Journal
GEOPHYSICAL RESEARCH LETTERS
Volume 49, Issue 16, Pages -Publisher
AMER GEOPHYSICAL UNION
DOI: 10.1029/2022GL099401
Keywords
weather regimes; medium-range weather forecasts; dynamical systems analysis; prediction skill
Categories
Funding
- NASA [80NSSC17K0266]
- ONR [N00014-20-1-2722]
- NSF [AGS-1921413]
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The predictability of different weather regimes during extended boreal summer in the Pacific-North American region was examined in this study. It was found that the Arctic high regime had the highest forecast skill and intrinsic predictability, while the Pacific trough regime had the lowest intrinsic predictability. The results also highlighted the link between prediction skill and intrinsic predictability.
The forecast skill of numerical weather prediction (NWP) models and the intrinsic predictability can be different among weather regimes. Here, we examine the predictability of distinct Pacific-North American weather regimes during extended boreal summer. The four identified weather regimes include Pacific trough, Arctic low, Arctic high, and Alaskan ridge. The medium range forecast skill of these regimes is quantified in the ECMWF and the National Centers for Environmental Prediction models from the TIGGE project. Based on anomaly correlation coefficient, persistence, and transition frequency, the highest forecast skill is consistently found for the Arctic high regime. Based on the instantaneous local dimension and persistence from a dynamical systems analysis, the Arctic high regime has the highest intrinsic predictability. The analysis also suggests that overall, the Pacific trough regime has the lowest intrinsic predictability. These findings are consistent with the forecast skills of the NWP models, and highlight the link between prediction skill and intrinsic predictability.
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