Search

The land surface temperature obtained from remote sensing was widely used in the simulation of permafrost mapping instead of air temperature with the rapid development of remote sensing technology. The land surface freezing and thawing index (LFI and LTI), which is commonly regarded as the ground surface freezing and thawing index (GFI and GTI), can produce certain errors in the simulation of permafrost distribution on the Qinghai–Tibet Plateau. This paper improved the accuracy of the thermal condition of the surface soil in the Qinghai–Tibet Engineering Corridor (QTEC) by calculating the LFI (or LTI) and N-factors. The environmental factors affecting the spatial distribution of the GFI and GTI were detected by the GeoDetector model. Finally, the multiple linear relationships between the GFI (or GTI) and the environmental factors were established. The results from 25 monitoring sites in the QTEC show that the Nf (ratio of GFI to LFI) is 1.088, and the Nt (ratio of GTI to LTI) is 0.554. The explanatory power of the interaction between elevation and latitude for the GFI and GTI is 79.3% and 85.6%, respectively. The multiple linear regression model with six explanatory variables established by GFI (or GTI) has good accuracy. This study can provide relatively accurate upper boundary conditions for the simulation of permafrost distribution in the QTEC region. [ABSTRACT FROM AUTHOR]

Soil moisture and soil temperature (SMST) are important state variables for quantifying the exchange of heat and water between land and atmosphere. Yet, long-term, regional-scale in situ SMST measurements are scarce on the Tibetan Plateau (TP), with even fewer are available for multiple soil depths. Tibet-Obs is such a long-term, regional-scale SMST observatory in the TP that has been established 10 years ago and includes three SMST monitoring networks, i.e. Maqu, Naqu, and Ngari (including Ali and Shiquanhe), located in the cold humid area covered by grassland, the cold semiarid area dominated by tundra, and the cold arid area dominated by desert, respectively. This paper presents a long-term (∼ 10 years) SMST profile dataset collected from the Tibet-Obs, which includes the original in situ measurements at a 15 min interval collected between 2008 and 2019 from all the three networks and the spatially upscaled data (SM ups and ST ups) for the Maqu and Shiquanhe networks. The quality of the upscaled data is proved to be good, with errors that are generally better than the measured accuracy of adopted SMST sensors. Long-term analysis of the upscaled SMST profile data shows that the amplitudes of SMST variations decrease with increasing soil depth, and the deeper soil layers present a later onset of freezing and an earlier start of thawing and, thus, a shorter freeze–thaw duration in both the Maqu and Shiquanhe networks. In addition, there are notable differences between the relationships of SM ups and ST ups under freezing conditions for the Maqu and Shiquanhe networks. No significant trend can be found for the SM ups profile in the warm season (from May to October) for both networks that is consistent with the tendency of precipitation. A similar finding is also found for the ST ups profile and air temperature in the Shiquanhe network during the warm season. For the cold season (from November to April), a drying trend is noted for the SM ups above 20 cm in the Maqu network, while no significant trend is found for those in the Shiquanhe network. Comparisons between the long-term upscaled data and five reanalysis datasets, including the ECMWF reanalysis v5 (ERA5), Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2), Global Land Data Assimilation System version 2 Catchment Land Surface Model (GLDAS-2.1 CLSM), GLDAS-2.1 Noah, and GLDAS-2.1 variable infiltration capacity (GLDAS-2.1 VIC), indicate that none of the current model-based products can reproduce the seasonal variations and interannual trend changes in the measured SMST profile dynamics in both networks. All the products underestimate the ST ups at every depth, leading to an earlier onset of freezing and a later onset of thawing, which essentially demonstrates that the current models are not able to adequately simulate winter conditions on the TP. In short, the presented dataset would be valuable for evaluation and improvement in long-term satellite- and model-based SMST products on the TP, enhancing the understanding of TP hydrometeorological processes and their response to climate change. The dataset is available in the 4TU.ResearchData repository at https://doi.org/10.4121/20141567.v1 (Zhang et al., 2022). [ABSTRACT FROM AUTHOR]

Soil moisture and soil temperature (SMST) are important state variables for quantifying exchange of heat and water between land and atmosphere. Yet, long-term regional-scale in-situ SMST measurements are scarce on the Tibetan Plateau (TP), even fewer are available for multiple soil depths. "Tibet-Obs" is such a long-term regional-scale SMST observatory in the TP established 10 years ago that includes three SMST monitoring networks, i.e., Maqu, Naqu, and Ngari (including Ali and Shiquanhe), located in the cold humid area covered by short grasses, the cold semiarid area dominated by tundra, and the cold arid area dominated by desert, respectively. This paper presents a long-term (~10 years) SMST profile dataset collected from the Tibet-Obs, which includes the original in-situ measurements at a 15-min interval collected between 2008 and 2019 from all the three networks and the spatially upscaled data (SMups and STups) for the Maqu and Shiquanhe networks. The quality of the upscaled data is proved to be good with errors that are generally better than the measured accuracy of adopted SMST sensors. Long term analysis of the upscaled SMST profile data shows that the amplitudes of SMST variations decrease with increasing soil depth, and the deeper soil layers present later onset of freezing and earlier start of thawing and thus shorter freeze-thaw duration in both Maqu and Shiquanhe networks. In addition, there are notably differences noted between the relationships of SMups and STups under freezing conditions for the Maqu and Shiquanhe networks. No significant trend can be found for the SMups profile in the warm season (from May to October) for both networks that is consistent with the tendency of precipitation. Similar finding is also found for the STups profile and air temperature in the Shiquanhe network during the warm season. For the cold season (from November to April), a drying trend is noted for the SMups above 20 cm in the Maqu network, while no significant trend is found for those in the Shiquanhe network. Comparisons between the long-term upscaled data and five reanalysis datasets indicate that none of current model-based products can reproduce the seasonal variations and inter-annual trend changes of measured SMST profile dynamics in both networks. All the products underestimate the STups at every depth, leading to earlier onset of freezing and later onset of thawing, which essentially demonstrates the current model are not able to adequately simulate winter conditions on the TP. In short, the presented dataset would be valuable for evaluation and improvement of long-term satellite- and model-based SMST products on the TP, enhancing the understanding of TP hydrometeorological processes and their response to climate change. The dataset is available in the 4TU.ResearchData repository at https://doi.org/10.4121/20141567.v1. [ABSTRACT FROM AUTHOR]

Sun sheds were once used as an effective roadbed cooling technique in permafrost regions. Numerical and indoor-experiment results have confirmed the cooling effects of the sun-shaded embankments, but field-monitored data are still necessary to evaluate their long-term performance. This paper discusses the cooling effects of a sun shed over a section of the Qinghai-Tibet Railway embankment, by examining near-surface air and ground temperatures and the permafrost table depth at the shaded section, at an unshaded embankment section, and in surrounding natural ground. Monitoring results from 2006 to 2010 indicate that the sun shed has lowered near-surface air temperatures and underlying permafrost temperatures beneath the embankment, and promoted permafrost aggradation. The estimated annual heat budget of the permafrost beneath the sun-shaded embankment section has been negative over the past nine years, indicating the sustained cooling performance of the sun shed. This study confirms the utility of sun sheds as an effective design and maintenance concept for infrastructure embankments in warm permafrost regions, provided that the structure can resist harsh environmental conditions. [ABSTRACT FROM AUTHOR]