Three NASA Ames Solar Spectral Flux Radiometers (SSFR) were used to measure downwelling and upwelling solar spectral irradiance during both the FIRE (First ISCPP Regional Experiment) Arctic Cloud Experiment and the SHEBA (Surface Heat Budget of the Arctic Ocean) experiment. The SSFRs covering a solar spectral region 360-2500nm were deployed on the NASA ER-2, the UW CV-580 and at the SHEBA ice camp. Each SSFR retrieved several thousand spectra.
Complications arising from spectral mixing make it important to discriminate individual components (coming from several sources) within the mixed signal. Using satellite data alone, it is very difficult to distinguish between a high reflectance stratus cloud layer and a high reflectance sea surface.The Principal Components Analysis (PCA) technique is used to determine the number of independent pieces of information (independent variables) that exist in the spectra. The technique can be summarized as a method of transforming the original variables into new uncorrelated variables. Instead of analyzing a large number of original variables with complex interrelationships, it will be possible to analyze a small number of uncorrelated principal components. Using the PCA technique, it is possible to determine the number of independent variables contained within the SSFR spectra ( eg cloud and molecular scattering, surface reflectance etc) and to establish in which regions of the spectrum these variables are strongest.