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This product shows the 10-day evolution of three parameters: 850hPa temperature, 6h precipitation (up to the time shown) and 500hPa geopotential height for user-defined locations during the 10 days of the forecast.   Lines show the evolution of the medium range ensemble (dotted for each individual ensemble member, solid for CONTROL-10).  Shading (for temperature and height only) denotes the probability that the value of the variable will fall in a particular range (see panel titles) at a given time. 

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 Fig8.1.7.1:  A plume diagram for Ventnor Paris based on medium range ensemble run DT 00UTC 4 March 201712UTC 21 June 2023.  Shading denotes the probability that the value of the variable will fall in a particular range (see top panel legend) at a given time.  For 850hPa temperature, for example, the lightest green shading denotes that the probability is between 0.5% and 10% that the observed value will lie within a range of +/-0.5C of the y-axis value.  Probability of 500hPa heights is shown similarly using a blue shading.  The ensemble forecast indicates uncertainty between days 5 and 7 with ensemble members showing a fall in 850hPa and 500hPa heights at differing times. The CONTROL-10 shows a later change in these values.

In contrast to Meteograms, plumes can display bi-modal characteristics.  Large-scale bi-modality shows uncertainty in the ensemble evolution (e.g. part of the ensemble may favour a transition to blocking; the rest may  favour a zonal regime).  Local bi-modality reflects smaller scale location or timing uncertainties (e.g. a front or minor low is forecast by different members either upstream or downstream of a particular location, resulting in quite different local weather forecasts).  It is important to distinguish between these kinds of bi-modality.  Large-scale bi-modaility might for example be denoted by a bimodal 500mb height plume (perhaps accompanied by a bimodal 850mb temperature distribition).  Local front-related bimodality might be indicated by having at the same time a bi-modal 850mb temperature plume and a 500mb height plume that is not bi-modal.  Clustering products can also help in the detection of large-scale bi-modality.

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