Monitoring the Progression of the Northeast MFRSR Network Using the NASA-GISS Calibration Algorithm to Obtain Aerosol Products

We monitor the progression of the Northeast Multi- Filter Rotating Shadowband Radiometer (MFRSR) network by implementing the novel NASA-GISS algorithm and compare its stability against the conventional Langley algorithm. The MFRSR network is advantageous because it provides a spatial and temporal resolution of aerosol products as well as a ground- based source to validate satellite aerosol retrievals. Satellite aerosol optical depth (AOD) data needs to be validated against ground- based retrievals to extract existing surface brightness bias. The bias is caused by variability in surface albedo that exists between urban and rural environments. It is essential that we explore a consistent means of calibrating the MFRSR. Precise calibration coefficients will enable us to determine AOD from real time raw data. The two algorithms were compared using the fractional errors between AOD at the 870 nm channel against the direct over the diffuse ratio for the same channel. As a result, the Langley algorithm exhibited a fractional error almost three times greater than the NASA-GISS approach due to the Langley method relying on homogenous aerosol loading in the atmosphere. The GISS algorithm produced a more stable calibration coefficient by relying on a stable spectral stability (color ratio), which is a much more robust assumption. The Langley and NASA-GISS algorithms were correlated against processed CIMEL AOD data. The CIMEL sun- photometer provides precise measurements of the direct solar irradiance as well as the sky radiance. As a result, we observe that the Langley approach exhibits instability and over-estimates AOD at the 870nm channel when compared to the more consistent NASA-GISS algorithm.