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Fig8.1.4-6: As Fig8.1.4-5 with the addition of M-climate data.  M-climate data is shown by colours with percentiles similar to the box and whisker scheme.  The temperature box and whisker for 24 June lies confidently above the 99th percentile of the M-climate.  The median wind forecast for 30 June lies above the M-climate values (above the 75th percentile of the M-climate) with the whisker extending above the 99th percentile of the M-climate.  The median precipitation for the 25 June lies between the 50th and 75th percentile.

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Fig8.1.4-7: Illustration of the relationship between 10day ensemble presentation and 15day presentation (truncated to 10days for ease of comparison).

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Fig8.1.4-8: Illustration of the relationship between 10day ensemble presentation and 15day presentation (truncated to 10days for ease of comparison).

Weather Parameters in the Ensemble Meteograms

• Total cloud cover in the 10-day ensemble meteogram is the instantaneous forecast value in oktas (eighths of the sky covered by cloud).  In the 15-day extended day extended ensemble meteogram it is the daily average daily average of ENS forecast values at 06, 12, 18 and 24UTC.  When all members have 0 cloudiness (clear sky) or 8 oktas cloudiness (overcast), there is no line or box at all.  Note:
  • When the forecast is very uncertain and all cloud amounts are more or less equally likely, the columns cover almost the whole range from 0 to 8 oktas, which can be wrongly interpreted as ““overcast””““overcast””.
  • An
  alternative
  • alternative display (currently only available within the ecCharts meteogram platform) has a circle divided clockwise into eight arcs, each arc representing 1/8 cloud cover. So, for example, the arc covering 45°-90° represents 2/8 cloud cover. The shading within each arc is proportional to the number of members that forecast this particular degree of cloud cover or more.
  • See also interpretation of total cloud cover.

• Total precipitation in the 10-day ensemble meteogram is the accumulated precipitation (sum of convective and large-scale) over 6hr periods (00-06UTC, 06-12UTC, etc).  In the 15-day meteogram it is the accumulated precipitation over 24hr periods (00-24UTC).  Note:

  • On the 10-day meteogram the box-and-whisker plot locations align with the end of the 6 hour period.

  • Probabilities for intervals longer than the 6hr and 24hr time intervals cannot be deduced from the ensemble meteogram.

  • Periods of probabilities >0% in every interval can be wrongly interpreted as uninterrupted rain.

  • Consideration of the median alone can be wrongly interpreted as protracted dry spells.

  • The precipitation shown on the ensemble meteograms cannot be directly inter-compared as the rainfall range (y-axis) varies from one location to the next and from one forecast to the next.  The rainfall range is chosen separately for each ensemble meteogram so that 100% of the predicted values are covered for the 15-day ensemble meteograms, and at least 90% of the predicted values are covered for the 10-day ensemble meteograms (if the top of the distribution is beyond the scale maximum the largest 6-hourly total is shown at the top as red numbers).

• 10m wind speed in the 10-day ensemble meteogram is the instantaneous forecast value in min m/s.  Note this is the mean speed, not the diagnosed gust.  In the 15-day ensemble meteogram as it is the 24-hour wind-speed average of ENS forecast values at 06, 12, 18 and 24UTC.  Note:
  
  • The peaks of the whiskers should not be interpreted as wind gusts.  ENS products related to gusts should be used (e.g. CDF diagrams).
    
    
• 10m wind direction (only shown in the 15-day ensemble meteogram) is the daily distribution of directions of directions obtained by taking each 6-hourly forecast step for the day (50 members x 4 forecast steps at 06-12-18-24UTC) and allocating it to the relevant octant.  The area of an octant is proportional to the probability of that wind direction (i.e. to the proportion of forecasts falling in that octant).  The probability of each octant is shown by shading light (low) to dark (high).  Note:
  • The wind roses shown on the ensemble meteograms cannot be directly compared as each is scaled to the size of the most populated octant. The size of the wind rose does not refer to wind speed.
    
    
• 2m temperature  in the 10- day ensemble meteogram is shown as instantaneous forecast values at 6-hourly intervals.  In the 15-day ensemble meteogram it is shown as daily maximum and minimum temperatures (in °C).  Note:
  • The forecast temperature is adjusted by using a 6.5K/km lapse rate applied across the difference between the station height (as displayed in the title) and the ENS orography (the relative heights of ENS and true orography are shown in the top right corner of the meteogram web page.  In some instances, some information is also included in the temperature panel title of the meteogram itself).

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• Bias: Verification of previous forecasts, particularly recent forecasts within a similar meteorological regime, may allow an insight into the bias of the latest forecast. 
• Bi-modal distribution of forecast results:  Occasionally ENS forecasts diverge into a bi-modal (or possibly multi-modal) distribution in two (or more) distinct patterns.  This might happen if there were model uncertainty regarding timing or positioning of a cold front.  So for a given location a number of ENS members may show warm midday temperatures while others show much cooler temperatures.   Bi-modal distribution of forecast results will not be shown by meteograms.  Box-and whisker plots cannot do this - the effect would be just to stretch out the boxes.  However bimodal distributions can be apparent on plume diagrams.
• Snow/rain discrimination:  If a majority of ENS members forecast temperatures below 0°C and, at the same time, a large number of members forecast substantial precipitation, there is no way to determine the likelihood of snowfall from the standard meteogram diagram alone.  It could be that the precipitating members might all have temperatures well above 0°C.   The ecCharts meteogram product shows ENS probabilities of precipitation types by category.  Probability of combined events can only be calculated from the original ENS data.  Several charts of combined probabilities are available on ecCharts.
• Relative spread of forecast results:  This may vary considerably between one parameter and another in the same forecast step.  For example: 
  • In a high-pressure blocking event, there might be a small spread in precipitation and wind, but a large spread in temperature and cloudiness.
  • in a zonal regime, there might be a large spread in the precipitation and wind and a small spread in the temperature and cloudiness.
• Severe weather events:  The ENS can only predict severe weather events of the kind that the can resolved by the current resolution (~9km).   Forecaster experience and local knowledge should help identify the severity and persistence of smaller scale active storms. 

Interpretation of total cloud cover

The top row of the standard 10-day meteogram shows the ENS total cloud cover in box and whisker format.  High total cloud cover on this diagram can give an impression of gloomy or dull conditions whereas the cloud layers may not be uniformly thick or extensive.   A better idea of the structure of the model cloud layers may be obtained from meteograms of high, medium and low cloud cover.  These are available by selecting "views" then "meteogram windows" on ecCharts.  This allows assessment of the impact of each cloud layer, and in particular whether the full total cloud cover is made up from:

• large amounts of cloud at all levels implying dull overcast conditions.
• large amounts of cloud at one or two levels implying less gloomy conditions.
• large amounts of high cloud alone implying brighter conditions.  

However, users should also refer to the vertical profiles to decide the thickness of each layer.  Thin high cloud can allow quite bright skies while thick high cloud can give a very gloomy day.

A better forecast can be obtained by assessing the cloud forecast meteograms and charts a little more deeply.

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Fig8.1.4-9: Example of a frontal canopy moving eastwards over St Andrews, East Scotland.  DT 00UTC 15 Mar 2024, VT 12UTC 16 March 2024 (indicated by dashed red line).  The total cloud is 8/8 cover and an initial impression is for grey dull conditions.  The other meteograms show:

• little low cloud (mostly <2/8 cover, low probability 5/8 cover, mean amount near 0/8 cover).
• little medium cloud (mostly <1/8 cover, low probability 7/8 cover, mean amount near 0/8).
• most cover is at high levels (8/8 cover, low probability 1/8 cover, mean cover near 8/8).

The total cloud cover in the ensemble is mostly 8 oktas, the low and middle levels have small amounts of cloud.  However, the vertical profile strongly suggests thick upper cloud layers.  implying greyer skies which is reasonable ahead of an approaching front.

Therefore a brighter sky may be expected than by considering the total cloud cover alone.  However, the vertical profile strongly suggests thick upper cloud layers implying progressively greyer skies which is reasonable ahead of an approaching front.

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Fig8.1.4.10: Example of frontal canopy moving eastwards over Pamiers, South France.  DT 00UTC 15 Mar 2024, VT 12UTC 16 March 2024 (indicated by dashed red line).  The total cloud cover is high and an initial impression is for grey dull conditions.  The other meteograms show:

• no low cloud.
• no medium cloud.
• most cover is at high levels (8/8 cover, low probability 1/8 cover, mean cover near 8/8).

The total cloud cover in the ensemble is mostly 8 oktas, the low and middle levels have no cloud.  The vertical profile strongly suggests only thin upper cloud layers.  Therefore a much brighter sky may be expected than by considering the total cloud cover alone.

Coastal and mountainous regions

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Note: the so-called land-sea mask processing (where the land or sea nature of the source and target points was used to adjust the interpolation weights) used by the old ECMWF interpolation software scheme (called EMOSLIB) is not used by default in the new MIR interpolation package that was introduced early in 2019.