Available options for the different filter algorithms

There are different operations for each of the filter algorithms that need to be specified in the call to pdaf_init. To display the available options in a compiled assimilation program, one can use run with the specification subtype=-1. In this case pdaf_init wil display the available options for the selected filter algorithm and exit with an error status of -1.

Below we list the options as they are displayed using subtype=-1.

SEIK (filtertype=1)

PDAF     Available options for SEIK:
PDAF     --- Sub-types (Parameter subtype) ---
PDAF       0: full ensemble integration; left-sided application of T
PDAF       1: full ensemble integration; right-sided application of T
PDAF       2: Fixed error space basis
PDAF       3: Fixed state covariance matrix
PDAF       4: Implementation with explicit ensemble transformation
PDAF       5: Offline mode
PDAF     --- Integer parameters (Array param_int) ---
PDAF       param_int(1): Dimension of state vector (>0), required
PDAF       param_int(2): Ensemble size (>0), required
PDAF       param_int(3): not used
PDAF       param_int(4): Apply incremental updating; optional
PDAF           0: no incremental updating (default)
PDAF           1: apply incremental updating
PDAF       param_int(5): Type of forgetting factor; optional
PDAF           0: fixed forgetting factor (default)
PDAF           1: adaptive forgetting factor (experimental)
PDAF       param_int(6): Type of ensemble transformation matrix; optional
PDAF           0: deterministic omega (default)
PDAF           1: random orthonormal omega orthogonal to (1,...,1)^T
PDAF           2: use product of 0 with random orthonomal matrix with eigenvector (1,...,1)^T
PDAF              (experimental; for random transformations, 1 is recommended)
PDAF       param_int(7): Type of transformation matrix square root; optional
PDAF           (Only relevant for subtype/=3)
PDAF           0: symmetric square root (default)
PDAF           1: Cholesky decomposition
PDAF       param_int(8): Application of observation operator H, optional
PDAF           0: Apply H to ensemble mean to compute residual (default)
PDAF           1: Apply H to all ensemble states and then compute residual from mean of these
PDAF              param_int(8)=1 is the recomended choice for nonlinear H
PDAF     --- Floating point parameters (Array param_real) ---
PDAF       param_real(1): Forgetting factor (usually >0 and <=1), required
PDAF     --- Further parameters ---
PDAF       n_modeltasks: Number of parallel model integration tasks
PDAF           >=1 for subtypes 0 and 1; not larger than total number of processors
PDAF           =1 required for subtypes 2 and 3
PDAF       screen: Control verbosity of PDAF
PDAF           0: no outputs
PDAF           1: basic output (default)
PDAF           2: 1 plus timing output
PDAF           3: 2 plus debug output
PDAF     --- Internal parameter (defined inside PDAF) ---
PDAF       Nm1vsN: Normalization of covariance matrix; default: 1
PDAF           0: normalization with 1/(Ensemble size)
PDAF              (original SEIK, mainly for compatibility with older studies)
PDAF           1: normalization with 1/(Ensemble size - 1)
PDAF           (sample covariance matrix consistent with other EnKFs)
PDAF     +++++++++ End of option overview for the SEIK filter ++++++++++

EnKF (filtertype=2)

PDAF     Available options for EnKF:
PDAF     --- Sub-types (Parameter subtype) ---
PDAF       0: Full ensemble integration; analysis for 2*dim_obs>dim_ens
PDAF       1: Full ensemble integration; analysis for 2*dim_obs<=dim_ens
PDAF       5: Offline mode
PDAF     --- Integer parameters (Array param_int) ---
PDAF       param_int(1): Dimension of state vector (>0), required
PDAF       param_int(2): Ensemble size (>0), required
PDAF       param_int(3): maximum rank for inversion of HPH^T, optional, default=0
PDAF           (for =0, HPH is inverted by solving the representer equation)
PDAF           (if set to >=ensemble size, it is reset to ensemble size - 1)
PDAF       param_int(4): not used
PDAF       param_int(5): Size of smoothing lag (>=0), optional
PDAF           0: no smoothing (default)
PDAF           >0: apply smoother up to specified lag
PDAF     --- Floating point parameters (Array param_real) ---
PDAF       param_real(1): Forgetting factor (usually >0 and <=1), required
PDAF     --- Further parameters ---
PDAF       n_modeltasks: Number of parallel model integration tasks
PDAF           (>=1; not larger than total number of processors)
PDAF       screen: Control verbosity of PDAF
PDAF           0: no outputs
PDAF           1: basic output (default)
PDAF           2: 1 plus timing output
PDAF           3: 2 plus debug output
PDAF     +++++++++ End of option overview for the EnKF ++++++++++

LSEIK (filtertype=3)

PDAF     Available options for LSEIK:
PDAF     --- Sub-types (Parameter subtype) ---
PDAF       0: full ensemble integration; left-sided application of T
PDAF       2: Fixed error space basis
PDAF       3: Fixed state covariance matrix
PDAF       5: Offline mode
PDAF     --- Integer parameters (Array param_int) ---
PDAF       param_int(1): Dimension of state vector (>0), required
PDAF       param_int(2): Ensemble size (>0), required
PDAF       param_int(3): not used
PDAF       param_int(4): Apply incremental updating; optional
PDAF           0: no incremental updating (default)
PDAF           1: apply incremental updating
PDAF       param_int(5): Type of forgetting factor; optional
PDAF           0: fixed forgetting factor (default)
PDAF           1: adaptive forgetting factor for full domain (experimental)
PDAF           2: locally adaptive forgetting factor (experimental)
PDAF       param_int(6): Type of ensemble transformation matrix; optional
PDAF           0: deterministic omega (default)
PDAF           1: random orthonormal omega orthogonal to (1,...,1)^T
PDAF           2: use product of 0 with random orthonomal matrix with eigenvector (1,...,1)^T
PDAF              (experimental; for random transformations, 1 is recommended)
PDAF       param_int(7): Type of transformation matrix square root; optional
PDAF           (Only relevant for subtype/=3)
PDAF           0: symmetric square root (default)
PDAF           1: Cholesky decomposition
PDAF     --- Floating point parameters (Array param_real) ---
PDAF       param_real(1): Forgetting factor (usually >0 and <=1), required
PDAF     --- Further parameters ---
PDAF       n_modeltasks: Number of parallel model integration tasks
PDAF           >=1 for subtypes 0 and 1; not larger than total number of processors
PDAF           =1 required for subtypes 2 and 3
PDAF       screen: Control verbosity of PDAF
PDAF           0: no outputs
PDAF           1: basic output (default)
PDAF           2: 1 plus timing output
PDAF           3: 2 plus debug output
PDAF     --- Internal parameter (defined inside PDAF) ---
PDAF       Nm1vsN: Normalization of covariance matrix; default: 1
PDAF           0: normalization with 1/(Ensemble size)
PDAF              (original SEIK, mainly for compatibility with older studies)
PDAF           1: normalization with 1/(Ensemble size - 1)
PDAF              (sample covariance matrix consistent with other EnKFs)
PDAF     +++++++++ End of option overview for the LSEIK filter ++++++++++

ETKF (filtertype=4)

PDAF     Available options for ETKF:
PDAF     --- Sub-types (Parameter subtype) ---
PDAF       0: full ensemble integration; apply T-matrix analogously to SEIK
PDAF       1: full ensemble integration; formulation without T matrix
PDAF       2: Fixed error space basis; analysis with T-matrix
PDAF       3: Fixed state covariance matrix; analysis with T-matrix
PDAF       5: Offline mode; analysis with T-matrix
PDAF     --- Integer parameters (Array param_int) ---
PDAF       param_int(1): Dimension of state vector (>0), required
PDAF       param_int(2): Ensemble size (>0), required
PDAF       param_int(3): Size of smoothing lag (>=0), optional
PDAF           0: no smoothing (default)
PDAF           >0: apply smoother up to specified lag
PDAF       param_int(4): not used
PDAF       param_int(5): Type of forgetting factor; optional
PDAF           0: fixed forgetting factor (default)
PDAF           1: adaptive forgetting factor (experimental)
PDAF       param_int(6): Type of ensemble transformation matrix; optional
PDAF           0: deterministic transformation (default)
PDAF           2: use product of 0 with random orthonomal matrix with eigenvector (1,...,1)^T
PDAF       param_int(7): not used
PDAF       param_int(8): Application of observation operator H
PDAF           0: Apply H to ensemble mean to compute residual (default)
PDAF           1: Apply H to all ensemble states; then compute residual from mean of these
PDAF              param_int(8)=1 is the recomended choice for nonlinear H
PDAF     --- Floating point parameters (Array param_real) ---
PDAF       param_real(1): Forgetting factor (usually >0 and <=1), required
PDAF     --- Further parameters ---
PDAF       n_modeltasks: Number of parallel model integration tasks
PDAF           >=1 for subtypes 0 and 1; not larger than total number of processors
PDAF           =1 required for subtypes 2 and 3
PDAF       screen: Control verbosity of PDAF
PDAF           0: no outputs
PDAF           1: basic output (default)
PDAF           2: 1 plus timing output
PDAF           3: 2 plus debug output
PDAF     +++++++++ End of option overview for the ETKF ++++++++++

LETKF (filtertype=5)

PDAF     Available options for LETKF:
PDAF     --- Sub-types (Parameter subtype) ---
PDAF       0: full ensemble integration;  apply T-matrix analogously to SEIK
PDAF       2: Fixed error space basis; analysis with T-matrix
PDAF       3: Fixed state covariance matrix; analysis with T-matrix
PDAF       5: Offline mode; analysis with T-matrix
PDAF     --- Integer parameters (Array param_int) ---
PDAF       param_int(1): Dimension of state vector (>0), required
PDAF       param_int(2): Ensemble size (>0), required
PDAF       param_int(3): Size of smoothing lag (>=0), optional
PDAF           0: no smoothing (default)
PDAF           >0: apply smoother up to specified lag
PDAF       param_int(4): not used
PDAF       param_int(5): Type of forgetting factor; optional
PDAF           0: fixed forgetting factor (default)
PDAF           1: adaptive forgetting factor for full domain (experimental)
PDAF           2: locally adaptive forgetting factor (experimental)
PDAF       param_int(6): Type of ensemble transformation matrix; optional
PDAF           0: deterministic transformation (default)
PDAF           2: use product of 0 with random orthonomal matrix with eigenvector (1,...,1)^T
PDAF     --- Floating point parameters (Array param_real) ---
PDAF       param_real(1): Forgetting factor (usually >0 and <=1), required
PDAF     --- Further parameters ---
PDAF       n_modeltasks: Number of parallel model integration tasks
PDAF           >=1 for subtypes 0 and 1; not larger than total number of processors
PDAF           =1 required for subtypes 2 and 3
PDAF       screen: Control verbosity of PDAF
PDAF           0: no outputs
PDAF           1: basic output (default)
PDAF           2: 1 plus timing output
PDAF           3: 2 plus debug output
PDAF     +++++++++ End of option overview for the LETKF ++++++++++

ESTKF (filtertype=6)

PDAF     Available options for ESTKF:
PDAF     --- Sub-types (Parameter subtype) ---
PDAF       0: Standard implementation with ensemble integration
PDAF       2: Fixed error space basis
PDAF       3: Fixed state covariance matrix
PDAF       5: Offline mode
PDAF     --- Integer parameters (Array param_int) ---
PDAF       param_int(1): Dimension of state vector (>0), required
PDAF       param_int(2): Ensemble size (>0), required
PDAF       param_int(3): Size of smoothing lag (>=0), optional
PDAF           0: no smoothing (default)
PDAF           >0: apply smoother up to specified lag
PDAF       param_int(4): not used
PDAF       param_int(5): Type of forgetting factor; optional
PDAF           0: fixed forgetting factor (default)
PDAF           1: adaptive forgetting factor (experimental)
PDAF       param_int(6): Type of ensemble transformation matrix; optional
PDAF           0: deterministic omega (default)
PDAF           1: random orthonormal omega orthogonal to (1,...,1)^T
PDAF           2: use product of 0 with random orthonomal matrix with eigenvector (1,...,1)^T
PDAF              (experimental; for random transformations, 0 or 1 are recommended)
PDAF       param_int(7): Type of transformation matrix square root; optional
PDAF           0: symmetric square root (default)
PDAF           1: Cholesky decomposition
PDAF       param_int(8): Application of observation operator H
PDAF           0: Apply H to ensemble mean to compute residual (default)
PDAF           1: Apply H to all ensemble states; then compute residual from mean of these
PDAF              param_int(8)=1 is the recomended choice for nonlinear H
PDAF     --- Floating point parameters (Array param_real) ---
PDAF       param_real(1): Forgetting factor (usually >0 and <=1), required
PDAF     --- Further parameters ---
PDAF       n_modeltasks: Number of parallel model integration tasks
PDAF           >=1 for subtypes 0 and 1; not larger than total number of processors
PDAF           =1 required for subtypes 2 and 3
PDAF       screen: Control verbosity of PDAF
PDAF           0: no outputs
PDAF           1: basic output (default)
PDAF           2: 1 plus timing output
PDAF           3: 2 plus debug output
PDAF     +++++++++ End of option overview for the ESTKF  ++++++++++

LESTKF (filtertype=7)

PDAF     Available options for LESTKF:
PDAF     --- Sub-types (Parameter subtype) ---
PDAF       0: Standard implementation with ensemble integration
PDAF       2: Fixed error space basis
PDAF       3: Fixed state covariance matrix
PDAF       5: Offline mode
PDAF     --- Integer parameters (Array param_int) ---
PDAF       param_int(1): Dimension of state vector (>0), required
PDAF       param_int(2): Ensemble size (>0), required
PDAF       param_int(3): Size of smoothing lag (>=0), optional
PDAF           0: no smoothing (default)
PDAF           >0: apply smoother up to specified lag
PDAF       param_int(4): not used
PDAF       param_int(5): Type of forgetting factor; optional
PDAF           0: fixed forgetting factor (default)
PDAF           1: adaptive forgetting factor for full domain (experimental)
PDAF           2: locally adaptive forgetting factor (experimental)
PDAF       param_int(6): Type of ensemble transformation matrix; optional
PDAF           0: deterministic omega (default)
PDAF           1: random orthonormal omega orthogonal to (1,...,1)^T
PDAF           2: use product of 0 with random orthonomal matrix with eigenvector (1,...,1)^T
PDAF              (experimental; for random transformations, 1 is recommended)
PDAF       param_int(7): Type of transformation matrix square root; optional
PDAF           0: symmetric square root (default)
PDAF           1: Cholesky decomposition
PDAF     --- Floating point parameters (Array param_real) ---
PDAF       param_real(1): Forgetting factor (usually >0 and <=1), required
PDAF     --- Further parameters ---
PDAF       n_modeltasks: Number of parallel model integration tasks
PDAF           >=1 for subtypes 0 and 1; not larger than total number of processors
PDAF           =1 required for subtypes 2 and 3
PDAF       screen: Control verbosity of PDAF
PDAF           0: no outputs
PDAF           1: basic output (default)
PDAF           2: 1 plus timing output
PDAF           3: 2 plus debug output
PDAF     +++++++++ End of option overview for the LESTKF ++++++++++

LEnKF (filtertype=8)

PDAF     Available options for LEnKF:
PDAF     --- Sub-types (Parameter subtype) ---
PDAF       0: Full ensemble integration; analysis with covariance localization
PDAF       5: Offline mode
PDAF     --- Integer parameters (Array param_int) ---
PDAF       param_int(1): Dimension of state vector (>0), required
PDAF       param_int(2): Ensemble size (>0), required
PDAF       param_int(3): maximum rank for inversion of HPH^T, optional, default=0
PDAF           (for =0, HPH is inverted by solving the representer equation)
PDAF           (if set to >=ensemble size, it is reset to ensemble size - 1)
PDAF     --- Floating point parameters (Array param_real) ---
PDAF       param_real(1): Forgetting factor (usually >0 and <=1), required
PDAF     --- Further parameters ---
PDAF       n_modeltasks: Number of parallel model integration tasks
PDAF           (>=1; not larger than total number of processors)
PDAF       screen: Control verbosity of PDAF
PDAF           0: no outputs
PDAF           1: basic output (default)
PDAF           2: 1 plus timing output
PDAF           3: 2 plus debug output
PDAF     +++++++++ End of option overview for the LEnKF ++++++++++

NETF (filtertype=9)

PDAF     Available options for NETF:
PDAF     --- Sub-types (Parameter subtype) ---
PDAF       0: Standard implementation with ensemble integration
PDAF       5: Offline mode
PDAF     --- Integer parameters (Array param_int) ---
PDAF       param_int(1): Dimension of state vector (>0), required
PDAF       param_int(2): Ensemble size (>0), required
PDAF       param_int(3): Size of smoothing lag (>=0), optional
PDAF           0: no smoothing (default)
PDAF           >0: apply smoother up to specified lag
PDAF       param_int(4): Type of ensemble perturbations, optional
PDAF           0: no perturbations (default)
PDAF           1: constant standard deviation
PDAF           2: relative to ensemble standard deviation
PDAF       param_int(5): Type of forgetting factor; optional
PDAF           0: forgetting factor on forecast ensemble (default)
PDAF           2: forgetting factor on analysis ensemble
PDAF       param_int(6): Type of ensemble transformation matrix; optional
PDAF           0: random orthonormal matrix orthogonal to (1,...,1)^T (default)
PDAF           1: deterministic transformation
PDAF       param_int(7): Type of weights inflation; optional
PDAF           0: no weights inflation (default)
PDAF           1: inflate so that N_eff/N > param_real(2)
PDAF     --- Floating point parameters (Array param_real) ---
PDAF       param_real(1): Forgetting factor (usually >0 and <=1), required
PDAF       param_real(2): Limit for weigts inflation N_eff/N > param_real(2), optional, default=0.0
PDAF       param_real(3): Ensemble perturbation level (>0), required, only used if param_int(4)>0
PDAF     --- Further parameters ---
PDAF       n_modeltasks: Number of parallel model integration tasks
PDAF           >=1 for subtypes 0 and 1; not larger than total number of processors
PDAF           =1 required for subtypes 2 and 3
PDAF       screen: Control verbosity of PDAF
PDAF           0: no outputs
PDAF           1: basic output (default)
PDAF           2: 1 plus timing output
PDAF           3: 2 plus debug output
PDAF     +++++++++ End of option overview for the NETF  ++++++++++

LNETF (filtertype=10)

PDAF     Available options for LNETF:
PDAF     --- Sub-types (Parameter subtype) ---
PDAF       0: Standard implementation with ensemble integration
PDAF       5: Offline mode
PDAF     --- Integer parameters (Array param_int) ---
PDAF       param_int(1): Dimension of state vector (>0), required
PDAF       param_int(2): Ensemble size (>0), required
PDAF       param_int(3): Size of smoothing lag (>=0), optional
PDAF           0: no smoothing (default)
PDAF           >0: apply smoother up to specified lag
PDAF       param_int(4): Type of ensemble perturbations, optional
PDAF           0: no perturbations (default)
PDAF           1: constant standard deviation
PDAF           2: relative to ensemble standard deviation
PDAF       param_int(5): Type of forgetting factor; optional
PDAF           0: forgetting factor on forecast ensemble (default)
PDAF           1: forgetting factor on forecast ensemble only observed domains
PDAF           2: forgetting factor on analysis ensemble
PDAF           3: forgetting factor on analysis ensemble only observed domains
PDAF       param_int(6): Type of ensemble transformation matrix; optional
PDAF           0: random orthonormal matrix orthogonal to (1,...,1)^T (default)
PDAF           1: deterministic transformation
PDAF       param_int(7): Type of weights inflation; optional
PDAF           0: no weights inflation (default)
PDAF           1: inflate so that N_eff/N > param_real(2)
PDAF     --- Floating point parameters (Array param_real) ---
PDAF       param_real(1): Forgetting factor (usually >0 and <=1), required
PDAF       param_real(2): Limit for weigts inflation N_eff/N > param_real(2), optional, default=0.0
PDAF       param_real(3): Ensemble perturbation level (>0), required, only used if param_int(4)>0
PDAF     --- Further parameters ---
PDAF       n_modeltasks: Number of parallel model integration tasks
PDAF           >=1 for subtypes 0 and 1; not larger than total number of processors
PDAF           =1 required for subtypes 2 and 3
PDAF       screen: Control verbosity of PDAF
PDAF           0: no outputs
PDAF           1: basic output (default)
PDAF           2: 1 plus timing output
PDAF           3: 2 plus debug output
PDAF     +++++++++ End of option overview for the LNETF  ++++++++++

LKNETF (filtertype=11)

Note: The LKNETF (hybrid local Kalman-nonlinear ensemble transform filter) was added in PDAF V2.1.

PDAF     Available options for LKNETF:
PDAF     --- Sub-types (Parameter subtype) ---
PDAF       0: HNK: 2-step LKNETF with NETF before LETKF
PDAF       1: HKN: 2-step LKNETF with LETKF before NETF
PDAF       4: HSync: LKNETF synchronous
PDAF       5: Offline mode - HNK: 2-step LKNETF with NETF before LETKF
PDAF     --- Integer parameters (Array param_int) ---
PDAF       param_int(1): Dimension of state vector (>0), required
PDAF       param_int(2): Ensemble size (>0), required
PDAF       param_int(3): not used
PDAF       param_int(4): not used
PDAF       param_int(5): Type of forgetting factor; optional
PDAF           0: inflate forecast ensemble by 1/forget (default)
PDAF           1: inflate forecast ensemble by 1/forget only observed domains
PDAF           2: inflate analysis ensemble by 1/forget
PDAF           3: inflate analysis ensemble by 1/forget only observed domains
PDAF       param_int(6): Type of ensemble transformation matrix; optional
PDAF           0: random orthonormal matrix orthogonal to (1,...,1)^T (default)
PDAF           1: deterministic transformation
PDAF       param_int(7): Type of hybrid weight; optional
PDAF           0: fixed value
PDAF           1: gamma_lin: (1 - N_eff/N_e)*param_real(2) (default)
PDAF           2: gamma_alpha: hybrid weight from N_eff/N>=param_real(2)
PDAF           3: gamma_ska: 1 - min(s,k)/sqrt(param_real(3)) with N_eff/N>=param_real(2)
PDAF           4: gamma_sklin: 1 - min(s,k)/sqrt(param_real(3)) >= 1-N_eff/N>=param_real(2)
PDAF     --- Floating point parameters (Array param_real) ---
PDAF       param_real(1): Forgetting factor (usually >0 and <=1), required
PDAF       param_real(2): prescribed hybrid weight gamma (usually >0 and <=1), optional, default=1.0
PDAF       param_real(3): hybrid norm kappa (>0), optional, default=dim_ens
PDAF     --- Further parameters ---
PDAF       n_modeltasks: Number of parallel model integration tasks
PDAF           >=1 for subtypes 0 and 1; not larger than total number of processors
PDAF           =1 required for subtypes 2 and 3
PDAF       screen: Control verbosity of PDAF
PDAF           0: no outputs
PDAF           1: basic output (default)
PDAF           2: 1 plus timing output
PDAF           3: 2 plus debug output
PDAF     +++++++++ End of option overview for the LKNETF  ++++++++++

PF (filtertype=12)

PDAF     Available options for PF:
PDAF     --- Sub-types (Parameter subtype) ---
PDAF       0: Standard implementation with ensemble integration
PDAF       5: Offline mode
PDAF     --- Integer parameters (Array param_int) ---
PDAF       param_int(1): Dimension of state vector (>0), required
PDAF       param_int(2): Ensemble size (>0), required
PDAF       param_int(3): Resampling type, optional
PDAF           1: probabilistic resamping (default)
PDAF           2: stochastic universal resampling
PDAF           3: residual resampling
PDAF       param_int(4): Type of ensemble perturbations, optional
PDAF           0: no perturbations (default)
PDAF           1: constant standard deviation
PDAF           2: relative to ensemble standard deviation
PDAF       param_int(5): Type of forgetting factor; optional
PDAF           0: forgetting factor on forecast ensemble (default)
PDAF           2: forgetting factor on analysis ensemble
PDAF       param_int(6): Type of weights inflation; optional
PDAF           0: no weights inflation (default)
PDAF           1: inflate so that N_eff/N > param_real(2)
PDAF     --- Floating point parameters (Array param_real) ---
PDAF       param_real(1): Ensemble pert. level (>0), required, only used if param_int(4)>0
PDAF       param_real(2): Forgetting factor (usually >0 and <=1), optional, default=1.0
PDAF       param_real(3): Limit for weigts inflation N_eff/N > param_real(2), optional, default=0.0
PDAF     --- Further parameters ---
PDAF       n_modeltasks: Number of parallel model integration tasks
PDAF           >=1 for subtypes 0 and 1; not larger than total number of processors
PDAF           =1 required for subtypes 2 and 3
PDAF       screen: Control verbosity of PDAF
PDAF           0: no outputs
PDAF           1: basic output (default)
PDAF           2: 1 plus timing output
PDAF           3: 2 plus debug output
PDAF     +++++++++ End of option overview for the PF  ++++++++++

GENOBS (filtertype=100)

Note: GENOBS used filtertype=11 before PDAF V2.0.

PDAF     Available options for GENOBS:
PDAF     --- Sub-types (Parameter subtype) ---
PDAF       0: Standard implementation with ensemble integration
PDAF     --- Integer parameters (Array param_int) ---
PDAF       param_int(1): Dimension of state vector (>0), required
PDAF       param_int(2): Ensemble size (>0), required
PDAF     --- Floating point parameters (Array param_real) ---
PDAF       param_real(1): Forgetting factor (usually >0 and <=1), required, but not used
PDAF     --- Further parameters ---
PDAF       n_modeltasks: Number of parallel model integration tasks
PDAF           =1 for GENOBS; not larger than total number of processors
PDAF           =1 required for subtypes 2 and 3
PDAF       screen: Control verbosity of PDAF
PDAF           0: no outputs
PDAF           1: basic output (default)
PDAF           2: 1 plus timing output
PDAF           3: 2 plus debug output
PDAF     +++++++++ End of option overview for GENOBS  ++++++++++

3DVAR (filtertype=200)

Note: 3D-Var methods were added in PDAF V2.0.

PDAF     Available options for 3D-Var:
PDAF     --- Sub-types (Parameter subtype) ---
PDAF       0: incremental 3D-Var with parameterized covariance matrix
PDAF       1: 3D ensemble Var using LESTKF for ensemble transformation
PDAF       4: 3D ensemble Var using ESTKF for ensemble transformation
PDAF       5: Offline mode; analysis chosen by PDAF_put_state/PDAF_assimilate
PDAF       6: hybrid 3D-Var using LESTKF for ensemble transformation
PDAF       7: hybrid 3D-Var using ESTKF for ensemble transformation
PDAF     --- Integer parameters (Array param_int) ---
PDAF       param_int(1): Dimension of state vector (>0), required
PDAF       param_int(2): Ensemble size (>0), required
PDAF       param_int(3): Select optimization method (solver), required
PDAF           0: LBFGS (default)
PDAF           1: CG+
PDAF           2: direct implementation of CG
PDAF           3: direct implementation of CG with decomposed control vector
PDAF       param_int(4): size of parameterized control vector (for parameterized and hybrid 3D-Var), required
PDAF       param_int(5): size of ensemble control vector (required for ensemble and hybrid 3D-Var), 
PDAF       param_int(6): Solver-specific parameter, optional
PDAF           LBFGS: parameter m (default=5)
PDAF                Number of corrections used in limited memory matrix; 3<=m<=20
PDAF           CG+: parameter method (default=2)
PDAF                (1) Fletcher-Reeves, (2) Polak-Ribiere, (3) positive Polak-Ribiere
PDAF           CG: maximum number of iterations (default=200)
PDAF       param_int(7): Solver-specific parameter, optional
PDAF           CG+: parameter irest (default=1)
PDAF                (0) no restarts; (n>0) restart every n steps
PDAF     --- Floating point parameters (Array param_real) ---
PDAF       param_real(1): Forgetting factor (usually >0 and <=1), required;
PDAF           (only used for ensemble and hybrid 3D-Var)
PDAF       param_real(2): hybrid weight beta, optional (only for hybrid 3D-Var)
PDAF           range >=0.0 and <=1.0, =1.0 for pure ensemble 3D-var  (default=0.5)
PDAF       param_real(3): Solver-specific parameter, optional
PDAF           LBFGS: Limit for stopping iterations (pgtol, default=1.0e-5)
PDAF           CG+: convergence parameter eps (default=1.0e-5)
PDAF           CG: convergence parameter eps (default=1.0e-6)
PDAF       param_real(4): Solver-specific parameter, optional
PDAF           LBFGS: Tolerance in termination test (factr, default=1.0e+7)
PDAF     --- Further parameters ---
PDAF       n_modeltasks: Number of parallel model integration tasks
PDAF           >=1 for subtypes 0 and 1; not larger than total number of processors
PDAF           =1 required for subtypes 2 and 3
PDAF       screen: Control verbosity of PDAF
PDAF           0: no outputs
PDAF           1: basic output (default)
PDAF           2: 1 plus timing output
PDAF           3: 2 plus debug output
PDAF     +++++++++ End of option overview for 3DVAR ++++++++++

SEEK (filtertype=0)

PDAF     Available options for SEEK:
PDAF     --- Sub-types (Parameter subtype) ---
PDAF       0: Evolve unit modes with finite difference approx. of TLM
PDAF       1: like 0 with modes scaled by eigenvalues, unit U
PDAF       2: Fixed basis vectors; variable U matrix
PDAF       3: Fixed covariance matrix (V and U kept constant)
PDAF       5: Offline mode
PDAF     --- Integer parameters (Array param_int) ---
PDAF       param_int(1): Dimension of state vector (>0), required
PDAF       param_int(2): Ensemble size (>0), required
PDAF       param_int(3): Interval for re-diagonalization of P (>0); optional: default 1
PDAF       param_int(4): 1 for incremental updating, 0 else; optional: default 0
PDAF     --- Floating point parameters (Array param_real) ---
PDAF       param_real(1): Forgetting factor (usually >0 and <=1), required
PDAF       param_real(2): epsilon for finite-difference approx. of TLM, required
PDAF     --- Further parameters ---
PDAF       n_modeltasks: Number of parallel model integration tasks
PDAF           >=1 for subtypes 0 and 1; not larger than total number of processors
PDAF           =1 required for subtypes 2 and 3
PDAF       screen: Control verbosity of PDAF
PDAF           0: no outputs
PDAF           1: basic output (default)
PDAF           2: 1 plus timing output
PDAF           3: 2 plus debug output
PDAF     +++++++++ End of option overview for the SEEK filter ++++++++++