1999Journal of Geophysical Research AtmospheresOpen access

Retrieval of aerosol properties over the ocean using Global Ozone Monitoring Experiment measurements: Method and applications to test cases

Francesca Torricella, Elsa Cattani, Marco Cervino, Rodolfo Guzzi, Chiara Levoni

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Abstract

Satellite monitoring of aerosol properties using passive techniques is widely considered a crucial tool for the study of climatic effects of atmospheric particulate [Kaufman et al., 1997]. Only space‐based observations can provide the required global coverage information on spatial distribution and temporal variation of the aerosol field. This paper describes a method for deriving aerosol optical thickness at 500 nm and aerosol type from Global Ozone Monitoring Experiment (GOME) data over the ocean under cloud‐free conditions. GOME, flying on board the second European Remote Sensing satellite (ERS 2) since April 1995, is a spectrometer that measures radiation reflected from Earth in the spectral range 240–793 nm. The features of the instrument relevant to the aerosol retrieval task are its high relative radiometric accuracy (better than 1%), its spectral coverage, and its spectral resolution, which allows wavelengths in spectral regions free of molecular absorption (atmospheric windows) to be selected. The method presented is based on a pseudo‐inversion approach in which measured reflectance spectra are fitted to simulated equivalents computed using a suitable radiative transfer model. The crucial aspects of this method are the high accuracy and the nonapproximate nature of the radiative transfer model, which simulates the spectra during the fitting procedure, and careful selection of candidate aerosol classes. A test application of the proposed method to a Saharan dust outbreak which occurred in June 1997 is presented, showing that in spite of the instrument's low spatial resolution, information on both optical thickness and spectral characterization of the aerosol can be retrieved from GOME data. Preliminary comparisons of the results with independent estimates of the aerosol content show that a good correlation exists, encouraging planning of a systematic application of the method.

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Satellite monitoring of aerosol properties using passive techniques is widely considered a crucial tool for the study of climatic effects of atmospheric particulate [Kaufman et al., 1997]. Only space‐based observations can provide the required global coverage information on spatial distribution and temporal variation of the aerosol field. This paper describes a method for deriving aerosol optical thickness at 500 nm and aerosol type from Global Ozone Monitoring Experiment (GOME) data over the ocean under cloud‐free conditions. GOME, flying on board the second European Remote Sensing satellite (ERS 2) since April 1995, is a spectrometer that measures radiation reflected from Earth in the spectral range 240–793 nm. The features of the instrument relevant to the aerosol retrieval task are its high relative radiometric accuracy (better than 1%), its spectral coverage, and its spectral resolution, which allows wavelengths in spectral regions free of molecular absorption (atmospheric windows) to be selected. The method presented is based on a pseudo‐inversion approach in which measured reflectance spectra are fitted to simulated equivalents computed using a suitable radiative transfer model. The crucial aspects of this method are the high accuracy and the nonapproximate nature of the radiative transfer model, which simulates the spectra during the fitting procedure, and careful selection of candidate aerosol classes. A test application of the proposed method to a Saharan dust outbreak which occurred in June 1997 is presented, showing that in spite of the instrument's low spatial resolution, information on both optical thickness and spectral characterization of the aerosol can be retrieved from GOME data. Preliminary comparisons of the results with independent estimates of the aerosol content show that a good correlation exists, encouraging planning of a systematic application of the method.

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Available abstract

Satellite monitoring of aerosol properties using passive techniques is widely considered a crucial tool for the study of climatic effects of atmospheric particulate [Kaufman et al., 1997]. Only space‐based observations can provide the required global coverage information on spatial distribution and temporal variation of the aerosol field. This paper describes a method for deriving aerosol optical thickness at 500 nm and aerosol type from Global Ozone Monitoring Experiment (GOME) data over the ocean under cloud‐free conditions. GOME, flying on board the second European Remote Sensing satellite (ERS 2) since April 1995, is a spectrometer that measures radiation reflected from Earth in the spectral range 240–793 nm. The features of the instrument relevant to the aerosol retrieval task are its high relative radiometric accuracy (better than 1%), its spectral coverage, and its spectral resolution, which allows wavelengths in spectral regions free of molecular absorption (atmospheric windows) to be selected. The method presented is based on a pseudo‐inversion approach in which measured reflectance spectra are fitted to simulated equivalents computed using a suitable radiative transfer model. The crucial aspects of this method are the high accuracy and the nonapproximate nature of the radiative transfer model, which simulates the spectra during the fitting procedure, and careful selection of candidate aerosol classes. A test application of the proposed method to a Saharan dust outbreak which occurred in June 1997 is presented, showing that in spite of the instrument's low spatial resolution, information on both optical thickness and spectral characterization of the aerosol can be retrieved from GOME data. Preliminary comparisons of the results with independent estimates of the aerosol content show that a good correlation exists, encouraging planning of a systematic application of the method.

Key concepts: Aerosol, Remote sensing, Environmental science, Radiative transfer, Satellite, Atmospheric radiative transfer codes, Spectrometer, Spectral resolution

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