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The comprehensive understanding of the occurred changes of permafrost, including the changes of mean annual ground temperature (MAGT) and active layer thickness (ALT), on the Qinghai‐Tibet Plateau (QTP) is critical to project permafrost changes due to climate change. Here, we use statistical and machine learning (ML) modeling approaches to simulate the present and future changes of MAGT and ALT in the permafrost regions of the QTP. The results show that the combination of statistical and ML method is reliable to simulate the MAGT and ALT, with the root‐mean‐square error of 0.53°C and 0.69 m for the MAGT and ALT, respectively. The results show that the present (2000–2015) permafrost area on the QTP is 1.04 × 106 km2 (0.80–1.28 × 106 km2), and the average MAGT and ALT are −1.35 ± 0.42°C and 2.3 ± 0.60 m, respectively. According to the classification system of permafrost stability, 37.3% of the QTP permafrost is suffering from the risk of disappearance. In the future (2061–2080), the near‐surface permafrost area will shrink significantly under different Representative Concentration Pathway scenarios (RCPs). It is predicted that the permafrost area will be reduced to 42% of the present area under RCP8.5. Overall, the future changes of MAGT and ALT are pronounced and region‐specific. As a result, the combined statistical method with ML requires less parameters and input variables for simulation permafrost thermal regimes and could present an efficient way to figure out the response of permafrost to climatic changes on the QTP. Key Points: The combined statistical method with machine learning is efficient to obtain the thermal regime of permafrost on the Qinghai‐Tibet Plateau (QTP)The present permafrost area on the QTP is ∼1.04 × 106 km2, and the average mean annual ground temperature and active layer thickness are −1.35 ± 0.42°C and 2.3 ± 0.60 m, respectivelyThe future changes of permafrost are projected to be pronounced due to climate change, but region‐specific [ABSTRACT FROM AUTHOR]

The spatial and temporal changes of the ground surface freezing indices (GFIs), ground surface thawing indices (GTIs), air freezing indices (AFIs), and air thawing indices (ATIs) in permafrost and seasonally frozen ground regions of the Qinghai-Tibet Plateau (QTP) were analyzed based on the daily ground surface and air temperatures from 69 meteorological stations using the Mann-Kendall test and Sen’s slope estimate. The spatial patterns of the freezing indices (FIs) and thawing indices (TIs) are nearly negatively correlated. On the annual scale, the GFI and GTI are greater than the AFI and ATI in both permafrost and seasonally frozen ground regions. The marked upward and downward trends have been observed for the time series of TI and FI, respectively, since 1998 on the QTP. Moreover, GFI and AFI decrease more significantly in permafrost regions than in seasonally frozen ground regions; the increasing rate of GTI and ATI in the seasonally frozen ground regions is greater than that in the permafrost regions. In permafrost regions, the downward trend of FI is greater than the upward trend of TI. However, the upward trend of TI shows a more drastic change than the FI in the seasonally frozen ground regions. The results indicate that the warming in the permafrost regions is more pronounced in winter than in the other seasons. The summer warming is more pronounced than the other seasons in the seasonally frozen ground regions. The decreasing rate of AFI and GFI increases as the altitude rises, while they decrease with increasing ATI. The average decreasing rate of GFI is greater than that of the AFI in different altitudinal zones. The greatest decrease of FI occurs in permafrost regions in the hinterland of the QTP, which indicates the dominant winter warming in this region. The downward trend of FI and upward trend of TI are responsible for the reported permafrost degradation on the QTP. [ABSTRACT FROM AUTHOR]

In this study, the ground surface temperature (GST) records from 16 meteorological stations, which are located in or adjacent to permafrost regions on the central Qinghai-Tibet Plateau (QTP), are analysed using Mann-Kendal test and Sen's slope estimate methods. We revealed that the GSTs have shown statistically significant warming. On average, mean annual ground surface temperature has increased at a rate of 0.60 °C decade−1 over the period of 1980-2007, which is more pronounced than the increase of mean annual air temperature on the plateau. The winter ground surface warming is especially prominent, which is similar to the seasonal trends in changes of air temperature. As important parameters to assess the changes of ground thermal regime in cold regions, surface freezing and thawing indices were also studied. The nonparametric statistic test and estimate indicate that surface freezing and thawing indices both show significant variations (−111.2 and 125.0 °C d decade−1, respectively) on the central QTP. The intensive ground surface warming is responsible for the concurrent increase in permafrost temperatures at the long-term observation sites on the plateau. The close correlations between ground surface and permafrost temperatures indicate that the dramatic ground surface warming could have significant influence on the change of permafrost thermal regime in the study region. Copyright © 2012 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

The change trends of air temperature, precipitation and evaporation from 1999 to 2008 shows that the climate in the Qinghai-Tibet Plateau permafrost region had become warmer. The analysis of the systematic active-layer data monitoring network along the Qinghai-Tibet Highway indicated that the active-layer thickness had been increasing and the soil temperature was rising. The soil temperature was rising in winter but not at the end of spring or during the entire summer. With thickening and warming of the active layer, the liquid water content of the active layer had an obvious downward migration and liquid water content in the top horizons decreased, but in the deeper horizons it increased. [ABSTRACT FROM AUTHOR]

Abstract Soil temperature is an important physical variable of soil and plays a key role in controlling the underground hydro-thermal processes in permafrost regions on the Qinghai-Tibetan Plateau (QTP). Daily soil temperatures were observed at five different vegetation cover sites (alpine wet meadow, alpine meadow, alpine steppe, alpine desert steppe and alpine desert) from 2012 to 2015 in permafrost regions on the QTP. The performance of three reanalysis soil temperature products (National Centers for Environmental Prediction Climate Forecast System and Climate Forecast System Reanalysis (CFSR), European Centre for Medium-Range Weather Forecasts interim reanalysis (ERA-Interim), and Global Land Data Assimilation System (GLDAS- NOAH)) at four depths (0–10, 10–40, 40–100 and 100–200 cm) was evaluated using the observation data. The results revealed that the CFSR soil temperature products had the best performance at most sites and that GLDAS-NOAH and Era-Interim had the poorest performance. However, the original CFSR soil temperature products underestimated the lowest temperatures. The calibration models for CFSR soil temperature products were established using the observed daily soil temperature from 2013 to 2015 and were validated with observed data from 2012. The results showed that the calibrated CFSv2 products were closer to the observations at different depths in the study sites. Moreover, we investigated the variations of seasonal and annual mean soil temperature from 1980 to 2015 at depths of 0–10, 10–40, 40–100 and 100–200 cm using the soil temperature calibration results. It was found that the soil temperatures at different depths all warmed fastest in spring, more slowly in winter and slowest in autumn at most sites. In addition, the average annual soil temperature exhibited significant warming trends in the permafrost regions on the QTP. The effect was largest with alpine desert steppe and smallest with alpine wet meadow, with statistically significant rates of 0.0599, 0.0468, 0.0438, 0.0282 and 0.0145 °C/year in alpine desert steppe, alpine desert, alpine steppe, alpine meadow and alpine wet meadow, respectively. This research provides a foundation for understanding the thermal properties of permafrost on the Qinghai-Tibetan Plateau under climate change. Highlights • Evaluate the performance of the reanalysis soil temperature products at different depths. • Establish calibration models for the reanalysis soil temperature products. • Examine the warming trend in the seasonal and annual mean soil temperatures. [ABSTRACT FROM AUTHOR]

Soil thermal diffusivity is a crucial physical parameter that affects soil temperature. By applying sinusoidal boundary conditions, an analytical solution using separated variables for the heat conduction-convection equation was developed. The thermal diffusivity and liquid water flux density were calculated with data collected at field observation sites in permafrost regions of Qinghai-Xizang (Tibet) Plateau (QXP). By taking the soil layer at the depth of 5 cm as the upper boundary, the soil temperature at a depth of 10 cm was modeled by the thermal conduction-convection method, amplitude method and phase method. The statistical analysis of the standard error of the estimate (SEE), the normalized standard error (NSEE) and the root mean square error (RMSE) demonstrated that the thermal conduction-convection method provided the most accurate prediction of soil temperature, with average SEE, NSEE, and RMSE of 0.72 °C, 9.26% and 0.72 °C, respectively. The thermal conduction-convection method provides a useful tool for calculating soil thermal parameters, simulating soil temperature and land surface processes parameterization for permafrost changes modelling under global warming. [ABSTRACT FROM AUTHOR]