Francesca Torricella

Atmospheric aerosol optical properties: a database of radiative characteristics for different components and classes

A database management system has been realized that, by taking physical and chemical properties (the complex refractive index and the size distribution) of basic components as its starting point, allows the user to obtain optical properties of default as well as user-defined aerosol classes. Default classes are defined in accordance with the most widely known and used aerosol models. We obtain user-defined classes by varying the mixing ratio of components, creating new mixtures of default components, or by defining user components, thereby supplying the size distribution and the refractive index. The effect of relative humidity (RH) on the refractive index and the size distribution is properly accounted for up to RH = 99%. The two known mechanisms of obtaining classes from components are allowed (internal or external mixing).

Simulations of time‐coincident, co‐located measurements from ENVISAT‐1 instruments for the characterization of tropospheric aerosols: a sensitivity study including cloud contamination effects

Abstract A sensitivity test of the aerosol properties retrieval is conducted using nadir viewing instruments on board the ENVISAT-1 platform trying to reproduce the natural variability of the aerosol field. The analysis highlights problems arising in the retrieval when aerosol loading, relative humidity, and cloud coverage are simultaneously varied.

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

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 instruments 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.

Aerosol optical thickness and classification: use of METEOSAT, GOME, and modeled data

Satellite measurements at high spectral resolution and span that avoid gas absorption bands and determine aerosol spectral optical properties are necessary for obtaining aerosol optical thickness values at the reference wavelength of 550 nm (hereinafter AOT). GOME (Global Ozone Monitoring Experiment on board the ERS-2 spacecraft) measurements fit such requirements, with a suitable spectral resolution over the region between UV and near IR while presenting a low spatial (320 X 40 Km2) and temporal resolution. The present new method overcomes these limitations by combining aerosol optical characteristics retrieved from GOME with METEOSAT visible data; the latter allow for monitoring aerosol events with adequate temporal resolution over wide cloud-free oceanic areas. The AOT results from fitting the measured broad-band visible METEOSAT radiance with the simulated radiance from radiative transfer calculations; aerosol properties estimated from GOME data are the essential input parameters. Several parameterizations of aerosol microphysical quantities have been tested to improve the AOT retrievals.

Characterization of plumes on top of deep convective storm using AVHRR imagery and radiative transfer simulations

Abstract Cirrus clouds often form on top of intense convective storms and influence the radiation exchange at the top of the atmosphere. From time to time these cirrus assume a typical plume form, whose origin is yet to be clearly explained. Investigation on plumes structure and composition is necessary using satellite observations and radiative transfer modeling, since in situ measurements are generally not available for the storms extreme scenarios. Plumes of ice crystals produce a significant increase of cloud top reflectivity in channel 3 (3.55–3.93 μm) of National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR), due to the small size of the crystals (of the order of the channel wavelength). AVHRR measurements over a severe storm are compared with radiative transfer simulations through a 1-D, plane-parallel radiative transfer model (RTM). The hydrometeor vertical distribution of a cumulonimbus tower is assumed, composed of a water droplet layer underlying an ice crystal layer. The presence of the plume on top of the cumulonimbus is simulated by an ice crystal layer whose optical depth and ice crystal size and habit are varied. The results of the comparisons show that channel 3 conveys relevant information on the ice crystal size and habit.

Lessons learned from synergistic use of polar and geostationary satellite sensors for the retrieval of aerosol characteristics

The interest in aerosol observations from satellite passive instrument is steadily increasing since satellite instruments supply unique global observations for establishing an aerosol climatology. A correct characterization of single aerosol events from satellite requires adequate temporal and spatial resolution. Most state-of-the-art algorithms are based on a single sensor, so that they often suffer from specific limitations: poor spatial or spectral resolution, large re-visitation time, poor de-clouding,... A method to exploit the synergy between the polar orbiting instrument GOME (Global Ozone Monitoring Experiment) and the METEOSAT geostationary system was proposed, aiming at increasing the accuracy of the aerosol characterization over the ocean by determining with GOME the actual aerosol model to be adopted for aerosol optical thickness determination with METEOSAT. Applications of the algorithm to relevant aerosol events are presented characterizing aerosol optical properties and thickness. The comparison with results obtained via independent space-time co-located ground-based measurements and retrievals from other algorithms that make use of satellite measurements such as POLDER, allows for a first validation of the algorithm. Comparisons also address limitations of the retrieved aerosol model in terms of time-space coverage.

Aerosol optical thickness retrieval from GOME spectra

The GOME instrument, on board the ERS-2 satellite, has been designed in order to collect radiation over the entire wavelength region from 240 to 790 nm, in which several atmospheric species and also aerosols and clouds can be observed. A prototypal processor for the aerosol optical thickness retrieval and aerosol classification starting from GOME data has been developed. This processor has been devised as a tool to be used for the development of an operational GOME data processing chain. The implemented retrieval algorithm is based on a spectral reflectance fitting procedure of the measured radiances by GOME instrument. The maximum likelihood principle has been used in order to define the objective function. The ranking is made choosing the minimum among the least squares residuals computed for different aerosol classes. For each pixel the output of processor gives the aerosol optical thickness, the aerosol classification, a relative retrieval residual and a flag that indicates if the pixel is cloudy. The results of some different GOME real data sets are shown.