Ensemble Square-Root Filter (EnSRF
/ std
)¶
Description¶
Compute an Ensemble Square Root Filter (EnSRF) based on CTDAS implementation (Peters et al., 2005).
Yaml arguments¶
The following arguments are used to configure the plugin. pyCIF will return an exception at the initialization if mandatory arguments are not specified, or if any argument does not fit accepted values or type:
Mandatory arguments¶
nsample: (mandatory)
Number of random samples in the ensemble
accepted type: <class ‘int’>
Optional arguments¶
reload_results: (optional): False
Reload results from previous simulations
accepted type: <class ‘bool’>
batch_sampling: (optional): False
Compute samples into a single observation operator or as separate jobs
accepted type: <class ‘bool’>
moving_window: (optional)
Information about the moving windows.
- accepted structure:
fwd_step: (mandatory)
Length of each step forward between segments
accepted type: <class ‘str’>
step_per_segment: (mandatory)
Number of forward step in each assimilation segment
accepted type: <class ‘int’>
Requirements¶
The current plugin requires the present plugins to run properly:
Requirement name |
Requirement type |
Explicit definition |
Any valid |
Default name |
Default version |
---|---|---|---|---|---|
obsvect |
False |
True |
standard |
std |
|
controlvect |
True |
True |
standard |
std |
|
obsoperator |
True |
True |
standard |
std |
|
platform |
True |
True |
None |
None |
Yaml template¶
Please find below a template for a Yaml configuration:
1mode:
2 plugin:
3 name: EnSRF
4 version: std
5 type: mode
6
7 # Mandatory arguments
8 nsample: XXXXX
9
10 # Optional arguments
11 reload_results: XXXXX
12 batch_sampling: XXXXX
13 moving_window: XXXXX