Abstract. The FRESCO (Fast Retrieval Scheme for Clouds from the Oxygen A-band) algorithm has been used to retrieve cloud information from measurements of the O 2 Aband around 760 nm by GOME, SCIAMACHY and GOME-2. The cloud parameters retrieved by FRESCO are the effective cloud fraction and cloud pressure, which are used for cloud correction in the retrieval of trace gases like O 3 and NO 2 . To improve the cloud pressure retrieval for partly cloudy scenes, single Rayleigh scattering has been included in an improved version of the algorithm, called FRESCO+. We compared FRESCO+ and FRESCO effective cloud fractions and cloud pressures using simulated spectra and one month of GOME measured spectra. As expected, FRESCO+ gives more reliable cloud pressures over partly cloudy pixels. Simulations and comparisons with ground-based radar/lidar measurements of clouds show that the FRESCO+ cloud pressure is about the optical midlevel of the cloud. Globally averaged, the FRESCO+ cloud pressure is about 50 hPa higher than the FRESCO cloud pressure, while the FRESCO+ effective cloud fraction is about 0.01 larger.The effect of FRESCO+ cloud parameters on O 3 and NO 2 vertical column density (VCD) retrievals is studied using SCIAMACHY data and ground-based DOAS measurements. We find that the FRESCO+ algorithm has a significant effect on tropospheric NO 2 retrievals but a minor effect on total O 3 retrievals. The retrieved SCIAMACHY tropospheric NO 2 VCDs using FRESCO+ cloud parameters (v1.1) are lower than the tropospheric NO 2 VCDs which used FRESCO cloud parameters (v1.04), in particular over heavily polluted areas with low clouds. The difference between

The primary goal of this paper is to introduce two new surface reflectivity climatologies. The two databases contain the Lambertian‐equivalent reflectivity (LER) of the Earth's surface, and they are meant to support satellite retrieval of trace gases and of cloud and aerosol information. The surface LER databases are derived from the Global Ozone Monitoring Experiment (GOME)‐2 and Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) instruments and can be considered as improved and extended descendants of earlier surface LER climatologies based on the Total Ozone Mapping Spectrometer (TOMS), GOME‐1, and Ozone Monitoring Instrument (OMI) instruments. The GOME‐2 surface LER database consists of 21 wavelength bands that span the wavelength range from 335 to 772 nm. The SCIAMACHY surface LER database covers the wavelength range between 335 and 1670 nm in 29 wavelength bands. The two databases are made for each month of the year, and their spatial resolution is 1° × 1°. In this paper we present the methods that are used to derive the surface LER; we analyze the spatial and temporal behavior of the surface LER fields and study the amount of residual cloud contamination in the databases. For several surface types we analyze the spectral surface albedo and the seasonal variation. When compared to the existing surface LER databases, both databases are found to perform well. As an example of possible application of the databases we study the performance of the Fast Retrieval Scheme for Clouds from the Oxygen A‐band (FRESCO) cloud information retrieval when it is equipped with the new surface albedo databases. We find considerable improvements. The databases introduced here can not only improve retrievals from GOME‐2 and SCIAMACHY but also support those from other instruments, such as TROPOspheric Monitoring Instrument (TROPOMI), to be launched in 2017.

[1] The solar radiative absorption by an aerosol layer above clouds is quantified using passive satellite spectrometry from the ultraviolet (UV) to the shortwave infrared (SWIR). UV-absorbing aerosols have a strong signature that can be detected using UV reflectance measurements, even when above clouds. Since the aerosol extinction optical thickness decreases rapidly with increasing wavelength for biomass burning aerosols, the properties of the clouds below the aerosol layer can be retrieved in the SWIR, where aerosol extinction optical thickness is sufficiently small. Using radiative transfer computations, the contribution of the clouds to the reflected radiation can be modeled for the entire solar spectrum. In this way, cloud and aerosol effects can be separated for a scene with aerosols above clouds. Aerosol microphysical assumptions and retrievals are avoided by modeling only the pure (aerosol-free) cloud spectra. An algorithm was developed using the spaceborne spectrometer Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY). The aerosol direct radiative effect (DRE) over clouds over the South Atlantic Ocean west of Africa, averaged through August 2006 was found to be 23 AE 8 Wm À2 with a mean variation over the region in this month of 22 Wm À2 . The largest aerosol DRE over clouds found in that month was 132 AE 8 Wm À2 . The algorithm can be applied to any instrument, or a combination of instruments, that measures UV, visible and SWIR reflectances at the top of the atmosphere (TOA) simultaneously.Citation: de Graaf, M., L. G. Tilstra, P. Wang, and P. Stammes (2012), Retrieval of the aerosol direct radiative effect over clouds from spaceborne spectrometry,

[1] This paper discusses Surface Insolation under Clear and Cloudy skies derived from SEVIRI imagery (SICCS), a physics-based, empirically adjusted algorithm developed for estimation of surface solar irradiance from satellite data. Its most important input are a cloud mask product and cloud properties derived from Meteosat/Spinning Enhanced Visible and Infrared Imager (SEVIRI) observations. These observations set the characteristics of the output, namely, a temporal resolution of 15 min, a nadir spatial resolution of 3 Â 3 km 2 , the period from January 2004 until at least November 2012, and the domain equal to most of the Meteosat disc. SICCS computes global, direct, and diffuse irradiance separately. Direct irradiance for cloudy skies is estimated with an empirical method. Hourly means retrieved with SICCS were validated with data from eight Baseline Surface Radiation Network stations for the year 2006. We found median values of the station biases of +6 W/m 2 (+5%) for direct irradiance, +1 W/m 2 (+1%) for diffuse irradiance, and +7 W/m 2 (+2%) for global irradiance. Replacing the three-hourly aerosol optical thickness input by monthly means introduces considerable additional biases in the clear-sky direct (À6%) and diffuse (+26%) irradiances. The performance of SICCS does not degrade when snow covers the surface. Biases do not vary with cloud optical thickness and cloud particle radius. However, the bias in global transmissivity tends to decrease with increasing cloud heterogeneity, and the bias in direct transmissivity is a function of the solar zenith angle. We discuss why satellite retrieval of surface solar irradiance is relatively successful.Citation: Greuell W., J. F. Meirink, and P. Wang (2013), Retrieval and validation of global, direct, and diffuse irradiance derived from SEVIRI satellite observations,

Abstract. The FRESCO (Fast Retrieval Scheme for Clouds from the Oxygen A-band) algorithm has been used to retrieve cloud information from measurements of the O2 A-band around 760 nm by GOME, SCIAMACHY and GOME-2. The cloud parameters retrieved by FRESCO are the effective cloud fraction and cloud pressure, which are used for cloud correction in the retrieval of trace gases like O3 and NO2. To improve the cloud pressure retrieval for partly cloudy scenes, single Rayleigh scattering has been included in an improved version of the algorithm, called FRESCO+. We compared FRESCO+ and FRESCO effective cloud fractions and cloud pressures using simulated spectra and one month of GOME measured spectra. As expected, FRESCO+ gives more reliable cloud pressures over partly cloudy pixels. Simulations and comparisons with ground-based radar/lidar measurements of clouds shows that the FRESCO+ cloud pressure is about the optical midlevel of the cloud. Globally averaged, the FRESCO+ cloud pressure is about 50 hPa higher than the FRESCO cloud pressure, while the FRESCO+ effective cloud fraction is about 0.01 larger. The effect of FRESCO+ cloud parameters on O3 and NO2 vertical column densities (VCD) is studied using SCIAMACHY data and ground-based DOAS measurements. We find that the FRESCO+ algorithm has a significant effect on tropospheric NO2 retrievals but a minor effect on total O3 retrievals. The retrieved SCIAMACHY tropospheric NO2 VCDs using FRESCO+ cloud parameters (v1.1) are lower than the tropospheric NO2 VCDs which used FRESCO cloud parameters (v1.04), in particular over heavily polluted areas with low clouds. The difference between SCIAMACHY tropospheric NO2 VCDs v1.1 and ground-based MAXDOAS measurements performed in Cabauw, The Netherlands, during the DANDELIONS campaign is about −2.12×1014 molec cm−2.