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.

Members in ensemble forecasts differ due to the representations of initial uncertainties and model uncertainties. The inclusion of stochastic schemes to represent model uncertainties has improved the probabilistic skill of the ECMWF ensemble by increasing reliability and reducing the error of the ensemble mean. Recent progress, challenges and future directions regarding stochastic representations of model uncertainties at ECMWF are described in this article. The coming years are likely to see a further increase in the use of ensemble methods in forecasts and assimilation. This will put increasing demands on the methods used to perturb the forecast model. An area that is receiving greater attention than 5–10 years ago is the physical consistency of the perturbations. Other areas where future efforts will be directed are the expansion of uncertainty representations to the dynamical core and other components of the Earth system, as well as the overall computational efficiency of representing model uncertainty.

Abstract. This paper aims to summarise the current performance of ozone data assimilation (DA) systems, to show where they can be improved, and to quantify their errors. It examines 11 sets of ozone analyses from 7 different DA systems. Two are numerical weather prediction (NWP) systems based on general circulation models (GCMs); the other five use chemistry transport models (CTMs). The systems examined contain either linearised or detailed ozone chemistry, or no chemistry at all. In most analyses, MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) ozone data are assimilated; two assimilate SCIAMACHY (Scanning Imaging Absorption Spectrometer for Atmospheric Chartography) observations instead. Analyses are compared to independent ozone observations covering the troposphere, stratosphere and lower mesosphere during the period July to November 2003.Biases and standard deviations are largest, and show the largest divergence between systems, in the troposphere, in the upper-troposphere/lower-stratosphere, in the upperstratosphere and mesosphere, and the Antarctic ozone hole region. However, in any particular area, apart from the troposphere, at least one system can be found that agrees well with independent data. In general, none of the differences can be linked to the assimilation technique (Kalman filter, three or four dimensional variational methods, direct inversion) orCorrespondence to: A. J. Geer (alan.geer@ecmwf.int) the system (CTM or NWP system). Where results diverge, a main explanation is the way ozone is modelled. It is important to correctly model transport at the tropical tropopause, to avoid positive biases and excessive structure in the ozone field. In the southern hemisphere ozone hole, only the analyses which correctly model heterogeneous ozone depletion are able to reproduce the near-complete ozone destruction over the pole. In the upper-stratosphere and mesosphere (above 5 hPa), some ozone photochemistry schemes caused large but easily remedied biases. The diurnal cycle of ozone in the mesosphere is not captured, except by the one system that includes a detailed treatment of mesospheric chemistry. These results indicate that when good observations are available for assimilation, the first priority for improving ozone DA systems is to improve the models.The analyses benefit strongly from the good quality of the MIPAS ozone observations. Using the analyses as a transfer standard, it is seen that MIPAS is ∼5% higher than HALOE (Halogen Occultation Experiment) in the mid and upper stratosphere and mesosphere (above 30 hPa), and of order 10% higher than ozonesonde and HALOE in the lower stratosphere (100 hPa to 30 hPa). Analyses based on SCIA-MACHY total column are almost as good as the MIPAS analyses; analyses based on SCIAMACHY limb profiles are worse in some areas, due to problems in the SCIAMACHY retrievals.

Abstract.A new global atmospheric carbon dioxide (CO 2 ) real-time forecast is now available as part of the preoperational Monitoring of Atmospheric Composition and Climate -Interim Implementation (MACC-II) service using the infrastructure of the European Centre for MediumRange Weather Forecasts (ECMWF) Integrated Forecasting System (IFS). One of the strengths of the CO 2 forecasting system is that the land surface, including vegetation CO 2 fluxes, is modelled online within the IFS. Other CO 2 fluxes are prescribed from inventories and from off-line statistical and physical models. The CO 2 forecast also benefits from the transport modelling from a state-of-the-art numerical weather prediction (NWP) system initialized daily with a wealth of meteorological observations. This paper describes the capability of the forecast in modelling the variability of CO 2 on different temporal and spatial scales compared to observations. The modulation of the amplitude of the CO 2 diurnal cycle by near-surface winds and boundary layer height is generally well represented in the forecast. The CO 2 forecast also has high skill in simulating day-today synoptic variability. In the atmospheric boundary layer, this skill is significantly enhanced by modelling the day-today variability of the CO 2 fluxes from vegetation compared to using equivalent monthly mean fluxes with a diurnal cycle. However, biases in the modelled CO 2 fluxes also lead to accumulating errors in the CO 2 forecast. These biases vary with season with an underestimation of the amplitude of the seasonal cycle both for the CO 2 fluxes compared to total optimized fluxes and the atmospheric CO 2 compared to observations. The largest biases in the atmospheric CO 2 forecast are found in spring, corresponding to the onset of the growing season in the Northern Hemisphere. In the future, the forecast will be re-initialized regularly with atmospheric CO 2 analyses based on the assimilation of CO 2 products retrieved from satellite measurements and CO 2 in situ observations, as they become available in near-real time. In this way, the accumulation of errors in the atmospheric CO 2 forecast will be reduced. Improvements in the CO 2 forecast are also expected with the continuous developments in the operational IFS.

Abstract. The transport pathways of carbon monoxide (CO) in the African Upper Troposphere (UT) during the West African Monsoon (WAM) is investigated through the assimilation of CO observations by the Aura Microwave Limb Sounder (MLS) in the MOCAGE Chemistry Transport Model (CTM). The assimilation setup, based on a 3-D First Guess at Assimilation Time (3-D-FGAT) variational method is described. Comparisons between the assimilated CO fields and in situ airborne observations from the MOZAIC program between Europe and both Southern Africa and Southeast Asia show an overall good agreement around the lowermost pressure level sampled by MLS (∼215 hPa). The 4-D assimilated fields averaged over the month of July 2006 have been used to determine the main dynamical processes responsible for the transport of CO in the African UT. The studied period corresponds to the second AMMA (African Monsoon Multidisciplinary Analyses) aircraft campaign. At 220 hPa, the CO distribution is characterized by a latitudinal maximum around 5 • N mostly driven by convective uplift of air masses impacted by biomass burning from Southern Africa, uplifted within the WAM region and vented predominantly southward by the upper branch of the winter hemisphere Hadley cell. Above 150 hPa, the African CO distribution is characterized by a broad maximum over northern Africa. This maximum is mostly controlled by the large scale UT circulation driven by the Asian Summer Monsoon (ASM) and characterized by the Asian Monsoon Anticyclone (AMA) centered at 30 • N and Correspondence to: B. Barret (barp@aero.obs-mip.fr) the Tropical Easterly Jet (TEJ) on the southern flank of the anticyclone. Asian pollution uplifted to the UT over large region of Southeast Asia is trapped within the AMA and transported by the anticyclonic circulation over Northeast Africa. South of the AMA, the TEJ is responsible for the tranport of CO-enriched air masses from India and Southeast Asia over Africa. Using the high time resolution provided by the 4-D assimilated fields, we give evidence that the variability of the African CO distribution above 150 hPa and north of the WAM region is mainly driven by the synoptic dynamical variability of both the AMA and the TEJ.