Abstract. This overview paper highlights the successes of the Ozone Monitoring Instrument (OMI) on board the Aura satellite spanning a period of nearly 14 years. Data from OMI has been used in a wide range of applications and research resulting in many new findings. Due to its unprecedented spatial resolution, in combination with daily global coverage, OMI plays a unique role in measuring trace gases important for the ozone layer, air quality, and climate change. With the operational very fast delivery (VFD; direct readout) and near real-time (NRT) availability of the data, OMI also plays an important role in the development of operational services in the atmospheric chemistry domain.

Producing a global and comprehensive description of atmospheric aerosols requires integration of ground-based, airborne, satellite and model datasets. Due to its complexity, aerosol monitoring requires the use of several data records with complementary information

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.

Abstract. An algorithm setup for the operational Aerosol Layer Height product for TROPOMI on the Sentinel-5 Precursor mission is described and discussed, applied to GOME-2A data, and evaluated with lidar measurements. The algorithm makes a spectral fit of reflectance at the O 2 A band in the near-infrared and the fit window runs from 758 to 770 nm. The aerosol profile is parameterised by a scattering layer with constant aerosol volume extinction coefficient and aerosol single scattering albedo and with a fixed pressure thickness. The algorithm's target parameter is the height of this layer. In this paper, we apply the algorithm to observations from GOME-2A in a number of systematic and extensive case studies, and we compare retrieved aerosol layer heights with lidar measurements. Aerosol scenes cover various aerosol types, both elevated and boundary layer aerosols, and land and sea surfaces. The aerosol optical thicknesses for these scenes are relatively moderate. Retrieval experiments with GOME-2A spectra are used to investigate various sensitivities, in which particular attention is given to the role of the surface albedo.From retrieval simulations with the single-layer model, we learn that the surface albedo should be a fit parameter when retrieving aerosol layer height from the O 2 A band. Current uncertainties in surface albedo climatologies cause biases and non-convergences when the surface albedo is fixed in the retrieval. Biases disappear and convergence improves when the surface albedo is fitted, while precision of retrieved aerosol layer pressure is still largely within requirement levels. Moreover, we show that fitting the surface albedo helps to ameliorate biases in retrieved aerosol layer height when the assumed aerosol model is inaccurate. Subsequent retrievals with GOME-2A spectra confirm that convergence is better when the surface albedo is retrieved simultaneously with aerosol parameters. However, retrieved aerosol layer pressures are systematically low (i.e., layer high in the atmosphere) to the extent that retrieved values no longer realistically represent actual extinction profiles. When the surface albedo is fixed in retrievals with GOME-2A spectra, convergence deteriorates as expected, but retrieved aerosol layer pressures become much higher (i.e., layer lower in atmosphere). The comparison with lidar measurements indicates that retrieved aerosol layer heights are indeed representative of the underlying profile in that case. Finally, subsequent retrieval simulations with two-layer aerosol profiles show that a model error in the assumed profile (two layers in the simulation but only one in the retrieval) is partly absorbed by the surface albedo when this parameter is fitted. This is expected in view of the correlations between errors in fit parameters and the effect is relatively small for elevated layers (less than 100 hPa). If one of the scattering layers is near the surface (boundary layer aerosols), the effect becomes surprisingly large, in such a way that the retrieved height of the sin...

[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,