An approach for obtaining best estimates of spectral optical depths and calibration intercepts from solar radiometer data corrupted by temporal variations

Calibration of solar radiometers is generally accomplished by the Langley plot method; however, slight temporal variations in optical depth can significantly bias zero-airmass intercepts thus derived. This paper presents signal processing techniques for improving the Langley analysis under temporally varying conditions, as well as better characterizing the variability itself. These techniques include spectral analysis of the data to identify systematic atmospheric variations and distinguish them from measurement noise, and exploitation of the correlation between measurements at different wavelengths and on different days. The processing is applied to data from an automated 10-channel radiometer