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Proceedings Paper

Possible improvement of the GPM's Dual-frequency Precipitation Radar (DPR) algorithm
Author(s): Toshio Iguchi; Kaya Kanemaru; Atsushi Hamada
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Paper Abstract

Development of precipitation retrieval algorithms for spaceborne radar began with the launch of the Tropical Rainfall Measuring Mission which carried the world first Precipitation Radar (PR). The standard Algorithm for the Dual-frequency Precipitation Radar (DPR) onboard the GPM satellite was developed based on the experience of the TRMM PR algorithm1. The latest DPR algorithm works well and satisfies the mission requirements. Nevertheless, there are still several output variables whose quality can be improved. For example, the threshold for precipitation detection can be lowered to detect more light precipitation without much increase of false detections by adopting a better filtering method than the current method. Removal of surface clutter is related to the detection of precipitation and expected to be improved too. Attenuation correction is another important area of improvement. The current attenuation correction method uses the surface reference technique (SRT) when the attenuation is large. There is a possibility of using radiometric noise for this purpose. The directions of the high sensitivity beams of the DPR’s Ka-band radar, which is called KaPR, were changed to cover the outer swath in March of 2018. Ku and Ka matched beam data are now available over the full swath so that the dualfrequency algorithm can be applied to the entire data. The new scan pattern is expected to improve not only the precipitation retrieval algorithm but also the classification algorithm. This paper summarizes these possible improvement areas in the DPR algorithm.

Paper Details

Date Published: 22 October 2018
PDF: 6 pages
Proc. SPIE 10776, Remote Sensing of the Atmosphere, Clouds, and Precipitation VII, 107760Q (22 October 2018); doi: 10.1117/12.2324290
Show Author Affiliations
Toshio Iguchi, National Institute of Information and Communications Technology (Japan)
Kaya Kanemaru, The Univ. of Tokyo (Japan)
Atsushi Hamada, Univ. of Toyama (Japan)


Published in SPIE Proceedings Vol. 10776:
Remote Sensing of the Atmosphere, Clouds, and Precipitation VII
Eastwood Im; Song Yang, Editor(s)

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