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Task 1: Plot probabilities and percentiles of total precipitation

Probabilities

Enter the folder Probabilities in the openifs_2018 folder.

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The prob_tp_compare.mv icon will produce maps over France showing the probability that total 6-hourly precipitation exceeds a threshold expressed in mm, for both the 2012 and 2016 forecast ensembles.

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Run the macro and view the map.Use the cursor data icon Image Removed an

Percentiles

Task 1. Plot percentiles of total precipitation

To further compare the 2012 and 2016 ensemble forecasts, plots showing the percentile amount and probabilities above a threshold can be made for total precipitation.

Use these icons:

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Both these macros will use the 6-hourly total precipitation for forecast steps at 90, 96 and 102 hours, plotted over France.

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Location for CDF

Using the probability map, click the cursor data icon Image Added and move the pointer over the map for +96h and select a location in the region of highest rainfall. Do this for both the 2012 or 2016 ensemble map.

Make a note of the latitude and longitude coordinates. The highest rainfall area was over the Cévennes mountains, approximately 44°25′34″N 03°44′21″E.

Edit prob

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_tp_compare.mv

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and set the location:

#The percentile of ENS precipitation forecast
perc=75

Run the macro and compare the percentiles from both the forecasts.  Change the percentiles to see how the forecasts differ.

Task 2: Plot the CDF

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Right-click, select 'Edit' and then plot a CDF for Toulouse:

param="tp"
station="TOU"
expID="ens_oper"

Make sure useClusters='off'.

Do the same for the 2016 operational ensemble reforecast:

expID="ens_2016"

Compare the CDF from the different forecast ensembles.

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location=[44.0,4.1]   # [ lat, lon ] -- use your own values!

and replot the map. A small purple dot will appear at the location specified.

If the dot is not in the right location, change it and replot.

Probabilities

Using the plotted probability map for 10mm precipitation threshold, use the cursor data icon to read the probability at the chosen location for +96 hours. Make a note of this value.

Edit prob_tp_compare.mv, and change the threshold value to 20mm:

prob=20

Replot the map and make a note of the probability at your chosen location.

Finally change the threshold probability to 30mm and replot:

prob=30

At your chosen location, using the cursor data icon, make a note of the probability for the 30mm threshold values.

You should now have the probability values that total precipitation will exceed 10mm, 20mm and 30mm, for both the 2012 and 2016 ensembles, for forecast time +96 hours.

Task 2: Plot the CDF

Image Added

This exercise uses the cdf.mv icon.

Right-click, select 'Edit' and then plot a CDF for your location chosen in Task 1 for the 2012 ensemble forecast:

param="tp"
station=[44.0,4.0]   # use your own values!
expID="ens_oper"

Make sure useClusters='off'.

Do the same for the 2016 operational ensemble reforecast:

expID="ens_2016"

Compare the CDF from the different forecast ensembles.

Compare with probability map values

Using the CDF graph for the 2012 ensemble, read the probability that total precipitation will exceed 10mm. For example, see what percentile value, p,  is indicated on the y-axis for x=10mm. The probability that total precipitation exceeds this value is then 100-p.

The value read from the CDF graph in this way should agree with the value you obtained by reading the probability value from the map in Task 1.

Check your probabilities for 20mm and 30mm total precipitation.

Task 3. Plot percentiles of total precipitation

To further compare the 2012 and 2016 ensemble forecasts, plots showing the percentile amount and probabilities above a threshold can be made for total precipitation.

Use these icons:

Image Added

Both these macros will use the 6-hourly total precipitation for forecast steps at 90, 96 and 102 hours, plotted over France.

Edit the percentile_tp_compare.mv icon.

Set the percentile for the total precipitation to 75%:

#The percentile of ENS precipitation forecast
perc=75

Run the macro and compare the percentiles from both the forecasts.  Change the percentiles to see how the forecasts differ.

Exercise 5: Cluster analysis

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