Prior Selection for QuikSCAT Ultra-High Resolution Wind and Rain Retrieval

Abstract

Abstract-QuikSCAT was designed for ocean wind retrieval. However, its wind estimation performance is limited in rainy conditions. Several estimation techniques have been proposed: wind-only (WO), simultaneous wind and rain (SWR), and rain-only, which are appropriate for different levels of rain contamination. To exploit the strengths of each estimation method at mitigating rain contamination, a Bayes estimator selection (BES) technique has been developed for 25-km wind products to select from among the several estimation techniques for each wind vector cell. This paper adapts the BES concept [1] to QuikSCAT ultrahigh resolution (UHR) 2.5-km, products and extends BES to include prior selection and noise reduction. Prior selection and noise reduction exploit general spatial characteristics of wind and rain fields to improve the accuracy of estimator selections. Together these techniques enable improved estimator selection performance so that the probability of selecting the estimate with minimum squared error approaches optimal levels. Optimal estimator selection reduces variability of wind estimates during rainy conditions and provides rain estimates when possible without using additional sources of information. Overall, UHR wind estimation performance with the new technique has improved bias and root mean-squared error, −0.16 m/s and 2.15 m/s, respectively, which are lower than either of the UHR WO and UHR SWR estimates.

Retrieval of Rain Rates for Tropical Cyclones From Sentinel-1 Synthetic Aperture Radar Images

“…Therefore, hurricane/typhoon winds are usually inverted from cross-polarization (vertical-horizontal (VH) and horizontal-vertical (HV)) SAR images [16], [17]. The effect of heavy rain on wind speed estimation has been discussed in several research reports [18][19][20][21] that have concluded that heavy rain has a significant influence on co-polarized microwave backscattering. To address this issue, a few studies have developed approaches for TC wind retrieval from co-polarized scatterometer [22] and SAR [23] data.…”

Ultrahigh Resolution Scatterometer Winds near Hawaii

“…Resolution enhancement and reconstruction techniques enable estimation of winds on an ultrahigh resolution (UHR) 2.5 km or 1.25 km grid [23][24][25]. UHR products have been produced for QuikSCAT [25][26][27][28][29], RapidSCAT [30], and ASCAT [31,32]. UHR wind processing reveals finer resolution detail of ocean wind phenomena and gives valuable insight to close to shore wind phenomena.…”