Book contents
- Frontmatter
- Contents
- Preface
- Acknowledgments
- Notation
- 1 Electromagnetic concepts useful for radar applications
- 2 Scattering matrix
- 3 Wave, antenna, and radar polarization
- 4 Dual-polarized wave propagation in precipitation media
- 5 Doppler radar signal theory and spectral estimation
- 6 Dual-polarized radar systems and signal processing algorithms
- 7 The polarimetric basis for characterizing precipitation
- 8 Radar rainfall estimation
- Appendices
- References
- Index
7 - The polarimetric basis for characterizing precipitation
Published online by Cambridge University Press: 14 October 2009
- Frontmatter
- Contents
- Preface
- Acknowledgments
- Notation
- 1 Electromagnetic concepts useful for radar applications
- 2 Scattering matrix
- 3 Wave, antenna, and radar polarization
- 4 Dual-polarized wave propagation in precipitation media
- 5 Doppler radar signal theory and spectral estimation
- 6 Dual-polarized radar systems and signal processing algorithms
- 7 The polarimetric basis for characterizing precipitation
- 8 Radar rainfall estimation
- Appendices
- References
- Index
Summary
The conventional single-polarized Doppler radar uses the measurement of radar reflectivity, radial velocity, and storm structure to infer some aspects of hydrometeor types and amounts. With the advent of dual-polarized radar techniques it is generally possible to achieve significantly higher accuracies in the estimation of hydrometeor types, and in some cases of hydrometeor amounts. A description of these techniques and their rationale, within the scattering and propagation theory presented in Chapters 3 and 4, is the main subject of this chapter. For certain important classes of hydrometeors, the information that can be obtained from dual-polarized radar is so dramatic that it is now considered to be an indispensable tool for the study of the formation and evolution of precipitation.
The determination of hydrometeor types and amounts can be formulated in terms of the elements of the covariance matrix. The covariance matrix defined in (3.183) is averaged over the particle size distribution N(D) (here D is the characteristic size of a hydrometeor) and over the joint probability density function of particle states (typically inclusive of shape, orientation, and density). The radar elevation angle is an independent variable and the radar operating frequency is fixed. Thus, if N(D) and the particle state distributions are assumed, then the covariance matrix (and radar observables derived from the matrix, such as differential reflectivity and linear depolarization ratio) can be computed as a function of elevation angle and operating frequency.
- Type
- Chapter
- Information
- Polarimetric Doppler Weather RadarPrinciples and Applications, pp. 378 - 533Publisher: Cambridge University PressPrint publication year: 2001
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