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.

A new fast clear-sky model called McClear was developed to estimate the downwelling shortwave direct and global irradiances received at ground level under clear skies. It is a fully physical model replacing empirical relations or simpler models used before. It exploits the recent results on aerosol properties, and total column content in water vapour and ozone produced by the MACC project (Monitoring Atmosphere Composition and Climate). It accurately reproduces the irradiance computed by the libRadtran reference radiative transfer model with a computational speed approximately 10⁵ times greater by adopting the abaci, or look-up table, approach combined with interpolation functions. It is therefore suited for geostationary satellite retrievals or numerical weather prediction schemes with many pixels or grid points, respectively. McClear irradiances were compared to 1 min measurements made in clear-sky conditions at several stations within the Baseline Surface Radiation Network in various climates. The bias for global irradiance comprises between −6 and 25 W m⁻². The RMSE ranges from 20 W m⁻² (3% of the mean observed irradiance) to 36 W m⁻² (5%) and the correlation coefficient ranges between 0.95 and 0.99. The bias for the direct irradiance comprises between −48 and +33 W m⁻². The root mean square error (RMSE) ranges from 33 W m⁻² (5%) to 64 W m⁻² (10%). The correlation coefficient ranges between 0.84 and 0.98. This work demonstrates the quality of the McClear model combined with MACC products, and indirectly the quality of the aerosol properties modelled by the MACC reanalysis

Part of the Earth Sciences CommonsThis Article is brought to you for free and open access by the Earth and Atmospheric Sciences, Department of at DigitalCommons@University of Nebraska -Lincoln. It has been accepted for inclusion in Papers in the Earth and Atmospheric Sciences by an authorized administrator of DigitalCommons@University of Nebraska -Lincoln.

Abstract. Black carbon, light-absorbing organic carbon (often called "brown carbon") and mineral dust are the major light-absorbing aerosols. Currently the sources and formation of brown carbon aerosol in particular are not well understood. In this study we estimated the amount of light-absorbing organic carbon and black carbon from AERONET measurements. We find that the columnar absorbing organic carbon (brown carbon) levels in biomass burning regions of South America and Africa are relatively high (about 15-20 mg m −2 during biomass burning season), while the concentrations are significantly lower in urban areas in US and Europe. However, we estimated significant absorbing organic carbon amounts from the data of megacities of newly industrialized countries, particularly in India and China, showing also clear seasonality with peak values up to 30-35 mg m −2 during the coldest season, likely caused by the coal and biofuel burning used for heating. We also compared our retrievals with the modeled organic carbon by the global Oslo CTM for several sites. Model values are higher in biomass burning regions than AERONET-based retrievals, while the opposite is true in urban areas in India and China.

[1] Several validation studies of surface UV irradiance based on the Ozone Monitoring Instrument (OMI) satellite data have shown a high correlation with ground-based measurements but a positive bias in many locations. The main part of the bias can be attributed to the boundary layer aerosol absorption that is not accounted for in the current satellite UV algorithms. To correct for this shortfall, a postcorrection procedure was applied, based on global climatological fields of aerosol absorption optical depth. These fields were obtained by using global aerosol optical depth and aerosol single scattering albedo data assembled by combining global aerosol model data and ground-based aerosol measurements from AERONET. The resulting improvements in the satellite-based surface UV irradiance were evaluated by comparing satellite and ground-based spectral irradiances at various European UV monitoring sites. The results generally showed a significantly reduced bias by 5 -20%, a lower variability, and an unchanged, high correlation coefficient.