CORRECTION article

Front. Environ. Sci., 05 May 2023

Sec. Atmosphere and Climate

Volume 11 - 2023 | https://doi.org/10.3389/fenvs.2023.1205591

Corrigendum: Spatiotemporal features of the soil moisture across Northwest China using remote sensing data, reanalysis data, and global hydrological model

  • 1. College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi, Xinjiang, China

  • 2. Research Center for Ecology and Environment of Central Asia, Chinese Academy of Sciences, Urumqi, Xinjiang, China

  • 3. Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi, Xinjiang, China

  • 4. University of Chinese Academy of Sciences, Beijing, China

  • 5. State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang, China

Article metrics

View details

1,2k

Views

287

Downloads

In the published article, there are some missing references both in section 2 Study area, dataset, and methodology, sub-section 2.3 Methodologies and in the section References. The corrected paragraph and the corresponding references appear below:

“The accuracy evaluation methods include the correlation coefficient (CC), relative error (RE), root mean square error (RMSE), distance between indices of simulation and observation (DISO) and the triple collocation (TC) method. The DISO index is widely used in many fields, such as climate change, medicine, and economics (Hu et al., 2019; Hu et al., 2020; Zhou et al., 2021; Hu et al., 2022; Liu et al., 2022; Yin et al., 2022; Zhang et al., 2022). TC (Stoffelen, 1998; Gruber et al., 2016) is a statistical method used to estimate the random error variance of three independent datasets. The specific method is described in the Supplementary Materials.”

The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.

Statements

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

References

  • 1

    GruberA.SuC.ZwiebackS.CrowW.DorigoW.WagnerW. (2016). Recent advances in (soil moisture) triple collocation analysis. Int. J. Appl. Earth Observation Geoinformation45, 200211. 10.1016/j.jag.2015.09.002

  • 2

    HuZ.ChenD.ChenX.ZhouQ.PengY.LiJ.et al (2022). CCHZ‐DISO: A timely new assessment system for data quality or model performance from da dao zhi jian. Geophys. Res. Lett.49. 10.1029/2022gl100681

  • 3

    HuZ.ChenX.ZhouQ.ChenD.LiJ. (2019). Diso: A rethink of taylor diagram. Int. J. Climatol.39, 28252832. 10.1002/joc.5972

  • 4

    HuZ.CuiQ.HanJ.WangX.ShaW. E.TengZ. (2020). Evaluation and prediction of the Covid-19 variations at different input population and quarantine strategies, a case study in Guangdong province, China. Int. J. Infect. Dis.95, 231240. 10.1016/j.ijid.2020.04.010

  • 5

    LiuW.ZhaoS.GongR.ZhangY.DingF.ZhangL.et al (2022). Interactive effects of meteorological factors and ambient air pollutants on mumps incidences in Ningxia, China between 2015 and 2019. Front. Environ. Sci.10. 10.3389/fenvs.2022.937450

  • 6

    StoffelenA. (1998). Toward the true near-surface wind speed: Error modeling and calibration using triple collocation. J. Geophys. Res. Oceans103 (C4), 77557766. 10.1029/97jc03180

  • 7

    YinW. J.YangS.HuL. T.TianS.WangX.ZhaoR.et al (2022). Improving understanding of spatiotemporal water storage changes over China based on multiple datasets. J. Hydrology612, 128098. 10.1016/j.jhydrol.2022.128098

  • 8

    ZhangX.DuanY. W.DuanJ. P.ChenL.JianD.LvM.et al (2022). A daily drought index-based regional drought forecasting using the global forecast system model outputs over China. Atmos. Res.273, 106166. 10.1016/j.atmosres.2022.106166

  • 9

    ZhouQ.ChenD.HuZ.ChenX. (2021). Decompositions of Taylor diagram and diso performance criteria. Int. J. Climatol.41 (12), 57265732. 10.1002/joc.7149

Summary

Keywords

soil moisture, microwave remote sensing data, lobal hydrological model, reanalysis data, spatiotemporal characteristics

Citation

Wang M, Yin G, Mao M, Zhang H, Zhang H, Hu Z and Chen X (2023) Corrigendum: Spatiotemporal features of the soil moisture across Northwest China using remote sensing data, reanalysis data, and global hydrological model. Front. Environ. Sci. 11:1205591. doi: 10.3389/fenvs.2023.1205591

Received

14 April 2023

Accepted

21 April 2023

Published

05 May 2023

Volume

11 - 2023

Edited and reviewed by

Lunche Wang, China University of Geosciences Wuhan, China

Updates

Copyright

*Correspondence: Zengyun Hu, ; Xi Chen,

Disclaimer

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Outline

Cite article

Copy to clipboard


Export citation file


Share article

Article metrics