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Gormsen, B. B.

Publications and source records attributed to Gormsen, B. B..

Development of data processing, interpretation and analysis system for remote sensing of trace atmospheric gas species

Highly efficient methods were developed for the analysis and reduction of Measurement of Air Pollution from Satellite (MAPS) data. Specific attention was directed to analyzing the data from the Office of Space and Terrestrial Applications 3 (OSTA-3) correlative measurements of aircraft research flights and from the OSTA-3 shuttle flight. Methods were developed for error analysis of the aircraft and spacecraft instruments. The LSI 11/23 software system was modified and expanded for future data analysis.

Gormsen, B. B.↗

Carbon monoxide mixing ratio inference from gas filter radiometer data

A new algorithm has been developed which permits, for the first time, real time data reduction of nadir measurements taken with a gas filter correlation radiometer to determine tropospheric carbon monoxide concentrations. The algorithm significantly reduces the complexity of the equations to be solved while providing accuracy comparable to line-by-line calculations. The method is based on a regression analysis technique using a truncated power series representation of the primary instrument output signals to infer directly a weighted average of trace gas concentration. The results produced by a microcomputer-based implementation of this technique are compared with those produced by the more rigorous line-by-line methods. This algorithm has been used in the reduction of Measurement of Air Pollution from Satellites, Shuttle, and aircraft data.

Wallio, H. A.↗

A new method for inferring carbon monoxide concentrations from gas filter radiometer data

A method for inferring carbon monoxide concentrations from gas filter radiometer data is presented. The technique can closely approximate the results of more costly line-by-line radiative transfer calculations over a wide range of altitudes, ground temperatures, and carbon monoxide concentrations. The technique can also be used over a larger range of conditions than those used for the regression analysis. Because the influence of the carbon monoxide mixing ratio requires only addition, multiplication and a minimum of logic, the method can be implemented on very small computers or microprocessors.

Wallio, H. A.↗