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This article describes the Integrated Forecasting System aerosol scheme (IFS-AER) used operationally in the IFS cycle 47R1, which was operated by the European Centre for Medium Range Weather Forecasts (ECMWF) in the framework of the Copernicus Atmospheric Monitoring Services (CAMS). It represents an update of the Rémy et al. (2019) article, which described cycle 45R1 of IFS-AER in detail. Here, we detail only the parameterisations of sources and sinks that have been updated since cycle 45R1, as well as recent changes in the configuration used operationally within CAMS. Compared to cycle 45R1, a greater integration of aerosol and chemistry has been achieved. Primary aerosol sources have been updated, with the implementation of new dust and sea salt aerosol emission schemes. New dry and wet deposition parameterisations have also been implemented. Sulfate production rates are now provided by the global chemistry component of IFS. This paper aims to describe most of the updates that have been implemented since cycle 45R1, not just the ones that are used operationally in cycle 47R1; components that are not used operationally will be clearly flagged. Cycle 47R1 of IFS-AER has been evaluated against a wide range of surface and total column observations. The final simulated products, such as particulate matter (PM) and aerosol optical depth (AOD), generally show a significant improvement in skill scores compared to results obtained with cycle 45R1. Similarly, the simulated surface concentration of sulfate, organic matter and sea salt aerosol are improved by cycle 47R1 compared to cycle 45R1. Some biases persist, such as the surface concentrations of nitrate and organic matter being simulated too high. The new wet and dry deposition schemes that have been implemented into cycle 47R1 have a mostly positive impact on simulated AOD, PM and speciated aerosol surface concentration.

The Integrated Forecasting System (IFS) of ECMWF is core of the Copernicus Atmosphere Monitoring Service (CAMS) to provide global analyses and forecasts of atmospheric composition, including reactive gases, as well as aerosol and greenhouse gases. The CAMS global model consists of the aerosol model of the IFS, IFS-AER, which is a sectional-bulk scheme, while the chemistry scheme is based on a CB05-based carbon-bond mechanism, with the option to couple this to BASCOE-based stratospheric chemistry. The composition model is updated regularly, aligned with updates of ECMWF’s operational meteorological model. Here we report on updates planned for the operational version after next, referred to as CY49R1. This concerns revisions on a large range of topics, as developed over the recent years, and therefore impacting many aspects of chemistry and aerosol composition in troposphere and stratosphere. Main aspects concern:A review of the representation of polar stratospheric clouds and of their impact on stratospheric ozone, An extension of IFS-AER to represent stratospheric sulfate aerosols, coupled with CB05 and BASCOE precursor gases, An upgrade of gas-particle partitioning through the implementation of EQSAM4Clim in the IFS, Computation of aerosol, cloud and rain pH, and use of the update pH values in aqueous chemistry, A combined representation of aerosols and chemistry deposition processes (wet and dry), Update of aerosol optics, including a simple representation of dust asphericity and hygroscopic growth, Update of PM diagnostic output In this contribution we provide an overview of expected changes with emphasis on changes in composition modeling aspects. We will present their expected impact on key atmospheric composition aspects, including air quality performance across major pollution regions across the world, aerosol optical depth, dust, and stratospheric composition products.

Emissions from vegetation fires in tropical forests have the potential to turn the global land carbon sink into a source, affect atmospheric chemistry, and hence air quality. While natural forest fires are a rare phenomenon in tropical forests of South America and are usually of rather low intensity, deforestation fires and small land clearings in systems with high fuel loads can cause intense fires and high emissions. However, the high moisture content in tropical forests causes incomplete combustion and higher emissions of carbon monoxide (CO) than of carbon dioxide. The interacting effects of land use change, fuel load and moisture on fire intensity and emissions is, however, difficult to quantify at large scales because not all of those components are readily available from Earth observations in a consistent way. Here, we make use of several satellite products on vegetation, fire activity and atmospheric composition to quantify the effects of land use, fuel loads, fuel moisture on fuel consumption, emission factors and hence on emissions and atmospheric trace gas concentration. First, we use observations of active fires and fire radiative power from the VIIRS and Sentinel-3 SLSTR sensors to map different fire types (forest fires, deforestation fires, small land clearing and agricultural fires, savannah fires). Second, we integrate satellite products of canopy height, above-ground biomass, leaf area index, land cover and soil moisture in a novel data-model fusion framework to estimate fuel loads and moisture in vegetation, surface litter and woody debris. We then combine in a bottom-up approach the fire types with fuel loads and moisture to estimate fuel consumption and fire emissions using default emission factors. Third, we use observations from Sentinel-5p TROPOMI and the Integrated Forecast Systems (IFS) of the Copernicus Atmosphere Monitoring Service to compare the bottom-up estimates with distributions of CO and NOx in the atmosphere, which allows optimising emissions and associated emission factors.Our reconciled estimates of fire emissions outperform previous CO estimates e.g. from the Global Fire Assimilation System, which demonstrates an improved estimation of fire carbon emissions. The results show that the high fire intensity and emissions in tropical deforestation fires originate from the burning of high loads of woody biomass and coarse woody debris. The high fuel moisture content causes higher emission factors of CO in tropical forests than in savannah fires and hence higher absolute emissions of CO. Our new model approaches and satellite products allow to provide an integrated assessments on the effects of fuel and fire behaviour on fire emissions.

The ECMWF’s Integrated Forecast System (IFS) is the global atmospheric model used by the Copernicus Atmospheric Monitoring Service (CAMS) to provide analyses and forecasts on atmospheric composition. Currently, the CAMS global model includes the aerosol model of the IFS, the aerosol module IFS-AER making use of a sectional-bulk scheme, and the chemistry scheme based on a CB05-based carbon-bond mechanism, with the option to couple this to stratospheric chemistry module BASCOE. The combined BASCOE will be used operationally in the CAMS global system starting from the upgrade to cycle 48R1 planned in June 2023. This abstract focuses on further developments related to stratospheric chemistry and aerosols that are to be implemented in the future operational cycle 49R1, as well as on a first evaluation of IFS’ performances in representing stratospheric aerosols and chemistry against different datasets.Initially focussing on the troposphere, IFS-AER has been extended to include and represent stratospheric sulfate aerosol processes, keeping the existing tracers. The extended IFS-AER(strato) has been coupled to IFS(BASCOE) through the gaseous sulphuric acid tracer, to the IFS radiation scheme, and to the 4Dvar assimilation scheme. The evaluation of aerosol aspects makes use of aerosol datasets (aerosol extinction, AOD, …) from the Global Ozone Monitoring by Occultation of Stars (GOMOS, onboard Envisat), and the Global Space-based Stratospheric Aerosol Climatology (GloSSAC), based on different cases studies including quiescent and (highly) volcanic periods. It has also been tested against reference simulations from WACCM-CARMA. These intercomparisons show a reasonable agreement against retrieval datasets such as GloSSAC and reference simulations from WACCM-CARMA. In quiescent conditions, the new system showed a decreasing trend with respect to the reference datasets.BASCOE includes a simple PSC parameterization, which has been updated and tuned in cycle 49R1. In order to assess the impact of this upgrade, we evaluate the composition of the polar lower stratosphere during the winter-spring seasons ("ozone hole" events) of 2008, 2009 and 2020 above the Antarctic and 2009, 2011, 2012 and 2020 above the Arctic, with a focus on 5 key species observed by Aura-MLS. This evaluation demonstrates the capacity of IFS(BASCOE) to forecast the chemical composition of the polar lower stratosphere above both the Arctic and the Antarctic for several years with very different evolution of the polar vortex. While further improvements are desirable and will require an overhaul of the PSC parameterization, the current performance allows us to study the interannual variability of ozone hole episodes.

The Integrated Forecasting System (IFS) of ECMWF is used within the Copernicus Atmosphere Monitoring Service (CAMS) to provide global analyses and forecasts of atmospheric composition, including aerosols as well as reactive trace gases and greenhouse gases. Inorganic gas/aerosol equilibrium involving the major sulphate and nitrate anions, i.e., H2SO4/HSO4-/SO42- and HNO3/NO3-, largely determines the aerosol acidity, while the gas/liquid/solid phase partitioning of semi-volatile cations, NH3/NH4+, and the liquid/solid partitioning of non-volatile mineral cations, particularly Ca2+, Mg2+, and K+, overall control the gas-liquid-solid aerosol equilibrium partitioning of reactive nitrogen compounds. For the NO3- and NH4+ equilibrium, our recent developments have focused on EQSAM4Clim, which has been recently integrated into the IFS as a computationally efficient means of describing aerosol pH in a global modeling system. EQSAM4Clim is used in the IFS to estimate gas-liquid-solid partitioning and the aerosol associated liquid water content, which is subsequently used to estimate the associated aerosol, cloud and rain acidity. The aerosol, cloud and rain pH is computed by considering the liquid water (H2O) content in the respective liquid water phase using either the aerosol associated water computed by EQSAM4clim, and if present, the cloud and/or rain water of the IFS. The pH is coupled to the aqueous phase chemistry in IFS(CB05) and in the wet deposition of SO2 and NH3, which in-turn affects the aerosol composition through changes in the SO2/SO42-, NH3/NH4+and HNO3/NO3- partitioning, the aerosol associated liquid water content and solution pH. Here we present first results of the of the impact of improved aerosol acidity in the solution (aerosol/cloud/rain water) on PM2.5 forecasts simulated in the IFS which are subject to gas-particle partitioning. In particular, the NH4+, NO3- and SO42- concentrations have been compared against observational datasets at the surface, showing promising improvements as a direct result of the new pH computations. When coupling the EQSAMClim pH into the aqueous phase chemistry routine, the surface concentrations of SO42- and the SO2 + SO42- wet deposition fluxes are improved over most of Europe, but degraded over parts of US. The relative impact of the improved pH appears generally small as compared to other related changes such as updates in aqueous chemistry rates. In the pH coupling, the aqueous chemistry component dominates the impact on the wet deposition of SO2/NH3. All of these results are highly dependent on the emissions input (SO2/NOx/NH3).

Concentrations of atmospheric methane (CH4), the second most important greenhouse gas, continue to grow. In recent years this growth rate has increased further (2020: +15.6 ppb), the cause of which remains largely unknown. Here, we demonstrate a high-resolution (∼80 km), short-window (24 h) 4D-Var global inversion system based on the ECMWF Integrated Forecasting System (IFS) and newly available satellite observations. The largest national disagreement found between prior (5.3 Tg per month) and posterior (5.0 Tg per month) CH4 emissions is from China, mainly attributed to the energy sector. Emissions estimated from our global system are in good agreement with those of previous regional studies and point source-specific studies. Emission events (leaks or blowouts) > 10 t CH4 h−1 were detected, but without appropriate prior uncertainty information, were not well quantified. Our results suggest that global anthropogenic CH4 emissions for the first 6 months of 2020 were, on average, 470 Gg per month (+1.6 %) higher than for 2019, mainly attributed to the energy and agricultural sectors. Regionally, the largest increases were seen from China (+220 Gg per month, 4.3 %), with smaller increases from India (+50 Gg per month, 1.5 %) and the USA (+40 Gg per month, 2.2 %). When assuming a consistent year-on-year positive trend in emissions, results show that during the onset of the global slowdown (March–April 2020) energy sector CH4 emissions from China increased above expected levels; however, during later months (May–June 2020) emissions decreased below expected levels. Results for the first 6 months of 2019/20 suggest that the accumulated impact of the COVID-19 slowdown on CH4 emissions from March–June 2020 might be small relative to the long-term positive trend in emissions. Changes in OH concentration, not investigated here, may have contributed to the observed growth in 2020.

The Copernicus Atmosphere Monitoring Service (CAMS) has recently produced a greenhouse gas reanalysis (version egg4) that covers almost 2 decades from 2003 to 2020 and which will be extended in the future. This reanalysis dataset includes carbon dioxide (CO2) and methane (CH4). The reanalysis procedure combines model data with satellite data into a globally complete and consistent dataset using the European Centre for Medium-Range Weather Forecasts' Integrated Forecasting System (IFS). This dataset has been carefully evaluated against independent observations to ensure validity and to point out deficiencies to the user. The greenhouse gas reanalysis can be used to examine the impact of atmospheric greenhouse gas concentrations on climate change (such as global and regional climate radiative forcing), assess intercontinental transport, and serve as boundary conditions for regional simulations, among other applications and scientific uses. The caveats associated with changes in assimilated observations and fixed underlying emissions are highlighted, as is their impact on the estimation of trends and annual growth rates of these long-lived greenhouse gases.

The Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) satellite consists of active and passive sensors whose observations will be acted on by an array of retrieval algorithms. Earth-CARE’s retrieval algorithms have undergone pre-launch verifications within a virtual observing system that consists of 3D atmosphere-surface data produced by the Global Environmental Multi-scale (GEM) NWP model, and instrument simulators that when applied to NWP data yield syn-thetic observations for EarthCARE’s four sensors. Retrieval algorithms operate on the synthetic observations and their estimates go into radiative transfer models that produce top-of-atmosphere solar and thermal broadband radiative quantities, which are compared to synthetic broadband measurements thus mimicking EarthCARE’s radiative closure assessment. Three high-resolution test frames were simulated; each measures ~6,200 km along-track by 200 km across-track. Hori-zontal grid-spacing is 250 m and there are 57 atmospheric layers up to 10 mb. The frames span wide ranges of conditions and extend over: i) Greenland to The Caribbean crossing a cold front off Nova Scotia; ii) Nunavut to Baja California crossing over Colorado’s Rooky Mountains; and iii) central equatorial Pacific Ocean that includes a mesoscale convective system. This report discusses how the test frames were produced and presents their key geophysical features. All data are publicly available and, owing to their high-resolution, could be used to simulate observations for other measurement systems.

The Copernicus Atmosphere Monitoring Service (CAMS) provides routine analyses and forecasts of trace gases and aerosols on a global scale. The core is the European Centre for Medium Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS), where modules for atmospheric chemistry and aerosols have been introduced and which allows for data assimilation of satellite retrievals of composition. We have updated both the homogeneous and heterogeneous NOx chemistry applied in the three independent tropospheric–stratospheric chemistry modules maintained within CAMS, referred to as IFS(CB05BASCOE), IFS(MOCAGE) and IFS(MOZART). Here we focus on the evaluation of main trace gas products from these modules that are of interest as markers of air quality, namely lower-tropospheric O3, NO2 and CO, with a regional focus over the contiguous United States. Evaluation against lower-tropospheric composition reveals overall good performance, with chemically induced biases within 10 ppb across species for regions within the US with respect to a range of observations. The versions show overall equal or better performance than the CAMS reanalysis, which includes data assimilation. Evaluation of surface air quality aspects shows that annual cycles are captured well, albeit with variable seasonal biases. During wintertime conditions there is a large model spread between chemistry schemes in lower-tropospheric O3 (∼ 10 %–35 %) and, in turn, oxidative capacity related to NOx lifetime differences. Analysis of differences in the HNO3 and PAN formation, which act as reservoirs for reactive nitrogen, revealed a general underestimate in PAN formation over polluted regions, likely due to too low organic precursors. Particularly during wintertime, the fraction of NO2 sequestered into PAN has a variability of 100 % across chemistry modules, indicating the need for further constraints. Notably, a considerable uncertainty in HNO3 formation associated with wintertime N2O5 conversion on wet particle surfaces remains. In summary, this study has indicated that the chemically induced differences in the quality of CAMS forecast products over the United States depends on season, trace gas, altitude and region. While analysis of the three chemistry modules in CAMS provide a strong handle on uncertainties associated with chemistry modeling, the further improvement of operational products additionally requires coordinated development involving emissions handling, chemistry and aerosol modeling, complemented with data-assimilation efforts.

In this paper, we report on the first implementation of atmospheric chemistry and aerosol as part of the European Centre for Medium-Range Weather Forecasts (ECMWF) OpenIFS model. OpenIFS is a portable version of ECMWF's global numerical weather prediction model. Modules and input data for model cycle CY43R3, which have been developed as part of the Copernicus Atmosphere Monitoring Service (CAMS), have been ported to OpenIFS with the modified CB05 tropospheric chemistry scheme, the bulk bin tropospheric aerosol module, and the option to use Belgian Assimilation System for Chemical ObsErvations (BASCOE)-based stratospheric ozone chemistry. We give an overview of the model, and describe the datasets used for emissions and dry deposition, which are similar to those used in the model configuration applied to create the CAMS reanalysis. We evaluate two reference model configurations with and without the stratospheric chemistry extension against standard observational datasets for tropospheric ozone, surface carbon monoxide (CO), tropospheric nitrogen dioxide (NO2), and aerosol optical depth. The results give basic confidence in the model implementation and configuration. This OpenIFS version with atmospheric composition components is open to the scientific user community under a standard OpenIFS license.

The Integrated Forecasting System (IFS) of ECMWF is used within the Copernicus Atmosphere Monitoring Service (CAMS) to provide global analyses and forecasts of atmospheric composition, including aerosols as well as reactive trace gases and greenhouse gases. Here we provide a first description and assessment of cloud and aerosol pH as computed in EQSAM4CLIM when implemented in the IFS. The more flexible pH computation is furthermore coupled to the aqueous phase chemistry governing the SO2 in-cloud oxidation, as well as to the wet deposition routine for gases. Currently the IFS describes acidity via the scavenging strong inorganic acids (HNO3, H2SO4) and the contribution from SO2 oxidation and buffering via NH3 using a simplistic description, which results in a pH ranging between 3-5. To provide a more diverse range in pH we have coupled the CB05 chemistry scheme and AER-aerosol components of IFS exploiting EQSAM4Clim-based [H+] calculations by introducing the resulting pH into the aqueous phase chemistry and wet deposition processes. The subsequent representation of aerosol acidity in the solution (aerosol/cloud/rain water) has been evaluated against observations and previous modelling studies using the GEOS-Chem global CTM. The use of aerosol induced acidity in the computation of aqueous phase chemical reaction rates was found to be most important for inorganic soluble gas and aerosol phase species, e.g. SO2, and their subsequent oxidative products, e.g. HNO3. The impact on simulated SO2 concentrations at the surface is significant, through changes to the aqueous phase chemistry and subsequent wet deposition. The impact on PM2.5 is generally small but regionally positive, over Europe, US and China. There is a positive impact on surface O3 with a reduction in the annual mean bias at the surface for Europe, the US and China when compared against observational networks for 2019. Surface SO42-concentrations are generally closer to observations, especially during wintertime over Europe and U.S., while surface NH3 shows only moderate changes. NH3 shows no significant improvement in observed biases against observations, but the impact on simulated surface concentration of NH4+ aerosol is generally positive, particularly in winter. Further improvements here can be expected by improving the coupling with mineral cations (Na+, K+, Ca2+, Mg2+), and by including major organic acids in the aerosol neutralisation reactions. For EQSAM4Clim, the neutralisation reactions and the total liquid water content (of aerosols, fog/cloud, rain) are key for the pH computation and the associated gas/aerosol partitioning, and most critical for NH3. Ammonia forms here the only volatile cation (NH4+), those presence in the aerosol phase critically depends on water and mineral cations.In summary, the production efficacy of sulphate and ammonium aerosol is critically dependent on an accurate representation of acidity in aqueous droplets and aerosol species at global scale. This development is not only expected to bring a much improved constraint on the modelling of surface concentrations of sulfur and nitrogen, together with its deposition. Also the cloud and rain water pH itself are within reach as new products of the CAMS global service.

The Copernicus Atmosphere Monitoring Service (CAMS) produces operationally global 5-day forecast of atmospheric composition and the weather using ECMWF’s Integrated Forecasting System (IFS) since 2015.Beginning with a system upgrade in June 2018 (45r1), the ozone and aerosol fields have been used in the radiation scheme to account for their radiative impact in the global CAMS forecasts. This approach replaced an aerosol and ozone climatology, which had been used before and which is still used in ECMWF's operational high-resolution medium-range NWP forecasts. The CAMS forecast system, which runs at a resolution of about 40 km, is applied here as a test-bed to explore the importance of aerosol direct feedback in an operational configuration, which can guide developments on composition-weather feedbacks for ECMWF's medium-range, monthly and seasonal forecasts. The CAMS prognostic aerosol simulations and the assimilation of different AOD retrievals (MODIS, VIIRS, S5P) have been substantially further modified in several upgrades of the CAMS operational system since 2018.We will discuss the changes and improvements of temperature forecast errors focusing on the impact of changing the aerosol simulation and AOD assimilation in the recent cycles. These changes were introduced to improve the realism of the aerosol forecasts, which is a key CAMS forecast product, and not developed specifically considering their impact on NWP.We will show NWP scores, evaluation with synop-observations and satellite radiation products to demonstrate the impact of the prognostic aerosols. We will also compare the results of the NWP forecast of the CAMS suite, with the NWP scores of ECMWF high resolution forecast run ay 9 km spatial resolution globally. We will further demonstrate that the consistent updates of both the climatological and prognostic aerosol fields are an important prerequisite for a sound assessment of the importance of prognostic aerosol in NWP applications.

The Copernicus Atmosphere Monitoring Service (CAMS) provides global analyses and forecasts of atmospheric composition, relying on the Integrated Forecasting System (IFS) of ECMWF. The CAMS global model consists of the aerosol model of the IFS, IFS-AER, which is a sectional-bulk scheme, while the chemistry scheme is based on a CB05-based carbon-bond mechanism, with the option to couple this to BASCOE-based stratospheric chemistry.The composition model is updated regularly, aligned with updates of ECMWF’s operational meteorological model. Here we report on updates planned for the next operational version, referred to as CY48R1. This concern revisions on a large range of topics, as developed over the recent years, and therefore impacting many aspects of chemistry and aerosol composition in troposphere and stratosphere. Main aspects concern:Isoprene oxidation has been redefined, resulting in increased OH recycling and including a first model description of glyoxal as well as basic aromatics chemistry. NOy chemistry has been updated to include HONO and the longer-lived species CH3O2NO2. A coupling with secondary organic aerosol formation has been established, and the coupling of secondary inorganic aerosol has been revisited. the option to use the BASCOE-based stratospheric chemistry for operational application is actively considered. Dry and wet deposition parameterizations have been revisited by including a GEOS-Chem based deposition parameterization using tile fraction specific deposition velocities. Aerosol dust emissions, and their optical properties have been revised. The emissions handling has been updated, along with updates of the CAMS global emission inventories themselves. The updates of the composition model and its emissions are tested in combination with updates to the tracer transport and data assimilation aspects, and the optimal configuration will be selected for operational application.In this contribution we provide an overview of expected changes with emphasis on changes in composition modeling aspects. We will present the subsequent impacts on key atmospheric composition aspects, including air quality performance for major pollution regions across the world, aerosol optical depth, dust, and stratospheric composition products.

We report on an evaluation of tropospheric ozone and its precursor gases in three atmospheric chemistry versions as implemented in the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS), referred to as IFS(CB05BASCOE), IFS(MOZART) and IFS(MOCAGE). While the model versions were forced with the same overall meteorology, emissions, transport and deposition schemes, they vary largely in their parameterisations describing atmospheric chemistry, including the organics degradation, heterogeneous chemistry and photolysis, as well as chemical solver. The model results from the three chemistry versions are compared against a range of aircraft field campaigns, surface observations, ozone-sondes and satellite observations, which provides quantification of the overall model uncertainty driven by the chemistry parameterisations. We find that they produce similar patterns and magnitudes for carbon monoxide (CO) and ozone (O3), as well as a range of non-methane hydrocarbons (NMHCs), with averaged differences for O3 (CO) within 10 % (20 %) throughout the troposphere. Most of the divergence in the magnitude of CO and NMHCs can be explained by differences in OH concentrations, which can reach up to 50 %, particularly at high latitudes. There are also comparatively large discrepancies between model versions for NO2, SO2 and HNO3, which are strongly influenced by secondary chemical production and loss. Other common biases in CO and NMHCs are mainly attributed to uncertainties in their emissions. This configuration of having various chemistry versions within IFS provides a quantification of uncertainties induced by chemistry modelling in the main CAMS global trace gas products beyond those that are constrained by data assimilation.

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.

The COVID-19 pandemic struck China in January 2020 and the rest of the world from February 2020 onwards. Public authorities enforced several kinds of lockdowns in order to limit the spread of the pandemic and reduce its impact on the health system: at the height of the first wave of the pandemic, more than one human in two was subjected to a lockdown, with associated disruption in local and international travel, industry, tourism etc. These lockdowns had a profound effect on anthropogenic emissions of aerosol, trace gases and greenhouse gases; in this work we focus on aerosols and a selection of trace gases.The Integrated Forecasting System (IFS) of ECMWF is core of the Copernicus Atmosphere Monitoring Service (CAMS) to provide global analyses and forecasts of atmospheric composition, including reactive gases, as well as aerosol and greenhouse gases. In this work, we use two emission reduction scenario with an experimental version of the IFS in its CAMS configuration: a global and a European one. Global simulations of aerosols were carried out with these two scenarii and compared to a reference simulation without any COVID-19 impact, and to worldwide observations of PM2.5, AOD and trace gases.The simulated PM2.5 using the global emission reduction scenario were found to reproduce quite accurately the observed evolution over China, India and United States. Over Europe, the simulated PM2.5 using the European reduction scenario were closer to observations and appeared more realistic. India was the only place where a significant impact on AOD and on temperature and radiation from the COVID-19 lockdowns was simulated. These simulations also provided information on how the aerosol speciation was altered by the COVID-19 lockdowns: over Europe and the U.S., most of the decrease in surface aerosols was simulated to come from nitrate aerosols. Over the U.S., this matched well with observations of speciated aerosols at surface.

The Integrated Forecasting System (IFS) of ECMWF is used within the Copernicus Atmosphere Monitoring Service (CAMS) to provide global analyses and forecasts of atmospheric composition, including aerosols as well as reactive trace gases and greenhouse gases.The aerosol model of the IFS, IFS-AER, is a simple sectional-bulk scheme that forecasts seven species: dust, sea-salt, black carbon, organic matter, sulfate, and since July 2019, nitrate and ammonium. The main developments that have been recently carried out, tested and are now contemplated for implementation in the next operational version (known as cycle 48r1) are presented here.The dry deposition velocities are computed as a function of roughness length, particle size and surface friction velocity, while wet deposition depends mainly on the precipitation fluxes. The parameterizations of both dry and wet deposition have been upgraded with more recent schemes, which have been shown to improve the simulated deposition fluxes for several aerosol species. The impact of this upgrade on the skill scores of simulated aerosol optical depth (AOD) and surface particulate matter concentrations against a range of observations is very positive.The simulated surface concentration of nitrate and ammonium are frequently strongly overestimated over Europe and the United States in the current version of the IFS. Nitrate, ammonium, and their precursors nitric acid and ammonia, were evaluated against a range of ground and remote data and it was found that the recently-implemented gas-particle partitioning scheme is too efficient in producing nitrate and ammonium particles.A series of small-scale changes, such as adjusting nitrate dry deposition velocity, direct particulate sulphate emission, and limiting nitrate/ammonium production by the concentration of mineral cations, have been implemented and shown to be effective in improving the simulated surface concentration of nitrate and ammonium.The representation of secondary organic aerosol (SOA) in the IFS has been overhauled with the introduction of a new SOA species, distinct from primary organic matter, with anthropogenic and biogenic components. The implementation of this new species leads to a significant improvement of the simulated surface concentration of organic carbon. An evaluation of simulated SOA concentrations at the surface against climatological values derived from observations using Positive Matrix Factorisation (PMF) techniques also shows a reasonable agreement.

We present interactive stratospheric aerosol simulations with the ICBG system, a global tropospheric-stratospheric combined aerosol-chemistry model which is an extension to the ECMWF Integrated Forecasting System (IFS), and is developed as part of the Copernicus Atmosphere Monitoring Service (CAMS). ICBG is the result of the merging of two existing CAMS configurations of the IFS:The IFS-GLOMAP tropospheric-stratospheric aerosol microphysics system, which has the GLOMAP-mode aerosol scheme configured for forecast-cycling experiments within the IFS, The IFS-CB05-BASCOE tropospheric (CB05) – stratospheric (BASCOE) chemistry scheme, which is also an established configuration of the IFS within CAMS. During the first phase of CAMS, the stratospheric chemistry scheme IFS-BASCOE was extended to include the stratospheric sulphur chemistry from the UM-UKCA model, with sulphuric acid production rates from IFS-BASCOE passed each timestep to the aerosol scheme IFS-GLOMAP for aerosol particle nucleation and condensation. The aerosol surface area densities (SAD) simulated by IFS-GLOMAP simulated are similarly passed each timestep to the stratospheric chemistry scheme IFS-BASCOE for heterogeneous reactions. In a recent progression of this strato-tropospheric modelling system, the climatology for meteoric smoke particles (MSP) used in UM-UKCA has also been implemented. Thus the simulated stratospheric aerosol layer comprises not only pure sulphuric particles nucleated homogeneously but also meteoric-sulphuric particles formed from the MSPs.We evaluate the simulated stratosphere aerosol layer in quiescent conditions, comparing it to SAGE-II measurements from the 1998-2002 period. The simulated stratospheric sulfate burden, aerosol extinction, stratospheric aerosol optical depth (sAOD) and surface area density (SAD) agree well with the SAGE-II retrievals. We also show results from ICBG simulations of the volcanic aerosol cloud from a large-magnitude tropical eruption (Pinatubo, June 1991, VEI6) and a medium-magnitude eruption at a northern mid-latitude (Raikoke, June 2019, VEI4).

The widespread presence of meteoric smoke particles (MSPs) within a distinct class of stratospheric aerosol particles has become clear from in-situ measurements in the Arctic, Antarctic and at mid-latitudes. We apply an adapted version of the interactive stratosphere aerosol configuration of the composition-climate model UM-UKCA, to predict the global distribution of meteoric-sulphuric particles nucleated heterogeneously on MSP cores. We compare the UM-UKCA results to new MSP-sulphuric simulations with the European stratosphere-troposphere chemistry-aerosol modelling system IFS-CB05-BASCOE-GLOMAP.The simulations show a strong seasonal cycle in meteoric-sulphuric particle abundance results from the winter-time source of MSPs transported down into the stratosphere in the polar vortex. Coagulation during downward transport sees high latitude MSP concentrations reduce from ~500 per cm3 at 40km to ~20 per cm3 at 25km, the uppermost extent of the stratospheric aerosol particle layer (the Junge layer). Once within the Junge layer's supersaturated environment, meteoric-sulphuric particles form readily on the MSP cores, growing to 50-70nm dry-diameter (Dp) at 20-25km. Further inter-particle coagulation between these non-volatile particles reduces their number to 1-5 per cc at 15-20km, particle sizes there larger, at Dp ~100nm.The model predicts meteoric-sulphurics in high-latitude winter comprise >90% of Dp>10nm particles above 25km, reducing to ~40% at 20km, and ~10% at 15km. These non-volatile particle fractions are slightly less than measured from high-altitude aircraft in the lowermost Arctic stratosphere (Curtius et al., 2005; Weigel et al., 2014), and consistent with mid-latitude aircraft measurements of lower stratospheric aerosol composition (Murphy et al., 1998), total particle concentrations also matching in-situ balloon measurements from Wyoming (Campbell and Deshler, 2014). The MSP-sulphuric interactions also improve agreement with SAGE-II observed stratospheric aerosol extinction in the quiescent 1998-2002 period. Simulations with a factor-8-elevated MSP input form more Dp>10nm meteoric-sulphurics, but the increased number sees fewer growing to Dp ~100nm, the increased MSPs reducing the stratospheric aerosol layer’s light extinction.

CO is an abundant tropospheric pollutant that originates from numerous emission sources. Large CO fluxes are emitted during intense Biomass Burning (BB) events over relatively short periods of a few days, which combined with the tropospheric lifetime of a month, act as a marker for air-masses influenced by burning events. Once lifted out the boundary layer, air masses influenced by BB undergo chemical processing which can be assessed by subsequent changes in tropospheric ozone. Increases in ozone and aerosol in the Free Troposphere influence photolysis at lower levels impact surface air-quality. Therefore, capturing this feedback is a necessary step towards determining tropospheric lifetimes of greenhouse gases and pollutants, which affects the fraction of transport out of the burning regions.Here we present results from the Integrated Forecasting System (IFS) of ECMWF, which is the core of the Copernicus Atmosphere Monitoring Service (CAMS). We perform simulations with three independent chemistry modules (modified CB05, MOZART, MOCAGE), including variable photolysis schemes and variable approaches for coupling tropospheric aerosol. We choose the simulation year of 2019 corresponding with the FIREXAQ measurement campaign which occurred over California. We subsequently assess the ability of IFS in terms of (i) the representation of the transport of air masses effected by large BB emissions, (ii) the ability towards capturing chemical processing which occurs in such plumes and (iii) using large discrepancies in the simulated tropospheric profiles to imply deficiencies in BB emission estimates.

The Integrated Forecasting System (IFS) of ECMWF is the core of the Copernicus Atmosphere Monitoring Service (CAMS) which provides global analyses and forecasts of atmospheric composition, namely reactive gases, aerosol and greenhouse gases. With respect to the atmospheric chemistry component, the operational system currently relies on a modified version of the CB05 chemistry scheme for the troposphere, combined with the Cariolle scheme to describe stratospheric ozone. In an alternative, more recent configuration also stratospheric ozone chemistry is included based on the BASCOE chemistry module. Alternative atmospheric chemistry modules which can be employed are based on MOZART and MOCAGE chemistry. Recently, further revisions to the modified CB05 tropospheric chemistry scheme have been developed, focusing both on inorganic and organic chemistry, with the aim of improving the quality of existing air-quality products, and the development of new products. On major update is a revision of the isoprene oxidation scheme based on those employed in existing chemistry transport models, as well as inclusion of the basic chemistry describing C8 and C9 aromatics degradation. An example of a new product derived from these updates include a description of global distribution of glyoxal, while this also resulted in an improved modeling of OH recycling particularly over tropical forests. Also we support improved secondary organic aerosol formation due to gaseous anthropogenic, biogenic and biomass burning sources.In this contribution we provide an overview of these revisions, and provide a first quantification of their uncertainties, by comparing products to observations and to those from alternative chemistry modules.

Launched in October 2017, the TROPOspheric Monitoring Instrument (TROPOMI) aboard Sentinel-5 Precursor provides the potential to monitor air quality over point sources across the globe with a spatial resolution as high as 5.5 km × 3.5 km (7 km × 3.5 km before 6 August 2019). The nitrogen dioxide (NO2) retrieval algorithm for the TROPOMI instrument consists of three steps: the spectral fitting of the slant column, the separation of stratospheric and tropospheric contributions, and the conversion of the slant column to a vertical column using an air mass factor (AMF) calculation. In this work, an improved tropospheric NO2 retrieval algorithm from TROPOMI measurements over Europe is presented. The stratospheric estimation is implemented using the STRatospheric Estimation Algorithm from Mainz (STREAM), which was developed as a verification algorithm for TROPOMI and does not require chemistry transport model data as input. A directionally dependent STREAM (DSTREAM) is developed to correct for the dependency of the stratospheric NO2 on the viewing geometry by up to 2 × 1014 molec/cm2. Applied to synthetic TROPOMI data, the uncertainty in the stratospheric column is 3.5 × 1014 molec/cm2 for polluted conditions. Applied to actual measurements, the smooth variation of stratospheric NO2 at low latitudes is conserved, and stronger stratospheric variation at higher latitudes are captured. For AMF calculation, the climatological surface albedo data is replaced by geometry-dependent effective Lambertian equivalent reflectivity (GE_LER) obtained directly from TROPOMI measurements with a high spatial resolution. Mesoscale-resolution a priori NO2 profiles are obtained from the regional POLYPHEMUS/DLR chemistry transport model with the TNO-MACC emission inventory. Based on the latest TROPOMI operational cloud parameters, a more realistic cloud treatment is provided by a clouds-as-layers (CAL) model, which treats the clouds as uniform layers of water droplets, instead of the clouds-as-reflecting-boundaries (CRB) model, in which clouds are simplified as Lambertian reflectors. For the error analysis, the tropospheric AMF uncertainty, which is the largest source of NO2 uncertainty for polluted scenarios, ranges between 20 % and 50 %, leading to a total uncertainty in the tropospheric NO2 column in the 30–60 % range. From a validation performed with ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements, the improved tropospheric NO2 data shows good correlations for nine European urban/suburban stations with an average correlation coefficient of 0.78. The implementation of the algorithm improvements leads to a decrease of the relative difference from −55.3 % to −34.7 % on average.

A reanalysis dataset produced by the Copernicus Atmosphere Monitoring service (CAMS reanalysis, 2003 - present day) augmented by ERA5 data for the years before 2003 is used to describe the evolutio...

Global tropospheric ozone reanalyses constructed using different state-of-the-art satellite data assimilation systems, prepared as part of the Copernicus Atmosphere Monitoring Service (CAMS-iRean and CAMS-Rean) as well as two fully independent reanalyses (TCR-1 and TCR-2, Tropospheric Chemistry Reanalysis), have been intercompared and evaluated for the past decade. The updated reanalyses (CAMS-Rean and TCR-2) generally show substantially improved agreements with independent ground and ozone-sonde observations over their predecessor versions (CAMS-iRean and TCR-1) for diurnal, synoptical, seasonal, and interannual variabilities. For instance, for the Northern Hemisphere (NH) mid-latitudes the tropospheric ozone columns (surface to 300 hPa) from the updated reanalyses show mean biases to within 0.8 DU (Dobson units, 3 % relative to the observed column) with respect to the ozone-sonde observations. The improved performance can likely be attributed to a mixture of various upgrades, such as revisions in the chemical data assimilation, including the assimilated measurements, and the forecast model performance. The updated chemical reanalyses agree well with each other for most cases, which highlights the usefulness of the current chemical reanalyses in a variety of studies. Meanwhile, significant temporal changes in the reanalysis quality in all the systems can be attributed to discontinuities in the observing systems. To improve the temporal consistency, a careful assessment of changes in the assimilation configuration, such as a detailed assessment of biases between various retrieval products, is needed. Our comparison suggests that improving the observational constraints, including the continued development of satellite observing systems, together with the optimization of model parameterizations such as deposition and chemical reactions, will lead to increasingly consistent long-term reanalyses in the future.

Intercomparisons between Chemistry-Climate Models (CCMs) have highlighted shortcomings in our understanding and/or modeling of long-term ozone trends, and there is a growing interest in the impact of stratospheric ozone changes on tropospheric chemistry via both ozone fluxes (e.g. from the projected strengthening of the Brewer-Dobson circulation) and actinic fluxes. Advances in this area require a good understanding of the modelling uncertainties in the present-day distribution of stratospheric ozone, and a correct attribution of these uncertainties to the processes governing this distribution: photolysis, chemistry and transport. These processes depend primarily on solar irradiance, temperature and dynamics.Here we estimate model uncertainties arising from different input datasets, and compare them with typical uncertainties arising from the transport and chemistry schemes. This study is based on four sets of tightly controlled sensititivity experiments which all use temperature and dynamics specified from reanalyses of meteorological observations. The first set of experiments uses one Chemistry-Transport Model (CTM) and evaluates the impact of using 3 different spectra of solar irradiance. In the second set, the CTM is run with 4 different input reanalyses: ERA-5, MERRA-2, ERA-I and JRA-55. The third set of experiments still relies on the same CTM, exploring the impact of the transport algorithm and its configuration. The fourth set is the most sophisticated as it is enabled by model developments for the Copernicus Atmopshere Monitoring Service, where the ECMWF model IFS is run with three different photochemistry modules named according to their parent CTM: IFS(CB05-BASCOE), IFS(MOCAGE) and IFS(MOZART).All modelling experiments start from the same initial conditions and last 2.5 years (2013-2015). The uncertainties arising from different input datasets or different model components are estimated from the spreads in each set of sensitivity experiments and also from the gross error between the corresponding model means and the BASCOE Reanalysis of Aura-MLS (BRAM2). The results are compared across the four sets of experiments, as a function of latitude and pressure, with a focus on two regions of the stratosphere: the polar lower stratosphere in winter and spring - in order to assess and understand the quality of our ozone hole forecasts - and the tropical middle and upper stratosphere - where noticeably large disagreements are found between the experiments.

As part of the Copernicus Atmosphere Monitoring Service (CAMS), operated by ECMWF on behalf of the European Commission, global analyses and forecasts of atmospheric composition have been produced operationally since 2015. These were built on many years of previous work under the GEMS and MACC projects, which began producing regular forecasts in 2007.Since the transition to an operational service, there have continued to be many new developments and improvements to the system in five major upgrades, including increased horizontal and vertical resolution, updated emissions and paramterisations, additional species such as nitrate aerosol, as well as updates to the underlying meteorological model and data assimilation. The components of this system (aerosols, gas-phase chemistry, meteorology and the ocean) are also now coupled more tightly via active feedbacks then ever before.In this interactive presentation, we will demonstrate the impact of a number of these developments on the performance of the resulting global air quality forecasts, alongside the continuing evolution of our approaches to assessing model improvement against independent in-situ and remote-sensing observations from a variety of platforms.Because the continuing evolution of an operational system can make the analysis of long-term trends problematic, we will also contrast this with the CAMS global reanalysis product, which (while not using the very latest version of the model) do provide a consistent long-term dataset from 2003 onwards.

The Copernicus Atmosphere Monitoring Service (CAMS) produces operationally global 5-day forecast of atmospheric composition and the weather using ECMWF’s Integrated Forecasting System (IFS) since 2015.Beginning with a system upgrade in June 2018 (45r1), the ozone and aerosol fields have been used in the radiation scheme to account for their radiative impact in the global CAMS forecasts. This approach replaced an aerosol and ozone climatology, which had been used before and which is still used in ECMWF's operational high-resolution medium-range NWP forecasts. The CAMS forecast system, which runs at a resolution of about 40 km, is applied here as a test-bed to explore the importance of aerosol direct feedback in an operational configuration, which can guide developments on composition-weather feedbacks for ECMWF's medium-range, monthly and seasonal forecasts.We will discuss the changes and improvements of temperature forecast errors (i) using typical NWP scores and (ii) by applying an event based approach that focuses on episodes of high aerosol burdens such as the transport of Sahara dust to Europe during the heatwave in June 2019. In more detail we will show to what extent the realism of the prognostic aerosol fields influences the temperature response by considering aerosol forecast which were, or were not, improved by data assimilation of aerosol optical depth at the start of the forecast. We will further demonstrate that the consistent updates of both the climatological and prognostic aerosol fields are an important prerequisite for a making progress.

Global tropospheric ozone reanalyses constructed using different state-of-the-art satellite data assimilation systems, prepared as part of the Copernicus Atmosphere Monitoring Service (CAMS-iRean and CAMS-Rean) as well as two fully independent Tropospheric Chemistry Reanalyses (TCR-1 and TCR-2), have been inter-compared and evaluated for the past decade. The updated reanalyses (CAMS-Rean and TCR-2) generally show substantially improved agreements with independent ground and ozonesonde observations over their predecessor versions (CAMS-iRean and TCR-1) for the diurnal, synoptical, seasonal, and decadal variability. The improved performance can be attributed to a mixture of various upgrades, such as revisions in the chemical data assimilation, including the assimilated measurements, and the forecast model performance. The updated chemical reanalyses agree well with each other for most cases, which highlights the usefulness of the current chemical reanalyses in a variety of studies. Meanwhile, significant temporal changes in the reanalysis quality in all the systems can be attributed to discontinuities in the observing systems. To improve the temporal consistency, a careful assessment of changes in the assimilation configuration, such as a detailed assessment of biases between various retrieval products, is needed. Even though the assimilation of multi-species data influences the representation of the trace gases in all the systems and also the precursors’ emissions in the TCR reanalyses, the influence of persistent model errors remains a concern, especially for the lower troposphere. Our comparison suggests that improving the observational constraints, including the continued development of satellite observing systems, together with the optimization of model parameterisations, such as deposition and chemical reactions, will lead to increasingly consistent long-term reanalyses in the future.

An improved tropospheric nitrogen dioxide (NO2) retrieval algorithm from the Global Ozone Monitoring Experiment-2 (GOME-2) instrument based on air mass factor (AMF) calculations performed with more realistic model parameters is presented. The viewing angle-dependency of surface albedo is taken into account by improving the GOME-2 Lambertian-equivalent reflectivity (LER) climatology with a directionally dependent LER (DLER) dataset over land and an ocean surface albedo parametrization over water. A priori NO2 profiles with higher spatial and temporal resolutions are obtained from the IFS(CB05BASCOE) chemistry transport model based on recent emission inventories. A more realistic cloud treatment is provided by a Cloud-As-Layers (CAL) approach, which treats the clouds as uniform layers of water droplets, instead of the current Clouds-as-Reflecting-Boundaries (CRB) model, which assumes the clouds as Lambertian reflectors. Improvements in the AMF calculation affect the tropospheric NO2 columns on average within ±15 % in winter and ±5 % in summer over largely polluted regions. In addition, the impact of aerosols on our tropospheric NO2 retrieval is investigated by comparing the concurrent retrievals based on ground-based aerosol measurements (explicit aerosol correction) and aerosol-induced cloud parameters (implicit aerosol correction). Compared to the implicit aerosol correction through the CRB cloud parameters, the use of CAL reduces the AMF errors by more than 10 %. Finally, to evaluate the improved GOME-2 tropospheric NO2 columns, a validation is performed using ground-based Multi-AXis Differential Optical Absorption Spectroscopy (MAXDOAS) measurements at the BIRA-IASB Xianghe station. The improved tropospheric NO2 dataset shows good agreement with coincident ground-based measurements with a correlation coefficient of 0.94 and a relative difference of −9.9 % on average.

This article describes the IFS-AER aerosol module used operationally in the Integrated Forecasting System (IFS) cycle 45R1, operated by the European Centre for Medium RangeWeather Forecasts (ECMWF) in the framework of the Copernicus Atmospheric Monitoring Services (CAMS). We describe the different parameterizations for aerosol sources, sinks and its chemical production in IFS-AER, as well as how the aerosols are integrated in the larger atmospheric composition forecasting system. The focus is on the entire 45R1 code-base, including some components that are not used operationally, in which case this will be clearly specified. This paper is an update to the Morcrette et al. (2009) article that described aerosol forecasts at ECMWF, using the cycle 32R2 of the IFS. Between cycles 32R2 and 45R1, a number of source and sink processes have been reviewed and/or added, increasing notably the complexity of IFS-AER. A greater integration with the tropospheric chemistry scheme of the IFS has been achieved, for the sulphur cycle as well as for nitrate production. Two new species, nitrate and ammonium, have also been included in the forecasting system. Global budgets and aerosol optical depth (AOD) fields are shown, as well as an evaluation of the simulated Particulate Matter (PM) and AOD against observations, showing an increase in skill from cycle 40R2, used in the CAMS interim Reanalysis (CAMSiRA), to cycle 45R1.