Dual-Pol and Differential Phase#
Overview#
This module provides algorithms to process polarimetric radar moments, namely the differential phase, \(Phi_{DP}\), and, based on successful \(Phi_{DP}\) retrieval, also the specific differential phase, \(K_{DP}\). Please note that the actual application of polarimetric moments is implemented in the corresponding wradlib modules, e.g.:
fuzzy echo classification from polarimetric moments (
wradlib.clutter.classify_echo_fuzzy
)attenuation correction (
wradlib.atten.pia_from_kdp
)direct precipitation retrieval from Kdp (
wradlib.trafo.kdp_to_r
)
Establishing a valid \(Phi_{DP}\) profile for \(K_{DP}\) retrieval
involves despeckling (linear_despeckle), phase unfolding, and iterative
retrieval of \(Phi_{DP}\) form \(K_{DP}\).
The main workflow and its single steps is based on a publication by
[Vulpiani et al., 2012]. For convenience, the entire workflow has been
put together in the function wradlib.dp.process_raw_phidp_vulpiani
.
Once a valid \(Phi_{DP}\) profile has been established, the kdp_from_phidp functions can be used to retrieve \(K_{DP}\).
Please note that so far, the functions in this module were designed to increase performance. This was mainly achieved by allowing the simultaneous application of functions over multiple array dimensions. The only requirement to apply these function is that the range dimension must be the last dimension of all input arrays.
Establish consistent \(Phi_{DP}\) profiles from raw data. |
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Retrieves \(K_{DP}\) from \(Phi_{DP}\). |
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Alternative phase unfolding which completely relies on \(K_{DP}\). |
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Unfolds differential phase by adjusting values that exceeded maximum ambiguous range. |
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Compute the texture of data. |
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Compute the depolarization ration. |