Changes between Version 53 and Version 54 of InitPdaf
 Timestamp:
 Feb 22, 2023, 3:56:28 PM (3 months ago)
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InitPdaf
v53 v54 94 94 The routine `init_pdaf` in the example also initializes several variables that are not used to call `PDAF_init`. These variables control some functionality of the usersupplied routines for the data assimilation system and are shared with these routines through the Fortran module `mod_assimilation`. These variables are for example: 95 95 * `delt_obs`: An integer specifying the number of time steps between two analysis steps 96 * `rms_obs`: Assumed observation error 96 * `rms_obs`: Assumed observation error (when PDAFOMI is used the observation error is usually defined separately for each observation, see the [wiki:PDAF_OMI_Overview description of OMI]) 97 97 * `cradius`: Localization cutoff radius in grid points for the observation domain 98 98 * `sradius`: support radius, if observation errors are weighted (i.e. `locweight>0`) … … 100 100 It is useful to define variables like these at this central position. Of course, their definition has to be adapted to the particular model used. The example codes describe the options for `locweight`. 101 101 102 The setting of `locweight` influence the weight function for the localization. If PDAFOMI is used, the choices are standardized as follows102 The setting of `locweight` influences the weight function for the localization. If PDAFOMI is used, the choices are standardized as follows 103 103 104 104 = '''locweight''' == '''0''' == '''1''' == '''2''' == '''3''' == '''4''' = 105 = '''function''' = unit weight  exponential  5th order polynomial  106 = '''regulation''' ==  ==  ==  == regulation using[[BR]]mean variance == regulation using variance[[BR]]of single observation point = 107 = '''cradius''' == weight=0 if distance > cradius = 108 = '''sradius''' == no impact == weight = exp(d / sradius) == weight = 0 if d >= sradius[[BR]] else[[BR]] weight = f(sradius, distance) = 105 = '''function''' = unit weight  exponential  5th order polynomial  106 = '''regulation''' =       regulation using[[BR]]mean variance  regulation using variance[[BR]]of single observation point  107 = '''cradius''' = weight=0 if distance > cradius  108 = '''sradius''' = no impact  weight = exp(d / sradius)  weight = 0 if d >= sradius[[BR]] else[[BR]] weight = f(sradius, distance)  109 110 Here, 'regulation' refers to the regulated localization introduced in Nerger, L., Janjić, T., Schröter, J., Hiller, W. (2012). A regulated localization scheme for ensemblebased Kalman filters. Quarterly Journal of the Royal Meteorological Society, 138, 802812. [https://doi.org/10.1002/qj.945 doi:10.1002/qj.945]. 109 111 110 112