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This is discussed further below (see e.g. Fig8.2.72-3).

Useful forecasts of the onset or cessation of anomalous, and even extreme surface weather over Europe may be made if the change from one circulation pattern to another, and the timing of that change, can be predicted well in advance of the event.  Additionally there needs to be an associated assessment of the confidence in any such transitions and their timing.  Errors in forecasting transitions from one type to another can lead to very large forecast errors in absolute (e.g. RMS error) terms. This is especially true in respect of the onset of blocking. 

Fig8.2.72-1: Geographical patterns of Euro-Atlantic climatological regimes (both anomalies and full fields) as used at ECMWF. North Atlantic Oscillation, positive phase (NAO+), North Atlantic Oscillation, negative phase (NAO­–), Blocking (BLO+), The Atlantic Ridge (AR) circulation pattern is a particular case of Anti-blocking (BLO–), in which the important feature is the trough over Scandinavia.  Geopotential anomalies (colour shading) and geopotential (contours) at 500 hPa are shown.

Fig:8.2.72-2: 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.

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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.

Fig8.2.72-3: 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.

Fig8.2.72-4:  Regime Projection Diagrams: NAO/BL phase space diagrams (Wheeler-Hendon diagrams) for the periods: Days11-17 and Days25-31, from extended 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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NAO–BLO phase space can be used to illustrate the relationship between severe cold European spells. 

Fig8.2.72-5: Severe cold European spells, detected using the 2m temperature reanalyses, represented in the NAO–BLO space.  Colours have no special meaning.  The arrangement of the NAO-BLO diagrams corresponds to the arrangement of areas of Europe as shown on the map.

The analysis of severe cold spells in Europe, plotted on NAO-BLO diagrams for different areas is shown in Fig8.2.72-5.  The diagrams show severe cold spells in:

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Predictability of the circulation patterns

Fig8.2.72-6: 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.

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A study using available extended 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 Fig8.2.72-7.

Fig8.2.72-7: Frequency (in percentages) of transitions to a given regime; stacked bar colour denotes the previous regime.  Colours show transitions from BLO+ (pale red), from BLO− (purple), from NAO+ (blue), from NAO− (green), no clear initial circulation pattern (grey).  Reanalysis values are shown in the column on the far left of each section.  The other bars indicate the forecast values at Day11, Day16, Day21 and Day31, respectively.  Where the frequency is larger than 5% its value is indicated on the bar.

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Example of circulation pattern and anomaly charts.

Fig8.2.72-8: 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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This implies anomalously strong westerlies at around 40N and strong southeasterlies Denmark to Iceland.

Fig8.2.72-9: Forecast precipitation mean anomaly verifying Day7-14 (23-30 Oct 2023).  The anomaly of precipitation from ER-M-climate suggests:

• a drier spell over Russia and northern Scandinavia, particularly over and to the lee of western Norway.
• a wetter spell over Europe, particularly over western Europe.
• a drier than normal spell between Azores and Canary Isles.

Fig8.2.72-10: Forecast precipitation mean anomaly verifying Day7-14 (23-30 Oct 2023).  The anomaly of 2 m temperature from ER-M-climate suggests:

• a cold spell over Russia and northeast Scandinavia.
• a warm spell over Europe, particularly over the Balkan states.
• a warm spell between Azores and Canary Isles.

Fig8.2.72-11: Forecast 500hPa height mean anomaly verifying Day7-14 (23-30 Oct 2023).  The anomaly of 500hPa height from ER-M-climate is:

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The 500hPa height pattern is similar to the BLO+ pattern (See Fig8.2.72-1).

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.

Fig8.2.72-12: Regime-based skill measures for ensemble mean fields from various global forecast systems. There is skill where correlation is above 0.5.

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The longer period of skill for NAO modes may be associated with the NAO modes being more persistent (notably NAO-), and the fact that models are correctly capturing that persistence.

Fig8.2.72-13: Continuous Ranked Probability Skill Score (CRPSS) for the four Euro-Atlantic Regimes for several forecast models. 

In Fig8.2.72-13, ECMWF (black) shows some skill for NAO-/NAO+ up to 20-23 days while for BLO+ (blocking) and AR (Atlantic Ridge) skill drops to zero at about 16-17 days.  In other words, the ECMWF extended range forecasts have more difficulty predicting episodes of "Blocking" and "Atlantic Ridge" than they do predicting episodes of NAO+ and NAO-.  Note that the plot is based on about 10 years of re-forecast data from all the models shown.  Every ENS forecast is represented on every panel - i.e. the plot does not just relate to questions such as "when NAO- was forecast did it happen?".

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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.  Fig8.2.72-14 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. 

Fig8.2.72-14: The mean ensemble variance as a function of lead time for all forecasts with the ensemble mean entering the BLO+ (red), BLO− (purple), NAO+ (blue), NAO− (green) sectors of an NAO-BLO diagram.  NAO- shows better predictability (less ensemble spread) than other circulation patterns.

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