[1] The Global Ozone Monitoring Instrument (GOME) was launched on European Space Agency's ERS-2 platform in April 1995. The GOME data processor (GDP) operational retrieval algorithm has generated total ozone columns since July 1995. In 2004 the GDP system was given a major upgrade to version 4.0, a new validation was performed, and the 10-year GOME level 1 data record was reprocessed. In two papers, we describe the GDP 4.0 retrieval algorithm and present an error budget and sensitivity analysis (paper 1) and validation of the GDP total ozone product and the overall accuracy of the entire GOME ozone record (paper 2). GDP 4.0 uses an optimized differential optical absorption spectroscopy (DOAS) algorithm, with air mass factor (AMF) conversions calculated using the radiative transfer code linearized discrete ordinate radiative transfer (LIDORT). AMF computation is based on the TOMS version 8 ozone profile climatology, classified by total column, and AMFs are adjusted iteratively to reflect the DOAS slant column result. GDP 4.0 has improved wavelength calibration and reference spectra and includes a new molecular Ring correction to deal with distortion of ozone absorption features due to inelastic rotational Raman scattering effects. Preprocessing for cloud parameter estimation in GDP 4.0 is done using two new cloud correction algorithms: OCRA and ROCINN. For clear and cloudy scenes the precision of the ozone column product is better than 2.4 and 3.3%, respectively, for solar zenith angles up to 80°. Comparisons with ground-based data are generally at the 1-1.5% level or better for all regions outside the poles.Citation: Van Roozendael, M., et al. (2006), Ten years of GOME/ERS-2 total ozone data-The new GOME data processor (GDP) version 4: 1. Algorithm description,

Abstract. The TROPOspheric Monitoring Instrument (TROPOMI) onboard the Copernicus Sentinel-5 Precursor (S-5P) platform will measure ultraviolet earthshine radiances at high spectral and improved spatial resolution (pixel size of 7 km × 3.5 km at nadir) compared to its predecessors OMI and GOME-2. This paper presents the sulfur dioxide (SO 2 ) vertical column retrieval algorithm implemented in the S-5P operational processor UPAS (Universal Processor for UV/VIS Atmospheric Spectrometers) and comprehensively describes its various retrieval steps. The spectral fitting is performed using the differential optical absorption spectroscopy (DOAS) method including multiple fitting windows to cope with the large range of atmospheric SO 2 columns encountered. It is followed by a slant column background correction scheme to reduce possible biases or across-track-dependent artifacts in the data. The SO 2 vertical columns are obtained by applying air mass factors (AMFs) calculated for a set of representative a priori profiles and accounting for various parameters influencing the retrieval sensitivity to SO 2 . Finally, the algorithm includes an error analysis module which is fully described here. We also discuss verification results (as part of the algorithm development) and future validation needs of the TROPOMI SO 2 algorithm.

Abstract. We report on updated trends using different merged datasets from satellite and ground-based observations for the period from 1979 to 2016. Trends were determined by applying a multiple linear regression

We use height-resolved and total column satellite observations and 3-D chemical transport model simulations to study stratospheric ozone variations during 1998-2017 as ozone-depleting substances decline. In 2017 extrapolar lower stratospheric ozone displayed a strong positive anomaly following much lower values in 2016. This points to large interannual variability rather than an ongoing downward trend, as reported recently by Ball et al. (2018Ball et al. ( , https://doi.org/10.5194/acp-18-1379Ball et al. ( -2018. The observed ozone variations are well captured by the chemical transport model throughout the stratosphere and are largely driven by meteorology. Model sensitivity experiments show that the contribution of past trends in short-lived chlorine species to the ozone changes is small. Similarly, the potential impact of modest trends in natural brominated short-lived species is small. These results confirm the important role that atmospheric dynamics plays in controlling ozone in the extrapolar lower stratosphere on multiannual time scales and the continued importance of monitoring ozone profiles as the stratosphere changes.Plain Language Summary Emission of long-lived chlorine and bromine-containing ozone-depleting substances has led to the depletion of the ozone layer, most notably the Antarctic ozone hole. Policy action through the Montreal Protocol has phased out the production of the major long-lived ozone-depleting substances. Consequently, stratospheric chlorine and bromine amounts are declining, and we expect the ozone layer to slowly recover. However, although the tropical lower stratosphere is not a region where large ozone loss has so-far been observed, a recent study by Ball et al. (2018) suggested that ozone there is decreasing, in disagreement with models and expectations of ozone recovery. We use updated observations and an atmospheric model to investigate these issues. First, we use an additional year of observations which show that ozone values in the lower stratosphere increased in 2017, which is a consequence of variations in atmospheric dynamics. Second, our 3-D model performs well in reproducing the observed ozone variations. Although the model is not perfect, the comparisons suggest that we do have a good understanding of the lower stratospheric ozone. Third, we quantify the role of short-lived chlorine and bromine compounds, which are not controlled by the Montreal Protocol, on the recent ozone changes. The effect is small.

Abstract. This paper presents the operational cloud retrieval algorithms for the TROPOspheric Monitoring Instrument (TROPOMI) on board the European Space Agency Sentinel-5 Precursor (S5P) mission scheduled for launch in 2017.Two algorithms working in tandem are used for retrieving cloud properties: OCRA (Optical Cloud Recognition Algorithm) and ROCINN (Retrieval of Cloud Information using Neural Networks). OCRA retrieves the cloud fraction using TROPOMI measurements in the ultraviolet (UV) and visible (VIS) spectral regions, and ROCINN retrieves the cloud top height (pressure) and optical thickness (albedo) using TROPOMI measurements in and around the oxygen A-band in the near infrared (NIR).Cloud parameters from TROPOMI/S5P will be used not only for enhancing the accuracy of trace gas retrievals but also for extending the satellite data record of cloud information derived from oxygen A-band measurements, a record initiated with the Global Ozone Monitoring Experiment (GOME) on board the second European Remote-Sensing Satellite (ERS-2) over 20 years ago.The OCRA and ROCINN algorithms are integrated in the S5P operational processor UPAS (Universal Processor for UV/VIS/NIR Atmospheric Spectrometers), and we present here UPAS cloud results using the Ozone Monitoring Instrument (OMI) and GOME-2 measurements. In addition, we examine anticipated challenges for the TROPOMI/S5P cloud retrieval algorithms, and we discuss the future validation needs for OCRA and ROCINN.