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Circulation patterns in the Euro-Atlantic Region

The large-scale circulation patterns that impact upon the European area can be categorised into four main classes:

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Fig:8.2.2-2: Anomalies in 2m temperature associated with the persistence (periods longer than 5 days) of the (a) positive North Atlantic Oscillation, NAO+, (b) negative North Atlantic Oscillation, NAO-, (c) Scandinavian Blocking, BL+, and (d) Atlantic Ridge (AR) (or Anti Blocking BLO-) regimes.

Presentation of circulation patterns

NAO-BLO diagrams

If NAO and BLO circulation systems are considered as orthogonal, a NAO-BLO phase space diagram (Wheeler-Hendon diagram) may be used to investigate and illustrate the relationship between circulation type and other forecast or observed parameters.  The NAO–BLO phase space can offer the advantage of a simplified framework for assessing model performance in predicting temperature extremes.

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Fig8.2.2-3: NAO–BLO phase space.  Well-defined circulation patterns lie towards the periphery of the diagram.  The central circle encloses a region where the circulation system is weak or cannot be confidently identified.

Examples of NAO–BLO phase space diagrams.

Fig8.2.2-4:  Regime Projection Diagrams: NAO/BL phase space diagrams (Wheeler-Hendon diagrams) for the periods: Days11-17 and Days25-31, from sub-seasonal range ensembles DT 20 Oct 2023.  Colours represent the proportion of members that have a similar mean solution during each seven day period.  The shaded area gives an indication of the spread of regime types.  Colours represent different proportions (taken as probabilities) of a combination of regime types. Note the colours represent different probabilities on each diagram.  Within the central circle there is only a weak indication of regime type.  The regime Projection Diagrams are derived using Mirror 2-regime scheme.

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• Central Europe (Area5) are associated strongly with BLO+ and NAO–,
• Northwest Europe (Areas 1&2) are associated strongly with NAO– and BLO–,
• Eastern Europe (Areas 3&6) are associated less strongly, and with a rather scattered distribution, to NAO+, BLO+ and NAO–.

Predictability of the circulation patterns

Fig8.2.2-6: Predictability distribution on NAO-BLO diagram.  Ensemble variance colour coded as the scale.  Ensemble variance (spread) is indicative of predictability.  Thus NAO– has relatively high predictability (probably because it tends to be more persistent than other regimes), BLO+ has relatively lower predictability.  The NAO–BLO space explains about 30% of the daily winter variability over Europe.

Transitions between circulation type or regimes

A study using available sub-seasonal range re-forecasts (12 years of re-forecasts) gives an indication of the ability of the forecasts to capture similar transitions that occurred during the six-day period preceding various selected forecast lead times (Day11, Day16, Day21, Day 31).  The results are shown in Fig8.2.2-7.

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The model statistics and relative frequencies, at all forecast ranges, compare well with those from the analysis, indicating that the IFS is well able to simulate transitions, and suggesting that model bias in this context is not a major problem.

Example of circulation pattern and anomaly charts.

Fig8.2.2-8: Forecast mean sea level pressure mean anomaly verifying Day7-14 (23-30 Oct 2023).  The anomaly of surface pressure from ER-M-climate is:

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The 500hPa height pattern is similar to the BLO+ pattern (See Fig8.2.2-1).

Skill

A measure of skill is the anomaly correlation between the observed and the ensemble mean forecasts of the principle circulation patterns - i.e. components associated with westerly/easterly flow across the Atlantic (NAO+/NAO–), blocked/anti-blocked flow over Scandinavia (BLO+/BLO­–), and the bivariate correlation using both of these.

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The skill in predicting heat waves or cold spells in the sub-seasonal range may be limited by the ability of the forecast model to represent transitions to anticyclonic circulation regimes (BLO+, NAO-) over Europe.  However, once an NAO- circulation pattern has formed there is a tendency for it to persist in reality and in the IFS.

Uncertainty and Predictability

The ensemble variance or spread is an indicator of forecast uncertainty and normally increases with forecast lead time.  The rate at which the spread grows during the forecast can be used as an estimate of predictability.  Fig8.2.2-14 shows the change in spread with elapsed time.  Beyond day 3, forecasts with the ensemble mean first entering the NAO− sector have a lower mean ensemble variance than those with the ensemble mean entering any other sectors.  The differences between the mean ensemble variances could be associated with the fact that, by entering into a circulation pattern (NAO–) associated with higher predictability, the forecast uncertainty increases at a slower rate. 

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• Fairly high with NAO–
• Moderate with transitions to BLO+

Additional Sources of Information

(Note: In older material there may be references to issues that have subsequently been addressed)

• Read more on the predictability of changes in large scale flow.
• Read more on diagnosis and verification of high-impact weather forecasts.

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