Difference between near-surface air, land surface and ground surface temperatures and their influences on the frozen ground on the Qinghai-Tibet Plateau

Surface temperature is critical for the simulation of climate change impacts on the ecology, environment, and particularly permafrost in the cryosphere. Virtually, surface temperatures are different in the near-surface air temperature (Ta) measured at a screen-height of 1.5–2m, the land surface temp...

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Published inGeoderma Vol. 312; pp. 74 - 85
Main Authors Luo, Dongliang, Jin, Huijun, Marchenko, Sergey S., Romanovsky, Vladimir E.
Format Journal Article
LanguageEnglish
Published Elsevier B.V 15.02.2018
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ISSN0016-7061
1872-6259
DOI10.1016/j.geoderma.2017.09.037

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Abstract Surface temperature is critical for the simulation of climate change impacts on the ecology, environment, and particularly permafrost in the cryosphere. Virtually, surface temperatures are different in the near-surface air temperature (Ta) measured at a screen-height of 1.5–2m, the land surface temperature (LST) on the top canopy layer, and the ground surface temperature (GST) 0–5 cm beneath the surface cover. However, not enough attention has been concentrated on the difference in these surface temperatures. This study aims at quantifying the distinction of surface temperatures by the comparisons and numerical simulations of observational field data collected in a discontinuous permafrost region on the northeastern Qinghai-Tibet Plateau (QTP). We compared the hourly, seasonal and yearly differences between Ta, LST, GST, and ground temperatures, as well as the freezing and thawing indices, the N-factors, and the surface and thermal offsets derived from these temperatures. The results showed that the peak hourly LST was reached earliest, closely followed by the hourly Ta. Mean annual LST (MALST) was moderately comparable to mean annual Ta (MAAT), and both were lower than mean annual GST (MAGST). Surface offsets (MAGST-MAAT) were all within 3.5 °C, which are somewhat consistent with other parts of the QTP but smaller than those in the Arctic and Subarctic regions with dense vegetation and thick, long-duration snow cover. Thermal offsets, the mean annual differences between the ground surface and the permafrost surface, were within −0.3°C, and one site was even reversed, which may be relevant to equally thawed to frozen thermal conductivities of the soils. Even with identical Ta (comparable to MAAT of −3.27 and −3.17°C), the freezing and thawing processes of the active layer were distinctly different, due to the complex influence of surface characteristics and soil textures. Furthermore, we employed the Geophysical Institute Permafrost Lab (GIPL) model to numerically simulate the dynamics of ground temperature driven by Ta, LST, and GST, respectively. Simulated results demonstrated that GST was a reliable driving indicator for the thermal regime of frozen ground, even if no thermal effects of surface characteristics were taken into account. However, great biases of mean annual ground temperatures, being as large as 3°C, were induced on the basis of simulations with LST and Ta when the thermal effect of surface characteristics was neglected. We conclude that quantitative calculation of the thermal effect of surface characteristics on GST is indispensable for the permafrost simulations based on the Ta datasets and the LST products that derived from thermal infrared remote sensing. •First comparisons of three different surface temperatures to soil science•Simulate ground temperature by near-surface air, land and ground surface temperatures.•Emphasize the importance of surface characteristics on mapping & modeling permafrost.•Suggest the ground surface temperature as a reliable indicator for permafrost.
AbstractList Surface temperature is critical for the simulation of climate change impacts on the ecology, environment, and particularly permafrost in the cryosphere. Virtually, surface temperatures are different in the near-surface air temperature (Ta) measured at a screen-height of 1.5–2m, the land surface temperature (LST) on the top canopy layer, and the ground surface temperature (GST) 0–5 cm beneath the surface cover. However, not enough attention has been concentrated on the difference in these surface temperatures. This study aims at quantifying the distinction of surface temperatures by the comparisons and numerical simulations of observational field data collected in a discontinuous permafrost region on the northeastern Qinghai-Tibet Plateau (QTP). We compared the hourly, seasonal and yearly differences between Ta, LST, GST, and ground temperatures, as well as the freezing and thawing indices, the N-factors, and the surface and thermal offsets derived from these temperatures. The results showed that the peak hourly LST was reached earliest, closely followed by the hourly Ta. Mean annual LST (MALST) was moderately comparable to mean annual Ta (MAAT), and both were lower than mean annual GST (MAGST). Surface offsets (MAGST-MAAT) were all within 3.5 °C, which are somewhat consistent with other parts of the QTP but smaller than those in the Arctic and Subarctic regions with dense vegetation and thick, long-duration snow cover. Thermal offsets, the mean annual differences between the ground surface and the permafrost surface, were within −0.3°C, and one site was even reversed, which may be relevant to equally thawed to frozen thermal conductivities of the soils. Even with identical Ta (comparable to MAAT of −3.27 and −3.17°C), the freezing and thawing processes of the active layer were distinctly different, due to the complex influence of surface characteristics and soil textures. Furthermore, we employed the Geophysical Institute Permafrost Lab (GIPL) model to numerically simulate the dynamics of ground temperature driven by Ta, LST, and GST, respectively. Simulated results demonstrated that GST was a reliable driving indicator for the thermal regime of frozen ground, even if no thermal effects of surface characteristics were taken into account. However, great biases of mean annual ground temperatures, being as large as 3°C, were induced on the basis of simulations with LST and Ta when the thermal effect of surface characteristics was neglected. Quantitative calculation of the thermal effect of surface characteristics on GST is indispensable for the purposes of engineering project designs and permafrost simulations based on the Ta datasets and the LST products derived from thermal infrared remote sensing.
Surface temperature is critical for the simulation of climate change impacts on the ecology, environment, and particularly permafrost in the cryosphere. Virtually, surface temperatures are different in the near-surface air temperature (Ta) measured at a screen-height of 1.5–2m, the land surface temperature (LST) on the top canopy layer, and the ground surface temperature (GST) 0–5 cm beneath the surface cover. However, not enough attention has been concentrated on the difference in these surface temperatures. This study aims at quantifying the distinction of surface temperatures by the comparisons and numerical simulations of observational field data collected in a discontinuous permafrost region on the northeastern Qinghai-Tibet Plateau (QTP). We compared the hourly, seasonal and yearly differences between Ta, LST, GST, and ground temperatures, as well as the freezing and thawing indices, the N-factors, and the surface and thermal offsets derived from these temperatures. The results showed that the peak hourly LST was reached earliest, closely followed by the hourly Ta. Mean annual LST (MALST) was moderately comparable to mean annual Ta (MAAT), and both were lower than mean annual GST (MAGST). Surface offsets (MAGST-MAAT) were all within 3.5 °C, which are somewhat consistent with other parts of the QTP but smaller than those in the Arctic and Subarctic regions with dense vegetation and thick, long-duration snow cover. Thermal offsets, the mean annual differences between the ground surface and the permafrost surface, were within −0.3°C, and one site was even reversed, which may be relevant to equally thawed to frozen thermal conductivities of the soils. Even with identical Ta (comparable to MAAT of −3.27 and −3.17°C), the freezing and thawing processes of the active layer were distinctly different, due to the complex influence of surface characteristics and soil textures. Furthermore, we employed the Geophysical Institute Permafrost Lab (GIPL) model to numerically simulate the dynamics of ground temperature driven by Ta, LST, and GST, respectively. Simulated results demonstrated that GST was a reliable driving indicator for the thermal regime of frozen ground, even if no thermal effects of surface characteristics were taken into account. However, great biases of mean annual ground temperatures, being as large as 3°C, were induced on the basis of simulations with LST and Ta when the thermal effect of surface characteristics was neglected. We conclude that quantitative calculation of the thermal effect of surface characteristics on GST is indispensable for the permafrost simulations based on the Ta datasets and the LST products that derived from thermal infrared remote sensing. •First comparisons of three different surface temperatures to soil science•Simulate ground temperature by near-surface air, land and ground surface temperatures.•Emphasize the importance of surface characteristics on mapping & modeling permafrost.•Suggest the ground surface temperature as a reliable indicator for permafrost.
Author Jin, Huijun
Luo, Dongliang
Marchenko, Sergey S.
Romanovsky, Vladimir E.
Author_xml – sequence: 1
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  surname: Luo
  fullname: Luo, Dongliang
  email: luodongliang@lzb.ac.cn
  organization: State Key Laboratory of Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
– sequence: 2
  givenname: Huijun
  surname: Jin
  fullname: Jin, Huijun
  organization: State Key Laboratory of Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
– sequence: 3
  givenname: Sergey S.
  surname: Marchenko
  fullname: Marchenko, Sergey S.
  organization: State Key Laboratory of Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
– sequence: 4
  givenname: Vladimir E.
  surname: Romanovsky
  fullname: Romanovsky, Vladimir E.
  organization: Permafrost Laboratory, Geophysical Institute, University of Alaska Fairbanks, Fairbanks, Alaska, USA
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Keywords Land surface temperature (LST)
Qinghai-Tibet Plateau (QTP)
Near-surface air temperature (Ta)
Ground surface temperature (GST)
Elevational permafrost
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Snippet Surface temperature is critical for the simulation of climate change impacts on the ecology, environment, and particularly permafrost in the cryosphere....
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StartPage 74
SubjectTerms air
air temperature
Arctic region
canopy
China
climate change
data collection
Elevational permafrost
engineering
freezing
geophysics
Ground surface temperature (GST)
Land surface temperature (LST)
mathematical models
Near-surface air temperature (Ta)
permafrost
Qinghai-Tibet Plateau (QTP)
remote sensing
snowpack
soil texture
surface temperature
thawing
vegetation
Title Difference between near-surface air, land surface and ground surface temperatures and their influences on the frozen ground on the Qinghai-Tibet Plateau
URI https://dx.doi.org/10.1016/j.geoderma.2017.09.037
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