Does the AO index have predictive power regarding extreme cold temperatures in Europe?
With a view to seasonal forecasting of extreme value statistics, we apply the method of Nonstationary extreme value statistics to determine the predictive power of large scale quantities. Regarding winter cold extremes over Europe, we find that the monthly mean daily minimum local temperature – whic...
| Main Authors: | , |
|---|---|
| Format: | Text |
| Language: | English |
| Published: |
2020
|
| Subjects: | |
| Online Access: | https://doi.org/10.5194/nhess-2020-117 https://nhess.copernicus.org/preprints/nhess-2020-117/ |
| Summary: | With a view to seasonal forecasting of extreme value statistics, we apply the method of Nonstationary extreme value statistics to determine the predictive power of large scale quantities. Regarding winter cold extremes over Europe, we find that the monthly mean daily minimum local temperature – which we call a native co-variate in the present context – has a much larger predictive power than the nonlocal monthly mean Arctic Oscillation index. Our results also prompt that the exploitation of both co-variates is not possible from 70 years-long data sets. |
|---|