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Choose your ensemble dataset by setting the value of 'expId', either 'ens_oper' or 'ens_2016' for this exercise.

One of the OpenIFS ensembles could also be used but it's recommended one of the operational ensembles is studied first.

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So far we have been looking at reducing the information in some way to visualise the ensemble.

To Stamp maps are used to visualise all the ensemble members as normal maps, we can use several visualisation methods, a popular way is to use stamp maps. These are small, stamp sized contour maps plotted for each ensemble member using a small set of contours.

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Code Block
languagebash
titleSet date/time to 24-09-2012 00Z
#Define forecast steps
steps=[2012-09-24 00:00,"to",2012-09-24 00:00,"by",6]

Make sure clustersId="off" for this task.

Precipitation over France

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Panel
titleUse pf_to_cf_diff.mv to compare two ensemble members to the control forecast

This will show the forecasts from the ensemble members and also their difference with the ensemble control forecast.

To animate the difference in MSLP with ensemble members '30' and '50', set:

Code Block
param="mslp"
pf=[30,50]
Panel
titleCross-sections of ensemble members

To show a cross-section of a particular ensemble member, use the macro 'ens_xs.mv'.

This works in the same way as the an_xs.mv and hres_xs.mv macros.

Panel

Find ensemble members that appear to produce a better forecast and look to see how the initial development in these members differs.

  • Select 'better' forecasts using the stamp plots and use ens_to_an.mv to modify the list of ensembles plots. Can you tell which area is more sensitive for the forecast?
  • Use pf_to_cf_diff and ens_to_an_diff to take the difference between these perturbed ensemble member forecasts from the control and analyses to also look at this.

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