Articles | Volume 17, issue 11
https://doi.org/10.5194/gmd-17-4579-2024
https://doi.org/10.5194/gmd-17-4579-2024
Methods for assessment of models
 | 
10 Jun 2024
Methods for assessment of models |  | 10 Jun 2024

A general comprehensive evaluation method for cross-scale precipitation forecasts

Bing Zhang, Mingjian Zeng, Anning Huang, Zhengkun Qin, Couhua Liu, Wenru Shi, Xin Li, Kefeng Zhu, Chunlei Gu, and Jialing Zhou

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Cited articles

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Casati, B., Wilson, L. J., Stephenson, D. B., Nurmi, P., Ghelli, A., Pocernich, M., Damrath, U., Ebert, E. E., Brown, B. G., and Mason, S.: Forecast verification: current status and future directions, Meteorol. Appl., 15, 3–18, https://doi.org/10.1002/met.52, 2008. 
Chen, F., Chen, J., Wei, Q., Li, J., Liu, C., Yang, D., Zhao, B., and Zhang, Z.: A new verification method for heavy rainfall forecast based on predictability II: Verification method and test, Acta. Meteorol. Sin., 77, 28–42, https://doi.org/10.11676/qxxb2019.003, 2019. 
Chen, H., Li, P., and Zhao, Y.: A review and outlook of verification and evaluation of precipitation forecast at convection-permitting resolution, Adv. Meteorol. Sci. Technol., 11, 155–164, https://doi.org/10.3969/j.issn.2095-1973.2021.03.018, 2021. 
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Short summary
By directly analyzing the proximity of precipitation forecasts and observations, a precipitation accuracy score (PAS) method was constructed. This method does not utilize a traditional contingency-table-based classification verification; however, it can replace the threat score (TS), equitable threat score (ETS), and other skill score methods, and it can be used to calculate the accuracy of numerical models or quantitative precipitation forecasts.
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