Keywords

Remote sensing, roughness correction, salinity retrieval

Abstract

The Aquarius/SAC-D is an Earth Science remote sensing satellite mission to measure global Sea Surface Salinity (SSS) that is sponsored by the NASA and the Argentine Space Agency (CONAE). The prime remote sensor is the Aquarius (AQ) L-band radiometer/scatterometer, which measures the L-band emitted blackbody radiation (brightness temperature) from the ocean. The brightness temperature at L-band is proportional to the ocean salinity as well as a number of physical parameters including ocean surface wind speed. The salinity retrieval algorithm make corrections for all other parameters before retrieving salinity, and the greatest of these is the increased brightness temperature due to roughness caused by surface wind speed. This thesis presents an independent approach for the AQ roughness correction, which is derived using simultaneous measurements from the CONAE Microwave Radiometer (MWR). When the wind blows over the ocean’s surface, the brightness temperature is increased because of the ocean wave surface roughness. The MWR provides a semi-empirical approach by measuring the excess ocean emissivity at 36.5 GHz and then applying radiative transfer theory (improved ocean surface emissivity model) to translate this to the AQ 1.4 GHz frequency (L-band). The theoretical basis of the MWR algorithm is described and empirical results are presented that demonstrate the effectiveness in reducing the salinity measurement error due to surface roughness.

Notes

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Graduation Date

2012

Semester

Spring

Advisor

Jones, W. Linwood

Degree

Master of Science in Electrical Engineering (M.S.E.E.)

College

College of Engineering and Computer Science

Department

Electrical Engineering and Computing

Degree Program

Electrical Engineering

Format

application/pdf

Identifier

CFE0004212

URL

http://purl.fcla.edu/fcla/etd/CFE0004212

Language

English

Release Date

May 2012

Length of Campus-only Access

None

Access Status

Masters Thesis (Open Access)

Subjects

Dissertations, Academic -- Engineering and Computer Science, Engineering and Computer Science -- Dissertations, Academic

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