Abstract. The three Global Ozone Monitoring Experiment-2 instruments will provide unique and long data sets for atmospheric research and applications. The complete time period will be 2007-2022, including the period of ozone depletion as well as the beginning of ozone layer recovery. Besides ozone chemistry, the GOME-2 (Global Ozone Monitoring Experiment-2) products are important e.g. for air quality studies, climate modelling, policy monitoring and hazard warnings. The heritage for GOME-2 is in the ERS/GOME and Envisat/SCIAMACHY instruments. The current Level 2 (L2) data cover a wide range of products such as ozone and minor trace gas columns (NO 2 , BrO, HCHO, H 2 O, SO 2 ), vertical ozone profiles in high and low spatial resolution, absorbing aerosol indices, surface Lambertian-equivalent reflectivity database, clear-sky and cloud-corrected UV indices and surface UV fields with different weightings and photolysis rates. The Satellite Application Facility on Ozone and Atmospheric Chemistry Monitoring (O3M SAF) processes and disseminates data 24/7. Data quality is guaranteed by the detailed review processes for the algorithms, validation of the products as well as by a continuous quality monitoring of the products and processing. This paper provides an overview of the O3M SAF project background, current status and future plans for the utilisation of the GOME-2 data. An important focus is the provision of summaries of the GOME-2 products including product principles and validation examples together with sample images. Furthermore, this paper collects references to the detailed product algorithm and validation papers.

One of the key challenges in polar middle atmosphere research is to quantify the total forcing by energetic particle precipitation (EPP) and assess the related response over solar cycle time scales. This is especially true for electrons having energies between about 30 keV and 1 MeV, so‐called medium‐energy electrons (MEE), where there has been a persistent lack of adequate description of MEE ionization in chemistry‐climate simulations. Here we use the Whole Atmosphere Community Climate Model (WACCM) and include EPP forcing by solar proton events, auroral electron precipitation, and a recently developed model of MEE precipitation. We contrast our results from three ensemble simulations (147 years) in total with those from the fifth phase of the Coupled Model Intercomparison Project (CMIP5) in order to investigate the importance of a more complete description of EPP to the middle atmospheric ozone, odd hydrogen, and odd nitrogen over decadal time scales. Our results indicate average EPP‐induced polar ozone variability of 12–24% in the mesosphere, and 5–7% in the middle and upper stratosphere. This variability is in agreement with previously published observations. Analysis of the simulation results indicate the importance of inclusion of MEE in the total EPP forcing: In addition to the major impact on the mesosphere, MEE enhances the stratospheric ozone response by a factor of 2. In the Northern Hemisphere, where wintertime dynamical variability is larger than in the Southern Hemisphere, longer simulations are needed in order to reach more robust conclusions.

Abstract. In this paper, we present a HARMonized dataset of OZone profiles (HARMOZ) based on limb and occultation measurements from Envisat (GOMOS, MIPAS and SCIAMACHY), Odin (OSIRIS, SMR) and SCISAT (ACE-FTS) satellite instruments. These measurements provide high-vertical-resolution ozone profiles covering the altitude range from the upper troposphere up to the mesosphere in years [2001][2002][2003][2004][2005][2006][2007][2008][2009][2010][2011][2012]. HARMOZ has been created in the framework of the European Space Agency Climate Change Initiative project.The harmonized dataset consists of original retrieved ozone profiles from each instrument, which are screened for invalid data by the instrument teams. While the original ozone profiles are presented in different units and on different vertical grids, the harmonized dataset is given on a common pressure grid in netCDF (network common data form)-4 format. The pressure grid corresponds to vertical sampling of ∼ 1 km below 20 km and 2-3 km above 20 km. The vertical range of the ozone profiles is specific for each instrument, thus all information contained in the original data is preserved. Provided altitude and temperature profiles allow the representation of ozone profiles in number density or mixing ratio on a pressure or altitude vertical grid. Geolocation, uncertainty estimates and vertical resolution are provided for each profile. For each instrument, optional parameters, which are related to the data quality, are also included.For convenience of users, tables of biases between each pair of instruments for each month, as well as bias uncertainties, are provided. These tables characterize the data consistency and can be used in various bias and drift analyses, which are needed, for instance, for combining several datasets to obtain a long-term climate dataset.This user-friendly dataset can be interesting and useful for various analyses and applications, such as data merging, data validation, assimilation and scientific research.The dataset is available at

Abstract. Satellite measurements sample continuous fields of atmospheric constituents at discrete locations and times. However, insufficient or inhomogeneous sampling, if not taken into account, can result in inaccurate average estimates and even induce spurious features. We propose to characterize the spatiotemporal inhomogeneity of atmospheric measurements by a measure, which is a linear combination of the asymmetry and entropy of a sampling distribution. It is shown that this measure is related to the so-called sampling uncertainty, which occurs due to non-uniform sampling patterns.We have estimated the sampling uncertainty of zonal mean ozone profiles for six limb-viewing satellite instruments participating in the European Space Agency Ozone Climate Change Initiative project using the high-resolution ozone field simulated with the FinROSE chemistry-transport model. It is shown that the sampling uncertainty for the instruments with coarse sampling is not negligible and can be as large as a few percent. It is found that the standard deviation of the sampling uncertainty in the monthly zonal mean data allows for a simple parameterization in terms of the product of the standard deviation of natural variations and the proposed inhomogeneity measure. The sampling uncertainty estimates improve the uncertainty quantification and can be used in comprehensive data analyses.The focus of this work is the vertical ozone distributions measured by limb-viewing satellite instruments, but the developed methods can also be applied to different satellite, ground-based and in situ measurements.

Abstract. Spectral solar UV radiation measurements are performed in France using three spectroradiometers located at very different sites. One is installed in Villeneuve d'Ascq, in the north of France (VDA). It is an urban site in a topographically flat region. Another instrument is installed in Observatoire de Haute-Provence, located in the southern French Alps (OHP). It is a rural mountainous site. The third instrument is installed in Saint-Denis, Réunion Island (SDR). It is a coastal urban site on a small mountainous island in the southern tropics. The three instruments are affiliated with the Network for the Detection of Atmospheric Composition Change (NDACC) and carry out routine measurements to monitor the spectral solar UV radiation and enable derivation of UV index (UVI). The ground-based UVI values observed at solar noon are compared to similar quantities derived from the Ozone Monitoring Instrument (OMI, onboard the Aura satellite) and the second Global Ozone Monitoring Experiment (GOME-2, onboard the Metop-A satellite) measurements for validation of these satellite-based products. The present study concerns the period 2009-September 2012, date of the implementation of a new OMI processing tool. The new version (v1.3) introduces a correction for absorbing aerosols that were not considered in the old version (v1.2).Both versions of the OMI UVI products were available before September 2012 and are used to assess the improvement of the new processing tool. On average, estimates from satellite instruments always overestimate surface UVI at solar noon. Under cloudless conditions, the satellite-derived estimates of UVI compare satisfactorily with ground-based data: the median relative bias is less than 8 % at VDA and 4 % at SDR for both OMI v1.3 and GOME-2, and about 6 % for OMI v1.3 and 2 % for GOME-2 at OHP. The correlation between satellite-based and ground-based data is better at VDA and OHP (about 0.99) than at SDR (0.96) for both space-borne instruments. For all sky conditions, the median relative biases are much larger, with large dispersion for both instruments at all sites (VDA: about 12 %; OHP: 9 %; SDR: 11 %). Correlation between satellite-based and ground-based data is still better at VDA and OHP (about 0.95) than at SDR (about 0.73) for both satellite instruments. These results are explained considering the time of overpass of the two satellites, which is far from solar noon, preventing a good estimation of the cloud cover necessary for a good modelling of the UVI. Site topography and environment are shown to have a non-significant influence. At VDA and OHP, OMI Published by Copernicus Publications on behalf of the European Geosciences Union.