slide 1 German Aerospace CenterMicrowaves and Radar Institute Methodology for obtaining physical parameters from fully polarimetric.

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Presentation transcript:

slide 1 German Aerospace CenterMicrowaves and Radar Institute Methodology for obtaining physical parameters from fully polarimetric coherent weather radar data: A first approach to unsupervised Entropy-Alpha-classification Dr. Thomas Börner DLR Oberpfaffenhofen Microwaves and Radar Institute D Weßling

slide 2 German Aerospace CenterMicrowaves and Radar Institute Outline Introduction to the H-  decomposition theorem Classification scheme Analysis and interpretation of the polarimetric time series data set Conclusions Future activities

slide 3 German Aerospace CenterMicrowaves and Radar Institute Decomposing the Scattering Matrix

slide 4 German Aerospace CenterMicrowaves and Radar Institute Entropy H and  angle

slide 5 German Aerospace CenterMicrowaves and Radar Institute What does  tell us?  = 0  = 90  = 45 

slide 6 German Aerospace CenterMicrowaves and Radar Institute H-  feasible area

slide 7 German Aerospace CenterMicrowaves and Radar Institute “Classic” Products Z yy [dBZ]Z DR [dB]

slide 8 German Aerospace CenterMicrowaves and Radar Institute Extracted Products Entropy H  angle [deg]

slide 9 German Aerospace CenterMicrowaves and Radar Institute Populated H-  plane

slide 10 German Aerospace CenterMicrowaves and Radar Institute Z yy and Classification Z yy [dBZ]Classes

slide 11 German Aerospace CenterMicrowaves and Radar Institute 15 consecutive PPI Sector Scans Z yy [dBZ]Classes

slide 12 German Aerospace CenterMicrowaves and Radar Institute Is there a Z-H relation?

slide 13 German Aerospace CenterMicrowaves and Radar Institute Is there a Z-  relation?

slide 14 German Aerospace CenterMicrowaves and Radar Institute Conclusions It has been shown that it is possible to apply the H-  decomposition to polarimetric weather radar data and to retrieve meaningful results. The classification provides knowledge about different types of scatterers without having to access empirical a-priori knowledge. Proper interpretation of PPI scans is difficult, because it is unclear what the radar beam is actually scanning. Regions with ground clutter can be easily detected, which might help to enhance clutter filtering.

slide 15 German Aerospace CenterMicrowaves and Radar Institute Future Activities Analyse RHI scans: different layers are easier to distinguish  enhance the classification scheme! Compare results with other sources of information about particles, preferably simultaneously collected. Compare results with other classification methods. Use additional parameters as 1 or the anisotropy to refine the classification scheme.