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 [Vulpiani et al., 2012] 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 oflinear_despeckle
- winlen (integer) –
winlen
parameter ofkdp_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 tophidp
output
Examples
See Routine verification measures for radar-based precipitation estimates.