Abstract. We present an improved tropospheric nitrogen dioxide column retrieval algorithm (DOMINO v2.0) for OMI based on better air mass factors (AMFs) and a correction for across-track stripes resulting from calibration errors in the OMI backscattered reflectances. Since October 2004, NO 2 retrievals from the Ozone Monitoring Instrument (OMI), a UV/Vis nadir spectrometer onboard NASA's EOSAura satellite, have been used with success in several scientific studies focusing on air quality monitoring, detection of trends, and NO x emission estimates. Dedicated evaluations of previous DOMINO tropospheric NO 2 retrievals indicated their good quality, but also suggested that the tropospheric columns were susceptible to high biases (by 0-40 %), probably because of errors in the air mass factor calculations. Here we update the DOMINO air mass factor approach. We calculate a new look-up table (LUT) for altitude-dependent AMFs based on more realistic atmospheric profile parameters, and include more surface albedo and surface pressure reference points than before. We improve the sampling of the TM4 model, resulting in a priori NO 2 profiles that are better mixed throughout the boundary layer. We evaluate the NO 2 profiles simulated with the improved TM4 sampling as used in the AMF calculations and show that they are highly consistent with in situ NO 2 measurements from aircraft during the INTEX-A and INTEX-B campaigns in 2004 and 2006. Our air mass factor calculations are furCorrespondence to: Folkert Boersma (boersma@knmi.nl) ther updated by the implementation of a high-resolution terrain height and a high-resolution surface albedo climatology based on OMI measurements. Together with a correction for across-track stripes, the overall impact of the improved terrain height and albedo descriptions is modest (<5 %) on average over large polluted areas, but still causes significant changes locally. The main changes in the DOMINO v2.0 algorithm follow from the new LUT and the improved TM4 sampling that results in more NO 2 simulated aloft, where sensitivity to NO 2 is higher, and amount to reductions in tropospheric NO 2 columns of up to 20 % in winter, and 10 % in summer over extended polluted areas. We investigate the impact of aerosols on the NO 2 retrieval, and based on a comparison of concurrent retrievals of clouds from OMI and aerosols from MODIS Aqua, we find empirical evidence that OMI cloud retrievals are sensitive to the presence of scattering aerosols. It follows that an implicit correction for the effects of aerosols occurs through the aerosol-induced cloud parameters in DOMINO, and we show that such an empirical correction amounts to a 20 % AMF reduction in summer and ±10 % changes in winter over the eastern United States.

Abstract. The Copernicus Atmosphere Monitoring Service (CAMS) reanalysis is the latest global reanalysis dataset of atmospheric composition produced by the European Centre for Medium-Range Weather Forecasts (ECMWF), consisting of three-dimensional time-consistent atmospheric composition fields, including aerosols and chemical species. The dataset currently covers the period 2003–2016 and will be extended in the future by adding 1 year each year. A reanalysis for greenhouse gases is being produced separately. The CAMS reanalysis builds on the experience gained during the production of the earlier Monitoring Atmospheric Composition and Climate (MACC) reanalysis and CAMS interim reanalysis. Satellite retrievals of total column CO; tropospheric column NO2; aerosol optical depth (AOD); and total column, partial column and profile ozone retrievals were assimilated for the CAMS reanalysis with ECMWF's Integrated Forecasting System. The new reanalysis has an increased horizontal resolution of about 80 km and provides more chemical species at a better temporal resolution (3-hourly analysis fields, 3-hourly forecast fields and hourly surface forecast fields) than the previously produced CAMS interim reanalysis. The CAMS reanalysis has smaller biases compared with most of the independent ozone, carbon monoxide, nitrogen dioxide and aerosol optical depth observations used for validation in this paper than the previous two reanalyses and is much improved and more consistent in time, especially compared to the MACC reanalysis. The CAMS reanalysis is a dataset that can be used to compute climatologies, study trends, evaluate models, benchmark other reanalyses or serve as boundary conditions for regional models for past periods.

We present a comprehensive description and benchmark evaluation of the tropospheric chemistry version of the global chemistry transport model TM5 (Tracer Model 5, version TM5-chem-v3.0). A full description is given concerning the photochemical mechanism, the interaction with aerosol, the treatment of the stratosphere, the wet and dry deposition parameterizations, and the applied emissions. We evaluate the model against a suite of ground-based, satellite, and aircraft measurements of components critical for understanding global photochemistry for the year 2006. <br><br> The model exhibits a realistic oxidative capacity at a global scale. The methane lifetime is ~8.9 years with an associated lifetime of methyl chloroform of 5.86 years, which is similar to that derived using an optimized hydroxyl radical field. <br><br> The seasonal cycle in observed carbon monoxide (CO) is well simulated at different regions across the globe. In the Northern Hemisphere CO concentrations are underestimated by about 20 ppbv in spring and 10 ppbv in summer, which is related to missing chemistry and underestimated emissions from higher hydrocarbons, as well as to uncertainties in the seasonal variation of CO emissions. The model also captures the spatial and seasonal variation in formaldehyde tropospheric columns as observed by SCIAMACHY. Positive model biases over the Amazon and eastern United States point to uncertainties in the isoprene emissions as well as its chemical breakdown. <br><br> Simulated tropospheric nitrogen dioxide columns correspond well to observations from the Ozone Monitoring Instrument in terms of its seasonal and spatial variability (with a global spatial correlation coefficient of 0.89), but TM5 fields are lower by 25–40%. This is consistent with earlier studies pointing to a high bias of 0–30% in the OMI retrievals, but uncertainties in the emission inventories have probably also contributed to the discrepancy. <br><br> TM5 tropospheric nitrogen dioxide profiles are in good agreement (within ~0.1 ppbv) with in situ aircraft observations from the INTEX-B campaign over (the Gulf of) Mexico. <br><br> The model reproduces the spatial and seasonal variation in background surface ozone concentrations and tropospheric ozone profiles from the World Ozone and Ultraviolet Radiation Data Centre to within 10 ppbv, but at several tropical stations the model tends to underestimate ozone in the free troposphere. <br><br> The presented model results benchmark the TM5 tropospheric chemistry version, which is currently in use in several international cooperation activities, and upon which future model improvements will take place

In September and October 2015 widespread forest and peatland fires burned over large parts of maritime southeast Asia, most notably Indonesia, releasing large amounts of terrestrially-stored carbon into the atmosphere, primarily in the form of CO2, CO and CH4. With a mean emission rate of 11.3 Tg CO2 per day during Sept-Oct 2015, emissions from these fires exceeded the fossil fuel CO2 release rate of the European Union (EU28) (8.9 Tg CO2 per day). Although seasonal fires are a frequent occurrence in the human modified landscapes found in Indonesia, the extent of the 2015 fires was greatly inflated by an extended drought period associated with a strong El Niño. We estimate carbon emissions from the 2015 fires to be the largest seen in maritime southeast Asia since those associated with the record breaking El Niño of 1997. Compared to that event, a much better constrained regional total carbon emission estimate can be made for the 2015 fires through the use of present-day satellite observations of the fire’s radiative power output and atmospheric CO concentrations, processed using the modelling and assimilation framework of the Copernicus Atmosphere Monitoring Service (CAMS) and combined with unique in situ smoke measurements made on Kalimantan.

Abstract. An eight-year long reanalysis of atmospheric composition data covering the period 2003–2010 was constructed as part of the FP7-funded Monitoring Atmospheric Composition and Climate project by assimilating satellite data into a global model and data assimilation system. This reanalysis provides fields of chemically reactive gases, namely carbon monoxide, ozone, nitrogen oxides, and formaldehyde, as well as aerosols and greenhouse gases globally at a horizontal resolution of about 80 km for both the troposphere and the stratosphere. This paper describes the assimilation system for the reactive gases and presents validation results for the reactive gas analysis fields to document the data set and to give a first indication of its quality. Tropospheric CO values from the MACC reanalysis are on average 10–20% lower than routine observations from commercial aircrafts over airports through most of the troposphere, and have larger negative biases in the boundary layer at urban sites affected by air pollution, possibly due to an underestimation of CO or precursor emissions. Stratospheric ozone fields from the MACC reanalysis agree with ozonesondes and ACE-FTS data to within ±10% in most seasons and regions. In the troposphere the reanalysis shows biases of −5% to +10% with respect to ozonesondes and aircraft data in the extratropics, but has larger negative biases in the tropics. Area-averaged total column ozone agrees with ozone fields from a multi-sensor reanalysis data set to within a few percent. NO2 fields from the reanalysis show the right seasonality over polluted urban areas of the NH and over tropical biomass burning areas, but underestimate wintertime NO2 maxima over anthropogenic pollution regions and overestimate NO2 in northern and southern Africa during the tropical biomass burning seasons. Tropospheric HCHO is well simulated in the MACC reanalysis even though no satellite data are assimilated. It shows good agreement with independent SCIAMACHY retrievals over regions dominated by biogenic emissions with some anthropogenic input, such as the eastern US and China, and also over African regions influenced by biogenic sources and biomass burning.

Abstract. A representation of atmospheric chemistry has been included in the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). The new chemistry modules complement the aerosol modules of the IFS for atmospheric composition, which is named C-IFS. C-IFS for chemistry supersedes a coupled system in which chemical transport model (CTM) Model for OZone and Related chemical Tracers 3 was two-way coupled to the IFS (IFS-MOZART). This paper contains a description of the new on-line implementation, an evaluation with observations and a comparison of the performance of C-IFS with MOZART and with a re-analysis of atmospheric composition produced by IFS-MOZART within the Monitoring Atmospheric Composition and Climate (MACC) project. The chemical mechanism of C-IFS is an extended version of the Carbon Bond 2005 (CB05) chemical mechanism as implemented in CTM Transport Model 5 (TM5). CB05 describes tropospheric chemistry with 54 species and 126 reactions. Wet deposition and lightning nitrogen monoxide (NO) emissions are modelled in C-IFS using the detailed input of the IFS physics package. A 1 year simulation by C-IFS, MOZART and the MACC re-analysis is evaluated against ozonesondes, carbon monoxide (CO) aircraft profiles, European surface observations of ozone (O3), CO, sulfur dioxide (SO2) and nitrogen dioxide (NO2) as well as satellite retrievals of CO, tropospheric NO2 and formaldehyde. Anthropogenic emissions from the MACC/CityZen (MACCity) inventory and biomass burning emissions from the Global Fire Assimilation System (GFAS) data set were used in the simulations by both C-IFS and MOZART. C-IFS (CB05) showed an improved performance with respect to MOZART for CO, upper tropospheric O3, and wintertime SO2, and was of a similar accuracy for other evaluated species. C-IFS (CB05) is about 10 times more computationally efficient than IFS-MOZART.

Abstract. We present a comparison of tropospheric NO 2 from OMI measurements to the median of an ensemble of Regional Air Quality (RAQ) models, and an intercomparison of the contributing RAQ models and two global models for the period July 2008-June 2009 over Europe. The model forecasts were produced routinely on a daily basis in the context of the European GEMS ("Global and regional Earth-system (atmosphere) Monitoring using Satellite and in-situ data") project. The tropospheric vertical column of the RAQ ensemble median shows a spatial distribution which agrees well with the OMI NO 2 observations, with a correlation r=0.8. This is higher than the correlations from any one of the individual RAQ models, which supports the use of a model ensemble approach for regional air pollution forecasting. The global models show high correlations compared Correspondence to: V. Huijnen (huijnen@knmi.nl) to OMI, but with significantly less spatial detail, due to their coarser resolution. Deviations in the tropospheric NO 2 columns of individual RAQ models from the mean were in the range of 20-34% in winter and 40-62% in summer, suggesting that the RAQ ensemble prediction is relatively more uncertain in the summer months.The ensemble median shows a stronger seasonal cycle of NO 2 columns than OMI, and the ensemble is on average 50% below the OMI observations in summer, whereas in winter the bias is small. On the other hand the ensemble median shows a somewhat weaker seasonal cycle than NO 2 surface observations from the Dutch Air Quality Network, and on average a negative bias of 14%.Full profile information was available for two RAQ models and for the global models. For these models the retrieval averaging kernel was applied. Minor differences are found for area-averaged model columns with and without applying the kernel, which shows that the impact of replacing the a priori profiles by the RAQ model profiles is on average small.Published by Copernicus Publications on behalf of the European Geosciences Union. V. Huijnen et al.:Comparison of NO 2 in regional and global models to OMI However, the contrast between major hotspots and rural areas is stronger for the direct modeled vertical columns than the columns where the averaging kernels are applied, related to a larger relative contribution of the free troposphere and the coarse horizontal resolution in the a priori profiles compared to the RAQ models.In line with validation results reported in the literature, summertime concentrations in the lowermost boundary layer in the a priori profiles from the DOMINO product are significantly larger than the RAQ model concentrations and surface observations over the Netherlands. This affects the profile shape, and contributes to a high bias in OMI tropospheric columns over polluted regions. The global models indicate that the upper troposphere may contribute significantly to the total column and it is important to account for this in comparisons with RAQ models. A combination of upper troposphere model biases, the a priori profile effec...

International audienceA new global reanalysis data set of atmospheric composition (AC) for the period 2003–2015 has been produced by the Copernicus Atmosphere Monitoring Service (CAMS). Satellite observations of total column (TC) carbon monoxide (CO) and aerosol optical depth (AOD), as well as several TC and profile observations of ozone, have been assimilated with the Integrated Forecasting System for Composition (C-IFS) of the European Centre for Medium-Range Weather Forecasting. Compared to the previous Monitoring Atmospheric Composition and Climate (MACC) reanalysis (MACCRA), the new CAMS interim reanalysis (CAMSiRA) is of a coarser horizontal resolution of about 110 km, compared to 80 km, but covers a longer period with the intent to be continued to present day. This paper compares CAMSiRA with MACCRA and a control run experiment (CR) without assimilation of AC retrievals. CAMSiRA has smaller biases than the CR with respect to independent observations of CO, AOD and stratospheric ozone. However, ozone at the surface could not be improved by the assimilation because of the strong impact of surface processes such as dry deposition and titration with nitrogen monoxide (NO), which were both unchanged by the assimilation. The assimilation of AOD led to a global reduction of sea salt and desert dust as well as an exaggerated increase in sulfate. Compared to MACCRA, CAMSiRA had smaller biases for AOD, surface CO and TC ozone as well as for upper stratospheric and tropospheric ozone. Finally, the temporal consistency of CAMSiRA was better than the one of MACCRA. This was achieved by using a revised emission data set as well as by applying careful selection and bias correction to the assimilated retrievals. CAMSiRA is therefore better suited than MACCRA for the study of interannual variability, as demonstrated for trends in surface CO