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

ObsVect

False

True

standard

std

controlvect

ControlVect

True

True

standard

std

obsoperator

ObsOperator

True

True

standard

std

platform

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