Evaluation of the Forecast Performance for Extreme Cold Events in East Asia With Subseasonal-to-Seasonal Data Sets From ECMWF

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.

Automated summary

The study evaluates the forecast skill for East Asian extreme cold events from 2015-2019 using the subseasonal-to-seasonal operational forecasts from the European Centre for Medium-Range Weather Forecasts. The results show that numerical models can capture extreme cold events with a lead time of 7 days, and long-persistent extreme cold events have a longer skillful forecast lead time, potentially due to high intrinsic predictability. This suggests the possibility of making skillful forecasts for subseasonal-to-seasonal and beyond time scales.