Preprints
https://doi.org/10.5194/hess-2020-611
https://doi.org/10.5194/hess-2020-611

  04 Jan 2021

04 Jan 2021

Review status: a revised version of this preprint was accepted for the journal HESS and is expected to appear here in due course.

Comprehensive evaluation of satellite-based and reanalysis soil moisture products using in situ observations over China

Xiaolu Ling1,3, Ying Huang2,3, Weidong Guo2,3, Yixin Wang2, Chaorong Chen2, and Jian Peng4,5 Xiaolu Ling et al.
  • 1School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, 221000, China
  • 2Institute for Climate and Global Change Research, School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
  • 3Joint International Research Laboratory of Atmospheric and Earth System Sciences, Nanjing University, 210023, Nanjing, China
  • 4Department of Remote Sensing, Helmholtz Centre for Environmental Research−UFZ, Permoserstrasse 15, 04318, Leipzig, Germany
  • 5Remote Sensing Centre for Earth System Research, Leipzig University, 04103, Leipzig, Germany

Abstract. Soil moisture (SM) plays a critical role in the water and energy cycles of the earth system; consequently, a long-term SM product with high quality is urgently needed. In this study, five SM products, including one microwave remote sensing product [European Space Agency's Climate Change Initiative (ESA CCI)] and four reanalysis datasets [European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis-Interim (ERAI), National Centers for Environmental Prediction (NCEP), the Twentieth Century Reanalysis Project from National Oceanic and Atmospheric Administration (NOAA) and the European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5)], are systematically evaluated using in situ measurements during 1981–2013 in four climate regions at different timescales over mainland China. The results show that ESA CCI is closest to the observations in terms of both the spatial distributions and magnitude of the monthly SM. All reanalysis products tend to overestimate soil moisture in all regions but have higher correlations than the remote sensing product except in Northwest China. The largest inconsistency is found in southern Northeast China, with a relative RMSE value larger than 0.1. However, none of the products can well reproduce the trends of interannual anomalies. The largest relative bias of 44.6 % is found for the ERAI SM product under severe drought conditions, and the lowest relative biases of 4.7 % and 9.5 % are found for the ESA CCI SM product under severe drought conditions and the NCEP SM product under normal conditions, respectively. As decomposing mean square errors in all the products suggests that the bias terms are the dominant contribution, the ESA CCI SM product is a good option for long-term hydrometeorological applications in mainland China. ERA5 is also a promising product, which is attributed to the incorporation of more observations. This long-term intercomparison study provides clues for SM product enhancement and further hydrological applications.

Xiaolu Ling et al.

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2020-611', Anonymous Referee #1, 12 Jan 2021
  • RC2: 'Comment on hess-2020-611', Anonymous Referee #2, 21 Jan 2021
  • CC1: 'Comment on hess-2020-611', Xingwang Fan, 21 Jan 2021

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2020-611', Anonymous Referee #1, 12 Jan 2021
  • RC2: 'Comment on hess-2020-611', Anonymous Referee #2, 21 Jan 2021
  • CC1: 'Comment on hess-2020-611', Xingwang Fan, 21 Jan 2021

Xiaolu Ling et al.

Xiaolu Ling et al.

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Short summary
Soil moisture plays a critical role in the water and energy cycles of the earth system, for which a long-term soil moisture product with high quality is urgently needed. In-situ observations are generally treated as the true value to systematically evaluate five soil moisture products including one remote sensing product and four reanalysis datasets during 1981–2013. This long-term inter-comparison study provides clues for SM product enhancement and further hydrological applications.