Simple analytical–statistical models (ASMs) for mean annual permafrost table temperature and active-layer thickness estimates

Abstract. A number of models have been developed for estimating the mean annual permafrost table temperature (MAPT) and active-layer thickness (ALT). These tools typically require at least a few ground physical properties as their input parameters in addition to air or ground temperatures. However, ground physical properties are frequently unavailable or unrepresentative and therefore need to be estimated, which introduces uncertainties into model outputs. Hence, we devised two simple analytical–statistical models (ASMs) for MAPT and ALT, which are driven solely by thawing and freezing indices from two depth levels within the active layer, while no ground physical properties are required. ASMs reproduced MAPT and ALT in the Earth's major permafrost regions with the total mean errors of less than 0.05 °C and 9 %, respectively. This is similar or better than other analytical or statistical models, which suggests that ASMs can be useful tools for estimating MAPT and ALT under a wide range of environmental conditions.