4.4 Retrieving Heavy Precipitation from Polarimetric Radio Occultation Observations with a Least Squares Approach

Tuesday, 8 January 2019: 3:45 PM
West 211B (Phoenix Convention Center - West and North Buildings)
Kuo-Nung Wang, SIO, La Jolla, CA; and C. O. Ao, R. Padullés, F. J. Turk, M. de la Torre Juárez, B. A. Iijima, D. Kuang, E. Cardellach, S. Oliveras, and J. S. Haase

In February 2018, the Spanish PAZ satellite was launched to demonstrate the proof of concept experiment “Radio-Occultation and Heavy Precipitation with PAZ (ROHP-PAZ)”. It is equipped with the capability to receive separate horizontal and vertical polarizations. The PAZ GPS-RO polarimetric phase difference observation can be related to the asymmetric shape of the hydrometeors along the propagation path. This unique observation gives the GPS-RO observing system the additional ability to detect and quantify heavy precipitation while simultaneously providing high vertical resolution moisture profiles that are retrievable from the standard GPS-RO measurements.

Retrieving the intensity and extent of heavy precipitation from the polarimetric phase difference measurements, however, is a challenging task. Fundamentally, the polarimetric phase difference is the sum of hydrometeor-induced effects along the entire line-of-sight, including ice as well as rain. It is therefore not possible to uniquely determine the intensity and horizontal extent of the rain cells from the polarimetric RO (PRO) observables. Here we propose a novel retrieval method that combines GPS-PRO with additional horizontal extent measurements acquired from collocated sensors (e.g., infrared or visible cloud imagery). By assuming the heavy precipitation horizontal extent is independently available, the rain-rate can be estimated using least squares optimization based on the retrieved bending angle difference between dual-polarizations.

In this presentation, we will discuss the processing of the PAZ polarimetric data at JPL and calibration/validation of the retrievals. Next, we will describe the least squares retrieval approach that we have developed, including a fast forward operator based on raytracing through the rain domain. The retrievals and the associated uncertainty are first characterized using end-to-end simulations. The method is then applied to a few selected cases from actual PAZ data collocated with Global Precipitation Measurement Dual Polarization Radar measurements. We will present the retrieval results and discuss the strengths and limitations of the technique.

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