Abstract

Abstract. Aerosol optical depth (AOD) retrievals from geostationary satellites have high temporal resolution compared to the polar orbiting satellites and thus enable us to monitor aerosol motion. However, current Geostationary Operational Environmental Satellites (GOES) have only one visible channel for retrieving aerosols and hence the retrieval accuracy is lower than those from the multichannel polar-orbiting satellite instruments such as the Moderate Resolution Imaging Spectroradiometer (MODIS). The operational GOES AOD retrieval algorithm (GOES Aerosol/Smoke Product, GASP) uses 28-day composite images from the visible channel to derive surface reflectance, which can produce large uncertainties. In this work, we develop a new AOD retrieval algorithm for the GOES imager by applying a modified Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. The algorithm assumes the surface Bidirectional Reflectance Distribution Function (BRDF) in the channel 1 of GOES is proportional to seasonal average MODIS BRDF in the 2.1 μm channel. The ratios between them are derived through time series analysis of the GOES visible channel images. The results of AOD and surface reflectance retrievals are evaluated through comparisons against those from Aerosol Robotic Network (AERONET), GASP, and MODIS. The AOD retrievals from the new algorithm demonstrate good agreement with AERONET retrievals at several sites across the US with correlation coefficients ranges from 0.71 to 0.85 at five out of six sites. At the two western sites Railroad Valley and UCSB, the MAIAC AOD retrievals have correlations of 0.8 and 0.85 with AERONET AOD, and are more accurate than GASP retrievals, which have correlations of 0.7 and 0.74 with AERONET AOD. At the three eastern sites, the correlations with AERONET AOD are from 0.71 to 0.81, comparable to the GASP retrievals. In the western US where surface reflectance is higher than 0.15, the new algorithm also produces larger AOD retrieval coverage than both GASP and MODIS.

Highlights

  • Aerosols play an important role in the atmosphere by modifying radiative forcing, climate, weather, and air quality

  • The quality assured level 2.0 Aerosol Robotic Network (AERONET) Aerosol optical depth (AOD) data is used for evaluating the AOD retrievals and for evaluating the surface Bidirectional Reflectance Distribution Function (BRDF) retrievals from Geostationary Operational Environmental Satellites (GOES) data

  • We develop a new AOD retrieval algorithm by modifying the MultiAngle Implementation of Atmospheric Correction (MAIAC) algorithm for Moderate Resolution Imaging Spectroradiometer (MODIS)

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Summary

Introduction

Aerosols play an important role in the atmosphere by modifying radiative forcing, climate, weather, and air quality. The GASP algorithm assumes that the surface reflectance does not change during the 28-day period for each observation time. The algorithm uses time series of multi-channel images to retrieve surface BRDF and aerosol properties. Surface BRDF in the blue band and the red band are assumed to be proportional to that in the 2.12 μm band, and the ratios are retrieved from time series analysis with the aid of a look-up-table (LUT). The benefit of this method is that it can be applied to regions where the surface reflectance relations between blue, red and SWIR band in MODIS operational retrieval algorithm (MOD04) are inaccurate.

GOES data
AERONET data
MODIS data
Aerosol optical depth retrieval algorithm
November
Comparison of AOD retrieval against AERONET and GASP
Backscatter geometry
Bright surface
Validation of AOD retrievals
Non-Lambertian effect
Evaluation of surface reflectance retrievals
Other sources of errors
A regional retrieval example
Conclusions
Full Text
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