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Exercise 4: Computing the EOFs and clusters
TO BE DONE
Exercise 4. Exploring the role of uncertainty using OpenIFS forecasts
To further understand the impact of the different types of uncertainty (initial and model), some forecasts with OpenIFS have been made in which the uncertainty has been selectively disabled. These experiments use a 40 member ensemble and are at T319 resolution, lower than the operational ensemble.
As part of this exercise you may have run OpenIFS yourself in the class to generate another ensemble; one participant per ensemble member.
Recap
- EDA is the Ensemble Data Assimilation.
- SV is the use of Singular Vectors to perturb the initial conditions.
- SPPT is the stochastic physics parametrisation scheme.
- SKEB is the stochastic backscatter scheme applied to the model dynamics.
Experiments available:
- Experiment id: ens_both. EDA+SV+SPPT+SKEB : Includes initial data uncertainty (EDA, SV) and model uncertainty (SPPT, SKEB)
- Experiment id: ens_initial. EDA+SV only : Includes only initial data uncertainty
- Experiment id: ens_model. SPPT+SKEB only : Includes model uncertainty only
- Experiment id: ens_oifs. SPPT+SKEB only, class ensemble : this is the result of the previous task using the ensemble run by the class
These are at T319 with start dates: 24/25/26/27 Oct at 00UTC for a forecast length of 5 days with 3hrly output.
The aim of this exercise is to use the same visualisation and investigation as in the previous exercises to understand the impact the different types of uncertainty make on the forecast.
A key difference between this exercise and the previous one is that these forecasts have been run at a lower horizontal resolution. In the exercises below, it will be instructive to compare with the operational ensemble plots from the previous exercise.
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For this exercise, we suggest either each team focus on one of the above experiments and compare it with the operational ensemble. Or, each team member focus on one of the experiments and the team discuss and compare the experiments. |
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The different macros available for this exercise are very similar to those in previous exercises.
For this exercise, use the icons in the row labelled 'Experiments'. These work in a similar way to the previous exercises. ens_exps_rmse.mv : this will produce RMSE plumes for all the above experiments and the operational ensemble. ens_exps_to_an.mv : this produces 4 plots showing the ensemble spread from the OpenIFS experiments compared to the analysis. ens_exps_to_an_spag.mv : this will produce spaghetti maps for a particular parameter contour value compared to the analysis. ens_part_to_all.mv : this allows the spread & mean of a subset of the ensemble members to be compared to the whole ensemble. Note that the larger geographical area, mapType=1, will only work for MSLP due to data volume restrictions. |
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For these tasks the Metview icons in the row labelled 'ENS' can also be used to plot the different experiments (e.g. stamp plots). Please see the comments in those macros for more details of how to select the different OpenIFS experiments. Remember that you can make copies of the icons to keep your changes. |
Task 1. RMSE plumes
Use the ens_exps_rmse.mv icon and plot the RMSE curves for the different OpenIFS experiments.
Q. Compare the spread from the different experiments.
Q. The OpenIFS experiments were at a lower horizontal resolution. How does the RMSE spread compare between the 'ens_oper' and 'ens_both' experiments?
If time: change the 'run=' line to select a different forecast lead-time (run).
Task 2. Ensemble spread and spaghetti plots
Use the ens_exps_to_an.mv icon and plot the ensemble spread for the different OpenIFS experiments.
Also use the ens_exps_to_an_spag.mv icon to view the spaghetti plots for MSLP for the different OpenIFS experiments.
Q. What is the impact of reducing the resolution of the forecasts? (hint: compare the spaghetti plots of MSLP with those from the previous exercise).
Q. How does changing the representation of uncertainty affect the spread?
Q. Which of the experiments ens_initial and ens_model gives the better spread?
Q. Is it possible to determine whether initial uncertainty or model uncertainty is more or less important in the forecast error?
If time:
- use the ens_part_to_all.mv icon to compare a subset of the ensemble members to that of the whole ensemble. Use the stamp_map.mv icon to determine a set of ensemble members you wish to consider (note that the stamp_map icons can be used with these OpenIFS experiments. See the comments in the files).
Task 3. What initial perturbations are important
The objective of this task is to identify what areas of initial perturbation appeared to be important for an improved forecast in the ensemble.
Using the macros provided, find an ensemble member(s) that gave a consistently improved forecast and take the difference from the control. Step back to the beginning of the forecast and look to see where the difference originates from.
Use the large geographical area for this task. It is only possible to use the MSLP parameter for this task as it is the only one provided for the ensemble.
Task 4. Non-linear development
Ensemble perturbations are applied in positive and negative pairs. This is done to centre the perturbations about the control forecast.
So, for each computed perturbation, two perturbed initial fields are created e.g. ensemble members 1 & 2 are a pair, where number 1 is a positive difference compared to the control and 2 is a negative difference.
- Choose an odd & even ensemble pair (use the stamp plots). Use the appropriate icon to compute the difference of the members from the ensemble control forecast.
- Study the development of these differences using the MSLP and wind fields. If the error growth is linear the differences will be the same but of opposite sign. Non-linearity will result in different patterns in the difference maps.
- Repeat looking at one of the other forecasts. How does it vary between the different forecasts?
If time:
- Plot PV at 330K. What are the differences between the forecast? Upper tropospheric differences played a role in the development of this shallow fast moving cyclone.
Notes from Frederic: email 7/4/16
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