Articles | Volume 17, issue 16
https://doi.org/10.5194/gmd-17-6249-2024
https://doi.org/10.5194/gmd-17-6249-2024
Model experiment description paper
 | 
23 Aug 2024
Model experiment description paper |  | 23 Aug 2024

Dynamical Madden–Julian Oscillation forecasts using an ensemble subseasonal-to-seasonal forecast system of the IAP-CAS model

Yangke Liu, Qing Bao, Bian He, Xiaofei Wu, Jing Yang, Yimin Liu, Guoxiong Wu, Tao Zhu, Siyuan Zhou, Yao Tang, Ankang Qu, Yalan Fan, Anling Liu, Dandan Chen, Zhaoming Luo, Xing Hu, and Tongwen Wu

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Cited articles

Adames, Á. F. and Kim, D.: The MJO as a Dispersive, Convectively Coupled Moisture Wave: Theory and Observations, J. Atmos. Sci., 73, 913–941, https://doi.org/10.1175/JAS-D-15-0170.1, 2016. 
Adames, Á. F. and Wallace, J. M.: Three-Dimensional Structure and Evolution of the MJO and Its Relation to the Mean Flow, J. Atmos. Sci., 71, 2007–2026, https://doi.org/10.1175/JAS-D-13-0254.1, 2014. 
Adames, Á. F. and Wallace, J. M.: Three-Dimensional Structure and Evolution of the Moisture Field in the MJO, J. Atmos. Sci., 72, 3733–3754, https://doi.org/10.1175/JAS-D-15-0003.1, 2015. 
Adler, R. F., Huffman, G. J., Chang, A., Ferraro, R., Xie, P.-P., Janowiak, J., Rudolf, B., Schneider, U., Curtis, S., Bolvin, D., Gruber, A., Susskind, J., Arkin, P., and Nelkin, E.: The Version-2 Global Precipitation Climatology Project (GPCP) Monthly Precipitation Analysis (1979–Present), J. Hydrometeorol., 4, 1147–1167, https://doi.org/10.1175/1525-7541(2003)004<1147:TVGPCP>2.0.CO;2, 2003. 
Ahn, M., Kim, D., Kang, D., Lee, J., Sperber, K. R., Gleckler, P. J., Jiang, X., Ham, Y., and Kim, H.: MJO Propagation Across the Maritime Continent: Are CMIP6 Models Better Than CMIP5 Models?, Geophys. Res. Lett., 47, e2020GL087250, https://doi.org/10.1029/2020GL087250, 2020. 
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Short summary
We give an overview of the Institute of Atmospheric Physics–Chinese Academy of Sciences subseasonal-to-seasonal ensemble forecasting system and Madden–Julian Oscillation forecast evaluation of the system. Compared to other S2S models, the IAP-CAS model has its benefits but also biases, i.e., underdispersive ensemble, overestimated amplitude, and faster propagation speed when forecasting MJO. We provide a reason for these biases and prospects for further improvement of this system in the future.
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