Abstract
Abstract. In this paper, we propose an ameliorated physically-based rain rate estimation algorithm for semi-arid regions using the Rayleigh approximation. The proposed algorithm simultaneously uses the reflectivity and the specific differential phase to provide an accurate estimation for both small and large rain rates. In order to validate the proposed estimator, simulated polarimetric rain rate data based on a dual approach, referring to both physical and statistical models of the rain target, are used. Moreover, experimental radar data (the same as used in Matrosov et al., 2006) taken in light to moderate stratiform rainfalls with rain rates varying between 2 and 15 mm h−1 were collected as part of the GPM pilot experiment. It is shown that the proposed algorithm for rain rate estimation based on the full set of polarimetric radar measurements agree better with in situ disdrometer ones.
Highlights
The rain rate is not a direct measurement of weather radars and it must be estimated from echoes of the rain events (Atlas, 1964)
It is important to remark that the specific differential phase Kdp, which is obtained as the slope of a local linear regression made on the differential phase φdp, will be very noisy for small values due to the noise resulting from the scattering differential phase
The data were collected by Matrosov et al (2006), using experimental Drop Size Distribution (DSD) that were recorded by an impact Joss-Waldvogel disdrometer (JWD) deployed at the Boulder Atmospheric Observatory (BAO) during June of 2004
Summary
The rain rate is not a direct measurement of weather radars and it must be estimated from echoes of the rain events (Atlas, 1964). Many physically-based algorithms for rain quantification have been proposed (Atlas and Ulbrich, 1977, 1990). In semi-arid regions as the south of Spain or Tunisia more rain events are either very light or very strong, changing from some mm h−1 up to 200 mm h−1 It is the purpose of this paper to develop an algorithm that presents good behavior on both extremes of the rain rate range for its application in semi-arid regions. The new rain rate estimation algorithm is tested and validated using generated data
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