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Introduction

The ECMWF operational ensemble forecasts for the western Mediterranean region exhibited high uncertainty while Hurricane Nadine was slowly moving over the eastern N. Atlantic in Sept. 2012. Interaction with an Atlantic cut-off low produced a bifurcation in the ensemble and significant spread, influencing both the track of Hurricane Nadine and the synoptic conditions downstream.

The HyMEX (Hydrological cycle in Mediterranean eXperiment) field campaign was also underway and forecast uncertainty was a major issue for planning observations during the first special observations period of the campaign.

This interesting case study examines the forecasts in the context of the interaction between Nadine and the Atlantic cut-off low in the context of ensemble forecasting. It will explore the scientific rationale for using ensemble forecasts, why they are necessary and how they can be interpreted, particularly in a "real world" situation of forecasting for an observational field campaign.

 

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titleThis case study is based on the following paper which is recommended reading

Pantillon, F., Chaboureau, J.-P. and Richard, E. (2015), 'Vortex-vortex interaction between Hurricane Nadine and an Atlantic cutoff dropping the predictability over the Mediterranean,    http://onlinelibrary.wiley.com/doi/10.1002/qj.2635/abstract

In this case study

In the exercises for this interesting case study we will:

  • Study the development of Hurricane Nadine and the interaction with the Atlantic cut-off low using the ECMWF analyses.
  • Study the performance of the ECMWF high resolution (HRES) deterministic forecast of the time.
  • Use the operational ensemble forecast to look at the forecast spread and understand the uncertainty downstream of the interaction.
  • Compare a reforecast using the May/2016 ECMWF operational ensemble with the 2012 ensemble forecasts.
  • Use manual clustering to characterize the behaviour of the ensembles and compare the results with clustering based on principal component analysis (PCA) with clustering techniques (; see Pantillon et al) to characterize the behaviour of the ensembles.
  • Study the performance of the ECMWF ensemble forecasts trough RMSE curves.


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Note

If the plotting produces thick contour lines and large labels, ensure that the environment variable LC_NUMERIC="C" is set before starting metview.



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These exercises use a relatively large domain with high resolution data. Some of the plotting options can therefore require significant amounts of memory. If the virtual machine freezes when running Metview, please try increasing the memory assigned to the VM.

Starting up

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Metview

To begin:

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titleType the following command in a terminal window
metview &

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Info

Please enter the folder 'openifs_2019' to begin working.

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titleAdditional tasks


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titleSavin images and animations


Info

The macros described in this tutorial can write PostScript and GIF image files to the 'figures' directory in the 'openifs_2019' folder.

To save the images, use the 'Execute' menu option on the icon, rather than 'Visualise'. The 'okular' command can be used to view the PDF & gif images.

To save any other images during these exercises for discussion later, you can either use:

"Export" button in Metview's display window under the 'File' menu to save to PNG image format. This will also allow animations to be saved into postscript.

or use the ksnapshot command to take a 'snapshot' of the screen and save it to a file.

If you want to create animations from other images, save the figures as postscript and then use the convert command:

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convert -delay 75 -rotate "90<" in.ps out.gif




Exercise 1: Hurricane Nadine and the cut-off low

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titleChanging the map geographical area

Right-click on an_1x1.mv icon and select  'Edit'.

In the edit window that appears you can see the map types available covering a different area:

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titleChanging geographical area
#Map type: 0=Atl-an, 1: Atl-fc, 2: France 
mapType=0

With mapType=0 , the map covers a large area centred on the Atlantic suitable for plotting the analyses and track of the storm (this area is only available for the analyses).

With mapType=1 , the map also covers the Atlantic but a smaller area than for the analyses. This is because the forecast data in the following exercises does not cover as large a geographical area as the analyses.

With mapType=2 , the map covers a much smaller region centred over France.

Change, mapType=0   to   mapType=1   then click the play button at the top of the window.

Repeat using mapType=2 to see the smaller region over France.

These different regions will be used in the following exercises.

Animate the storm on this smaller geographical map.


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Wind fields, sea surface temperature (SST)
titleWind fields, sea surface temperature (SST)

The an_2x2.mv icon plots up to 4 separate figures on a single frame.

Right-click on the an_2x2.mv icon and select the 'Edit' menu item.

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titleMultiple plots per page
#Define plot list (min 1- max 4)
plot1=["mslp"]
plot2=["wind10"]
plot3=["speed500","z500"]
plot4=["sst"]

Click the play button at the top of the window to run this macro with the existing plots as shown above.

Each plot can be a single field or overlays of different fields.

Wind parameters can be shown either as arrows or as wind flags ('barbs') by adding '.flag' to the end of variable name e.g. "wind10.flag".

Info

Animating. If only one field on the 2x2 plot animates, make sure the menu item 'Animation -> Animate all scenes' is selected.

Plotting may be slow depending on the computer used. This reads a lot of data files.


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Q. What do you notice about the SST field?



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