Case description

In this exercise we will use Metview to explore the various ways ensemble forecasts can be processed and visualised. The case we will investigate is related to a low pressure system crossing the UK on 10 August 2014: it caused high winds and heavy rain especially in the South-Western part of the country.

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South/West/North/East: 43/-20/60/10

Set up a new Coastlines icon with the following:

• the land coloured in cream
• the coastlines thick black
• use grey grid lines at every 5 degrees.

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Our GRIB contains three time steps (78, 84 , and 90 and 96 hours, respectively) and we would like to compute the ensemble mean for each one separately. To achieve this goal we will write a loop going through the time steps. First, define the fieldset that will contain the results

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Create a new Macro and edit it. Drop your Geographical View and the Coastlines icons into the Macro editor. Once you've tidied up the code, define a 6x9 layout so that each plot should contain your view:

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title = mtext(text_line_1 : "PF: " & i)

Finish the loop by plotting Last, plot the field into the right map in our layout:

plot(dw[i],title,f,wgust_shade)

Having done so , run we have finished the code inside the loop. Now visualise your Macro (this will take a minute or so) and try to identify the ENS members predicting high wind speeds in our area.

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Create a new Macro and edit it. Drop your Geographical View and the Coastlines icons into the Macro editor and change the map area to

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Here we used the where statement inside the grib_info tag (as described here)  to make the title appear for one member (the 50th member) only.

We finish the loop by plotting Last, plot the field with our contour settings and title (inside the loop) :

plot(your_view,f,cont_spag,title) 

Having done so we have finished the code inside the loop. Now visualise your Macro (it will take half a minute or so) and animate through the steps to see how the spaghetti is spreading out over time.

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