Articles | Volume 17, issue 3
https://doi.org/10.5194/amt-17-1123-2024
https://doi.org/10.5194/amt-17-1123-2024
Research article
 | 
16 Feb 2024
Research article |  | 16 Feb 2024

Impacts of anemometer changes, site relocations and processing methods on wind speed trends in China

Yi Liu, Lihong Zhou, Yingzuo Qin, Cesar Azorin-Molina, Cheng Shen, Rongrong Xu, and Zhenzhong Zeng

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Cited articles

Azorin-Molina, C., Vicente-Serrano, S. M., McVicar, T. R., Jerez, S., Sanchez-Lorenzo, A., López-Moreno, J.-I., Revuelto, J., Trigo, R. M., Lopez-Bustins, J. A., and Espírito-Santo, F.: Homogenization and Assessment of Observed Near-Surface Wind Speed Trends over Spain and Portugal, 1961–2011, J. Climate, 27, 3692–3712, https://doi.org/10.1175/JCLI-D-13-00652.1, 2014. 
Azorin-Molina, C., Asin, J., McVicar, T. R., Minola, L., Lopez-Moreno, J. I., Vicente-Serrano, S. M., and Chen, D.: Evaluating anemometer drift: A statistical approach to correct biases in wind speed measurement, Atmos. Res., 203, 175–188, https://doi.org/10.1016/j.atmosres.2017.12.010, 2018. 
Azorin-Molina, C., Guijarro, J. A., McVicar, T. R., Trewin, B. C., Frost, A. J., and Chen, D.: An approach to homogenize daily peak wind gusts: An application to the Australian series, Int. J. Climatol., 39, 2260–2277, https://doi.org/10.1002/joc.5949, 2019. 
Bathiany, S., Scheffer, M., van Nes, E. H., Williamson, M. S., and Lenton, T. M.: Abrupt Climate Change in an Oscillating World, Sci. Rep., 8, 5040, https://doi.org/10.1038/s41598-018-23377-4, 2018. 
Camuffo, D., della Valle, A., Becherini, F., and Zanini, V.: Three centuries of daily precipitation in Padua, Italy, 1713–2018: history, relocations, gaps, homogeneity and raw data, Climatic Change, 162, 923–942, https://doi.org/10.1007/s10584-020-02717-2, 2020. 
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Short summary
Our research analyzed China's wind speed data and addressed inconsistencies caused by factors like equipment changes and station relocations. After improving data quality, China's recent wind speed decrease reduced by 41 %, revealing an increasing trend. This emphasizes the importance of rigorous data processing for accurate trend assessments in various research fields.