Frozen ground temperature trends associated with climate change in the Tibetan Plateau Three River Source Region from 1980 to 2014

Luo, Siqi; Fang, Xuewei; Lyu, Shihua; Ma, Di; Chang, Yong; Song, Minghong; Chen, Xuejiao

doi:10.3354/cr01371

Cited by 32 publications

(28 citation statements)

References 34 publications

(37 reference statements)

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“…Higher air temperatures resulted in higher increases in the predicted ALT at different depths. Research on the Three‐River Headwater Region of the Qinghai–Tibetan Plateau also revealed that the mean annual temperature of shallow soil layers (i.e., 0–20 cm) will increase by 2.86°C and that the mean annual temperature of deep soil layers (i.e., 40 cm and below) will increase by 2.5°C with an air temperature increase of 2.75°C . In our study region, similar results were obtained through predictions of the ANN model system.…”

Section: Discussionsupporting

confidence: 86%

Simulation of soil thermal dynamics using an artificial neural network model for a permafrost alpine meadow on the Qinghai–Tibetan plateau

Chang

Wang

Guo

2019

Permafrost & Periglacial

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The thermal regime of the active layer temperature (ALT) is a key variable with which to monitor permafrost changes and to improve the precision of simulations and predictions of land surface processes. The dynamics of the active layer thermal regime can differ substantially under various land surface types and climatic conditions. The proper simulation of these different processes is essential for accurately predicting the changes in water cycles and ecosystems under a warming climate scenario. In this paper, an artificial neural network (ANN) forecasting model system was developed using only two accessible parameters, air and ground surface temperatures, to predict and simulate the ALT thermal regime. The model results show that the ANN model has better real‐time prediction capability than other physics‐based models and performs well at simulating and forecasting variations in soil temperature with a step size of 12 days in permafrost regions on the Qinghai–Tibetan Plateau. The influence of an increase in air temperature on the ALT thermal regime was more intense during the thawing process than during the freezing process, and this influence decreased with an increase in soil depth.

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Section: Discussionsupporting

confidence: 86%

Simulation of soil thermal dynamics using an artificial neural network model for a permafrost alpine meadow on the Qinghai–Tibetan plateau

Chang

Wang

Guo

2019

Permafrost & Periglacial

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“…They are common methods that have been widely accepted for statistical diagnosis in modern climatic analysis studies (Luo et al 2016;Silva et al 2015;Yue et al 2002).…”

Section: Methodsmentioning

confidence: 99%

“…The observation of ST from 0 to 40 cm underground were conducted four times per day (02:00, 08:00, 14:00, and 20:00, Beijing Time) and averaged as the daily mean, while once per day (14:00, Beijing Time) from 80 to 320 cm (CMA 2003). The values of FD were observed once per day (08:00, Beijing Time) using frozen soil apparatus when the surface ST was below 0°C (CMA 2003;Luo et al 2016). All values were obtained from the monthly means of daily values from 1960 to 2014, with the exception of P. The monthly P, however, was obtained from the monthly accumulation of daily values.…”

Section: Datamentioning

confidence: 99%

“…Studies have shown that the frozen ground of TP is relatively warm and thin compared with high latitude frozen ground in both North America and Russia sections, and thus is more sensitive to climate change (Cheng 1999;Luo et al 2016). The freezing and thawing processes that occurred at the soil profile play an important role in determining the nature of land and atmosphere interactions (Guo et al 2011).…”

Section: Introductionmentioning

confidence: 99%

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Observed soil temperature trends associated with climate change in the Tibetan Plateau, 1960–2014

Fang

Luo

Lyu

2018

Theor Appl Climatol

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Soil temperature, an important indicator of climate change, has rarely explored due to scarce observations, especially in the Tibetan Plateau (TP) area. In this study, changes observed in five meteorological variables obtained from the TP between 1960 and 2014 were investigated using two non-parametric methods, the modified Mann-Kendall test and Sen's slope estimator method. Analysis of annual series from 1960 to 2014 has shown that surface (0 cm), shallow (5-20 cm), deep (40-320 cm) soil temperatures (ST), mean air temperature (AT), and precipitation (P) increased with rates of 0.47°C/decade, 0.36°C/decade, 0.36°C/decade, 0.35°C/decade, and 7.36 mm/decade, respectively, while maximum frozen soil depth (MFD) as well as snow cover depth (MSD) decreased with rates of 5.58 and 0.07 cm/decade. Trends were significant at 99 or 95% confidence level for the variables, with the exception of P and MSD. More impressive rate of the ST at each level than the AT indicates the clear response of soil to climate warming on a regional scale. Monthly changes observed in surface ST in the past decades were consistent with those of AT, indicating a central place of AT in the soil warming. In addition, with the exception of MFD, regional scale increasing trend of P as well as the decreasing MSD also shed light on the mechanisms driving soil trends. Significant negative-dominated correlation coefficients (α = 0.05) between ST and MSD indicate the decreasing MSD trends in TP were attributable to increasing ST, especially in surface layer. Owing to the frozen ground, the relationship between ST and P is complicated in the area. Higher P also induced higher ST, while the inhibition of freeze and thaw process on the ST in summer. With the increasing AT, P accompanied with the decreasing MFD, MSD should be the major factors induced the conspicuous soil warming of the TP in the past decades.

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“…It has been shown that the TP experienced a greater rate of warming than the Northern Hemisphere and the globe during 1984–2009 (Zhang et al, ). Such a rapid warming has caused significant permafrost degradation and environmental deterioration across the TP (Wang et al, ; Yao et al, ; Wu et al, ; Yao et al, ; Chen et al, ; Guo and Wang, ; Luo et al, ; Luo et al, ). For example, Wu and Zhang () showed that the permafrost thickness had decreased by tens of meters during the past 30 years, and the active layer was continually increasing.…”

Section: Introductionmentioning

confidence: 99%

Estimation of permafrost on the Tibetan Plateau under current and future climate conditions using the CMIP5 data

Chang

Lyu

Luo

et al. 2018

Intl Journal of Climatology

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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 × 104 km2. 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 × 104 km2 (9.7%) and 14.6 × 104 km2 (10.5%) under the RCP4.5 and RCP8.5 scenarios, respectively, in the next 20 years and by 36.7 × 104 km2 (26.6%) and 45.7 × 104 km2 (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.

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Frozen ground temperature trends associated with climate change in the Tibetan Plateau Three River Source Region from 1980 to 2014

Cited by 32 publications

References 34 publications

Simulation of soil thermal dynamics using an artificial neural network model for a permafrost alpine meadow on the Qinghai–Tibetan plateau

Simulation of soil thermal dynamics using an artificial neural network model for a permafrost alpine meadow on the Qinghai–Tibetan plateau

Observed soil temperature trends associated with climate change in the Tibetan Plateau, 1960–2014

Estimation of permafrost on the Tibetan Plateau under current and future climate conditions using the CMIP5 data

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