A correction has been applied to this article in:
Corrigendum: Spatiotemporal features of the soil moisture across Northwest China using remote sensing data, reanalysis data, and global hydrological model
Meijun Wang1,2
Gang Yin
Zengyun Hu
Xi Chen- 1College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi, Xinjiang, China
- 2Research Center for Ecology and Environment of Central Asia, Chinese Academy of Sciences, Urumqi, Xinjiang, China
- 3Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi, Xinjiang, China
- 4University of Chinese Academy of Sciences, Beijing, China
- 5State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang, China
A Corrigendum on
Spatiotemporal features of the soil moisture across Northwest China using remote sensing data, reanalysis data, and global hydrological model
by Wang M, Yin G, Mao M, Zhang H, Zhang H, Hu Z and Chen X (2023). Front. Environ. Sci. 11:1164895. doi: 10.3389/fenvs.2023.1164895
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.
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References
Gruber, A., Su, C., Zwieback, S., Crow, W., Dorigo, W., and Wagner, W. (2016). Recent advances in (soil moisture) triple collocation analysis. Int. J. Appl. Earth Observation Geoinformation 45, 200–211. doi:10.1016/j.jag.2015.09.002
Hu, Z., Chen, D., Chen, X., Zhou, Q., Peng, Y., Li, J., 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. doi:10.1029/2022gl100681
Hu, Z., Chen, X., Zhou, Q., Chen, D., and Li, J. (2019). Diso: A rethink of taylor diagram. Int. J. Climatol. 39, 2825–2832. doi:10.1002/joc.5972
Hu, Z., Cui, Q., Han, J., Wang, X., Sha, W. E., and Teng, Z. (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, 231–240. doi:10.1016/j.ijid.2020.04.010
Liu, W., Zhao, S., Gong, R., Zhang, Y., Ding, F., Zhang, L., 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. doi:10.3389/fenvs.2022.937450
Stoffelen, A. (1998). Toward the true near-surface wind speed: Error modeling and calibration using triple collocation. J. Geophys. Res. Oceans 103 (C4), 7755–7766. doi:10.1029/97jc03180
Yin, W. J., Yang, S., Hu, L. T., Tian, S., Wang, X., Zhao, R., et al. (2022). Improving understanding of spatiotemporal water storage changes over China based on multiple datasets. J. Hydrology 612, 128098. doi:10.1016/j.jhydrol.2022.128098
Zhang, X., Duan, Y. W., Duan, J. P., Chen, L., Jian, D., Lv, M., et al. (2022). A daily drought index-based regional drought forecasting using the global forecast system model outputs over China. Atmos. Res. 273, 106166. doi:10.1016/j.atmosres.2022.106166
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.
Edited and reviewed by:
Lunche Wang, China University of Geosciences Wuhan, ChinaCopyright © 2023 Wang, Yin, Mao, Zhang, Zhang, Hu and Chen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Zengyun Hu, huzengyun@ms.xjb.ac.cn; Xi Chen, chenxi@ms.xjb.ac.cn