Abstract. This paper describes the pre-operational analysis and forecasting system developed during MACC (Monitoring Atmospheric Composition and Climate) and continued in the MACC-II (Monitoring Atmospheric Composition and Climate: Interim Implementation) European projects to provide air quality services for the European continent. This system is based on seven state-of-the art models developed and run in Europe (CHIMERE, EMEP, EURAD-IM, LOTOS-EUROS, MATCH, MOCAGE and SILAM). These models are used to calculate multi-model ensemble products. The paper gives an overall picture of its status at the end of MACC-II (summer 2014) and analyses the performance of the multimodel ensemble. The MACC-II system provides daily 96 h forecasts with hourly outputs of 10 chemical species/aerosols (O 3 , NO 2 , SO 2 , CO, PM 10 , PM 2.5 , NO, NH 3 , total NMVOCs (non-methane volatile organic compounds) and PAN+PAN Published by Copernicus Publications on behalf of the European Geosciences Union. V. Marécal et al.:A regional air quality forecasting system over Europe precursors) over eight vertical levels from the surface to 5 km height. The hourly analysis at the surface is done a posteriori for the past day using a selection of representative air quality data from European monitoring stations.The performance of the system is assessed daily, weekly and every 3 months (seasonally) through statistical indicators calculated using the available representative air quality data from European monitoring stations. Results for a case study show the ability of the ensemble median to forecast regional ozone pollution events. The seasonal performances of the individual models and of the multi-model ensemble have been monitored since September 2009 for ozone, NO 2 and PM 10 . The statistical indicators for ozone in summer 2014 show that the ensemble median gives on average the best performances compared to the seven models. There is very little degradation of the scores with the forecast day but there is a marked diurnal cycle, similarly to the individual models, that can be related partly to the prescribed diurnal variations of anthropogenic emissions in the models. During summer 2014, the diurnal ozone maximum is underestimated by the ensemble median by about 4 µg m −3 on average. Locally, during the studied ozone episodes, the maxima from the ensemble median are often lower than observations by 30-50 µg m −3 . Overall, ozone scores are generally good with average values for the normalised indicators of 0.14 for the modified normalised mean bias and of 0.30 for the fractional gross error. Tests have also shown that the ensemble median is robust to reduction of ensemble size by one, that is, if predictions are unavailable from one model. Scores are also discussed for PM 10 for winter 2013-1014. There is an underestimation of most models leading the ensemble median to a mean bias of −4.5 µg m −3 . The ensemble median fractional gross error is larger for PM 10 (∼ 0.52) than for ozone and the correlation is lower (∼ 0.35 for PM 10 and ∼ 0.54 for ...

Abstract. Accurate and temporally resolved fields of freetroposphere ozone are of major importance to quantify the intercontinental transport of pollution and the ozone radiative forcing. We consider a global chemical transport model (MOdèle de Chimie Atmosphérique à Grande Échelle, MOCAGE) in combination with a linear ozone chemistry scheme to examine the impact of assimilating observations from the Microwave Limb Sounder (MLS) and the Infrared Atmospheric Sounding Interferometer (IASI). The assimilation of the two instruments is performed by means of a variational algorithm (4D-VAR) and allows to constrain stratospheric and tropospheric ozone simultaneously. The analysis is first computed for the months of August and November 2008 and validated against ozonesonde measurements to verify the presence of observations and model biases. Furthermore, a longer analysis of 6 months (July-December 2008) showed that the combined assimilation of MLS and IASI is able to globally reduce the uncertainty (root mean square error, RMSE) of the modeled ozone columns from 30 to 15 % in the upper troposphere/lower stratosphere (UTLS, 70-225 hPa). The assimilation of IASI tropospheric ozone observations (1000-225 hPa columns, TOC -tropospheric O 3 column) decreases the RMSE of the model from 40 to 20 % in the tropics (30 • S-30 • N), whereas it is not effective at higher latitudes. Results are confirmed by a comparison with additional ozone data sets like the Measurements of OZone and wAter vapour by aIrbus in-service airCraft (MOZAIC) data, the Ozone Monitoring Instrument (OMI) total ozone columns and several high-altitude surface measurements. Finally, the analysis is found to be insensitive to the assimilation parameters. We conclude that the combination of a simplified ozone chemistry scheme with frequent satellite observations is a valuable tool for the longterm analysis of stratospheric and free-tropospheric ozone.

Abstract. This paper presents results of the extensive field campaign CLACE 2010 (Cloud and Aerosol Characterization Experiment) performed in summer 2010 at the Jungfraujoch (JFJ) and the Kleine Scheidegg (KLS) in the Swiss Alps. The main goal of this campaign was to investigate the vertical variability of aerosol optical properties around the JFJ and to show the consistency of the different employed measurement techniques considering explicitly the effects of relative humidity (RH) on the aerosol light scattering. Various aerosol optical and microphysical parameters were recorded using in-situ and remote sensing techniques. In-situ measurements of aerosol size distribution, light scattering, light absorption and scattering enhancement due to water uptake were performed at the JFJ at 3580 m a.s.l.. A unique set-up allowed remote sensing measurements of aerosol columnar and vertical properties from the KLS located about 1500 m below and within the line of sight to the JFJ (horizontal distance of approx. 4.5 km). In addition, two satellite retrievals from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) and the Moderate Resolution Imaging Spectroradiometer (MODIS) as well as back trajectory analyses were added to the comparison to account for a wider geographical context. All in-situ and remote sensing measurements were in clear correspondence. The ambient extinction coefficient measured in situ at the JFJ agreed well with the KLSbased LIDAR (Light Detection and Ranging) retrieval at the altitude-level of the JFJ under plausible assumptions on the LIDAR ratio. However, we can show that the quality of this comparison is affected by orographic effects due to the exposed location of the JFJ on a saddle between two mountains and next to a large glacier. The local RH around the JFJ was often higher than in the optical path of the LIDAR measurement, especially when the wind originated from the south via the glacier, leading to orographic clouds which remained lower than the LIDAR beam. Furthermore, the dominance of long-range transported Saharan dust was observed in all measurements for several days, however only for a shorter time period in the in-situ measurements due to the vertical structure of the dust plume. The optical properties of the aerosol column retrieved from SEVIRI and MODIS showed the same magnitude and a similar temporal evolution as the measurements at the KLS and the JFJ. Remaining differences are attributed to the complex terrain and simplifications in the aerosol retrieval scheme in general.

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Abstract. In this study, we describe the development of the aerosol optical depth (AOD) assimilation module in the chemistry transport model (CTM) MOCAGE (Modèle de Chimie Atmosphérique à Grande Echelle). Our goal is to assimilate the spatially averaged 2-D column AOD data from the National Aeronautics and Space Administration (NASA) Moderate-resolution Imaging Spectroradiometer (MODIS) instrument, and to estimate improvements in a 3-D CTM assimilation run compared to a direct model run. Our assimilation system uses 3-D-FGAT (first guess at appropriate time) as an assimilation method and the total 3-D aerosol concentration as a control variable. In order to have an extensive validation dataset, we carried out our experiment in the northern summer of 2012 when the pre-ChArMEx (CHemistry and AeRosol MEditerranean EXperiment) field campaign TRAQA (TRAnsport à longue distance et Qualité de l'Air dans le bassin méditerranéen) took place in the western Mediterranean basin. The assimilated model run is evaluated independently against a range of aerosol properties (2-D and 3-D) measured by in situ instruments (the TRAQA size-resolved balloon and aircraft measurements), the satellite Spinning Enhanced Visible and InfraRed Imager (SE-VIRI) instrument and ground-based instruments from the Aerosol Robotic Network (AERONET) network. The evaluation demonstrates that the AOD assimilation greatly improves aerosol representation in the model. For example, the comparison of the direct and the assimilated model run with AERONET data shows that the assimilation increased the correlation (from 0.74 to 0.88), and reduced the bias (from 0.050 to 0.006) and the root mean square error in the AOD (from 0.12 to 0.07). When compared to the 3-D concentration data obtained by the in situ aircraft and balloon measurements, the assimilation consistently improves the model output. The best results as expected occur when the shape of the vertical profile is correctly simulated by the direct model. We also examine how the assimilation can influence the modelled aerosol vertical distribution. The results show that a 2-D continuous AOD assimilation can improve the 3-D vertical profile, as a result of differential horizontal transport of aerosols in the model.

[1] Aerosol spatial distribution in populated mountain areas is very heterogeneous and often characterized by scales of variability of several kilometers. Satellites provide an effective tool to map aerosols on an operational basis, but most of the aerosol products intended for continental/global applications have a coarse spatial resolution (10-18 km). The Multiangle Implementation of Atmospheric Correction (MAIAC) is a recently developed algorithm for the Moderate Resolution Imaging Spectroradiometer (MODIS), which provides Aerosol Optical Depth (AOD) at a high resolution of 1 km. We analyze the quality and potential of MAIAC AOD in the Alpine region and we derive high resolution AOD maps for the years 2008 and 2009. Cloudiness and snow in mountain regions occasionally lead to an overestimation of AOD due to unresolved cloud and snow pixel contamination. Therefore, we developed a filter that almost preserves the spatial resolution of the product to ensure the good accuracy of MAIAC AOD for air-quality and climatological applications. The AOD is validated with AERONET measurements in the region and compared to the standard MODIS AOD product (MOD04). Similar accuracies are found for both products (RMSE = 0.05) but with MAIAC providing about 50% more observations at the examined locations, because of its higher spatial resolution and less restrictive filtering. Comparison with ground measurements of aerosol mass (PM 10 ) shows that MAIAC AOD can be used to detect the fine scales of aerosol variability (2-3 km) in the mountains. Finally, AOD maps for the Alpine region demonstrate that topography is correlated with the average aerosol spatial distribution.

Abstract. The Infrared Atmospheric Sounder Instrument (IASI) allows global coverage with very high spatial resolution and its measurements are promising for long-term ozone monitoring. In this study, Microwave Limb Sounder (MLS) O3 profiles and IASI O3 partial columns (1013.25–345 hPa) are assimilated in a chemistry transport model to produce 6-hourly analyses of tropospheric ozone for 6 years (2008–2013). We have compared and evaluated the IASI-MLS analysis and the MLS analysis to assess the added value of IASI measurements. The global chemical transport model MOCAGE (MOdèle de Chimie Atmosphérique à Grande Echelle) has been used with a linear ozone chemistry scheme and meteorological forcing fields from ERA-Interim (ECMWF global reanalysis) with a horizontal resolution of 2°  ×  2° and 60 vertical levels. The MLS and IASI O3 retrievals have been assimilated with a 4-D variational algorithm to constrain stratospheric and tropospheric ozone respectively. The ozone analyses are validated against ozone soundings and tropospheric column ozone (TCO) from the OMI-MLS residual method. In addition, an Ozone ENSO Index (OEI) is computed from the analysis to validate the TCO variability during the ENSO events. We show that the assimilation of IASI reproduces the variability of tropospheric ozone well during the period under study. The variability deduced from the IASI-MLS analysis and the OMI-MLS measurements are similar for the period of study. The IASI-MLS analysis can reproduce the extreme oscillation of tropospheric ozone caused by ENSO events over the tropical Pacific Ocean, although a correction is required to reduce a constant bias present in the IASI-MLS analysis.

Abstract. Present and future satellite observations offer great potential for monitoring air quality on a daily and global basis. However, measurements from currently orbiting satellites do not allow a single sensor to accurately probe surface concentrations of gaseous pollutants such as tropospheric ozone. Combining information from IASI (Infrared Atmospheric Sounding Interferometer) and GOME-2 (Global Ozone Monitoring Experiment-2) respectively in the TIR and UV spectra, a recent multispectral method (referred to as IASI+GOME-2) has shown enhanced sensitivity for probing ozone in the lowermost troposphere (LMT, below 3 km altitude) with maximum sensitivity down to 2.20 km a.s.l. over land, while sensitivity for IASI or GOME-2 alone only peaks at 3 to 4 km at the lowest.In this work we develop a pseudo-observation simulator and evaluate the potential of future EPS-SG (EUMET-SAT Polar System -Second Generation) satellite observations, from new-generation sensors IASI-NG (Infrared Atmospheric Sounding Interferometer -New Generation) and UVNS (Ultraviolet Visible Near-infrared Shortwaveinfrared), to observe near-surface O 3 through the IASI-NG+UVNS multispectral method. The pseudo-real state of the atmosphere is provided by the MOCAGE (MOdèle de Chimie Atmosphérique à Grande Échelle) chemical transport model. We perform full and accurate forward and inverse radiative transfer calculations for a period of 4 days (8-11 July 2010) over Europe.In the LMT, there is a remarkable agreement in the geographical distribution of O 3 partial columns between IASI-NG+UVNS pseudo-observations and the corresponding MOCAGE pseudo-reality. With respect to synthetic IASI+GOME-2 products, IASI-NG+UVNS shows a higher correlation between pseudo-observations and pseudo-reality, which is enhanced by about 12 %. The bias on high ozone retrieval is reduced and the average accuracy increases by 22 %. The sensitivity to LMT ozone is also enhanced. On average, the degree of freedom for signal is higher by 159 % over land (from 0.29 to 0.75) and 214 % over ocean (from 0.21 to 0.66). The mean height of maximum sensitivity for the LMT peaks at 1.43 km over land and 2.02 km over ocean, respectively 1.03 and 1.30 km below that of IASI+GOME-2. IASI-NG+UVNS also shows good retrieval skill in the surface-2 km altitude range. It is one of a kind for retrieving ozone layers of 2-3 km thickness, in the first 2-3 km of the atmosphere. IASI-NG+UVNS is expected to largely enhance the capacity to observe ozone pollution from space.