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The ensemble spread is the standard deviation of the ENS members. We can compute it in a very similar way to the ensemble mean. The only difference is that this time you need to use the stdev() function instead of mean(). Now it is your task to write a Macro for it. Once you finished your Macro drag it into the bottom right map and customise it with the wgust_spread_shade Contouring icon and with a custom Text Plotting icon. You will see that the ensemble spread is fairly high in the investigated area.

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Now duplicate the ensemble mean Macro and edit it.   Find the line computing the mean and replace it with this code block:

f=f > 22	
f=100*mean(f)

The first line of our computations in the code above, performs a logical operation on the fieldset and results in a new fieldset. In this new fieldset we have only 1s and 0s:

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Once you finished your Macro drag it into the bottom right map and customise it with the prob_shade Contouring icon. Also use a custom Text Plotting icon to define the title. As for the probabilities, you should see that there is a reasonable some probability hinting for of high wind speeds.

Creating a stamp plot

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so that our map could show a larger (North Atlantic) area.

Next, define the contouring used for the "spaghetti"drop the cont_spag Contouring into the Macro. A code like this should be generated for you:

cont_spag = mcont(
	contour_label: "off",
	contour_level_selection_type	:	"level_list",
	contour_level_list	:	560,
	contour_line_colour: "blue",
	contour_highlight: "off"
 )

In this mcont() we turned contour labels off to keep the plot uncluttered and defined only a single contour value (560 gpm). 

The "spaghetti" will be generated by plotting each perturbed forecasts member as a separate layer into the same map. To achieve this goal we need to write a loop like this:

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