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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 MACCII (summer 2014) and analyses the performance of the multimodel ensemble. The MACC-II system provides daily 96h forecasts with hourly outputs of 10 chemical species/aerosols (O3, NO2, SO2, CO, PM10, PM2.5, NO, NH3, total NMVOCs (non-methane volatile organic compounds) and PAN+PAN precursors) over eight vertical levels from the surface to 5km 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.

Stikstofdepositie in Duitsland wordt berekend met het verbeterde Lotos-Euros model. Verdere detaillering van weersafhankelijke emissiepatronen is nodig om de depositiekaarten te verfijnen

Het KNMI regionaal klimaat model RACMO wordt in toenemende mate gebruikt bij de detaillering van Klimaatscenario’s. Voorbeelden zijn de frequentie en intensiteit van hittegolven en de veranderingen daarin. Of te verwachten wijzigingen in het optreden van lokale neerslagextremen. In dit project zijn een aantal componenten van RACMO verder ontwikkeld. De bodemhydrologie van het model is verder verfijnd door ruimtelijke heterogeniteit in te voeren voor een aantal bodemparameters, zoals bodemtype en worteldiepte. Deze aanpassing resulteert in meer uitgesproken ruimtelijke structuren op regionale schaal.

Monitoring aerosols over wide areas is important for the assessment of the population's exposure to health relevant particulate matter (PM). Satellite observations of aerosol optical depth (AOD) can contribute to the improvement of highly needed analyzed and forecasted distributions of PM when combined with a model and ground-based observations. In this paper, we evaluate the contribution of column AOD observations from a future imager on a geostationary satellite by performing an Observing System Simulation Experiment (OSSE). In the OSSE simulated imager, AOD observations and ground-based PM observations are assimilated in the chemistry transport model LOTOS-EUROS to assess the added value of the satellite observations relative to the value of ground-based observations. Results show that in highly polluted situations, the imager AOD observations improve analyzed and forecasted PM2.5 concentrations even in the vicinity of simultaneously incorporated ground-based PM observations. The added value of the proposed imager is small when considering monthly averaged PM distributions. This is attributed to relatively large errors in the imager AODs in case of background aerosol loads coupled to the fact that the imager AODs are column values and an indirect estimate of PM. In the future, model improvements and optimization of the assimilation system should be achieved for better handling of situations with aerosol plumes above the boundary layer and satellite observations containing aerosol profile information. With the suggested improvements, the developed OSSE will form a powerful tool for determining the added value of future missions and defining requirements for planned satellite observations. © 2009 IEEE.

To acquire daily estimates of PM2.5 distributions based on satellite data one depends critically on an established relation between AOD and ground level PM2.5. In this study we aimed to experimentally establish the AOD-PM2.5 relationship for the Netherlands. For that purpose an experiment was set-up at the AERONET site Cabauw. The average PM 2.5 concentration during this ten month study was 18 μg/m 3, which confirms that the Netherlands are characterised by a high PM burden. A first inspection of the AERONET level 1.5 (L1.5) AOD and PM2.5 data at Cabauw showed a low correlation between the two properties. However, after screening for cloud contamination in the AERONET L1.5 data, the correlation improved substantially. When also constraining the dataset to data points acquired around noon, the correlation between AOD and PM2.5 amounted to R2=0.6 for situations with fair weather. This indicates that AOD data contain information about the temporal evolution of PM2.5. We had used LIDAR observations to detect residual cloud contamination in the AERONET L1.5 data. Comparison of our cloud-screed L1.5 with AERONET L2 data that became available near the end of the study showed favorable agreement. The final relation found for Cabauw is PM 2.5=124.5*AODĝ€"0.34 (with PM2.5 in μg/m3) and is valid for fair weather conditions. The relationship determined between MODIS AOD and ground level PM2.5 at Cabauw is very similar to that based on the much larger dataset from the sun photometer data, after correcting for a systematic overestimation of the MODIS data of 0.05. We applied the relationship to a MODIS composite map to assess the PM2.5 distribution over the Netherlands. Spatial dependent systematic errors in the MODIS AOD, probably related to variability in surface reflectance, hamper a meaningful analysis of the spatial distribution of PM2.5 using AOD data at the scale of the Netherlands.

This study investigates the ability to derive height-resolved information on equatorial Kelvin wave activity from three different Global Ozone Monitoring Experiment (GOME) ozone profile data sets. The ozone profiles derived using the Ozone Profile Retrieval Algorithm (OPERA) based on optimal estimation and the Neural Network Ozone Retrieval System (NNORSY) both show Kelvin wave signals in agreement with previously identified signals in the GOME total ozone columns. However, because of the inadequate vertical resolution, these two data sets are not able to resolve the vertical structure of the Kelvin wave activity. The third data set, consisting of assimilated OPERA ozone profiles, does provide height-resolved information on Kelvin wave activity that is consistent with results from the analysis of GOME total ozone columns and ECMWF Re-Analysis (ERA-40) temperature data. Largest Kelvin-wave-induced perturbations of up to 0.69 DU/km coincide with the maximum vertical gradient in ozone around 35 hPa and show an in-phase relationship with temperature perturbations in ERA-40 as expected from theoretical considerations. These results indicate that the ozone perturbations in the lower stratosphere and in the total column of ozone are transport related. Between 10 and 1 hPa, large Kelvin-wave-induced fluctuations in ozone mixing ratio are present that, however, because of their small contribution to the total column, do not constitute a large contribution to the total ozone column perturbations. The ozone perturbations between 10 and 1 hPa show an out-of-phase relationship with temperature perturbations in ERA-40, indicating that the perturbations can either be caused by transport effects or photochemical influences. Copyright 2005 by the American Geophysical Union.