pyPDAF.PDAFomi.init_dim_obs_l_noniso_locweights

pyPDAF.PDAFomi.init_dim_obs_l_noniso_locweights()

Initialize the observation information corresponding to a non-isotropic local analysis domain.

One can set localization parameters, like the localization radius, for each observation type.

Here, each dimension can use a different localisation radius and a different localisation weight.

The function has to be called in user-supplied function of init_dim_obs_l_OBTYPE in each observation module if a domain-localized filter (LESTKF/LETKF/LNETF/LSEIK)is used.

It initialises the local observation information for PDAF-OMI for a single local analysis domain. This is used for isotropic localisation where the localisation radius is the same in all directions.

See also relevant PDAF wiki page as well as non-isotropic localisation page

Parameters:

  • i_obs (int) – index of observation type

  • coords_l (ndarray[tuple[ncoord, ...], np.float64]) – Coordinates of current analysis domain The array dimension ncoord is number of coordinate dimension

  • locweights (ndarray[tuple[2, ...], np.intc]) – Types of localization function 0) unit weight; 1) exponential; 2) 5-th order polynomial; 3) 5-th order polynomial with regulatioin using mean variance; 4) 5-th order polynomial with regulatioin using variance of single observation point; The first dimension is horizontal weight function and the second is the vertical function

  • cradius (ndarray[tuple[ncoord, ...], np.float64]) – Vector of localization cut-off radii for each dimension; observation weight=0 if distance > cradius The array dimension ncoord is number of coordinate dimension

  • sradius (ndarray[tuple[ncoord, ...], np.float64]) – Vector of support radii of localization function for each dimension. It has no impact if locweight=0; weight = exp(-d / sradius) if locweight=1; weight = 0 if d >= sradius else f(sradius, distance) if locweight in [2,3,4]. The array dimension ncoord is number of coordinate dimension

  • cnt_obs_l (int) – Local dimension of current observation vector

Returns:

cnt_obs_l – Local dimension of current observation vector

Return type:

int