Preprints
https://doi.org/10.5194/essd-2023-108
https://doi.org/10.5194/essd-2023-108
14 Jul 2023
 | 14 Jul 2023
Status: a revised version of this preprint was accepted for the journal ESSD and is expected to appear here in due course.

Multiscale observation network of ground surface temperature under different landcover types on NE Qinghai-Tibet Plateau

Raul-David Șerban, Huijun Jin, Mihaela Șerban, Giacomo Bertoldi, Dongliang Luo, Qingfeng Wang, Qiang Ma, Ruixia He, Xiaoying Jin, Xinze Li, Jianjun Tang, and Hongwei Wang

Abstract. Ground surface temperature (GST), measured at approximately 5 cm in depth is a key parameter controlling subsurface biophysical processes at the land-atmosphere boundary. This work presents a valuable dataset of GST observations at various spatial scales in the Headwater Area of the Yellow River (HAYR). The HAYR is a representative area of high plateau permafrost on northeastern Qinghai-Tibet Plateau (QTP). GST was measured every three hours using 72 iButton temperature loggers (DS1922L) at 39 sites from 2019 to 2020. At each site, GST was recorded in two plots at distances from 2 to 16 m under similar and different landcover conditions (steppe, meadow, swamp meadow, and bare ground). These sensors proved their reliability in harsh environments as only 165 measurements were biased from a total of 210,816. A high significant correlation (> 0.96, p < 0.001) was observed between plots, with a mean absolute error (MAE) of 0.2 to 1.2 °C. The daily intra-plot differences in GST were mainly < 2 °C for sites with similar landcover in both plots and > 2 °C when bare ground was compared to vegetation. From autumn to spring, the differences can increase to 4–5 °C for up to 15 days. The values of the frost number (FN) were quite similar between the plots with differences < 0.05 for most of the sites. This dataset complements the sparse observations of GST on the QTP and helps to identify the permafrost distribution and degradation at high resolution and to validate and calibrate the regional permafrost models. The datasets are openly available in the National Tibetan Plateau/Third Pole Environment Data Center (https://dx.doi.org/10.11888/Cryos.tpdc.272945, Șerban and Jin, 2022).

Raul-David Șerban, Huijun Jin, Mihaela Șerban, Giacomo Bertoldi, Dongliang Luo, Qingfeng Wang, Qiang Ma, Ruixia He, Xiaoying Jin, Xinze Li, Jianjun Tang, and Hongwei Wang

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2023-108', Anonymous Referee #1, 17 Sep 2023
    • AC1: 'Reply on RC1', Raul-David Șerban, 06 Oct 2023
  • RC2: 'Comment on essd-2023-108', Anonymous Referee #2, 23 Sep 2023
    • AC2: 'Reply on RC2', Raul-David Șerban, 06 Oct 2023
  • RC3: 'Comment on essd-2023-108', Anonymous Referee #3, 15 Oct 2023
    • AC3: 'Reply on RC3', Raul-David Șerban, 18 Nov 2023

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2023-108', Anonymous Referee #1, 17 Sep 2023
    • AC1: 'Reply on RC1', Raul-David Șerban, 06 Oct 2023
  • RC2: 'Comment on essd-2023-108', Anonymous Referee #2, 23 Sep 2023
    • AC2: 'Reply on RC2', Raul-David Șerban, 06 Oct 2023
  • RC3: 'Comment on essd-2023-108', Anonymous Referee #3, 15 Oct 2023
    • AC3: 'Reply on RC3', Raul-David Șerban, 18 Nov 2023
Raul-David Șerban, Huijun Jin, Mihaela Șerban, Giacomo Bertoldi, Dongliang Luo, Qingfeng Wang, Qiang Ma, Ruixia He, Xiaoying Jin, Xinze Li, Jianjun Tang, and Hongwei Wang

Data sets

Multiscale observation of topsoil temperature below different landcover types on northeastern Qinghai-Tibet Plateau (2019-2020) Raul-David Șerban, Huijun Jin https://doi.org/10.11888/Cryos.tpdc.272945

Raul-David Șerban, Huijun Jin, Mihaela Șerban, Giacomo Bertoldi, Dongliang Luo, Qingfeng Wang, Qiang Ma, Ruixia He, Xiaoying Jin, Xinze Li, Jianjun Tang, and Hongwei Wang

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Short summary
A particular observational network for ground surface temperature (GST) has been established on the northeastern Qinghai-Tibet Plateau covering various environmental conditions and scales. This analysis revealed the substantial influences of the landcover on the spatial variability in GST over short distances (<16 m). Improving the monitoring of GST is important for the biophysical processes at the land-atmosphere boundary and for understanding the climate change impacts on cold environments.
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