius and 0.462 degree celsius, respectively, for the ground surface and the depth of zero annual amplitude, during a reference period of 2003-2016. Furthermore, we provide a range of possible permafrost extents based on established equations for calculating the temperature at the top of the permafrost to demonstrate temperature sensitivity to soil moisture and snow cover. The MODIS-AIRS product is recommended to be a robust source of ground temperature estimates, which may be sufficient for inferring mountain permafrost presence in HMA. Incorporating the influence of soil moisture and snow depth, although limited by biased estimates, also produces estimates of permafrost regional areas comparable to previously reported permafrost indices. A total permafrost area of 1.69 (+/- 0.32) million km(2) is estimated for the entire HMA, across 15 mountain subregions.

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.