Graduate Thesis Or Dissertation

Calibration of the Nimbus-7 scanning multichannel microwave radiometer (SMMR), 1979-1984

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  • Six years of Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) data from 1979 to 1984 are recalibrated at the radiometric level. New statistical techniques are developed to quantify the temporal and orbital data errors and to generate numerical corrections for brightness temperatures prior to estimation of geophysical parameters. The foundations of passive microwave satellite radiometry are reviewed. The Nimbus-7 spacecraft and the SMMR experiment are described, along with the radiometric data calibration methods. Sensor design weaknesses and orbit-related problems are summarized. Physical temperatures of various components of the SMMR sensor and housing structure, analyzed for six selected days of data, show systematic thermal changes throughout the orbit due to direct and indirect effects of solar heating. Changes in the operating temperatures, which impact the calibration, also occur from orbit-to-orbit following instrument startup on the SMMR's alternate sampling days. These errors and others contaminate the radiometric data. Incidence angle data, computed from measurements of spacecraft attitude, are analyzed for 1983 and found to contain discontinuities during every orbit due to the use of two different attitude sensors, and temporal drifts and jumps. The post-launch error corrections are developed from the NASA CELL-ALL brightness temperature data. The data are first converted to antenna temperatures, re-calibrated with a bias and slope adjustment, and corrected for temporal drifts. The cross-track bias and mean along-track error for an average annual orbit are statistically derived as well as a mean start-up bias for the first four orbits of each sampling day. The corrections describe only systematic errors found in global averages and are allowed to vary from year to year. Comparisons with Seasat radiometric data show that the errors are unique to the Nimbus-7 SMMR. The corrections are applied to the six years of data and initial retrievals of integrated atmospheric water vapor are examined in a preliminary analysis. Global fields of 1°x 1° monthly averaged water vapor show that the SMMR can map large scale features and document seasonal events, such as the Asian monsoons, and interannual events, such as the El Nino/ Southern Oscillation.
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