def METHOD_NAME(obs_list: list, cfg) -> str:
    # Sets up variable for the model register
    tmpdir = const.LOCAL_TMP_DIR
    const.add_data_search_dir(tmpdir)
    model_id = "dummy_model"
    outdir = os.path.join(tmpdir, f"{model_id}/renamed")
    os.makedirs(outdir, exist_ok=True)
    # Finds dates and freq to use, so that all observations are covered
    (start, stop) = get_max_period_range(cfg.time_cfg.periods)
    freq = get_highest_resolution(*cfg.time_cfg.freqs)
    tmp_var_obj = Variable()
    # Loops over variables in obs
    for obs in obs_list:
        for var in cfg.obs_cfg[obs]["obs_vars"]:
            # Create dummy cube
            dummy_cube = make_dummy_cube(var, start_yr=start, stop_yr=stop, freq=freq)
            # Converts cube to GriddedData
            dummy_grid = GriddedData(dummy_cube)
            # Set the value to be the mean of acceptable values to prevent incorrect outlier removal
            # This needs some care though because the defaults are (currently) -inf and inf, which leads to erroneous removal
            if not (
                dummy_grid.var_info.minimum == tmp_var_obj.VMIN_DEFAULT
                or dummy_grid.var_info.maximum == tmp_var_obj.VMAX_DEFAULT
            ):
                dummy_grid.data *= (dummy_grid.var_info.minimum + dummy_grid.var_info.maximum) / 2
            # Loop over each year
            yr_gen = dummy_grid.split_years()
            for dummy_grid_yr in yr_gen:
                # Add to netcdf
                yr = dummy_grid_yr.years_avail()[0]
                vert_code = cfg.obs_cfg[obs]["obs_vert_type"]
                save_name = dummy_grid_yr.aerocom_savename(model_id, var, vert_code, yr, freq)
                dummy_grid_yr.to_netcdf(outdir, savename=save_name)
    # Add dummy model to cfg
    cfg.model_cfg["dummy"] = ModelEntry(model_id="dummy_model")
    return model_id