Comparison of Algorithms in the Processing of a MFRSR Network
نویسنده
چکیده
In this paper, we explore the performance of a novel NASA-GISS algorithm which is used to calibrate and extract aerosol optical depth (AOD) from a portable Multi-filter Shadowband radiometer (MFRSR) instrument in comparison to the standard Langley regression algorithm. We show that the NASA-GISS algorithm results has stable calibration coefficients in comparison to those obtained using the conventional Langley regression. The NASA-GISS algorithm does not require the aerosol loading to be homogenous over an extended period but is based on the stability of aerosol color ratios. Statistical analysis shows the stability of the aerosol color ratio as measured by the angstrom coefficient has RMSE variations three times smaller. Therefore, it is able to generate better calibrating statistics over longer periods. In addition, we explore the accuracy of the MFRSR retrieval against a far more expensive coincident, CIMEL, sky scanning radiometer and show that the MFRSR accurately retrieves both the total and the fine mode AOD but underestimates the coarse mode. This is reasonable since the MFRSR filter wavelengths only go to 870nm as compared to the 1620nm available in the CIMEL instrument. Finally, we report our progress on deployment of the MFRSR network over the NYC metropolitan area and describe comparisons between AOD measurements both inside and outside NYC in an effort to explore local aerosol production.
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