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https://doi.org/10.5194/essd-2020-209
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-2020-209
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  16 Oct 2020

16 Oct 2020

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This preprint is currently under review for the journal ESSD.

Status of the Tibetan Plateau observatory (Tibet-Obs) and a 10-year (2009–2019) surface soil moisture dataset

Pei Zhang1,2, Donghai Zheng2, Rogier van der Velde1, Jun Wen3, Yijian Zeng1, Xin Wang4, Zuoliang Wang4, Jiali Chen2,5, and Zhongbo Su1 Pei Zhang et al.
  • 1Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, 7514AE, the Netherlands
  • 2National Tibetan Plateau Data Center, Key Laboratory of Tibetan Environmental Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, 100101, China
  • 3College of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu, 610225, China
  • 4Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China
  • 5College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China

Abstract. The Tibetan Plateau observatory of plateau scale soil moisture and soil temperature (Tibet-Obs) was established ten years ago, which has been widely used to calibrate/validate satellite- and model-based soil moisture (SM) products for their applications to the Tibetan Plateau (TP). This paper reports on the status of the Tibet-Obs and presents a 10-year (2009–2019) surface SM dataset produced based on in situ measurements taken at a depth of 5 cm collected from the Tibet-Obs that consists of three regional-scale SM monitoring networks, i.e. the Maqu, Naqu, and Ngari (including Ali and Shiquanhe) networks. This surface SM dataset includes the original 15-min in situ measurements collected by multiple SM monitoring sites of the three networks, and the spatially upscaled SM records produced for the Maqu and Shiquanhe networks. Comparisons between four spatial upscaling methods, i.e. arithmetic averaging, Voronoi diagram, time stability and apparent thermal inertia, show that the arithmetic average of the monitoring sites with long-term (i.e. ≥ six years) continuous measurements are found to be most suitable to produce the upscaled SM records. Trend analysis of the 10-year upscaled SM records using the Mann-Kendall method shows that the Maqu network area in the eastern part of the TP is drying while the Shiquanhe network area in the west is getting wet that generally follow the change of precipitation. To further demonstrate the uniqueness of the upscaled SM records in validating existing SM products for long term period (~ 10 years), comparisons are conducted to evaluate the reliability of three reanalysis datasets for the Maqu and Shiquanhe network areas. It is found that current model-based SM products still show deficiencies in representing the trend and variation of measured SM dynamics in the Tibetan grassland (i.e. Maqu) and desert ecosystems (i.e. Shiquanhe) that dominate the landscape of the TP. The dataset would be also valuable for calibrating/validating long-term satellite-based SM products, evaluation of SM upscaling methods, development of data fusion methods, and quantifying the coupling strength between precipitation and SM at 10-year scale. The dataset is available in the 4TU.ResearchData repository at https://doi.org/10.4121/uuid:21220b23-ff36-4ca9-a08f-ccd53782e834 (Zhang et al., 2020).

Pei Zhang et al.

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A 10-year (2009-2019) surface soil moisture dataset produced based on in situ measurements collected from the Tibet-Obs P. Zhang, D. Zheng, R. van der Velde, J. Wen, Y. Zeng, X. Wang, et al. https://doi.org/10.4121/uuid:21220b23-ff36-4ca9-a08f-ccd53782e834

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Short summary
We present a 10-year (2009–2019) surface soil moisture (5 cm) dataset produced based on in situ measurements collected from monitoring networks on the Tibetan Plateau. The dataset provides a reasonable regional-scale soil moisture time series that is valuable for calibration/validation of long term soil moisture products, evaluation/development of upscaling and data fusion methods, and quantification of coupling strength between precipitation and soil moisture at a 10-year scale.
We present a 10-year (2009–2019) surface soil moisture (5 cm) dataset produced based on in situ...
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