    def __determine_NWP_skill_for_next_timestep(self, t, j, worker_state):
        """
        Compute the skill of NWP model components for the next lead time (t0 + t),
        blending with extrapolation skill if configured. Updates the worker state
        with the final blended skill forecast.
        """
        if self.__config.blend_nwp_members:
            rho_nwp_forecast = []
            for model_index in range(self.__params.rho_nwp_models.shape[0]):
                rho_value = blending.skill_scores.lt_dependent_cor_nwp(
                    lt=(t * int(self.__config.timestep)),
                    correlations=self.__params.rho_nwp_models[model_index],
                    outdir_path=self.__config.outdir_path_skill,
                    n_model=model_index,
                    skill_kwargs=self.__params.climatology_kwargs,
                )
                rho_nwp_forecast.append(rho_value)
            rho_nwp_forecast = np.stack(rho_nwp_forecast)
            # Concatenate rho_extrap_cascade and rho_nwp
            worker_state.rho_final_blended_forecast = np.concatenate(
                (worker_state.rho_extrap_cascade[None, :], rho_nwp_forecast), axis=0
            )
        else:
            # TODO: check if j is the best accessor for this variable
            rho_nwp_forecast = blending.skill_scores.lt_dependent_cor_nwp(
                lt=(t * int(self.__config.timestep)),
                correlations=self.__params.rho_nwp_models[j],
                outdir_path=self.__config.outdir_path_skill,
                n_model=worker_state.mapping_list_NWP_member_to_ensemble_member[j],
                skill_kwargs=self.__params.climatology_kwargs,
            )
            # Concatenate rho_extrap_cascade and rho_nwp
            worker_state.rho_final_blended_forecast = np.concatenate(
                (worker_state.rho_extrap_cascade[None, :], rho_nwp_forecast[None, :]),
                axis=0,
            )
Compute the skill of NWP model components for the next lead time (t0 + t),
blending with extrapolation skill if configured. Updates the worker state
with the final blended skill forecast.
pysteps/blending/steps.py