评估当前和未来多年冻土空间分布和动态变化对全球碳循环模拟、气候变化预测以及工程风险评估至关重要。本文使用经广泛验证和应用的半经验模型Kudryavtsev方法，综合考虑温度、积雪、植被、土壤等因素对冻土的影响，以国际耦合模式比较计划第六阶段（CMIP6）模式模拟结果和SoilGrids2.0数据集等作为输入，计算了2015-2100年北半球冻土顶板温度与活动层厚度在SSP126、SSP245、SSP370和SSP585四种不同情景下的逐年时间序列数据，并根据顶板温度计算了北半球冻土面积。该数据集填补了未来不同情境下冻土分布预测数据的空缺，为冻土退化、气候变化、北极生态等相关研究提供了数据参考。数据集包括2015-2100年逐年以下实验数据：（1）冻土顶板温度数据；（2）活动层厚度数据；（3）冻土面积数据。数据集存储为.tif和.xls格式，空间分辨率为0.625°×0.4712°，由690个数据文件组成，数据量为35.6 MB。

Permafrost has significant impacts on climate change through its strong interaction with the climate system. In order to better understand the permafrost variation and the role it plays in climate change, model outputs from Phase 5 of the Coupled Model Intercomparison Project (CMIP5) are used in the present study to diagnose the near-surface permafrost on the Tibetan Plateau (TP), assess the abilities of the models to simulate present-day (1986-2005) permafrost and project future permafrost change on the TP under four different representative concentration pathways (RCPs). The results indicate that estimations of present-day permafrost using the surface frost index (SFI) and the Kudryavtsev method (KUD) show a spatial distribution similar to that of the frozen soil map on the TP. However, the permafrost area calculated via the KUD is larger than that calculated via the SFI. The SFI produces a present-day permafrost area of 127.2 x 10(4) km(2). The results also indicate that the permafrost on the TP will undergo regional degradation, mainly at the eastern, southern and northeastern edges, during the 21st century. Furthermore, most of the sustainable permafrost will probably exist only in the northwestern TP by 2099. The SFI also indicates that the permafrost area will shrink by 13.3 x 10(4) km(2) (9.7%) and 14.6 x 10(4) km(2) (10.5%) under the RCP4.5 and RCP8.5 scenarios, respectively, in the next 20 years and by 36.7 x 10(4) km(2) (26.6%) and 45.7 x 10(4) km(2) (32.7%), respectively, in the next 50 years. The results are helpful for us to better understand the permafrost response to climate change over the TP, further investigate the physical mechanism of the freeze-thaw process and improve the model parameterization scheme.

Wilhelm et al. (2015) employed the widely used Stefan and Kudryavtsev equations to predict the maximum active-layer thickness (ALT) on Amsler Island, Western Antarctic Peninsula. Their predictions far exceed the observations of ALT reported from other parts of the region. Here, I demonstrate that the values of ALT are significantly overestimated by the predictive equations because the authors incorrectly assumed that little or no latent heat of phase change is absorbed during thawing. Although the area is the warmest in the Antarctic Peninsula region, with a rapid increase in air temperature and permafrost temperatures close to 0 degrees C, the active layer is likely to be substantially thinner than values predicted by Wilhelm et al. (2015). Copyright (c) 2016 John Wiley & Sons, Ltd.