A meteorological model for rain-induced cross polarization

Brussaard, G.

doi:10.1109/tap.1976.1141282

Cited by 75 publications

(38 citation statements)

References 19 publications

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“…This has the additional advantage that the influence of wind and turbulence on the orientation of raindrops, so-called canting (e.g. Brussaard, 1974Brussaard, , 1976, does not have to be considered. On the other hand, the fact that larger raindrops tend to be more oblate than smaller ones, and hence that the average drop shape in a radar sample volume tends to become more oblate as the rain rate increases, can also be used to our benefit: It forms the basis of all polarimetric radar rainfall retrieval algorithms (e.g.…”

Section: Rainfall Microstructure a Static Picture Of Rainfallmentioning

confidence: 99%

Measurement and parameterization of rainfall microstructure

Uijlenhoet

Sempere‐Torres

2006

Journal of Hydrology

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Section: Rainfall Microstructure a Static Picture Of Rainfallmentioning

confidence: 99%

Measurement and parameterization of rainfall microstructure

Uijlenhoet

Sempere‐Torres

2006

Journal of Hydrology

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“…This airflow creates low pressure at the crystal edges resulting in a torque which tends to align the axis of symmetry of the particle along the airflow's direction (Brussaard, 1976). However, different dynamical mechanisms, such as windshear or strong updraft, can act upon the airflow's orientation, changing the particle's orientation.…”

Section: Characterization Of Ice Crystal Orientationmentioning

confidence: 99%

Towards the improvement of cloud microphysical retrievals using simultaneous Doppler and polarimetric radar measurements

Dufournet

Russchenberg

2011

Atmos. Meas. Tech.

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Abstract. Radar-based retrievals are often employed to characterize the microphysical properties of cloud hydrometeors, i.e. their phases, habits, densities as well as their respective size and orientation distributions. These techniques are based on a synergetic use of different cloud observation sensor(s) and microphysical model(s) where the information extracted from both sensors and models is combined and converted into microphysical cloud properties. However, the amount of available information is often limited, which forces current microphysical retrieval techniques to base their algorithms on several microphysical assumptions which affect the retrieval accuracy.By simultaneously combining Doppler and polarimetric measurements obtained from fully Doppler polarimetric radars, it is possible to create spectral polarimetric parameters. Although these parameters are easily contaminated with unwanted echoes, this work shows that, from a correct radar signal processing based on filtering and averaging techniques, spectral polarimetric parameters can be correlated to microphysical cloud properties. In particular, preliminary results suggest that particle orientations and habits can be determined from the sole use of such spectral polarimetric parameters. Therefore, such additional spectral polarimetric information offers an opportunity to improve current microphysical retrievals by reducing the number of microphysical assumptions in them.

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“…[1], [2]. It is well known that hydrometeors such as rain and ice can significantly depolarize radiowave signals at microwave and millimeter wave frequencies [3], [4].…”

Section: Introductionmentioning

confidence: 99%