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Global maps of the Earth's surface Lambertian equivalent reflectance (LER) are constructed using 3 years of Ozone Monitoring Instrument (OMI) measurements obtained between October 2004 and October 2007 at 23 wavelengths between 328 and 500 nm. The maps are constructed on a 0.5° by 0.5° longitude‐latitude grid for each calendar month using an algorithm based on temporal histograms of the observed LER values per geophysical location. The algorithm allows seasonal effects related to vegetation, snow, and ice but excludes statistical outliers. The maps show typical features like open ocean regions with high reflectivity indicative of low phytoplankton levels, coastal waters with high reflectance caused by silt, and oceanic regions with low reflectance correlated with chlorophyll. Open oceans in general have a higher reflectivity than does land up to 420 nm. The highest reflectivity values of oceans occur at 380 nm. Good agreement is found with a similar LER map based on data from the Total Ozone Mapping Spectrometer (TOMS) at 331, 340, 360, and 380 nm, which is 0.015 lower on average. The comparison with data from the Global Ozone Monitoring Experiment (GOME) at 335, 380, 440, and 494 nm is also satisfactory, being 0.005 lower on average. The LER derived from OMI data is approximately 0.02 higher than the black sky albedo as derived from the Moderate Resolution Imaging Spectroradiometer at 470 nm, which is partly related to viewing geometry effects of the bidirectional reflectance distribution function of the surface. The data set presented contains residual cloud features over tropical rain forest regions, has a higher spatial resolution than those created using TOMS and GOME data, and includes more wavelengths.

A global database of Lambert‐equivalent reflectivity (LER) of the Earth's surface has been constructed by analyzing observations of the reflectivity at the top of the atmosphere made by the Global Ozone Monitoring Experiment (GOME). Since its launch on board the ERS‐2 satellite in April 1995, the GOME instrument has been measuring spectra of the Earth between 237 and 794 nm, with a spectral resolution between 0.2 and 0.4 nm and a spatial resolution between 40 × 80 and 40 × 320 km2. The LER database covers eleven 1‐nm‐wide wavelength bins centered at 335, 380, 416, 440, 463, 494.5, 555, 610, 670, 758, and 772 nm, which were selected for various retrieval applications. The database has a spatial resolution of 1° × 1°, is made for each month of the year, and pertains to the period June 1995–December 2000. Typical spectra of various surface types are presented. Attention is paid to instrument degradation and residual cloud contamination. We have found satisfactory agreement between our database at 380 nm and the Total Ozone Mapping Spectrometer (TOMS) LER database at 340–380 nm, with negligible average difference and a standard deviation of 0.013. The database presented here can be used to improve retrievals of trace gases, clouds and aerosols from GOME, Scanning Imaging Absorption Spectrometer or Atmospheric Cartography (SCIAMACHY), Ozone Monitoring Instrument (OMI), and GOME‐2.

[1] We present an operational method for cloud pressure retrieval from the Earth's reflectance spectrum in the visible, using the O 2 -O 2 absorption band at 477 nm. The algorithm is simple and robust. Apart from cloud pressure, an effective cloud fraction is also retrieved. Using simulations and Global Ozone Monitoring Instrument (GOME) data the accuracy of the O 2 -O 2 retrieval method is estimated. The Ozone Monitoring Instrument (OMI), to be space-borne on board the EOS-AURA platform in 2004, will use this algorithm to produce an official cloud product. The cloud product will be used to support the cloud correction of several of the OMI trace gas retrievals.

Abstract. We present measured scattering matrices as functions of the scattering angle in the range 5ø-173 ø and at wavelengths of 441.6 nra and 632.8 nra for seven distinct irregularly shaped mineral aerosol samples with properties representative of mineral aerosols present in the Earth's atmosphere. The aerosol samples, i.e., feldspar, red clay, quartz, loess, Pinatubo and Lokon volcanic ash, and Sahara sand, represent a wide variety of particle size (typical diameters between 0.1 and 100 pra) and composition (mainly silicates). We investigate the effects of differences in size and complex refractive index on the light-scattering properties of these irregular particles. In particular, we find that the measured scattering matrix elements when plotted as functions of the scattering angle are confined to rather limited domains. This similarity in scattering behavior justifies the construction of an average aerosol scattering matrix as a function of scattering angle to facilitate, for example, the use of our results for the interpretation of remote sensing data. We show that results of ray-optics calculations, using Gaussian random shapes, are able to describe the experimental data well when taking into account the high irregularity in shape of the aerosols, even when these aerosols are rather small. Using the results of ray-optics calculations, we interpret the differences found between the measured aerosol scattering matrices in terms of differences in complex refractive index and particle size relative to the wavelength. The importance of our results for studies of astronomical objects, such as planets, comets, asteroids, and circumstellar dust shells is discussed.

Abstract. The Global Ozone Monitoring Experiment (GOME) on board the ERS-2 isdesigned to measure trace gas column densities in the Earth's atmosphere. Such retrievals are hindered by the presence of clouds. The most important cloud parameters that are needed to correct trace gas column density retrievals for the disturbing effects of clouds are the (effective) cloud fraction and cloud top pressure. At present, in the operational GOME data processor an effective cloud fraction is derived for each pixel, but cloud top pressure is assumed a priori and is deduced from a climatological database. Here we report an improved cloud retrieval scheme, which simultaneously retrieves the effective cloud fraction and cloud top pressure from GOME data.

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