Search

Peatlands are major natural carbon pool in terrestrial ecosystems globally and are essential to a variety of fields, including global ecology, hydrology, and ecosystem services. Under the context of climate change, the management and conservation of peatlands has become a topic of international concern. Nevertheless, few studies have yet systematized the overall international dynamics of existing peatland research. In this study, based on an approach integrating bibliometrics and a literature review, we systematically analyzed peatland research from a literature perspective. Alongside traditional bibliometric analyses (e.g., number of publications, research impact, and hot areas), recent top keywords in peatland research were found, including 'oil palm', 'tropical peatland', 'permafrost', and so on. Furthermore, six hot topics of peatland research were identified: (1) peatland development and the impacts and degradations, (2) the history of peatland development and factors of formation, (3) chemical element contaminants in peatlands, (4) tropical peatlands, (5) peat adsorption and its humic acids, and (6) the influence of peatland conservation on the ecosystem. In addition, this review found that the adverse consequences of peatland degradation in the context of climate change merit greater attention, that peatland-mapping techniques suitable for all regions are lacking, that a unified global assessment of carbon stocks in peatlands urgently needs to be established, spanning all countries, and that a reliable system for assessing peatland-ecosystem services needs to be implemented expeditiously. In this study, we argued that enhanced integration in research will bridge knowledge gaps and facilitate the systematic synthesis of peatlands as complex systems, which is an imperative need. [ABSTRACT FROM AUTHOR]

The freezing index (FI) is one of the most important indicators that shows the variation of permafrost. However, the relationship between climate change and the thermal conditions of permafrost is not understood well. This study analyzed the variation of FI based on 5-cm soil temperature derived from 74 meteorological stations from 1977 to 2016 on the Qinghai-Tibet Plateau (QTP). Furthermore, the factors affecting the FI variation and its relationship with permafrost degradation were also discussed. The results showed that FI was much smaller in the interior than other areas of the QTP, and it increased at a rate of 53.0 °C d/10a during the 40 years. FI in the main body of the QTP was relatively stable than surrounding areas; it was more stable in the northern part than in the southern part. On average, the FI variation coefficient was larger than 10%, indicating the large fluctuation of FI during the 40 years. FI decreased with the increasing altitude; it was more sensitive to the altitude in the south of 33° N than in the north. The variation of FI was closely related to the maximum freezing depth (MFD) and the active layer thickness (ALT). It was observed that MFD decreased and ALT increased by approximately 1.4 cm and 1.6 cm, respectively, with each 10.0 °C d increase in FI. The results exhibited the thermal condition variation of the permafrost in QTP and revealed a degrading trend of the permafrost. [ABSTRACT FROM AUTHOR]

Climate changes significantly impact the hydrological cycle. Precipitation is one of the most important atmospheric inputs to the terrestrial hydrologic system, and its variability considerably influences environmental and socioeconomic development. Atmospheric warming intensifies the hydrological cycle, increasing both atmospheric water vapor concentration and global precipitation. The relationship between heavy precipitation and temperature has been extensively investigated in literature. However, the relationship in different percentile ranges has not been thoroughly analyzed. Moreover, a percentile-based regression provides a simple but effective framework for investigation into other factors (precipitation type) affecting this relationship. Herein, a comprehensive investigation is presented on the temperature dependence of daily precipitation in various percentile ranges over the Qinghai–Tibet Plateau. The results show that 1) most stations exhibit a peaklike scaling structure, while the northeast part and south margin of the plateau exhibit monotonic positive and negative scaling structures, respectively. The scaling structure is associated with the precipitation type, and 2) the positive and negative scaling rates exhibit similar spatial patterns, with stronger (weaker) sensitivity in the south (north) part of the plateau. The overall increase rate of daily precipitation with temperature is scaled by Clausius–Clapeyron relationship. 3) The higher percentile of daily precipitation shows a larger positive scaling rate than the lower percentile. 4) The peak-point temperature is closely related to the local temperature, and the regional peak-point temperature is roughly around 10°C. Significance Statement: This study aims to better understand the relationship between precipitation and surface air temperature in various percentile ranges over the Qinghai–Tibet Plateau. This is important because percentile-based regression not only accurately describes the response of precipitation to warming temperature but also provides a simple but effective framework for investigating other factors (precipitation type) that may be affecting this relationship. Furthermore, the sensitivity and peak-point temperature are evaluated and compared among different regions and percentile ranges; this study also attempts to outline their influencing factors. To our knowledge, this study is the first integration of percentile-based analysis of the dependence of daily precipitation on surface air temperature. [ABSTRACT FROM AUTHOR]

The Qinghai–Tibet Plateau is an area known to be sensitive to global climate change, and the problems caused by permafrost degradation in the context of climate warming potentially have far-reaching effects on regional hydrogeological processes, ecosystem functions, and engineering safety. Soil thermal conductivity (STC) is a key input parameter for temperature and surface energy simulations of the permafrost active layer. Therefore, understanding the spatial distribution patterns and variation characteristics of STC is important for accurate simulation and future predictions of permafrost on the Qinghai–Tibet Plateau. However, no systematic research has been conducted on this topic. In this study, based on a dataset of 2972 STC measurements, we simulated the spatial distribution patterns and spatiotemporal variation of STC in the shallow layer (5 cm) of the Qinghai–Tibet Plateau and the permafrost area using a machine learning model. The monthly analysis results showed that the STC was high from May to August and low from January to April and from September to December. In addition, the mean STC in the permafrost region of the Qinghai–Tibet Plateau was higher during the thawing period than during the freezing period, while the STC in the eastern and southeastern regions is generally higher than that in the western and northwestern regions. From 2005 to 2018, the difference between the STC in the permafrost region during the thawing and freezing periods gradually decreased, with a slight difference in the western hinterland region and a large difference in the eastern region. In areas with specific landforms such as basins and mountainous areas, the changes in the STC during the thawing and freezing periods were different or even opposite. The STC of alpine meadow was found to be most sensitive to the changes during the thawing and freezing periods within the permafrost zone, while the STC for bare land, alpine desert, and alpine swamp meadow decreased overall between 2005 and 2018. The results of this study provide important baseline data for the subsequent analysis and simulation of the permafrost on the Qinghai–Tibet Plateau. [ABSTRACT FROM AUTHOR]

Relict permafrost presents an ideal opportunity to understand the impacts of climatic warming on the ground thermal regime since it is characterized by mean annual ground temperature close to 0 °C and relatively thin permafrost. The long-term and continuous observations of permafrost thermal state and climate background are of great importance to reveal the links between the energy balance on hourly to annual timescales, to evaluate the variations of permafrost thermal state over multi-annual periods and to validate the remote sensing dataset. Until now there are few data available in relict permafrost regions although those data are important to understand the impacts of climate changes on permafrost especially in the boundary regions between permafrost and seasonally frozen ground regions. In this study, we present 11 years of meteorological and soil data in a relict permafrost site of the Mahan Mountain on the northeast of the Qinghai-Tibet Plateau. The meteorological data are comprised of air and ground surface temperature, relative humidity, wind speed and direction, shortwave and longwave downward and upward radiation, water vapor pressure, and precipitation on half-an-hour timescale. The active layer data include daily soil temperature and soil moisture at five different depths. The permafrost data consist of ground temperature at twenty different depths up to 28.4 m. The high-quality and long-term datasets are expected to serve as accurate forcing data in land surface models and evaluate remote-sensing products for a broader geoscientific community. The datasets are available from the National Tibetan Plateau/Third Pole Environment Data Center (https://doi.org/10.11888/Cryos.tpdc.271838, Wu and Xie, 2021). [ABSTRACT FROM AUTHOR]

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]

Soil hydrothermal regime of the active layer in the permafrost regions of the Qinghai‐Tibet Plateau (QTP) is important to the underlying permafrost and the climate change dynamics in Asia. However, a large bias still exists in current land surface models in the representation of soil temperature and moisture. This study assessed and augmented the Noah land surface model with multiparameterization options (Noah‐MP) for simulating soil hydrothermal dynamics at the Tanggula (alpine meadow) and Beiluhe (alpine swamp) stations located in the permafrost regions of the QTP. The results showed that the default Noah‐MP tended to underestimate soil temperature and moisture. Specifically, the default model overestimated the snow depth and duration due to the low snow sublimation rate. This resulted in a cold deviation in the soil temperature at two stations. Such underestimation was reduced by introducing a scheme that considered the sublimation loss from wind. Moreover, the remaining cold bias in the soil profiles of two stations was greatly resolved by a combined scheme of roughness length for heat (Z0h) and undercanopy aerodynamic resistance (ra,g). A soil thermal conductivity scheme, which can produce more realistic soil thermal conductivity in frozen soil, further improved the deep soil temperature simulation. The consideration of soil organic matter could mitigate the underestimation of the shallow soil moisture to some extent, but this improvement was more obvious at the Tanggula station, which had coarser mineral soil than the Beiluhe station. Key Points: Noah‐MP tends to underestimate soil temperature and moistureAdding snow sublimation from wind, combination of Z0h and ra,g, and realistic frozen soil thermal conductivity improves soil temperatureOrganic matter plays an important role in functioning coarse soil moisture [ABSTRACT FROM AUTHOR]

Air and soil temperatures are important factors that contribute to hydro-thermal processes and ecosystem dynamics in permafrost regions. However, there is little research regarding soil thermal dynamics during freeze-thaw processes in permafrost regions with thermal orbits on the Tibetan Plateau. Thermal orbits can provide simplified illustrations of the relationships between air and ground temperatures. This paper presents a new quantitative analysis for thermal orbits by combining the characteristics of ellipse and linear regression theories. A sensibility analysis of thermal orbits was conducted with different air and ground temperatures and vegetation types on the Tibetan Plateau. Results indicated that the thermal orbit regression slopes and intercepts had variations in characteristics between air and ground temperatures at different depths. More specifically, both air and ground temperatures showed homologous variation with increasing depth. This type of analysis is important for a better understanding of permafrost thermal properties as they relate to soil moisture, climate change, and vegetation effects in permafrost regions on the Tibetan Plateau. [ABSTRACT FROM AUTHOR]

• The Qinghai-Tibet Plateau has assimilated 43.16 Tg C/a from 1981 to 2016. • The carbon sink on the Qinghai-Tibet Plateau has weakened during 1981-2016. • The carbon sink on the Qinghai-Tibet Plateau is projected to weaken by 2080–2100. Cold regions contain a large amount of soil organic carbon, and the warming-accelerated loss of this carbon pool could cause important feedback to climatic change. The changes of carbon budgets in cold regions are poorly quantified especially for the Qinghai–Tibet Plateau (QTP) due to limited field observation data. By considering the soil freeze–thaw process and establishing new plant functional types with localized parameters, we used the Integrated Biosphere Simulator (IBIS) model to simulate the changes of carbon budget on the QTP during 1980–2016. The model was calibrated and validated using carbon flux data from eddy covariance observations at 16 sites. The results showed that the QTP has assimilated 43.16 Tg C/yr during 1980–2016, with permafrost and non-permafrost regions accounting for approximately 15% and 85% of the carbon sink, respectively. During the past four decades, the gross primary production and ecosystem respiration have increased by 1.74 and 2.04 Tg C/yr2, resulting in that the carbon sink on the QTP has weakened during 1980–2016. Moreover, the weakening of carbon sink is more pronounced in the non-permafrost regions. We project that the ecosystems will release 12.30 and 24.40 Tg C by 2080–2100 under the moderate and high shared socio-economic pathways (SSP 370 and SSP 585), respectively. This could largely offset the carbon sink and even shift the carbon sink to carbon source on the QTP. [ABSTRACT FROM AUTHOR]

[Display omitted] • Soil water contents on the Tibetan Plateau during 1986–2016 were analyzed. • Soil water in permafrost areas had smaller changes than non-permafrost areas. • Climate factors could not explain the different soil water content patterns. • Permafrost favors the stability of soil water regimes. Permafrost is an important factor affecting soil hydrology in cold regions, while the effects of permafrost on temporal changes in soil water content largely remain unknown. Here, based on the calibrated Climate Change Initiative (CCI) soil moisture products using field observation soil water data at 5 cm depth from 8 representative sites, we examined changing trends of climate conditions and soil water contents during 1986–2016 between the permafrost and permafrost-free sites on the Qinghai-Tibetan Plateau (QTP). We found that all the sites have been experienced continuous warming during this period. Soil water contents showed significant increasing or decreasing trends at three of the four permafrost-free sites, but there were no significant increasing or decreasing changes at all the four permafrost sites. In addition, the Mann-Kendall (M−K) test showed that there were 2 change-points in soil water content for the sites with the active layer thickness was about 2 m, while the sites with active layer thickness larger than 3 m and permafrost-free sites showed 3–5 change-points, indicating that the soil water contents in areas with shallower active layer showed smaller changes. The different changing trends and change-points between permafrost and permafrost-free sites were associated with the existence of permafrost and active layer thickness. Although soil water contents can be affected by many factors, our results suggested that permafrost existence can affect interannual changes in soil water contents, and permafrost degradation including increasing active layer thickness and disappearance of permafrost may decrease ecosystem resilience in the face of climate change. [ABSTRACT FROM AUTHOR]