Available options for the different filter algorithms
Contents of this page
- SEIK (filtertype=1)
- EnKF (filtertype=2)
- LSEIK (filtertype=3)
- ETKF (filtertype=4)
- LETKF (filtertype=5)
- ESTKF (filtertype=6)
- LESTKF (filtertype=7)
- LEnKF (filtertype=8)
- NETF (filtertype=9)
- LNETF (filtertype=10)
- LKNETF (filtertype=11)
- PF (filtertype=12)
- GENOBS (filtertype=100)
- 3DVAR (filtertype=200)
- SEEK (filtertype=0)
| This page documents the options for PDAF 2.3.1. See the page on available options in PDAF3 for the revised options in PDAF V3. |
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 --- 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 --- 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 --- 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 --- 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 --- 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 --- 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 --- 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 --- 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 --- 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 --- 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 --- 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 --- 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 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)
Note: The SEEK filter is deprecated and will be removed in a future release of PDAF.
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 --- 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 ++++++++++
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