RapidSCAT Sigma-0 and Tb Measurements Validation  

RapidSCAT Sigma-0 and Tb Measurements Validation

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作  者:Patrick Fiati Patrick Fiati(Department of Electrical, Electronic Engineering, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana)

机构地区:[1]Department of Electrical, Electronic Engineering, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

出  处:《World Journal of Engineering and Technology》2016年第2期183-192,共10页世界工程和技术(英文)

摘  要: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.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.

关 键 词:RapidSCAT QUIKSCAT SCATTEROMETER HIRAD Sigma-0 

分 类 号:TN9[电子电信—信息与通信工程]

 

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