| Autor: |
Julia F. Lockwood, Nicky Stringer, Hazel E. Thornton, Adam A. Scaife, Philip E. Bett, Tamara Collier, Ruth Comer, Nick Dunstone, Margaret Gordon, Leon Hermanson, Sarah Ineson, Jamie Kettleborough, Jeff Knight, Joseph Mancell, Peter McLean, Doug Smith, Tony Wardle, Prince Xavier, Ben Youngman |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
Atmospheric Science Letters, Vol 23, Iss 12, Pp n/a-n/a (2022) |
| Druh dokumentu: |
article |
| ISSN: |
1530-261X |
| DOI: |
10.1002/asl.1126 |
| Popis: |
Abstract Boreal winter (December–February) 2020/2021 in the North Atlantic/European region was characterised by a negative North Atlantic Oscillation (NAO) index. Although this was captured within the ensemble spread of predictions from the Met Office Global Seasonal forecast system (GloSea5), with 17% of ensemble members predicting an NAO less than zero, the forecast ensemble mean was shifted towards a positive NAO phase. The observed monthly NAO anomalies were particularly negative in January and February, following an early January sudden stratospheric warming (SSW), and a prolonged period of Phase 6 or 7 of the Madden Julian Oscillation (MJO) in late January/early February. In contrast, predictions showed the expected teleconnection from the observed La Niña, with a positive NAO signal resulting from a weakening of the Aleutian Low leading to a reduction in tropospheric wave activity, an increase in polar vortex strength and a reduced chance of an SSW. Forecasts initialised later in the winter season successfully predicted the negative NAO in January and February once the SSW and MJO were within the medium range timescale. GloSea5 likely over‐predicted the strength of the La Niña which we estimate caused a small negative bias in the SSW probability. However, this error is smaller than the uncertainty in SSW probability from the finite forecast ensemble size, emphasising the need for large forecast ensembles. This case study also demonstrates the advantage of continuously updated lagged ensemble forecasts over a ‘burst’ ensemble started on a fixed date, since a change in forecast signal due to events within the season can be detected early and promptly communicated to users. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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