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In 2012, at the time of this case study, ECMWF operational forecasts consisted of:
- HRES : spectral T1279 (16km 18km grid) highest resolution 10 day deterministic forecast.
- ENS : spectral T639 (34km grid) resolution ensemble forecast (50 members) is run for days 1-10 of the forecast, T319 (70km) is run for days 11-15.
In 2016, the ECMWF operational forecasts has been was upgraded compared to 2012 and consisted of:
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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 metviewMetview, please try increasing the memory assigned to the VM.
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In this exercise, the development of Hurricane Nadine and the cut-off flow up to the 20th September 2012 is studied.
Begin by entering the folder labelled 'Analysis':
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This task will look at the synoptic development of Hurricane Nadine and the cutoff low up to 00Z, 20th September 2012. The forecasts in the next exercises start from this time and date.
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an_1x1.mv : this plots horizontal maps of parameters from the ECMWF analyses overlaid on one plot. an_2x2.mv : this plots horizontal maps of parameters from the ECMWF analyses four plots to a page (two by two). |
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The ECMWF operational deterministic forecast is called HRES. At the time of this case study, the model ran with a spectral resolution of T1279, equivalent to 16km 18km grid spacing.
Only a single forecast is run at this resolution as the computational resources required are demanding. The ensemble forecasts are run at a lower resolution.
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For this exercise, you will use the metview Metview icons in the folder ' hres_1x1.mv &
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Q. Look at the PV field, how do the vertical structures of Nadine and the cut-off low differ? |
Changing forecast time
Cross-section data is only available every 24hrs until the 30th Sept 00Z (step 240).
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fclen=5 |
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fclen=10 |
Changing cross-section location
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#Cross section line [ South, West, North, East ] line = [30,-29,45,-15] |
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If the forecast time is changed, the storm centres will move and the cross-section line will need to be repositioned to follow specific features. This is not computed automatically, but must be changed by altering the coordinates above. Use the cursor data icon 
to find the new position of the line.
Change the forecast time again to day+8 (28th Sept), or a different date if you are interested, relocate and plot the cross-section of Nadine and the low pressure system. Use the hres_1x1.mv icon from task 1 if you need to follow location of Nadine.
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Q. What changes are there to the vertical structure of Nadine during the forecast? |
Cyclone phase space (CPS) diagrams
An objectively defined cyclone phase space (CPS) is described using the storm-motion-relative thickness asymmetry (symmetric/non-frontal versus asymmetric/frontal) and vertical derivative of horizontal height gradient (cold- versus warm-core structure via the thermal wind relationship). A cyclone's life cycle can then be analyzed within this phase space, providing insight into the cyclone structural evolution.
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Additional plots for further study
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Q. What is different about SST between the two ensemble forecasts? |
Cross-sections of
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an ensemble member
To show a cross-section of a particular ensemble member, use the macro ens_xs.mv.
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If your cluster definition file is has another name, e.g. ens_oper_cluster.fred.txt, then members_1=["cl.fred.1"].
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A quantitative way of clustering an ensemble uses empirical orthogonal functions from the differences between the ensemble members and the control forecast and then using a an algorithm to determine the clusters from each ensemble as projected in EOF space (mathematically).
As a smooth dynamical field, geopotential height at 500hPa at 00 00Z 24/9/2012 is recommend (it used in the paper by Pantillon et al.), but the steps described below can be used for any parameter at any step.
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Q. What are the two scenarios proposed by the two clusters? |
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Task 4: Forecast error curve
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: this plots the root-mean-square-error growth curves for the operational HRES forecast compared to the ECMWF analyses.
In this task, we'll look at the difference between the forecast and the analysis by using "root-mean-square error" (RMSE) curves as a way of summarising the performance of the forecast.
Root-mean square error curves are a standard measure to determine forecast error compared to the analysis and several of the exercises will use them. The RMSE is computed by taking the square-root of the mean of the forecast difference between the HRES and analyses. RMSE of the 500hPa geopotential is a standard measure for assessing forecast model performance at ECMWF (for more information see: http://www.ecmwf.int/en/forecasts/quality-our-forecasts).
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Right-click the hres_rmse.mv icon, select 'Edit' and plot the RMSE curve for z500.
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Q. Using the stamp and stamp difference maps, study the ensemble. Identify which ensembles produce "better" forecasts. |
Appendix
Further reading
For more information on the stochastic physics scheme in IFS, see the article:
Shutts et al, 2011, ECMWF Newsletter 129.
Acknowledgements
We gratefully acknowledge the following for their contributions in preparing these exercises. From ECMWF: Glenn Carver, Gabriella Szepszo, Sandor Kertesz, Linus Magnusson, Iain Russell, Simon Lang, Filip Vana. From ENM/Meteo-France: Frédéric Ferry, Etienne Chabot, David Pollack and Thierry Barthet for IT support at ENM.
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