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IntroductionThe 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, which controls 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 a observational field campaign. | Panel |
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| title | This case study is based on the following paper which is recommended reading |
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| 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 studyIn 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 principal component analysis (PCA) with clustering techniques (see Pantillon et al) to characterize the behaviour of the ensembles.
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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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Begin by entering the folder labelled 'Analysis':
Task
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TODO: - Etienne to send new animations that do not go beyond 20th.
- Original 'satellite' folder should go into the 'Forecast errors' folder?
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Open the folder 'satellite'.
This folder contains satellite images (water vapour, infra-red, false colour) for 00Z on 20-09-2012 and animations of the infra-red and water vapour images.
Double click the images to display them.
Task 2: Mean-sea-level pressure and track
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TODO: Fred/Etienne. This exercise needs more thought. I think the first two tasks are ok, look at the analyses and the difference to the HRES and ensembles with the RMSE curve. But then do we want the students to redo the RMSE with clustering on, look at stamp differences etc? |
Task 1: Satellite images
Image Added
Open the folder 'satellite'.
This folder contains satellite images (water vapour, infra-red, false colour) for 00Z on 20-09-2012 and animations of the infra-red and water vapour images.
Double click the images to display them and watch the observed behaviour of Nadine and the cut-off low.
Task 2: Analyses from 20th Sept.
The first task is to now look at the analyses from 20th Sept to observe what actually happened.
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Click the play button and animate the plot
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3: Compare forecast to analysis
Plot forecast difference maps to see how and when the forecast differed from the analyses.
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hres_to_an_diff.mv : this plots a single parameter as a difference map between the operational HRES forecast and the ECMWF analysis. Use this to understand the forecast errors. |
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Q. How does the behaviour of Nadine and the cut-off low differ from the HRES deterministic forecast?
Q. Did the ensemble spread represent the uncertainty between the analyses and the HRES forecast?
Q. Was HRES a good forecast for the HyMEX campaign? |
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4: Forecast error curve
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hres_rmse.mv : this plots the root-mean-square-error growth curves for the operational HRES forecast compared to the ECMWF analyses. |
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Q. What do the RMSE curves show?
Q. Why are the curves different between the two regions? |
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5: RMSE "plumes" for the ensemble
This is similar to the previous exercise, except the RMSE curves for all the ensemble members from a particular forecast will be plotted.
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Q. How do the HRES, ensemble control forecast and ensemble mean compare?
Q. How do the ensemble members behave, do they give better or worse forecasts?
Q. Is the spread in the RMSE curves the same in using other pressure levels in the atmosphere? |
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6: Difference stamp maps
Use the stamp_diff.mv plot to look at the differences between the ensemble members and the analysis. It can be easier to understand the difference in the ensembles by using difference stamp maps.
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