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Two key differences between the 2016 and 2012 operational ensembles are: higher horizontal resolution, and coupling of NEMO ocean model to provide forecast fields of SST (sea-surface temperature) from the start of the forecast.
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Key parameters: MSLP and z500. We suggest concentrating on viewing these fields. If time, visualize other parameters (e.g. PV320K).
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TODO: Any macro that computes a difference to analyses needs to move to the last exercise on 'Forecast differences'. Any macro that uses analysis to plot could use HRES forecast instead?. |
Available plot types
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For these exercises please use the Metview icons in the row labelled 'ENS'. TODO: move ens_rmse.mv : this is similar to the hres_rmse.mv in the previous exercise. It will plot the root-mean-square-error growth for the ensemble forecasts.& stamp_diff.mv to folder Forecast Differences ens_to_an.mv : this will plot (a) the mean of the ensemble forecast, (b) the ensemble spread, (c) the HRES deterministic forecast and (d) the analysis for the same date. TODO: remove 'AN' from this & rename ens_mean_spread.mv ens_to_an_runs_spag.mv : this plots a 'spaghetti map' for a given parameter for the ensemble forecasts compared to the analysis. Another way of visualizing ensemble spread. TODO: remove 'AN' from this and replace with HRES & rename ens_spag.mv stamp.mv : this plots all of the ensemble forecasts for a particular field and lead time. Each forecast is shown in a stamp sized map. Very useful for a quick visual inspection of each ensemble forecast. stamp_diff.mv : similar to stamp.mv except that for each forecast it plots a difference map from the analysis. Very useful for quick visual inspection of the forecast differences of each ensemble forecast. TODO: remove 'AN'
Additional plots for further analysis:
pf_to_cf_diff.mv : this useful macro allows two individual ensemble forecasts to be compared to the control forecast. As well as plotting the forecasts from the members, it also shows a difference map for each. TODO: OK as is. Does not use AN. ens_to_an_diff.mv : this will plot the difference between the ensemble control, ensemble mean or an individual ensemble member and the analysis for a given parameter. TODO: move this to Forecast_differences folder. Make copy & rename to ens_to_hres_diff.mv and use HRES instead of AN. |
Group working
If working in groups, each group could follow the tasks below with a different ensemble forecast. e.g. one group uses the 'ens_oper', another group uses 'ens_2016' and so on.
Choose your ensemble dataset by setting the value of 'expId', either 'ens_oper' or 'ens_2016' for this exercise.
One of the OpenIFS ensembles could also be used but it's recommended one of the operational ensembles is studied first.
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#The experiment. Possible values are: # ens_oper = operational ENS # ens_2016 = 2016 operational ENS expId="ens_oper" |
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In these tasks, the performance of the ensemble forecast is studied.
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Q. How does the ensemble mean MSLP and Z500 fields compare to the HRES forecast and analysis? |
Task 1: Ensemble spread
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TODO: need to remove plotting the analysis from ens_to_an |
This task will explore the 'ensemble spread'.
and replace with HRES |
Use the ens_to_an.mv (rename as ens_mean_spread.mv) icon and plot the MSLP and z500. This will produce plots showing: the mean of of all the ensemble forecasts, the spread of the ensemble forecasts and the operational HRES deterministic forecast.
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#ENS members (use ["all"] or a list of members like [1,2,3] members=["all"] #[1,2,3,4,5] or ["all"] or ["cl.example.1"]"] |
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Q. Does the ensemble spread capture the error in the forecast? |
Task
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2: Spaghetti plots - another way to visualise spread
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TODO: remove analysis from the spaghetti plots, plot HRES instead & rename ens_spag.mv |
A "spaghetti" plot is where a single contour of a parameter is plotted for all ensemble members. It is another way of visualizing the differences between the ensemble members and focussing on features.
Use the ens_to_an_runs_spag.mv(rename ens_spag.mv & remove AN) icon. Plot and animate the MSLP and z500 fields using your suitable choice for the contour level. Find a value that highlights the low pressure centres. Note that not all members may reach the low pressure set by the contour.
The red contour line shows the control forecast of the ensemble.
Note that this macro this may animate slowly because of the computations required.
Experiment with changing the contour value and (if time) plotting other fields.
Task
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3: Visualise ensemble members
Stamp maps are used to visualise all the ensemble members as normal maps. These are small, stamp sized contour maps plotted for each ensemble member using a small set of contours.
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Make sure clustersId="off" for this task. Clustering will be used later.
Precipitation over France
Use stamp.mv and plot total precipitation ('tp') over France (mapType=2) for 00Z 24-09-2012 (compare with Figure 2 in Pantillon)..
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Q. How much uncertainty is there in the precipitation forecast over southern France? |
Compare ensemble members to
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the deterministic forecast
After visualizing the stamp maps, it can be useful to animate a comparison of individual ensemble members to the it can be useful to animate a comparison of individual ensemble members to the HRES deterministic forecast.
This can help in identifying individual ensemble members that produce a better forecast than the control or HRES forecastanalyses.
ens_to_an_diff.mv (rename ens_to_hres_diff.mv and replace 'an' with 'hres') and pf_to_cf_diff.mv can be used to compare ensemble members.
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TODO: move original ens_to_an_diff.mv to Forecast Difference folder. Make copy and use HRES instead of AN for the ensembles. |
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To animate the difference in MSLP of an individual ensemble member 30 to the analysis, edit the lines:
To compare the control forecast:
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Further analysis using ensembles
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This will show the forecasts from the ensemble members and also their difference with the ensemble control forecast. To animate the difference in MSLP with ensemble members '30' and '50', set:
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Sea-surface temperature
Compare the SST parameter used for the ens_oper and ens_2016 ensemble forecasts. The 2016 reforecast of this case study used a coupled ocean model unlike the 2012 ensemble and HRES forecast that used climatology for the first 5 days.
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Q. What is different about SST between the two ensemble forecasts? |
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To show a cross-section of a particular ensemble member, use the macro 'ens_xs.mv'. This works in the same way as the an_xs.mv and hres_xs.mv macros. |
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