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Variability of active layer thickness (ALT) in permafrost regions is critical for assessments of climate change, water resources, and engineering applications. Detailed knowledge of ALT variations is also important for studies on ecosystem, hydrological, and geomorphological processes in cold regions. The primary objective of this study is therefore to provide a comprehensive 1971–2000 climatology of ALT and its changes across the entire Northern Hemisphere from 1850 through 2100. To accomplish this, in situ observations, the Stefan solution based on a thawing index, and the edaphic factor (E factor) are employed to calculate ALT. The thawing index is derived from (i) the multimodel ensemble mean of 16 models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) over 1850–2005, (ii) three representative concentration pathways (RCP2.6, RCP4.5, and RCP8.5) for 2006–2100, and (iii) Climatic Research Unit (CRU) gridded observations for 1901–2014. The results show significant spatial variability in in situ ALT that generally ranges from 40 to 320 cm, with some extreme values of 900 cm in the Alps. The differences in the ALT climatology between the three RCPs and the historical experiments ranged from 0 to 200 cm. The biggest increases, of 120–200 cm, are on the Qinghai–Tibetan Plateau, while the smallest increases of less than 20 cm are in Alaska. Averaged over all permafrost regions, mean ALT from CMIP5 increased significantly at 0.57 ± 0.04 cm decade−1 during 1850–2005, while 2006–2100 projections show ALT increases of 0.77 ± 0.08 cm decade−1 for RCP2.6, 2.56 ± 0.07 cm decade−1 for RCP4.5, and 6.51 ± 0.07 cm decade−1 for RCP8.5.

Historical temperature variability over China during the twentieth century and projected changes under three emission scenarios for the twenty-first century are evaluated on the basis of a multimodel ensemble of 20 GCMs from phase 5 of the Coupled Model Intercomparison Project (CMIP5) and two observational datasets. Changes relative to phase 3 of the Coupled Model Intercomparison Project (CMIP3) are assessed, and the performance of individual GCMs is also quantified. Compared with observations, GCMs have substantial cold biases over the Tibetan Plateau, especially in the cold season. The timing and location of these biases also correspond to the greatest disagreement among the individual models, indicating GCMs’ limitations in reproducing climatic features in this complex terrain. The CMIP5 multimodel ensemble shows better agreement with observations than CMIP3 in terms of the temperature biases. Both CMIP3 and CMIP5 capture the climatic warming over the twentieth century. However, the magnitude of the annual mean temperature trends is underestimated. There is also limited agreement in the spatial and seasonal patterns of temperature trends over China. Based on six statistical measures, four individual models—the Max Planck Institute Earth System Model, low resolution (MPI-ESM-LR), Second Generation Canadian Earth System Model (CanESM2), Model for Interdisciplinary Research on Climate, Earth System Model (MIROC-ESM), and Community Climate System Model, version 4 (CCSM4)—best represent surface air temperature variability over China. The future temperature projections indicate that the representative concentration pathway (RCP) 8.5 and RCP 4.5 scenarios exhibit a gradual increase in annual temperature during the twenty-first century at a rate of 0.60° and 0.27°C (10 yr)−1, respectively. As the lowest-emission mitigation scenario, RCP 2.6 projects the lowest rate of temperature increase [0.10°C (10 yr)−1]. By the end of the twenty-first century, temperature is projected to increase by 1.7°–5.7°C, with larger warming over northern China and the Tibetan Plateau.

A new and distinctly interdecadal signal in the climate of the Pacific Ocean has been uncovered by examining the coupled behavior of sea surface temperatures (SSTs) and Northern Hemisphere atmospheric circulation. This interdecadal Pacific signal (IPS) of ocean–atmosphere interaction exhibits a highly statistically significant interdecadal component yet contains little to no interannual (El Niño scale) variability common to other Pacific climate anomaly patterns. The IPS thus represents the only empirically derived, distinctly interdecadal signal of Pacific Ocean SST variability that likely also represents the true interdecadal behavior of the Pacific Ocean–atmosphere system. The residual variability of the Pacific’s leading SST pattern, after removal of the IPS, is highly correlated with El Niño anomalies. This indicates that by simply including an atmospheric component, the leading mode of Pacific SST variability has been decomposed into its interdecadal and interannual patterns. Although the interdecadal signal is unrelated to interannual El Niño variability, the interdecadal ocean–atmosphere variability still seems closely linked to tropical Pacific SSTs. Because prior abrupt changes in Pacific SSTs have been related to anomalies in a variety of physical and biotic parameters throughout the Northern Hemisphere, and because of the persistence of these changes over several decades, isolation of this interdecadal signal in the Pacific Ocean–atmosphere system has potentially important and widespread implications to climate forecasting and climate impact assessment.