A Multi-angle Aerosol Optical Depth Retrieval Algorithm for GOES Hai Zhang1, Alexei Lyapustin2, Yujie Wang2, Shobha Kondragunta3, Istvan Laszlo3 1. JCET/UMBC 2.GEST/UMBC 3. STAR/NOAA ABSTRACT Aerosol retrievals from geostationary satellites have high temporal resolution compared to those from polar orbiting satellites, which enables us to monitor aerosol motion. However, the current GOES imager has only one visible channel that can be used for retrieving aerosol and hence the retrieval accuracy is lower than that of polar-orbiting satellites such as Moderate Resolution Imaging Spectroradiometer (MODIS). The operational GOES aerosol optical depth (AOD) retrieval algorithm (GOES Aerosol/Smoke Product, GASP) uses 28-day composite images from the visible channel to derive surface reflectance. In this work, we investigate a new AOD retrieval algorithm from the GOES imager. The algorithm assumes the surface Bidirectional Reflectance Distribution Function (BRDF) at channel 1 of GOES is proportional to the BRDF at 2.1 m from MODIS. The ratios between them are derived through timeseries analysis of visible channel images. The results of the AOD and surface reflectance retrievals are compared against Aerosol Robotic Network (AERONET), GASP, and MODIS retrievals. The benefit of the new algorithm is that the time period for the surface reflectance retrieval is much shorter than GASP algorithm so that it can capture the rapid change in the surface reflectance. Compared to GASP algorithm, the new algorithm has significantly better retrievals during early spring at some of the AERONET sites, and similar retrievals during summer and fall. Validation at selected AERONET sites and comparison against GASP AOD retrieval at bright site -- Railroad Valley, NV Validation period: March-October 2008. LUT made using 6S with continental aerosol model. Scatter plots of AOD retrievals at selected AERONET sites The overall accuracy of MAIAC is similar to GASP. With increasing threshold of surface reflectance in MAIAC, retrieval accuracy decreases. GASP uses a surface reflectance threshold of 0.15. Algorithm modification The BRDF shape is not quite the same between GOES channel 1 and 2.1 m channel in summer Divide sun-lit time into slices, for example: before 1514UTC, between 1515-1814 UTC, after 1815UTC. Assume the proportionality of BRDF in each time slice, and apply MAIAC algorithm Monthly variation of correlation coefficients and RMSE. Algorithm description and assumptions Apply MAIAC (Multi-Angle Implementation of Atmospheric Correction) algorithm for MODIS (Lyapustin and Wang, 2008) to GOES AOD retrieval MODIS MAIAC algorithm derive AOD from time sequences of MODIS images Assumptions: AOD is homogeneous over 25x25 km2 area Surface BRDF in blue channel and red channel is proportional to 2.1 m channel Modifications for GOES No 2.1 m channel: Use MODIS 2.1 m seasonally averaged surface BRDF, assuming that the BRDF shape does not have large variation over short period Only one visible channel 0.52-0.72 m (channel 1) can be used for AOD retrieval: : Assume BRDF shape at GOES channel 1 spectrum is the same as that at MODIS 2.1 mm. The ratio is derived from the retrieval algorithm. Here the ratio b is called spectral regression coefficient (SRC). Comparison with MODIS MODIS Terra Original MAIAC algorithm MAIAC performs better in spring at GSFC, Walker Branch and Bondville, and in summer at UCSB. AOD and surface reflectance at selected sites/months Algorithm flowchart GASP Modified MAIAC algorithm The modified algorithm reduces underestimation of AOD retrievals. Future works Revise and test the algorithm with full BRDF LUT. Compare AOD and surface reflectance retrievals against the latest revised version of GASP. The surface reflectance retrievals follow the diurnal change of AERONET retrievals. In March at GSFC, low GASP surface reflectance in the morning and afternoon may be caused by Large variation in solar zenith angle in 28-day period and more chance of picking up cloud shadow. In August at Walker Branch, the underestimation of AOD corresponds to the overestimation of surface reflectance. Acknowledgement The project is supported by NOAA grant NA09NES4400010. References Lyapustin, A. and Wang, Y. MAIAC: Multi-Angle Implementation of Atmospheric Correction for MODIS ATBD, 2008. Zhang, H., Lyapustin,A., Wang,Y., Kondragunta,S., Laszlo, I., Ciren,P., Multi-angle Aerosol Optical Depth Retrieval from Geostationary Satellite Data, in prep.