P2b.1 Constrained Gamma Drop Size Model for Polarimetric Radar Rain Estimation: Justification and Development

Accurate rain estimation from radar measurements has been a difficult task due to the variation of raindrop size distribution (DSD), lack of accurate axis ratio model, measurement error, clutter, and so forth. Previously, rain estimation from weather radars has been largely dependent upon empirical relations such as R-Z relations. The development of polarimetric radar makes accurate rain DSD retrieval and rain rate estimation possible. Polarimetric radar observables: ZDR and KDP depend on the shape of raindrops while the raindrop shape is directly related to drop size, and hence contain the information about rain DSD, and are used to retrieve rain DSDs and improve rain rate estimation. Recently, the constrained Gamma rain DSD retrieval was developed [Brandes et al., 2002&2003a; Vivekanandan et al., 2003; Zhang et al., 2001]. Since KDP has large measurement error and poor range resolution, the constrained Gamma DSD method uses radar measured Z, ZDR, and an observed relation between the shape and slope parameters to retrieve the parameters of Gamma rain DSD, and then calculate rain parameters such as rain rate and median volume diameter. In this paper, we summarize the development of the constrained gamma DSD model for rain estimation from polarimetric radar measurements. Justification for using the constrained Gamma DSD retrieval is provided. The verification and application of the retrieval algorithm is described by Brandes et al. (2003a&b). It is shown that the constrained Gamma DSD retrieval improves rain estimations from a pair of remote measurements, such as, reflectivity and differential reflectivity, and it reduces the bias and standard error in retrieved rain parameters.