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: int
Optional arguments¶
reload_results: (optional): False
Reload results from previous simulations
accepted type: bool
sequential: (optional): False
Compute control vector updates sequentially for each observation.
accepted type: bool
batch_sampling: (optional): False
Compute samples into a single observation operator or as separate jobs if False
accepted type: bool
moving_window: (optional)
Information about the moving windows.
- accepted structure:
fwd_step: (mandatory)
Length of each step forward between segments
accepted type: str
step_per_segment: (mandatory)
Number of forward step in each assimilation segment
accepted type: 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 # int
9
10 # Optional arguments
11 reload_results: XXXXX # bool
12 sequential: XXXXX # bool
13 batch_sampling: XXXXX # bool
14 moving_window:
15 fwd_step: XXXXX # str
16 step_per_segment: XXXXX # int
