In this presentation we will discuss the performance of classification and retrieval algorithms for spaceborne cloud and precipitation radars such as the Global Precipitation Measurement mission [1] Dual-frequency Precipitation Radar (GPM/DPR) [2], and notional radar for the Aerosol/Clouds/Ecosystem (ACE) [1] mission and related concepts. Spaceborne radar measurements are simulated either from Airborne Precipitation Radar 2^nd Generation (APR-2, [3]) observations, or from atmospheric model outputs via instrument simulators contained in the NASA Earth Observing Systems Simulators Suite (NEOS³). Both methods account for the three dimensional nature of the scattering field at resolutions smaller than that of the spaceborne radar under consideration. We will focus on the impact of nonhomogeneities of the field of hydrometeors within the beam. We will discuss also the performance of methods to identify and mitigate such conditions, and the resulting improvements in retrieval accuracy. The classification and retrieval algorithms analyzed in this study are those derived from APR-2’s Suite of Processing and Retrieval Algorithms (ASPRA); here generalized to operate on an arbitrary set of radar configuration parameters to study the expected performance of spaceborne cloud and precipitation radars. The presentation will highlight which findings extend to other algorithm families and which ones do not.

Date Published: 8 November 2012
PDF: 9 pages
Proc. SPIE 8523, Remote Sensing of the Atmosphere, Clouds, and Precipitation IV, 852308 (8 November 2012); doi: 10.1117/12.977375

Published in SPIE Proceedings Vol. 8523:
Remote Sensing of the Atmosphere, Clouds, and Precipitation IV
Tadahiro Hayasaka; Kenji Nakamura; Eastwood Im, Editor(s)