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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-10HRES/Ensemble control).  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 Paris based on medium range ensemble run DT 12UTC 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 Higher probabilities are shown with darker shades.

The 850hPa temperature plume becomes wider beyond Sunday 25 June as the forecasts of ensemble members diverge.   Most ensemble members show a clear fall in temperature with darker shading.  A few, including HRES/Control, maintain higher temperatures rather longer.

The 500hPa height plume shows most ensemble members show heights remain above 578dam until Wednesday 28 June before becoming more uncertain later.  Note a few ensemble members fall below 570dam on Monday/Tuesday 26/27 June suggesting a possible though less likely passage of an upper trough.

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  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 bi-modal 500mb height plume (perhaps accompanied by a bimodal bi-modal 850mb temperature distribitiondistribution).  Local front-related bimodality bi-modality 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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 Fig8.1.7.2 Plume for 52°N 33°E (far NE Ukraine) DT 12UTC 23 May 2017A plume diagram for Cluj-Napoca, Romania  based on medium range ensemble run DT 00UTC 21 June 2023.  An example of trimodal tri-modal characteristics within a plume.  On Sunday 28 May the forecast Tuesday 21 June the ensemble forecasts of 850hPa temperature of ensemble members splits into three main branches which persist for about two days: one rising to 10°C17°C, the other with slightly more ensemble members falling to -3°C7°C, and another , which includes CONTROL-10, lying between.  The forecast 500hPa heights show a similar split with some showing a temporary significant dip in contour heights while others show minor rise.  Note also that on 31 May, CONTROL-10 30 June, HRES/CONTROL shows greater 500hPa geopotential height than almost any member of the ensemble.

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