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Meteograms

Fig8.1.4-1: To view meteograms:

  1. On charts page, click ENS Meteograms.
  2. Select meteogram type from drop-down menu or display all ENSgrams by clicking on square icon.
  3. Select location by name or Lat/Long.


Fig8.1.4-2: Alternative way to view meteograms:

  1. On Forecast Charts and Data page, click on any Forecast Range.  A menu of available charts appears.
  2. Select Medium Range and Point Based Products.  A selection of products appears.
  3. Select the Meteograms display.
  4. Select meteogram type from drop-down menu or display all ENSgrams by clicking on square icon.
  5. Select location by name or Lat/Long.


View directly an example of the meteogram site.

Overview

The ensemble meteogram provides a probabilistic interpretation of the ENS for specific locations.  It displays the time evolution of the distribution of several meteorological parameters from the ensemble by a box and whisker plot.  All ENS meteograms have a title section, giving the name (unless overwritten by the user), the true height of the chosen location, and the co-ordinates of the grid point used based on the ENS resolution.   

The sub-section “Selection of grid points for Meteograms” explains the method of interpolation of grid point forecast data for presentation for a given location.

Box and Whisker Plot

Forecast distributions are displayed using a box and whisker plot (see Fig8.1.4-3) which shows the median (short horizontal line), the 25th and 75th percentiles (wide vertical box), 10th and 90th percentiles (narrower boxes) and the minimum and maximum values (vertical lines).

 Fig8.1.4-3: The box and whisker plot used in the ECMWF 10- and 15-day ensemble meteograms.

Ensemble meteograms are available for:

  • 10-day medium-range plot at 6hr intervals for:
    • weather (total cloud cover, 10m wind strength, 6hr rainfall total, 2m temperature).
    • waves (significant wave height, mean wave direction, mean wave period, and strength and distribution of direction of the 10m wind).  If no sea grid point nearby, only wind data is plotted from the nearest land grid point and the wave diagrams are empty. 
  • 15-day extended-range plot at 24hr intervals for:
    • weather only (mean total cloud cover, 24hr rainfall total, mean strength and distribution of direction of the 10m wind, max and min 2m temperature).
    • weather only (as above) but also showing M-climate.

Note:

  • The HRES forecast values are shown as a blue line on the 10-day ENS meteogram.   The medium range ensemble control (CTRL) is virtually identical to HRES and is not shown.
  • The 15-day ENS meteogram displays the probability distribution for each calendar day from 00UTC to 00UTC.  For forecasts with data time of 12UTC the first and last 12 hours in the forecast period are excluded and only 14 (instead of 15) daily distributions are generated. 

10-day ENS meteogram

Fig8.1.4-4: 10-day medium-range meteogram for Athens data time 00UTC 12 May 2017.  Solid blue lines are HRES/Control.  The red numbers above the precipitation panel are the greatest precipitation value reached by any ENS member.  ENS extreme values cannot be ignored as the evolution of every ENS member is considered to be equally probable.  Note: the forecast temperatures are at 00UTC, 06UTC, 12UTC, 18UTC each day (15-day meteograms show forecast maximum and minimum temperatures for each day).  UTC is used exclusively in the meteograms and maxima or minima will occur according to the longitude (or local time) of the location in question.

15-day ENS meteogram

Fig8.1.4-5: 15-day medium-range meteogram for Dublin from ENS data time 12UTC 22 June 2023.  The displayed values are for the 24hr period each day, with additionally the distribution of 10m wind direction. Note: the forecast maximum and minimum temperatures are shown for each day (10-day meteograms show forecast temperatures at 00UTC, 06UTC, 12UTC, 18UTC).

15-day ENS meteogram with M-climate

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.

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


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 ensemble meteogram it is the 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””.

    • An 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.

  • 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 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 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).

At longer lead times, the ensemble mean and the ensemble median will tend to gravitate asymptotically towards the M-climate.  This is most clearly seen when the first ten days of the forecast are anomalous (e.g. after an initial spell of cold and rainy weather, the ensemble tends to indicate a return to milder and drier conditions at longer forecast ranges).  This follows logically from the fact that at an infinite range, when predictive skill is completely lost, a climatological value constitutes the optimal forecast.

Interpreting Ensemble Meteograms

It is necessary to assess critically the parameters shown on ENS meteograms. 

  • 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. 


Coastal and mountainous regions

When creating a meteogram for a specific location, the land-sea mask at the four surrounding ENS grid points is considered.

  • If there is at least one land grid point within these four, then the nearest land point will be chosen and the meteogram title section shows "ENS Land Point" together with its location and ENS altitude.
  • If only sea points are available then the nearest sea grid point will be chosen and the meteogram title section shows "ENS Sea Point" together with its location and ENS altitude of 0m.

Data at the selected ENS point is calculated using HTESSEL and FLake according to the proportions of land and sea cover within the surrounding grid point box (see examples below, or the Land-Sea Mask section for details).

Some influences of the adjacent sea areas or mountains may be over- or under-represented by the ENS meteograms.  This can significantly affect the forecast parameter on the meteogram (temperature, wind, etc).    Users should assess differences in meteograms for coastal, island or mountainous regions.   In particular consider:

  • the impact of the grid point(s) relative to the land-sea mask.
  • the variation of the altitude of the land.   Forecast values at the grid point nearest to the location are adjusted for altitude using a standard lapse rate assumption.  The difference in temperature can be considerable.




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.   





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