wradlib.dp.process_raw_phidp_vulpiani

wradlib.dp.process_raw_phidp_vulpiani(phidp, dr, ndespeckle=5, winlen=7, niter=2, copy=False, **kwargs)

Establish consistent \(Phi_{DP}\) profiles from raw data.

This approach is based on [Vulpiani2012] and involves a two step procedure of \(Phi_{DP}\) reconstruction.

Processing of raw \(Phi_{DP}\) data contains the following steps:

  • Despeckle
  • Initial \(K_{DP}\) estimation
  • Removal of artifacts
  • Phase unfolding
  • \(Phi_{DP}\) reconstruction using iterative estimation of \(K_{DP}\)
Parameters:
  • phidp (array) – array of shape (n azimuth angles, n range gates)
  • dr (float) – gate length in km
  • ndespeckle (int) – ndespeckle parameter of linear_despeckle
  • winlen (integer) – winlen parameter of kdp_from_phidp
  • niter (int) – Number of iterations in which \(Phi_{DP}\) is retrieved from \(K_{DP}\) and vice versa
  • copy (bool) – if True, the original \(Phi_{DP}\) array will remain unchanged
Returns:

  • phidp (numpy.ndarray) – array of shape (n azimuth angles, n range gates) reconstructed \(Phi_{DP}\)
  • kdp (numpy.ndarray) – array of shape (n azimuth angles, n range gates) kdp estimate corresponding to phidp output

Examples

See Routine verification measures for radar-based precipitation estimates.