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The emphasis is on large-scale developments when clustering ensemble members and so the 500hPa and 1000hPa geopotential forecast fields are used for daily Weather Scenariosweather scenarios.   The area considered covers Europe and its immediate surroundings including the northeast Atlantic.

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The root mean square (RMS) of all solutions of the ensemble members within this area is used as the norm. 

Clustering is performed over four predefined lead-time windows: forecasts for

• 3-4 days ahead

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• 5-7 days ahead

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• 8-10 days ahead

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• 11-15 days ahead.

  Clustering in this way, rather than on individual forecast days, has the advantage that temporal continuity and synoptic consistency are more likely to be retained.   The clustering is flow-dependent and is not based on pre-defined regimes.  Since all members are regarded as equally likely, the number of members in each cluster could define its probability.

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A cluster is represented not by the mean of its members but by its most representative member (MRM or cluster scenario).  This is selected by a pattern-matching algorithm minimising root mean square differences between the cluster’’s ““centre of gravity”” and each member.  The MRM most representative member is chosen to symbolize the cluster, but .  But it should not be used as a deterministic forecast,  nor nor should it be seen as a substitute for the cluster average (cluster averages are not currently available as web charts but are available for download from MARS).

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 Fig8.1.3.2: The most representative 500hPa members selected to describe the clustering of the forecast DT 00UTC 12 March 2017  2017, T+120 to T+168 hours.   Here  Here there are 3 clusters (one per row).  The most representative member or cluster scenario is the member of the cluster which has the minimum difference from the RMS of the cluster members.  On 500hPa cluster scenario charts, shading denotes the 500mb height anomaly, that is difference between the instantaneous 500mb height field for that member (i.e. as is contoured) and the long term climatological average 500mb height field for that time of year.

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The web site includes cluster products equivalent to Fig8.1.3.2 for each of the four predefined lead-time windows.  For additional information, the 1000 hPa 1000hPa geopotential fields are also provided for each ENS ensemble scenario to show the corresponding near-surface evolution.  Users should note that for these the clustering has been made on the 500hPa fields, not the 1000hPa fields.  Whilst the user should not treat the most representative members as deterministic solutions, it can nonetheless be helpful to examine the details of the evolution in such members, to see how a particular scenario can plausibly arise and evolve.  One good way to do this is to use the cyclone database products presented by the extratropical cyclone diagrams, specifically the animations, at 12 hour intervals, of synoptic patterns for individual members.

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Fig8.1.3.5: As Fig8.1.3.2 but referring to the forecast DT 00UTC 05 March 2017  2017, T+264 to T+360hr.  The colour of the frame surrounding each most representative member indicates the large scale climatological weather regimes to which it has been attributed.  On 500hPa plots such as these, shading denotes anomalies relative to climatology (as in Fig8.1.3.2).

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• BL leads to the least accuracy in the forecasts - from Day3 the blocking frequencies are systematically underestimated.
• AR also leads to reduced accuracy in the forecasts – tends to be too persistent and missing transitions to BL.
• Transitions to BL are not well predicted in general, and appear particularly difficult when initially the cross-Atlantic westerly jet is in the southern location (NAO-) or the northern location (AR).
• Persistence of BL tends to be underestimated.
• Maintenance and/or transitions to an enhanced zonal flow (NAO+) tends to be overestimated.
• The ensemble spread is a useful indicator of the forecast error,.
• -NAO has a higher skill than other types – The spread of the forecasts initiated in -NAO is significantly smaller than for the forecasts initiated in the other regimes.

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