Abstract
Scatterometer Radar Backscatter Calibration since the first SeaSat-A Satellite Scatterometer (Birer et al., 1982), the Amazon tropical rain forest has been recognized as a spatially large extent, homogeneous radar calibration target. During the commissioning of NSCAT (1996) and later QuikSCAT (1999), CFRSL worked with the JPL Scatterometer Cal/Val team to perform normalized radar cross section (Sigma-0) calibrations using the Amazon (see Zec et al., 1999-A and 1999-B) [1]. It is important to continue this activity using RapidSCAT to validate the Sigma-0 measurement provided in the L-1A data product, and moreover the time series of these backscatter observations can be used to establish an improved Ku-band Amazon calibration site for future on-orbit radar calibration [2]. Unfortunately, the Amazon radar backscatter (Sigma-0) exhibits a time of day dependence that is not well characterized, and for the sun-synchronous polar orbiting satellites (SeaSat-A, ADEOS-I and QuikSCAT), the observations occur at specific times of day, during the morning and night passes. But now with the low-earth-orbit of the ISS, there will be an orderly orbit precession, which allows the region to be uniformly sampled over the 24-hour period [3]. Also, since the RapidSCAT employs a conical scanning geometry, we can examine the isotropic nature of Amazon backscatter established by Zec’s (1998-A) analysis of NSCAT and later (1999-B) of QuikSCAT observations [4]. Thus, observations, collected over the RapidSCAT two-year mission will sample the Amazon with high spatial/temporal resolution, as a function of time of day, and over seasons. We propose to analyze these data to develop a high spatial resolution Sigma-0 Amazon map that can be used by future satellite radar missions.
Highlights
Scatterometer Radiometric Brightness Temperature previously under the QuikSCAT program, the LL developed a QRad brightness temperature (Tb) measurement capability included in the scatterometer L-1B data product
The QRad Tb had been shown by Ahmed et al (2005) to be capable of providing measurements of rain simultaneous with the scatterometer backscatter measurements
CFRSL developed an empirical correction algorithm that was implemented by PODAAC; the QRad Tb was adversely compromised as reported by Rastogi et al (2005) [7]
Summary
Scatterometer Radiometric Brightness Temperature previously under the QuikSCAT program, the LL developed a QRad brightness temperature (Tb) measurement capability included in the scatterometer L-1B data product This Tb measurement was implemented using the QuikSCAT L-1A and L-1B data products during ground data processing at the JPL PODAAC [5]. The QRad Tb had been shown by Ahmed et al (2005) to be capable of providing measurements of rain simultaneous with the scatterometer backscatter measurements. As such, it could provide a reliable rain flag (e.g., used in the MUDD rain flag) or independent measurements (Tbh & Tbv) for use in an active/passive OVW retrieval algorithm (Laupattarakasem et al (2009) and Alsweiss et al (2011)) [6]. CFRSL developed an empirical correction algorithm that was implemented by PODAAC; the QRad Tb was adversely compromised as reported by Rastogi et al (2005) [7]
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