A new method was developed to estimate the cloud optical depth (τ_c) from photovoltaic (PV) power measurements under overcast sky conditions. It is a fully physical method utilizing directly PV power measurements. It exploits the recent advances and real-time availability at global scale of aerosol properties, downwelling shortwave irradiance and its direct and diffuse components received at ground level under clear-sky conditions and ground albedo, altogether provided by the Copernicus Atmosphere Monitoring Service (CAMS) radiation service. In addition to CAMS data, wind speed and air temperature from European Centre for Medium-Range Weather Forecasts twentieth century reanalysis ERA5 products are also used as inputs. The τ_c estimates have been compared to different data sources of τ_c retrievals at four experimental PV sites located in various climates. When compared to τ_c retrieved from groundbased pyranometer measurements serving as reference, the correlation coefficient is greater than 0.97. The bias ranges between -3 and 4, i.e., -8 % and 14 % in relative value. The root mean square error (RMSE) lies in the interval [3,8] ([9,21] % in relative value). When compared to satellitebased retrievals from Meteosat Second Generation and Moderate Resolution Imaging Spectroradiometer, both relative errors become comprehensively greater. Nevertheless, our method remarkably reduces the relative bias and RMSE, by up to 10 % and 20 % respectively, compared to the existing state-of-the-art approach. This work demonstrates the accuracy of the method and clearly shows its great potential use whenever PV power measurements are available.

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.