spacepy.data_assimilation.ensemble¶
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class
spacepy.data_assimilation.
ensemble
(ensembles=50)[source]¶ Ensemble-based data assimilation subroutines for the Radiation Belt Model
EnKF
(A, Psi, Inn, HAp)analysis subroutine after code example in EnKF_oneobs
(A, Psi, Inn, HAp)analysis subroutine for a single observations add_model_error
(model, A, PSDdata)this routine will add a standard error to the ensemble states add_model_error_obs
(model, A, Lobs, y)this routine will add a standard error to the ensemble states getHA
(model, Lobs, A)compute HA provided L vector of observations getHAprime
(HA)calculate ensemble perturbation of HA getHPH
(Lobs, Pfxx)compute HPH getInnovation
(y, Psi, HA)compute innovation ensemble D’ getperturb
(model, y)compute perturbations of observational vector -
EnKF
(A, Psi, Inn, HAp)[source]¶ analysis subroutine after code example in Evensen 2003 this will take the prepared matrices and calculate the analysis most efficiently, A will be returned
Parameters: A :
Psi :
Inn :
HAp :
Returns: out :
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EnKF_oneobs
(A, Psi, Inn, HAp)[source]¶ analysis subroutine for a single observations with the EnKF. This is a special case.
Parameters: A :
Psi :
Inn :
HAp :
Returns: out :
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add_model_error
(model, A, PSDdata)[source]¶ this routine will add a standard error to the ensemble states
Parameters: model :
A :
PSDdata :
Returns: out :
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add_model_error_obs
(model, A, Lobs, y)[source]¶ this routine will add a standard error to the ensemble states
Parameters: model :
A :
Lobs :
y :
Returns: out :
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getHA
(model, Lobs, A)[source]¶ compute HA provided L vector of observations and ensemble matrix A
Parameters: model :
Lobs :
A :
Returns: out :
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getHAprime
(HA)[source]¶ calculate ensemble perturbation of HA HA’ = HA-HA_mean
Parameters: HA : Returns: out :
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