The Surface Reference Technique (SRT) is used by the TRMM 2A25 algorithm to produce rainfall profiles. The SRT relies on Path-Integrated Attenuation (PIA) estimates obtained by comparing the radar measured backscatter cross-sections of the ocean surface between the rainy region of interest and the neighboring rain-free areas, as a constraint in the rain retrieval process. It is anticipated that a dual-frequency version of the SRT will be developed for use by the GPM Ku/Ka-band Dual-frequency Precipitation Radar (DPR) for accurate retrievals of rain drop-size distribution parameters and vertical rainfall rate profiles.
In order to develop such an algorithm, one must understand the underlying physics and characteristics associated with the Ka-band ocean surface cross-sections both in and out of rain, the correlation between the Ku- and Ka-band cross-sections, as well as how these physical and statistical features affect the corresponding estimates of PIAs, PIA differences, and rain parameter retrievals.
Furthermore, non-Uniform Beam Filling (NUBF) must be considered for spaceborne radar applications, and contributions by water vapor and cloud liquid water, particularly at Ka-band, must be accounted for when using the PIA estimate in the rain parameter retrievals. To quantify these factors would require realistic radar measurements at the same frequencies and in the same viewing geometry as those of the DPR, which have not been in existence until recently.
Since 2001, the Airborne Dual-frequency Precipitation Radar (APR-2) has acquired high-quality ocean surface and rainfall measurements in two major field campaigns, CAMEX-4 and Wakasa Bay AMSR validation experiments, at vastly different environmental regimes. Using these data sets, we have begun to investigate the characteristic properties of the Ka-band cross-section and the inter-relationship between the Ku- and Ka-band cross-sections in clear oceans.
For the PMM science study, we propose to use the APR-2's high-resolution data and the data generated by cloud resolving models to support the GPM DPR algorithm development and validation. Our goals include:
- investigating the characteristics of the dual-frequency ocean ocean-section measurements and the associated uncertainties,
- quantifying the uncertainty in dual-frequency PIA and SRT estimation methods accounting for GPM's specific geometry, and assessing the feasibility of a dual-frequency NUBF detection/correction method based on such estimates.
