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Evaluation of the Forecast Performance for Extreme Cold Events in East Asia With Subseasonal‐to‐Seasonal Data Sets From ECMWF
Journal of Geophysical Research: Atmospheres ( IF 3.8 ) Pub Date : 2020-12-14 , DOI: 10.1029/2020jd033860 Guokun Dai 1, 2 , Mu Mu 1 , Chunxiang Li 3 , Zhe Han 3 , Lei Wang 1
Journal of Geophysical Research: Atmospheres ( IF 3.8 ) Pub Date : 2020-12-14 , DOI: 10.1029/2020jd033860 Guokun Dai 1, 2 , Mu Mu 1 , Chunxiang Li 3 , Zhe Han 3 , Lei Wang 1
Affiliation
Utilizing the subseasonal‐to‐seasonal (S2S) operational forecasts from the European Centre for Medium‐Range Weather Forecasts, the forecast skill for East Asian extreme cold events during 2015–2019 is evaluated. The results from the ensemble mean surface air temperature anomaly, the extreme forecast index, and the continuous ranked probability score skill reveal that extreme cold events can be captured by numerical models with a lead time of 7 days. It is also found that long‐persistent extreme cold events tend to have a longer skillful forecast lead time, which can exceed 10 days. The long skillful forecast lead time indicates that these events have a high intrinsic predictability, and the remote sea surface temperature anomaly, tropical intra‐seasonal oscillation and stratospheric polar vortex may be possible reasons for this predictability. The results suggest that it may be possible to make S2S and beyond skillful forecasts.
中文翻译:
利用ECMWF的季节到季节数据集评估东亚极端寒冷事件的预报性能
利用欧洲中距离天气预报中心的季节到季节(S2S)运营预报,评估了2015-2019年东亚极端寒冷事件的预报技巧。整体平均地面气温异常,极端预报指数和连续排名概率得分技巧的结果表明,可以通过提前7天的数值模型捕获极端寒冷事件。还发现,长期持续的极端寒冷事件往往具有较长的熟练预测提前期,可能会超过10天。长期熟练的预报提前期表明这些事件具有很高的内在可预测性,而遥远的海面温度异常,热带季节内振荡和平流层极涡可能是造成这种可预测性的原因。
更新日期:2021-01-10
中文翻译:
![](https://scdn.x-mol.com/jcss/images/paperTranslation.png)
利用ECMWF的季节到季节数据集评估东亚极端寒冷事件的预报性能
利用欧洲中距离天气预报中心的季节到季节(S2S)运营预报,评估了2015-2019年东亚极端寒冷事件的预报技巧。整体平均地面气温异常,极端预报指数和连续排名概率得分技巧的结果表明,可以通过提前7天的数值模型捕获极端寒冷事件。还发现,长期持续的极端寒冷事件往往具有较长的熟练预测提前期,可能会超过10天。长期熟练的预报提前期表明这些事件具有很高的内在可预测性,而遥远的海面温度异常,热带季节内振荡和平流层极涡可能是造成这种可预测性的原因。