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Predictability of the wintertime 500 hPa geopotential height over Ural-Siberia in the NCEP climate forecast system

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Abstract

Using hindcast and forecast data from the National Centers for Environmental Prediction (NCEP) climate forecast system version 2 (CFSv2) for the period 1982–2017, we comprehensively assess the predictability of the climatology, interannual variability, and dominant modes of the wintertime 500 hPa height over Ural-Siberia (40–80° N and 30–100° E). Although the climatic mean 500 hPa height over Ural-Siberia simulated by NCEP CFSv2 has a negative bias, especially over the eastern part of the region, NCEP CFSv2 well predicts the spatial distribution of the two major modes (EOF1 and EOF2) over this region 2 months in advance. The forecasting skill of the principal component (PC) of the two major modes, PC1 (PC2), is highest 1 (0) month in advance, where the linear correlation coefficient between the predicted and observed time series reaches + 0.36 (+ 0.67), exceeding the 95% confidence level. Conversely, the forecasting skill of PC1 (PC2) is very low 0 (1) month in advance. The main reason for the poorer (better) prediction of PC1 0 (1) month in advance is associated with a less (more) accurate response of the Eurasian pattern to SST anomalies over the southwestern Atlantic. For PC2, the better (poorer) prediction of PC2 0 (1) month in advance may be due to more (less) accurate responses of the stratospheric polar vortex and the Scandinavian pattern to the dipole SST anomalies over the North Pacific. These results are useful for evaluating the predictability of the East Asian winter climate.

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Acknowledgements

This study acknowledges the support of the National Key Research and Development Program of China (2017YFC1502301), the Key Program of the National Natural Science Foundation of China (41530531), the General Program of the National Natural Science Foundation of China (41905057, 41905050, 41975088, 41875101), and the China Postdoctoral Science Foundation funded project (2018M640848).

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Authors and Affiliations

  1. School of Atmospheric Sciences and Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, Sun Yat-sen University, Zhuhai, China

    Shaobo Qiao, Meng Zou, Ho Nam Cheung, Qingxiang Li & Wenjie Dong

  2. Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai, China

    Shaobo Qiao, Ho Nam Cheung, Qingxiang Li & Wenjie Dong

  3. Guy Carpenter Asia–Pacific Climate Impact Centre, School of Energy and Environment, City University of Hong Kong, Hong Kong, China

    Wen Zhou

  4. City University of Hong Kong Shenzhen Research Institute, Shenzhen, China

    Wen Zhou

  5. National Climate Centre, China Meteorological Administration, Beijing, China

    Guolin Feng

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  1. Shaobo Qiao
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Correspondence to Ho Nam Cheung or Wenjie Dong.

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Qiao, S., Zou, M., Cheung, H.N. et al. Predictability of the wintertime 500 hPa geopotential height over Ural-Siberia in the NCEP climate forecast system. Clim Dyn 54, 1591–1606 (2020). https://doi.org/10.1007/s00382-019-05074-8

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