def read_analysis_spline_info (clead_use, master_directory_panal_spline,\
    cmonth):

    """ read netCDF file here for inverse spline parameters for
    the combined CCPA/MSWEP precip analysis CDFs on the 
    Lambert-conformal NDFD 2.5 km grid surrounding the CONUS.  
  
    **** Note that if we are applying to cycles other than 
    forecasts with 00UTC init, we'll need adjust the dates 
    of the spline files that we use to sync up. 
    """ 
    
    from netCDF4 import Dataset
    import numpy as np
   
    ndays = int(clead_use) // 24
    ilead = int(clead_use)-ndays*24
    if ilead == 0:
        cleada = '00'
    elif ilead == 6:
        cleada = '06'
    elif ilead == 12:
        cleada = '12'
    elif ilead == 18:
        cleada = '18'
        
    infile = master_directory_panal_spline + cmonth + \
        '_conus_CCPA_spline_info_h' + cleada + 'UTC.nc'
    print ('reading from ', infile)
    nc = Dataset(infile)
    spline_info_inv = nc.variables['spline_info_inv'][:,:,:,:]
    fraction_zero_ndfd = nc.variables['fzero'][:,:]
    usegamma_ndfd = nc.variables['usegamma'][:,:]
    number_knots_ndfd = nc.variables['number_knots'][:,:] 
    lons_ndfd = nc.variables['lons'][:,:]
    lons_ndfd = lons_ndfd
    lats_ndfd = nc.variables['lats'][:,:]
    ny_ndfd, nx_ndfd = np.shape(lons_ndfd)
    nc.close() 
    
    return spline_info_inv, fraction_zero_ndfd, usegamma_ndfd, \
        number_knots_ndfd, lons_ndfd, lats_ndfd, ny_ndfd, nx_ndfd