Changes between Initial Version and Version 1 of AvailableOptionsforInitPDAFuntilPDAF231


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Timestamp:
Mar 20, 2025, 7:12:09 PM (13 days ago)
Author:
lnerger
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  • AvailableOptionsforInitPDAFuntilPDAF231

    v1 v1  
     1= Available options for the different filter algorithms =
     2
     3
     4[[PageOutline(2-3,Contents of this page)]]
     5
     6There 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.
     7
     8Below we list the options as they are displayed using `subtype=-1`.
     9
     10
     11== SEIK (filtertype=1) ==
     12
     13{{{
     14PDAF     Available options for SEIK:
     15PDAF     --- Sub-types (Parameter subtype) ---
     16PDAF       0: full ensemble integration; left-sided application of T
     17PDAF       1: full ensemble integration; right-sided application of T
     18PDAF       2: Fixed error space basis
     19PDAF       3: Fixed state covariance matrix
     20PDAF       4: Implementation with explicit ensemble transformation
     21PDAF     --- Integer parameters (Array param_int) ---
     22PDAF       param_int(1): Dimension of state vector (>0), required
     23PDAF       param_int(2): Ensemble size (>0), required
     24PDAF       param_int(3): not used
     25PDAF       param_int(4): Apply incremental updating; optional
     26PDAF           0: no incremental updating (default)
     27PDAF           1: apply incremental updating
     28PDAF       param_int(5): Type of forgetting factor; optional
     29PDAF           0: fixed forgetting factor (default)
     30PDAF           1: adaptive forgetting factor (experimental)
     31PDAF       param_int(6): Type of ensemble transformation matrix; optional
     32PDAF           0: deterministic omega (default)
     33PDAF           1: random orthonormal omega orthogonal to (1,...,1)^T
     34PDAF           2: use product of 0 with random orthonomal matrix with eigenvector (1,...,1)^T
     35PDAF              (experimental; for random transformations, 1 is recommended)
     36PDAF       param_int(7): Type of transformation matrix square root; optional
     37PDAF           (Only relevant for subtype/=3)
     38PDAF           0: symmetric square root (default)
     39PDAF           1: Cholesky decomposition
     40PDAF       param_int(8): Application of observation operator H, optional
     41PDAF           0: Apply H to ensemble mean to compute residual (default)
     42PDAF           1: Apply H to all ensemble states and then compute residual from mean of these
     43PDAF              param_int(8)=1 is the recomended choice for nonlinear H
     44PDAF     --- Floating point parameters (Array param_real) ---
     45PDAF       param_real(1): Forgetting factor (usually >0 and <=1), required
     46PDAF     --- Further parameters ---
     47PDAF       n_modeltasks: Number of parallel model integration tasks
     48PDAF           >=1 for subtypes 0 and 1; not larger than total number of processors
     49PDAF           =1 required for subtypes 2 and 3
     50PDAF       screen: Control verbosity of PDAF
     51PDAF           0: no outputs
     52PDAF           1: basic output (default)
     53PDAF           2: 1 plus timing output
     54PDAF           3: 2 plus debug output
     55PDAF     --- Internal parameter (defined inside PDAF) ---
     56PDAF       Nm1vsN: Normalization of covariance matrix; default: 1
     57PDAF           0: normalization with 1/(Ensemble size)
     58PDAF              (original SEIK, mainly for compatibility with older studies)
     59PDAF           1: normalization with 1/(Ensemble size - 1)
     60PDAF           (sample covariance matrix consistent with other EnKFs)
     61PDAF     +++++++++ End of option overview for the SEIK filter ++++++++++
     62}}}
     63
     64
     65== EnKF (filtertype=2) ==
     66
     67{{{
     68PDAF     Available options for EnKF:
     69PDAF     --- Sub-types (Parameter subtype) ---
     70PDAF       0: Full ensemble integration; analysis for 2*dim_obs>dim_ens
     71PDAF       1: Full ensemble integration; analysis for 2*dim_obs<=dim_ens
     72PDAF     --- Integer parameters (Array param_int) ---
     73PDAF       param_int(1): Dimension of state vector (>0), required
     74PDAF       param_int(2): Ensemble size (>0), required
     75PDAF       param_int(3): maximum rank for inversion of HPH^T, optional, default=0
     76PDAF           (for =0, HPH is inverted by solving the representer equation)
     77PDAF           (if set to >=ensemble size, it is reset to ensemble size - 1)
     78PDAF       param_int(4): not used
     79PDAF       param_int(5): Size of smoothing lag (>=0), optional
     80PDAF           0: no smoothing (default)
     81PDAF           >0: apply smoother up to specified lag
     82PDAF     --- Floating point parameters (Array param_real) ---
     83PDAF       param_real(1): Forgetting factor (usually >0 and <=1), required
     84PDAF     --- Further parameters ---
     85PDAF       n_modeltasks: Number of parallel model integration tasks
     86PDAF           (>=1; not larger than total number of processors)
     87PDAF       screen: Control verbosity of PDAF
     88PDAF           0: no outputs
     89PDAF           1: basic output (default)
     90PDAF           2: 1 plus timing output
     91PDAF           3: 2 plus debug output
     92PDAF     +++++++++ End of option overview for the EnKF ++++++++++
     93}}}
     94
     95
     96== LSEIK (filtertype=3) ==
     97
     98{{{
     99PDAF     Available options for LSEIK:
     100PDAF     --- Sub-types (Parameter subtype) ---
     101PDAF       0: full ensemble integration; left-sided application of T
     102PDAF       2: Fixed error space basis
     103PDAF       3: Fixed state covariance matrix
     104PDAF     --- Integer parameters (Array param_int) ---
     105PDAF       param_int(1): Dimension of state vector (>0), required
     106PDAF       param_int(2): Ensemble size (>0), required
     107PDAF       param_int(3): not used
     108PDAF       param_int(4): Apply incremental updating; optional
     109PDAF           0: no incremental updating (default)
     110PDAF           1: apply incremental updating
     111PDAF       param_int(5): Type of forgetting factor; optional
     112PDAF           0: fixed forgetting factor (default)
     113PDAF           1: adaptive forgetting factor for full domain (experimental)
     114PDAF           2: locally adaptive forgetting factor (experimental)
     115PDAF       param_int(6): Type of ensemble transformation matrix; optional
     116PDAF           0: deterministic omega (default)
     117PDAF           1: random orthonormal omega orthogonal to (1,...,1)^T
     118PDAF           2: use product of 0 with random orthonomal matrix with eigenvector (1,...,1)^T
     119PDAF              (experimental; for random transformations, 1 is recommended)
     120PDAF       param_int(7): Type of transformation matrix square root; optional
     121PDAF           (Only relevant for subtype/=3)
     122PDAF           0: symmetric square root (default)
     123PDAF           1: Cholesky decomposition
     124PDAF     --- Floating point parameters (Array param_real) ---
     125PDAF       param_real(1): Forgetting factor (usually >0 and <=1), required
     126PDAF     --- Further parameters ---
     127PDAF       n_modeltasks: Number of parallel model integration tasks
     128PDAF           >=1 for subtypes 0 and 1; not larger than total number of processors
     129PDAF           =1 required for subtypes 2 and 3
     130PDAF       screen: Control verbosity of PDAF
     131PDAF           0: no outputs
     132PDAF           1: basic output (default)
     133PDAF           2: 1 plus timing output
     134PDAF           3: 2 plus debug output
     135PDAF     --- Internal parameter (defined inside PDAF) ---
     136PDAF       Nm1vsN: Normalization of covariance matrix; default: 1
     137PDAF           0: normalization with 1/(Ensemble size)
     138PDAF              (original SEIK, mainly for compatibility with older studies)
     139PDAF           1: normalization with 1/(Ensemble size - 1)
     140PDAF              (sample covariance matrix consistent with other EnKFs)
     141PDAF     +++++++++ End of option overview for the LSEIK filter ++++++++++
     142}}}
     143
     144
     145== ETKF (filtertype=4) ==
     146
     147{{{
     148PDAF     Available options for ETKF:
     149PDAF     --- Sub-types (Parameter subtype) ---
     150PDAF       0: full ensemble integration; apply T-matrix analogously to SEIK
     151PDAF       1: full ensemble integration; formulation without T matrix
     152PDAF       2: Fixed error space basis; analysis with T-matrix
     153PDAF       3: Fixed state covariance matrix; analysis with T-matrix
     154PDAF     --- Integer parameters (Array param_int) ---
     155PDAF       param_int(1): Dimension of state vector (>0), required
     156PDAF       param_int(2): Ensemble size (>0), required
     157PDAF       param_int(3): Size of smoothing lag (>=0), optional
     158PDAF           0: no smoothing (default)
     159PDAF           >0: apply smoother up to specified lag
     160PDAF       param_int(4): not used
     161PDAF       param_int(5): Type of forgetting factor; optional
     162PDAF           0: fixed forgetting factor (default)
     163PDAF           1: adaptive forgetting factor (experimental)
     164PDAF       param_int(6): Type of ensemble transformation matrix; optional
     165PDAF           0: deterministic transformation (default)
     166PDAF           2: use product of 0 with random orthonomal matrix with eigenvector (1,...,1)^T
     167PDAF       param_int(7): not used
     168PDAF       param_int(8): Application of observation operator H
     169PDAF           0: Apply H to ensemble mean to compute residual (default)
     170PDAF           1: Apply H to all ensemble states; then compute residual from mean of these
     171PDAF              param_int(8)=1 is the recomended choice for nonlinear H
     172PDAF     --- Floating point parameters (Array param_real) ---
     173PDAF       param_real(1): Forgetting factor (usually >0 and <=1), required
     174PDAF     --- Further parameters ---
     175PDAF       n_modeltasks: Number of parallel model integration tasks
     176PDAF           >=1 for subtypes 0 and 1; not larger than total number of processors
     177PDAF           =1 required for subtypes 2 and 3
     178PDAF       screen: Control verbosity of PDAF
     179PDAF           0: no outputs
     180PDAF           1: basic output (default)
     181PDAF           2: 1 plus timing output
     182PDAF           3: 2 plus debug output
     183PDAF     +++++++++ End of option overview for the ETKF ++++++++++
     184}}}
     185
     186
     187== LETKF (filtertype=5) ==
     188
     189{{{
     190PDAF     Available options for LETKF:
     191PDAF     --- Sub-types (Parameter subtype) ---
     192PDAF       0: full ensemble integration;  apply T-matrix analogously to SEIK
     193PDAF       2: Fixed error space basis; analysis with T-matrix
     194PDAF       3: Fixed state covariance matrix; analysis with T-matrix
     195PDAF     --- Integer parameters (Array param_int) ---
     196PDAF       param_int(1): Dimension of state vector (>0), required
     197PDAF       param_int(2): Ensemble size (>0), required
     198PDAF       param_int(3): Size of smoothing lag (>=0), optional
     199PDAF           0: no smoothing (default)
     200PDAF           >0: apply smoother up to specified lag
     201PDAF       param_int(4): not used
     202PDAF       param_int(5): Type of forgetting factor; optional
     203PDAF           0: fixed forgetting factor (default)
     204PDAF           1: adaptive forgetting factor for full domain (experimental)
     205PDAF           2: locally adaptive forgetting factor (experimental)
     206PDAF       param_int(6): Type of ensemble transformation matrix; optional
     207PDAF           0: deterministic transformation (default)
     208PDAF           2: use product of 0 with random orthonomal matrix with eigenvector (1,...,1)^T
     209PDAF     --- Floating point parameters (Array param_real) ---
     210PDAF       param_real(1): Forgetting factor (usually >0 and <=1), required
     211PDAF     --- Further parameters ---
     212PDAF       n_modeltasks: Number of parallel model integration tasks
     213PDAF           >=1 for subtypes 0 and 1; not larger than total number of processors
     214PDAF           =1 required for subtypes 2 and 3
     215PDAF       screen: Control verbosity of PDAF
     216PDAF           0: no outputs
     217PDAF           1: basic output (default)
     218PDAF           2: 1 plus timing output
     219PDAF           3: 2 plus debug output
     220PDAF     +++++++++ End of option overview for the LETKF ++++++++++
     221}}}
     222
     223
     224== ESTKF (filtertype=6) ==
     225
     226{{{
     227PDAF     Available options for ESTKF:
     228PDAF     --- Sub-types (Parameter subtype) ---
     229PDAF       0: Standard implementation with ensemble integration
     230PDAF       2: Fixed error space basis
     231PDAF       3: Fixed state covariance matrix
     232PDAF     --- Integer parameters (Array param_int) ---
     233PDAF       param_int(1): Dimension of state vector (>0), required
     234PDAF       param_int(2): Ensemble size (>0), required
     235PDAF       param_int(3): Size of smoothing lag (>=0), optional
     236PDAF           0: no smoothing (default)
     237PDAF           >0: apply smoother up to specified lag
     238PDAF       param_int(4): not used
     239PDAF       param_int(5): Type of forgetting factor; optional
     240PDAF           0: fixed forgetting factor (default)
     241PDAF           1: adaptive forgetting factor (experimental)
     242PDAF       param_int(6): Type of ensemble transformation matrix; optional
     243PDAF           0: deterministic omega (default)
     244PDAF           1: random orthonormal omega orthogonal to (1,...,1)^T
     245PDAF           2: use product of 0 with random orthonomal matrix with eigenvector (1,...,1)^T
     246PDAF              (experimental; for random transformations, 0 or 1 are recommended)
     247PDAF       param_int(7): Type of transformation matrix square root; optional
     248PDAF           0: symmetric square root (default)
     249PDAF           1: Cholesky decomposition
     250PDAF       param_int(8): Application of observation operator H
     251PDAF           0: Apply H to ensemble mean to compute residual (default)
     252PDAF           1: Apply H to all ensemble states; then compute residual from mean of these
     253PDAF              param_int(8)=1 is the recomended choice for nonlinear H
     254PDAF     --- Floating point parameters (Array param_real) ---
     255PDAF       param_real(1): Forgetting factor (usually >0 and <=1), required
     256PDAF     --- Further parameters ---
     257PDAF       n_modeltasks: Number of parallel model integration tasks
     258PDAF           >=1 for subtypes 0 and 1; not larger than total number of processors
     259PDAF           =1 required for subtypes 2 and 3
     260PDAF       screen: Control verbosity of PDAF
     261PDAF           0: no outputs
     262PDAF           1: basic output (default)
     263PDAF           2: 1 plus timing output
     264PDAF           3: 2 plus debug output
     265PDAF     +++++++++ End of option overview for the ESTKF  ++++++++++
     266}}}
     267
     268
     269== LESTKF (filtertype=7) ==
     270
     271{{{
     272PDAF     Available options for LESTKF:
     273PDAF     --- Sub-types (Parameter subtype) ---
     274PDAF       0: Standard implementation with ensemble integration
     275PDAF       2: Fixed error space basis
     276PDAF       3: Fixed state covariance matrix
     277PDAF     --- Integer parameters (Array param_int) ---
     278PDAF       param_int(1): Dimension of state vector (>0), required
     279PDAF       param_int(2): Ensemble size (>0), required
     280PDAF       param_int(3): Size of smoothing lag (>=0), optional
     281PDAF           0: no smoothing (default)
     282PDAF           >0: apply smoother up to specified lag
     283PDAF       param_int(4): not used
     284PDAF       param_int(5): Type of forgetting factor; optional
     285PDAF           0: fixed forgetting factor (default)
     286PDAF           1: adaptive forgetting factor for full domain (experimental)
     287PDAF           2: locally adaptive forgetting factor (experimental)
     288PDAF       param_int(6): Type of ensemble transformation matrix; optional
     289PDAF           0: deterministic omega (default)
     290PDAF           1: random orthonormal omega orthogonal to (1,...,1)^T
     291PDAF           2: use product of 0 with random orthonomal matrix with eigenvector (1,...,1)^T
     292PDAF              (experimental; for random transformations, 1 is recommended)
     293PDAF       param_int(7): Type of transformation matrix square root; optional
     294PDAF           0: symmetric square root (default)
     295PDAF           1: Cholesky decomposition
     296PDAF     --- Floating point parameters (Array param_real) ---
     297PDAF       param_real(1): Forgetting factor (usually >0 and <=1), required
     298PDAF     --- Further parameters ---
     299PDAF       n_modeltasks: Number of parallel model integration tasks
     300PDAF           >=1 for subtypes 0 and 1; not larger than total number of processors
     301PDAF           =1 required for subtypes 2 and 3
     302PDAF       screen: Control verbosity of PDAF
     303PDAF           0: no outputs
     304PDAF           1: basic output (default)
     305PDAF           2: 1 plus timing output
     306PDAF           3: 2 plus debug output
     307PDAF     +++++++++ End of option overview for the LESTKF ++++++++++
     308}}}
     309
     310
     311== LEnKF (filtertype=8) ==
     312
     313{{{
     314PDAF     Available options for LEnKF:
     315PDAF     --- Sub-types (Parameter subtype) ---
     316PDAF       0: Full ensemble integration; analysis with covariance localization
     317PDAF     --- Integer parameters (Array param_int) ---
     318PDAF       param_int(1): Dimension of state vector (>0), required
     319PDAF       param_int(2): Ensemble size (>0), required
     320PDAF       param_int(3): maximum rank for inversion of HPH^T, optional, default=0
     321PDAF           (for =0, HPH is inverted by solving the representer equation)
     322PDAF           (if set to >=ensemble size, it is reset to ensemble size - 1)
     323PDAF     --- Floating point parameters (Array param_real) ---
     324PDAF       param_real(1): Forgetting factor (usually >0 and <=1), required
     325PDAF     --- Further parameters ---
     326PDAF       n_modeltasks: Number of parallel model integration tasks
     327PDAF           (>=1; not larger than total number of processors)
     328PDAF       screen: Control verbosity of PDAF
     329PDAF           0: no outputs
     330PDAF           1: basic output (default)
     331PDAF           2: 1 plus timing output
     332PDAF           3: 2 plus debug output
     333PDAF     +++++++++ End of option overview for the LEnKF ++++++++++
     334}}}
     335
     336
     337== NETF (filtertype=9) ==
     338
     339{{{
     340PDAF     Available options for NETF:
     341PDAF     --- Sub-types (Parameter subtype) ---
     342PDAF       0: Standard implementation with ensemble integration
     343PDAF     --- Integer parameters (Array param_int) ---
     344PDAF       param_int(1): Dimension of state vector (>0), required
     345PDAF       param_int(2): Ensemble size (>0), required
     346PDAF       param_int(3): Size of smoothing lag (>=0), optional
     347PDAF           0: no smoothing (default)
     348PDAF           >0: apply smoother up to specified lag
     349PDAF       param_int(4): Type of ensemble perturbations, optional
     350PDAF           0: no perturbations (default)
     351PDAF           1: constant standard deviation
     352PDAF           2: relative to ensemble standard deviation
     353PDAF       param_int(5): Type of forgetting factor; optional
     354PDAF           0: forgetting factor on forecast ensemble (default)
     355PDAF           2: forgetting factor on analysis ensemble
     356PDAF       param_int(6): Type of ensemble transformation matrix; optional
     357PDAF           0: random orthonormal matrix orthogonal to (1,...,1)^T (default)
     358PDAF           1: deterministic transformation
     359PDAF       param_int(7): Type of weights inflation; optional
     360PDAF           0: no weights inflation (default)
     361PDAF           1: inflate so that N_eff/N > param_real(2)
     362PDAF     --- Floating point parameters (Array param_real) ---
     363PDAF       param_real(1): Forgetting factor (usually >0 and <=1), required
     364PDAF       param_real(2): Limit for weigts inflation N_eff/N > param_real(2), optional, default=0.0
     365PDAF       param_real(3): Ensemble perturbation level (>0), required, only used if param_int(4)>0
     366PDAF     --- Further parameters ---
     367PDAF       n_modeltasks: Number of parallel model integration tasks
     368PDAF           >=1 for subtypes 0 and 1; not larger than total number of processors
     369PDAF           =1 required for subtypes 2 and 3
     370PDAF       screen: Control verbosity of PDAF
     371PDAF           0: no outputs
     372PDAF           1: basic output (default)
     373PDAF           2: 1 plus timing output
     374PDAF           3: 2 plus debug output
     375PDAF     +++++++++ End of option overview for the NETF  ++++++++++
     376}}}
     377
     378== LNETF (filtertype=10) ==
     379
     380{{{
     381PDAF     Available options for LNETF:
     382PDAF     --- Sub-types (Parameter subtype) ---
     383PDAF       0: Standard implementation with ensemble integration
     384PDAF     --- Integer parameters (Array param_int) ---
     385PDAF       param_int(1): Dimension of state vector (>0), required
     386PDAF       param_int(2): Ensemble size (>0), required
     387PDAF       param_int(3): Size of smoothing lag (>=0), optional
     388PDAF           0: no smoothing (default)
     389PDAF           >0: apply smoother up to specified lag
     390PDAF       param_int(4): Type of ensemble perturbations, optional
     391PDAF           0: no perturbations (default)
     392PDAF           1: constant standard deviation
     393PDAF           2: relative to ensemble standard deviation
     394PDAF       param_int(5): Type of forgetting factor; optional
     395PDAF           0: forgetting factor on forecast ensemble (default)
     396PDAF           1: forgetting factor on forecast ensemble only observed domains
     397PDAF           2: forgetting factor on analysis ensemble
     398PDAF           3: forgetting factor on analysis ensemble only observed domains
     399PDAF       param_int(6): Type of ensemble transformation matrix; optional
     400PDAF           0: random orthonormal matrix orthogonal to (1,...,1)^T (default)
     401PDAF           1: deterministic transformation
     402PDAF       param_int(7): Type of weights inflation; optional
     403PDAF           0: no weights inflation (default)
     404PDAF           1: inflate so that N_eff/N > param_real(2)
     405PDAF     --- Floating point parameters (Array param_real) ---
     406PDAF       param_real(1): Forgetting factor (usually >0 and <=1), required
     407PDAF       param_real(2): Limit for weigts inflation N_eff/N > param_real(2), optional, default=0.0
     408PDAF       param_real(3): Ensemble perturbation level (>0), required, only used if param_int(4)>0
     409PDAF     --- Further parameters ---
     410PDAF       n_modeltasks: Number of parallel model integration tasks
     411PDAF           >=1 for subtypes 0 and 1; not larger than total number of processors
     412PDAF           =1 required for subtypes 2 and 3
     413PDAF       screen: Control verbosity of PDAF
     414PDAF           0: no outputs
     415PDAF           1: basic output (default)
     416PDAF           2: 1 plus timing output
     417PDAF           3: 2 plus debug output
     418PDAF     +++++++++ End of option overview for the LNETF  ++++++++++
     419}}}
     420
     421
     422== LKNETF (filtertype=11) ==
     423
     424Note: The LKNETF (hybrid local Kalman-nonlinear ensemble transform filter) was added in PDAF V2.1.
     425
     426{{{
     427PDAF     Available options for LKNETF:
     428PDAF     --- Sub-types (Parameter subtype) ---
     429PDAF       0: HNK: 2-step LKNETF with NETF before LETKF
     430PDAF       1: HKN: 2-step LKNETF with LETKF before NETF
     431PDAF       4: HSync: LKNETF synchronous
     432PDAF     --- Integer parameters (Array param_int) ---
     433PDAF       param_int(1): Dimension of state vector (>0), required
     434PDAF       param_int(2): Ensemble size (>0), required
     435PDAF       param_int(3): not used
     436PDAF       param_int(4): not used
     437PDAF       param_int(5): Type of forgetting factor; optional
     438PDAF           0: inflate forecast ensemble by 1/forget (default)
     439PDAF           1: inflate forecast ensemble by 1/forget only observed domains
     440PDAF           2: inflate analysis ensemble by 1/forget
     441PDAF           3: inflate analysis ensemble by 1/forget only observed domains
     442PDAF       param_int(6): Type of ensemble transformation matrix; optional
     443PDAF           0: random orthonormal matrix orthogonal to (1,...,1)^T (default)
     444PDAF           1: deterministic transformation
     445PDAF       param_int(7): Type of hybrid weight; optional
     446PDAF           0: fixed value
     447PDAF           1: gamma_lin: (1 - N_eff/N_e)*param_real(2) (default)
     448PDAF           2: gamma_alpha: hybrid weight from N_eff/N>=param_real(2)
     449PDAF           3: gamma_ska: 1 - min(s,k)/sqrt(param_real(3)) with N_eff/N>=param_real(2)
     450PDAF           4: gamma_sklin: 1 - min(s,k)/sqrt(param_real(3)) >= 1-N_eff/N>=param_real(2)
     451PDAF     --- Floating point parameters (Array param_real) ---
     452PDAF       param_real(1): Forgetting factor (usually >0 and <=1), required
     453PDAF       param_real(2): prescribed hybrid weight gamma (usually >0 and <=1), optional, default=1.0
     454PDAF       param_real(3): hybrid norm kappa (>0), optional, default=dim_ens
     455PDAF     --- Further parameters ---
     456PDAF       n_modeltasks: Number of parallel model integration tasks
     457PDAF           >=1 for subtypes 0 and 1; not larger than total number of processors
     458PDAF           =1 required for subtypes 2 and 3
     459PDAF       screen: Control verbosity of PDAF
     460PDAF           0: no outputs
     461PDAF           1: basic output (default)
     462PDAF           2: 1 plus timing output
     463PDAF           3: 2 plus debug output
     464PDAF     +++++++++ End of option overview for the LKNETF  ++++++++++
     465}}}
     466
     467== PF (filtertype=12) ==
     468
     469{{{
     470PDAF     Available options for PF:
     471PDAF     --- Sub-types (Parameter subtype) ---
     472PDAF       0: Standard implementation with ensemble integration
     473PDAF     --- Integer parameters (Array param_int) ---
     474PDAF       param_int(1): Dimension of state vector (>0), required
     475PDAF       param_int(2): Ensemble size (>0), required
     476PDAF       param_int(3): Resampling type, optional
     477PDAF           1: probabilistic resamping (default)
     478PDAF           2: stochastic universal resampling
     479PDAF           3: residual resampling
     480PDAF       param_int(4): Type of ensemble perturbations, optional
     481PDAF           0: no perturbations (default)
     482PDAF           1: constant standard deviation
     483PDAF           2: relative to ensemble standard deviation
     484PDAF       param_int(5): Type of forgetting factor; optional
     485PDAF           0: forgetting factor on forecast ensemble (default)
     486PDAF           2: forgetting factor on analysis ensemble
     487PDAF       param_int(6): Type of weights inflation; optional
     488PDAF           0: no weights inflation (default)
     489PDAF           1: inflate so that N_eff/N > param_real(2)
     490PDAF     --- Floating point parameters (Array param_real) ---
     491PDAF       param_real(1): Ensemble pert. level (>0), required, only used if param_int(4)>0
     492PDAF       param_real(2): Forgetting factor (usually >0 and <=1), optional, default=1.0
     493PDAF       param_real(3): Limit for weigts inflation N_eff/N > param_real(2), optional, default=0.0
     494PDAF     --- Further parameters ---
     495PDAF       n_modeltasks: Number of parallel model integration tasks
     496PDAF           >=1 for subtypes 0 and 1; not larger than total number of processors
     497PDAF           =1 required for subtypes 2 and 3
     498PDAF       screen: Control verbosity of PDAF
     499PDAF           0: no outputs
     500PDAF           1: basic output (default)
     501PDAF           2: 1 plus timing output
     502PDAF           3: 2 plus debug output
     503PDAF     +++++++++ End of option overview for the PF  ++++++++++
     504}}}
     505
     506== GENOBS (filtertype=100) ==
     507
     508Note: GENOBS used filtertype=11 before PDAF V2.0.
     509
     510{{{
     511PDAF     Available options for GENOBS:
     512PDAF     --- Sub-types (Parameter subtype) ---
     513PDAF       0: Standard implementation with ensemble integration
     514PDAF     --- Integer parameters (Array param_int) ---
     515PDAF       param_int(1): Dimension of state vector (>0), required
     516PDAF       param_int(2): Ensemble size (>0), required
     517PDAF     --- Floating point parameters (Array param_real) ---
     518PDAF       param_real(1): Forgetting factor (usually >0 and <=1), required, but not used
     519PDAF     --- Further parameters ---
     520PDAF       n_modeltasks: Number of parallel model integration tasks
     521PDAF           =1 for GENOBS; not larger than total number of processors
     522PDAF           =1 required for subtypes 2 and 3
     523PDAF       screen: Control verbosity of PDAF
     524PDAF           0: no outputs
     525PDAF           1: basic output (default)
     526PDAF           2: 1 plus timing output
     527PDAF           3: 2 plus debug output
     528PDAF     +++++++++ End of option overview for GENOBS  ++++++++++
     529}}}
     530
     531== 3DVAR (filtertype=200) ==
     532
     533Note: 3D-Var methods were added in PDAF V2.0.
     534
     535{{{
     536PDAF     Available options for 3D-Var:
     537PDAF     --- Sub-types (Parameter subtype) ---
     538PDAF       0: incremental 3D-Var with parameterized covariance matrix
     539PDAF       1: 3D ensemble Var using LESTKF for ensemble transformation
     540PDAF       4: 3D ensemble Var using ESTKF for ensemble transformation
     541PDAF       6: hybrid 3D-Var using LESTKF for ensemble transformation
     542PDAF       7: hybrid 3D-Var using ESTKF for ensemble transformation
     543PDAF     --- Integer parameters (Array param_int) ---
     544PDAF       param_int(1): Dimension of state vector (>0), required
     545PDAF       param_int(2): Ensemble size (>0), required
     546PDAF       param_int(3): Select optimization method (solver), required
     547PDAF           0: LBFGS (default)
     548PDAF           1: CG+
     549PDAF           2: direct implementation of CG
     550PDAF           3: direct implementation of CG with decomposed control vector
     551PDAF       param_int(4): size of parameterized control vector (for parameterized and hybrid 3D-Var), required
     552PDAF       param_int(5): size of ensemble control vector (required for ensemble and hybrid 3D-Var),
     553PDAF       param_int(6): Solver-specific parameter, optional
     554PDAF           LBFGS: parameter m (default=5)
     555PDAF                Number of corrections used in limited memory matrix; 3<=m<=20
     556PDAF           CG+: parameter method (default=2)
     557PDAF                (1) Fletcher-Reeves, (2) Polak-Ribiere, (3) positive Polak-Ribiere
     558PDAF           CG: maximum number of iterations (default=200)
     559PDAF       param_int(7): Solver-specific parameter, optional
     560PDAF           CG+: parameter irest (default=1)
     561PDAF                (0) no restarts; (n>0) restart every n steps
     562PDAF     --- Floating point parameters (Array param_real) ---
     563PDAF       param_real(1): Forgetting factor (usually >0 and <=1), required;
     564PDAF           (only used for ensemble and hybrid 3D-Var)
     565PDAF       param_real(2): hybrid weight beta, optional (only for hybrid 3D-Var)
     566PDAF           range >=0.0 and <=1.0, =1.0 for pure ensemble 3D-var  (default=0.5)
     567PDAF       param_real(3): Solver-specific parameter, optional
     568PDAF           LBFGS: Limit for stopping iterations (pgtol, default=1.0e-5)
     569PDAF           CG+: convergence parameter eps (default=1.0e-5)
     570PDAF           CG: convergence parameter eps (default=1.0e-6)
     571PDAF       param_real(4): Solver-specific parameter, optional
     572PDAF           LBFGS: Tolerance in termination test (factr, default=1.0e+7)
     573PDAF     --- Further parameters ---
     574PDAF       n_modeltasks: Number of parallel model integration tasks
     575PDAF           >=1 for subtypes 0 and 1; not larger than total number of processors
     576PDAF           =1 required for subtypes 2 and 3
     577PDAF       screen: Control verbosity of PDAF
     578PDAF           0: no outputs
     579PDAF           1: basic output (default)
     580PDAF           2: 1 plus timing output
     581PDAF           3: 2 plus debug output
     582PDAF     +++++++++ End of option overview for 3DVAR ++++++++++
     583}}}
     584
     585
     586
     587== SEEK (filtertype=0) ==
     588
     589**Note:** The SEEK filter is deprecated and will be removed in a future release of PDAF.
     590
     591{{{
     592PDAF     Available options for SEEK:
     593PDAF     --- Sub-types (Parameter subtype) ---
     594PDAF       0: Evolve unit modes with finite difference approx. of TLM
     595PDAF       1: like 0 with modes scaled by eigenvalues, unit U
     596PDAF       2: Fixed basis vectors; variable U matrix
     597PDAF       3: Fixed covariance matrix (V and U kept constant)
     598PDAF     --- Integer parameters (Array param_int) ---
     599PDAF       param_int(1): Dimension of state vector (>0), required
     600PDAF       param_int(2): Ensemble size (>0), required
     601PDAF       param_int(3): Interval for re-diagonalization of P (>0); optional: default 1
     602PDAF       param_int(4): 1 for incremental updating, 0 else; optional: default 0
     603PDAF     --- Floating point parameters (Array param_real) ---
     604PDAF       param_real(1): Forgetting factor (usually >0 and <=1), required
     605PDAF       param_real(2): epsilon for finite-difference approx. of TLM, required
     606PDAF     --- Further parameters ---
     607PDAF       n_modeltasks: Number of parallel model integration tasks
     608PDAF           >=1 for subtypes 0 and 1; not larger than total number of processors
     609PDAF           =1 required for subtypes 2 and 3
     610PDAF       screen: Control verbosity of PDAF
     611PDAF           0: no outputs
     612PDAF           1: basic output (default)
     613PDAF           2: 1 plus timing output
     614PDAF           3: 2 plus debug output
     615PDAF     +++++++++ End of option overview for the SEEK filter ++++++++++
     616}}}