pyPDAF.PDAFlocal.set_increment_weights

pyPDAF.PDAFlocal.set_increment_weights()

Initialises a PDAF_internal local array of increment weights.

This is called in the user-supplied function py__init_dim_l_pdaf.

The weights are applied in in pyPDAF.PDAFlocal.l2g_cb() where the local state vector is weighted by given weights. These can e.g. be used to apply a vertical localisation.

In vertical localization, the local state vector is a full vertical column of the model grid. In this case, one can make the increment weight depending on the height (or depth) of a grid point.

Another application is to implement weakly-coupled assimilation in which the local state vector contains all variables, but only a subset of them is updated.

This is achieved by givening those element that should not be updated the weight 0.

Parameters:

• dim_l (int) – Dimension of local state vector

• weights (ndarray[np.float64, dim=1]) – Weights array. Shape: (dim_l,)