Proof of concept: EDA control perturb - #856
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…r_central_block(None))
+ self.jedi_rendering.add_key('saber_outer_block', self.config.saber_outer_block(None))
ens_mean_var read output from obs perturbed 3d-Var
{% for i in range( 1, models[model_component]['ensemble_num_members'] + 1 ) %}
{% for i in range(1, 5) %}
it is only 50% working
ensemble_block.py two_states.py state_ensemble.py IP.
- select minimal state variables / field_io_names - add `if state == ensemble` selection - correct typo filenames -> filename
…ding input/output dirnames in yaml
2. qd.window_length("PT6H"),
3. geos_atmosphere
background_time_offset:
default_value: PT9H
1. remove localensembleda from tier-1 test 2. disable localensembleda from code test
…ure/ygyu/superset_eda_Lanczos
- use dict to replace string i by j for jedi config dict
nnode=3, nx/ny=4/5; perhost=120
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Description
After:
this PR can be merged.
The ControlPert class from JEDI oops is used to execute EDA under the concept of incremental data simulation. As a proof of concept, this workflow framework is set up and named eda_controlpert_atmos.
Realistic runs with all observations, however, fail due to memory issues. I can only run a few conventional observations with the Control Pert method. Including IASI and other IR data will force NCCS nodes to reboot, so I have only included aircraft temperature and wind data in the eda_control_pert_tier_1_fast question default. We expect this issue be resolved in oops in the future.
To run EDA control pert, issue command:
The output data structure will contain files such as:
Note
I will continue to clean up the code, once #804 is merged.
Dependencies
Impact
Proof of concept only. Not for full observation runs.