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The TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel 5 Precursor (S5P) satellite launched in October 2017 yields a wealth of atmospheric composition data, including retrievals of total column ozone (TCO3) that are provided in near-real time (NRT) and off-line. These NRT TCO3 retrievals (V1.0.0) have been included in the data assimilation system of the Copernicus Atmosphere Monitoring Service (CAMS), and tests to monitor the data and to carry out first assimilation experiments with them have been performed for the period 26 November 2017 to 3 May 2018. TROPOMI was still in its commissioning phase until 24 April 2018. Nevertheless, the results show that, even at this early stage, the TROPOMI TCO3 data generally agree well with the CAMS analysis over large parts of the Globe and also with TCO3 retrievals from the Ozone Monitoring Instrument (OMI) and the Global Ozone Monitoring Experiment-2 (GOME-2) that are routinely assimilated by CAMS. However, the TCO3 NRT data from TROPOMI show some retrieval anomalies at high latitudes, at low solar elevations and over snow/ice (e.g. Antarctica) where the differences with the CAMS analysis and the other datasets are larger. These differences come mainly from the surface albedo climatology that is used in the NRT TROPOMI TCO3 retrieval. This climatology has a coarser horizontal resolution than the TROPOMI TCO3 data which leads to problems in areas where there are large changes in reflectivity from pixel to pixel, e.g. pixels covered by snow/ice or not. The assimilation of TROPOMI TCO3 has been tested in the CAMS system for data between 60°N and 60°S and for solar elevations less than 10° and is found to have only little impact on the ozone analysis, because the CAMS analysis is already well constrained by several other ozone retrievals that are routinely assimilated. Variational bias correction is applied to the TROPOMI NRT TCO3 data and successfully corrects for the biases seen in the data. Averaged over the period 26 November 2017 to 3 May 2018, difference between experiments with and without assimilation of TROPOMI data are less than 2% for TCO3 and less than 1% in the vertical for averaged zonal mean O3 mixing ratios. Compared to independent observation (Brewer spectrometers, ozone sondes, IAGOS ozone profiles and GAW surface measurements) the differences between the assimilation run and a run without TROPOMI assimilation are also small. The only noteworthy differences between the experiment with and without assimilation of TROPOMI data are seen compared to IAGOS profiles at West African airports where the assimilation of TROPOMI improves the fit of the CAMS analysis to the independent data. Despite the small impact of TROPOMI TCO3 in the CAMS analysis it will be beneficial to include the TROPOMI TCO3 NRT data actively in the operational NRT CAMS analysis after more tests. This will add some redundancy and resilience in the system and will allow us to use a more robust observation system in case some of the other older instruments, whose retrievals are currently assimilated by CAMS, stop working.

Stratosphere-to-troposphere transport (STT) is an important natural source of tropospheric ozone, which can occasionally influence ground-level ozone concentrations relevant for air quality. Here, we analyse and evaluate the Copernicus Atmosphere Monitoring Service (CAMS) global and regional forecast systems during a deep STT event over Europe for the time period from 4 to 9 January 2017. The predominant synoptic condition is described by a deep upper level trough over eastern and central Europe, favouring the formation of tropopause folding events along the jet stream axis and therefore the intrusion of stratospheric ozone into the troposphere. Both global and regional CAMS forecast products reproduce the “hook-shaped” streamer of ozone-rich and dry air in the middle troposphere depicted from the observed satellite images of water vapour. The CAMS global model successfully reproduces the folding of the tropopause at various European sites, such as Trapani (Italy), where a deep folding down to 550 hPa is seen. The stratospheric ozone intrusions into the troposphere observed by WOUDC ozonesonde and IAGOS aircraft measurements are satisfactorily forecasted up to 3 days in advance by the CAMS global model in terms of both temporal and vertical features of ozone. The fractional gross error (FGE) of CAMS ozone day 1 forecast between 300 and 500 hPa is 0.13 over Prague, while over Frankfurt it is 0.04 and 0.19, highlighting the contribution of data assimilation, which in most cases improves the model performance. Finally, the meteorological and chemical forcing of CAMS global forecast system in the CAMS regional forecast systems is found to be beneficial for predicting the enhanced ozone concentrations in the middle troposphere during a deep STT event.

Elevated ozone (O3) pollution is observed every spring over the Northern Indian region including the Himalayan foothills, with a maximum typically in the month of May. However, studies investigating influences of photochemistry and dynamics in the valleys of Central Himalaya are limited. Here, in situ surface O3 observations conducted at Dehradun (77.99° E, 30.27° N, 600 m above mean sea level) in the Doon Valley during April-July 2018 are presented. These O3 observations reveal the prevalence of an urban environment over Dehradun with enhanced levels during noontime (66.4 ppbv ± 11.0 ppbv in May) and lower levels during night (26.7 ppbv ± 11.5 ppbv). Morning time O3 enhancement rate at Dehradun (7.5 ppbv h-1) is found to be comparable to that at Bode (7.3 ppbv h-1) in another valley of Himalayan foothills (Kathmandu), indicating stronger anthropogenic emissions in the Doon Valley as well. Daily average O3 at Dehradun varied in the range of 13.7-71.3 ppbv with hourly values reaching up to 103.1 ppbv during the study period. Besides the in situ photochemical O3 production, the entrainment of O3-rich air through boundary layer dynamics also contributes in noontime O3 enhancement in the Doon Valley. Monthly average O3 at Dehradun (49.3 ppbv ± 19.9 ppbv) is observed to be significantly higher than that over urban sites in Northern India (35-41 ppbv) and Bode (38.5 ppbv) in the Kathmandu Valley during May. O3 photochemical buildup, estimated to be 30.3 ppbv and 39.7 ppbv during April and May, respectively, is significantly lower in June (21.2 ppbv). Copernicus Atmosphere Monitoring Service (CAMS) model simulations successfully reproduce the observed variability in noontime O3 at Dehradun (r = 0.86); however, absolute O3 levels were typically overestimated. The positive relationship between CAMS O3 and CO (r = 0.65) together with an O3/CO slope of 0.16 is attributed to the influences of biomass burning besides anthropogenic emissions on observed O3 variations in the Doon Valley. O3 observations show an enhancement by 35-56% at Dehradun during a high-fire activity period in May 2018 as compared to a low-fire activity period over the Northern Indian region in agreement with the enhancement found in CAMS O3 fields (10-65%) over the region in the vicinity of Dehradun.

This work is an extended evaluation of near-surface ozone as part of the global reanalysis of atmospheric composition, produced within the European-funded project MACC (Monitoring Atmospheric Composition and Climate). It includes an evaluation over the period 2003–2012 and provides an overall assessment of the modeling system performance with respect to near-surface ozone for specific European subregions. Measurements at rural locations from the European Monitoring and Evaluation Program (EMEP) and the European Air Quality Database (AirBase) were used for the evaluation assessment. The fractional gross error of near-surface ozone reanalysis is on average 24 % over Europe, the highest found over Scandinavia (27 %) and the lowest over the Mediterranean marine stations (21 %). Near-surface ozone shows mostly a negative bias in winter and a positive bias during warm months. Assimilation reduces the bias in near-surface ozone in most of the European subregions – with the exception of Britain and Ireland and the Iberian Peninsula and its impact is mostly notable in winter. With respect to the seasonal cycle, the MACC reanalysis reproduces the photochemically driven broad spring-summer maximum of surface ozone of central and south Europe. However, it does not capture adequately the early spring peak and the shape of the seasonality at northern and north-eastern Europe. The diurnal range of surface ozone, which is as an indication of the local photochemical production processes, is reproduced fairly well, with a tendency for a small overestimation during the warm months for most subregions (especially in central and southern Europe). Possible reasons leading to discrepancies between the MACC reanalysis and observations are discussed.

The Copernicus Atmosphere Monitoring Service (CAMS) is one of the six thematic services of the European Union's flagship Earth Observation programme Copernicus. CAMS is implemented by the European Centre for Medium-Range Weather Forecasts (ECMWF) together with a network of about 60 entities distributed in 20 European countries: it is thus a truly international and collaborative effort. CAMS delivers operationally a wide range of information products and services on air quality, emissions and surface fluxes, solar radiation and climate forcings. All CAMS atmospheric composition outputs are unrestricted and provided free-of-charge to users worldwide. The CAMS global forecasting system is using ECMWF's Integrated Forecasting System (IFS), which is used successfully for Numerical Weather Prediction and has been extended with modules for atmospheric chemistry, aerosols and greenhouse gases. Over 60 different satellite data streams are assimilated to provide twice daily global atmosphere composition forecasts.

The El Niño–Southern Oscillation (ENSO) not only affects meteorological fields but also has a large impact on atmospheric composition. Atmospheric composition fields from the Monitoring Atmospheric Composition and Climate (MACC) reanalysis are used to identify the ENSO signal in tropospheric ozone, carbon monoxide, nitrogen oxide and smoke aerosols, concentrating on the months October to December. During El Niño years, all of these fields have increased concentrations over maritime South East Asia in October. The MACC Composition Integrated Forecasting System (C-IFS) model is used to quantify the relative magnitude of dynamically induced and emission-driven changes in the atmospheric composition fields. While changes in tropospheric ozone are a combination of dynamically induced and emission-driven changes, the changes in carbon monoxide, nitrogen oxides and smoke aerosols are almost entirely emission-driven in the MACC model. The ozone changes continue into December, i.e. after the end of the Indonesian fire season while changes in the other fields are confined to the fire season.

International audience; Data assimilation is used in atmospheric chemistry models to improve air quality forecasts, construct re-analyses of three-dimensional chemical (including aerosol) concentrations and perform inverse modeling of input variables or model parameters (e.g., emissions). Coupled chemistry meteorology models (CCMM) are atmospheric chemistry models that simulate meteorological processes and chemical transformations jointly. They offer the possibility to assimilate both meteorological and chemical data; however, because CCMM are fairly recent, data assimilation in CCMM has been limited to date. We review here the current status of data assimilation in atmospheric chemistry models with a particular focus on future prospects for data assimilation in CCMM. We first review the methods available for data assimilation in atmospheric models, including variational methods, ensemble Kalman filters, and hybrid methods. Next, we review past applications that have included chemical data assimilation in chemical transport models (CTM) and in CCMM. Observational data sets available for chemical data assimilation are described, including surface data, surface-based remote sensing, airborne data, and satellite data. Several case studies of chemical data assimilation in CCMM are presented to highlight the benefits obtained by assimilating chemical data in CCMM. A case study of data assimilation to constrain emissions is also presented. There are few examples to date of joint meteorological and chemical data assimilation in CCMM and potential difficulties associated with data assimilation in CCMM are discussed. As the number of variables being assimilated increases, it is essential to characterize correctly the errors; in particular, the specification of error cross-correlations may be problematic. In some cases, offline diagnostics are necessary to ensure that data assimilation can truly improve model performance. However, the main challenge is likely to be the paucity of chemical data available for assimilation in CCMM. © Author(s) 2015. CC Attribution 3.0 License.

A 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.

The two Global Ozone Monitoring Instrument (GOME-2) sensors operated in tandem are flying onboard EUMETSAT's (European Organisation for the Exploitation of Meteorological Satellites) MetOp-A and MetOp-B satellites, launched in October 2006 and September 2012 respectively. This paper presents the operational GOME-2/MetOp-A (GOME-2A) and GOME-2/MetOp-B (GOME-2B) total ozone products provided by the EUMETSAT Satellite Application Facility on Ozone and Atmospheric Chemistry Monitoring (O3M-SAF). These products are generated using the latest version of the GOME Data Processor (GDP version 4.7). The enhancements in GDP 4.7, including the application of Brion–Daumont–Malicet ozone absorption cross sections, are presented here. On a global scale, GOME-2B has the same high accuracy as the corresponding GOME-2A products. There is an excellent agreement between the ozone total columns from the two sensors, with GOME-2B values slightly lower with a mean difference of only 0.55±0.29%. First global validation results for 6 months of GOME-2B total ozone using ground-based measurements show that on average the GOME-2B total ozone data obtained with GDP 4.7 are slightly higher than, both, Dobson observations by about 2.0±1.0% and Brewer observations by about 1.0±0.8%. It is concluded that the total ozone columns (TOCs) provided by GOME-2A and GOME-2B are consistent and may be used simultaneously without introducing systematic effects, which has been illustrated for the Antarctic ozone hole on 18 October 2013. GOME-2A total ozone data have been used operationally in the Copernicus atmospheric service project MACC-II (Monitoring Atmospheric Composition and Climate – Interim Implementation) near-real-time (NRT) system since October 2013. The magnitude of the bias correction needed for assimilating GOME-2A ozone is reduced (to about −6 DU in the global mean) when the GOME-2 ozone retrieval algorithm changed to GDP 4.7.

In 2002, the European Space Agency (ESA) launched the ENVIromental SATellite (ENVISAT), which carried ten instruments to provide continuous observation of Earth's land, atmosphere, oceans and ice caps. During the satellite's lifetime, the European Centre for Medium Range Weather Forecasts (ECMWF) has routinely monitored a variety of products from many of its instruments. A subset of these data has also been assimilated in the ECMWF operational system, along with two of its applications: the reanalysis and the Monitoring Atmospheric Composition and Climate (MACC) systems. This article reviews those activities and summarizes the lessons learnt in monitoring and assimilating data from a research satellite within a numerical weather prediction system. The value of continuous data monitoring and the benefits that a close collaboration between data provider and data user can bring to both parties are highlighted. For observations that were assimilated, impact assessments on the ECMWF products have been performed periodically. Two cases are presented in this article. The first one shows that the assimilation of ocean wave information can reduce the wave-height model random error by up to 8% at the analysis time, with benefits at later forecast times extending to up to 5 days in the Tropics. The second example shows that the assimilation of two ENVISAT ozone products improves the agreement of the ozone analyses with independent ozone observations obtained from sondes and the Microwave Limb Sounder. Finally, the use of ENVISAT reprocessed data is presented, with an emphasis on the importance of data reprocessing and long-term data preservation as key activities to ensure the future usage of these datasets.

This study examines the adequacy of the existing Brewer network to supplement other networks from the ground and space to detect SO2 plumes of volcanic origin. It was found that large volcanic eruptions of the last decade in the Northern Hemisphere have a positive columnar SO2 signal seen by the Brewer instruments located under the plume. It is shown that a few days after the eruption the Brewer instrument is capable of detecting significant columnar SO2 increases, exceeding on average 2 DU relative to an unperturbed pre-volcanic 10-day baseline, with a mean close to 0 and σ = 0.46, as calculated from the 32 Brewer stations under study. Intercomparisons with independent measurements from the ground and space as well as theoretical calculations corroborate the capability of the Brewer network to detect volcanic plumes. For instance, the comparison with OMI (Ozone Monitoring Instrument) and GOME-2 (Global Ozone Monitoring Experiment-2) SO2 space-borne retrievals shows statistically significant agreement between the Brewer network data and the collocated satellite overpasses in the case of the Kasatochi eruption. Unfortunately, due to sparsity of satellite data, the significant positive departures seen in the Brewer and other ground networks following the Eyjafjallajökull, Bárðarbunga and Nabro eruptions could not be statistically confirmed by the data from satellite overpasses. A model exercise from the MACC (Monitoring Atmospheric Composition and Climate) project shows that the large increases in SO2 over Europe following the Bárðarbunga eruption in Iceland were not caused by local pollution sources or ship emissions but were clearly linked to the volcanic eruption. Sulfur dioxide positive departures in Europe following Bárðarbunga could be traced by other networks from the free troposphere down to the surface (AirBase (European air quality database) and EARLINET (European Aerosol Research Lidar Network)). We propose that by combining Brewer data with that from other networks and satellites, a useful tool aided by trajectory analyses and modelling could be created which can also be used to forecast high SO2 values both at ground level and in air flight corridors following future eruptions.

The EU FP7 projects MACC (Monitoring Atmospheric Composition and Climate, 2009–2011) prepared for the operational Global Monitoring for Environment and Security (GMES) atmospheric core service on greenhouse gases, reactive gases and aerosols which is envisaged to start in 2014. This paper describes the data assimilation and modelling system which has been implemented for global monitoring of reactive gases in the troposphere and stratosphere. The MACC reactive gases system uses a coupling software to integrate the Model for Ozone And Related Tracers, version 3 (MOZART-3) chemistry transport model with the Integrated Forecast System (IFS) of the European Centre for Medium-range Weather Forecasts (ECMWF). The focus is placed on the tropospheric simulations with this MACC-IFS-MOZ model. The MACC reanalysis (2003–2010) and the forecasts performed in near real time (NRT) benefit from the multi-sensor approach for data assimilation of total columns, tropospheric columns and vertically resolved observations of o...

Three global Chemistry Transport Models – MOZART, MOCAGE, and TM5 – as well as MOZART coupled to the IFS meteorological model including assimilation of ozone (O3) and carbon monoxide (CO) satellite column retrievals, have been compared to surface measurements and MOZAIC vertical profiles in the troposphere over Western/Central Europe for summer 2003. The models reproduce the meteorological features and enhancement of pollution during the period 2–14 August, but not fully the ozone and CO mixing ratios measured during that episode. Modified normalised mean biases are around −25% (except ~5% for MOCAGE) in the case of ozone and from −80% to −30% for CO in the boundary layer above Frankfurt. The coupling and assimilation of CO columns from MOPITT overcomes some of the deficiencies in the treatment of transport, chemistry and emissions in MOZART, reducing the negative biases to around 20%. The high reactivity and small dry deposition velocities in MOCAGE seem to be responsible for the overestimation of O3 in this model. Results from sensitivity simulations indicate that an increase of the horizontal resolution to around 1°×1° and potential uncertainties in European anthropogenic emissions or in long-range transport of pollution cannot completely account for the underestimation of CO and O3 found for most models. A process-oriented TM5 sensitivity simulation where soil wetness was reduced results in a decrease in dry deposition fluxes and a subsequent ozone increase larger than the ozone changes due to the previous sensitivity runs. However this latest simulation still underestimates ozone during the heat wave and overestimates it outside that period. Most probably, a combination of the mentioned factors together with underrepresented biogenic emissions in the models, uncertainties in the modelling of vertical/horizontal transport processes in the proximity of the boundary layer as well as limitations of the chemistry schemes are responsible for the underestimation of ozone (overestimation in the case of MOCAGE) and CO found in the models during this extreme pollution event.

This paper demonstrates that SO2 columnar amounts have significantly increased following the five largest volcanic eruptions of the past decade in the Northern Hemisphere. A strong positive signal was detected by all the existing networks either ground based (Brewer, EARLINET, AirBase) or from satellites (OMI, GOME-2). The study particularly examines the adequacy of the existing Brewer network to detect SO2 plumes of volcanic origin in comparison to other networks and satellite platforms. The comparison with OMI and GOME-2 SO2 space-borne retrievals shows statistically significant agreement between the Brewer network data and the collocated satellite overpasses. It is shown that the Brewer instrument is capable of detecting significant columnar SO2 increases following large volcanic eruptions, when SO2 levels rise well above the instrumental noise of daily observations, estimated to be of the order of 2 DU. A model exercise from the MACC project shows that the large increases of SO2 over Europe following the Bárðarbunga eruption in Iceland were not caused by local sources or ship emissions but are clearly linked to the eruption. We propose that by combining Brewer data with that from other networks and satellites, a useful tool aided by trajectory analyses and modeling could be created which can be used to forecast high SO2 values both at ground level and in air flight corridors following future eruptions.

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.

Carbon monoxide (CO) is a key atmospheric compound that can be remotely sensed by satellite on the global scale. Fifteen years of continuous observations are now available from the MOPITT/Terra mission (2000 to present). Another 15 and more years of observations will be provided by the IASI/MetOp instrument series (2007-2023 >). In order to study long-term variability and trends, a homogeneous record is required, which is not straightforward as the retrieved quantities are instrument and processing dependent. The present study aims at evaluating the consistency between the CO products derived from the MOPITT and IASI missions, both for total columns and vertical profiles, during a 6-year overlap period (2008-2013). The analysis is performed by first comparing the available 2013 versions of the retrieval algorithms (v5T for MOPITT and v20100815 for IASI), and second using a dedicated reprocessing of MOPITT CO profiles and columns using the same a priori information as the IASI product. MOPITT total columns are generally slightly higher over land (bias ranging from 0 to 13 %) than IASI data. When IASI and MOPITT data are retrieved with the same a priori constraints, correlation coefficients are slightly improved. Large discrepancies (total column bias over 15 %) observed in the Northern Hemisphere during the winter months are reduced by a factor of 2 to 2.5. The detailed analysis of retrieved vertical profiles compared with collocated aircraft data from the MOZAIC-IAGOS network, illustrates the advantages and disadvantages of a constant vs. a variable a priori. On one hand, MOPITT agrees better with the aircraft profiles for observations with persisting high levels of CO throughout the year due to pollution or seasonal fire activity (because the climatology-based a priori is supposed to be closer to the real atmospheric state). On the other hand, IASI performs better when unexpected events leading to high levels of CO occur, due to a larger variability associated with the a priori., SCOPUS: ar.j, info:eu-repo/semantics/published

Daily global analyses and 5-day forecasts are generated in the context of the European Monitoring Atmospheric Composition and Climate (MACC) project using an extended version of the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). The IFS now includes modules for chemistry, deposition and emission of reactive gases, aerosols, and greenhouse gases, and the 4-dimensional variational data assimilation scheme makes use of multiple satellite observations of atmospheric composition in addition to meteorological observations. This paper describes the data assimilation setup of the new Composition-IFS (C-IFS) with respect to reactive gases and validates analysis fields of ozone (O3), carbon monoxide (CO), and nitrogen dioxide (NO2) for the year 2008 against independent observations and a control run without data assimilation. The largest improvement in CO by assimilation of Measurements of Pollution in the Troposphere (MOPITT) CO columns is seen in the lower troposphere of the Northern Hemisphere (NH) extratropics during winter, and during the South African biomass-burning season. The assimilation of several O3 total column and stratospheric profile retrievals greatly improves the total column, stratospheric and upper tropospheric O3 analysis fields relative to the control run. The impact on lower tropospheric ozone, which comes from the residual of the total column and stratospheric profile O3 data, is smaller, but nevertheless there is some improvement particularly in the NH during winter and spring. The impact of the assimilation of tropospheric NO2 columns from the Ozone Monitoring Instrument (OMI) is small because of the short lifetime of NO2, suggesting that NO2 observations would be better used to adjust emissions instead of initial conditions. The results further indicate that the quality of the tropospheric analyses and of the stratospheric ozone analysis obtained with the C-IFS system has improved compared to the previous "coupled" model system of MACC.

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.

The Monitoring Atmospheric Composition and Climate (MACC) project represents the European Union's Copernicus Atmosphere Monitoring Service (CAMS) (http://www.copernicus.eu/), which became fully operational during 2015. The global near-real-time MACC model production run for aerosol and reactive gases provides daily analyses and 5-day forecasts of atmospheric composition fields. It is the only assimilation system worldwide that is operational to produce global analyses and forecasts of reactive gases and aerosol fields. We have investigated the ability of the MACC analysis system to simulate tropospheric concentrations of reactive gases covering the period between 2009 and 2012. A validation was performed based on carbon monoxide (CO), nitrogen dioxide (NO2) and ozone (O3) surface observations from the Global Atmosphere Watch (GAW) network, the O3 surface observations from the European Monitoring and Evaluation Programme (EMEP) and, furthermore, NO2 tropospheric columns, as well as CO total columns, derived from satellite sensors. The MACC system proved capable of reproducing reactive gas concentrations with consistent quality; however, with a seasonally dependent bias compared to surface and satellite observations – for northern hemispheric surface O3 mixing ratios, positive biases appear during the warm seasons and negative biases during the cold parts of the year, with monthly modified normalised mean biases (MNMBs) ranging between −30 and 30 % at the surface. Model biases are likely to result from difficulties in the simulation of vertical mixing at night and deficiencies in the model's dry deposition parameterisation. Observed tropospheric columns of NO2 and CO could be reproduced correctly during the warm seasons, but are mostly underestimated by the model during the cold seasons, when anthropogenic emissions are at their highest level, especially over the US, Europe and Asia. Monthly MNMBs of the satellite data evaluation range from values between −110 and 40 % for NO2 and at most −20 % for CO, over the investigated regions. The underestimation is likely to result from a combination of errors concerning the dry deposition parameterisation and certain limitations in the current emission inventories, together with an insufficiently established seasonality in the emissions.

In 2013, the vast majority of the monitored climate variables reported here maintained trends established in recent decades. ENSO was in a neutral state during the entire year, remaining mostly on the cool side of neutral with modest impacts on regional weather patterns around the world. This follows several years dominated by the effects of either La Niña or El Niño events. According to several independent analyses, 2013 was again among the 10 warmest years on record at the global scale, both at the Earths surface and through the troposphere. Some regions in the Southern Hemisphere had record or near-record high temperatures for the year. Australia observed its hottest year on record, while Argentina and New Zealand reported their second and third hottest years, respectively. In Antarctica, Amundsen-Scott South Pole Station reported its highest annual temperature since records began in 1957. At the opposite pole, the Arctic observed its seventh warmest year since records began in the early 20th century. At 20-m depth, record high temperatures were measured at some permafrost stations on the North Slope of Alaska and in the Brooks Range. In the Northern Hemisphere extratropics, anomalous meridional atmospheric circulation occurred throughout much of the year, leading to marked regional extremes of both temperature and precipitation. Cold temperature anomalies during winter across Eurasia were followed by warm spring temperature anomalies, which were linked to a new record low Eurasian snow cover extent in May. Minimum sea ice extent in the Arctic was the sixth lowest since satellite observations began in 1979. Including 2013, all seven lowest extents on record have occurred in the past seven years. Antarctica, on the other hand, had above-average sea ice extent throughout 2013, with 116 days of new daily high extent records, including a new daily maximum sea ice area of 19.57 million km2 reached on 1 October. ENSO-neutral conditions in the eastern central Pacific Ocean and a negative Pacific decadal oscillation pattern in the North Pacific had the largest impacts on the global sea surface temperature in 2013. The North Pacific reached a historic high temperature in 2013 and on balance the globally-averaged sea surface temperature was among the 10 highest on record. Overall, the salt content in nearsurface ocean waters increased while in intermediate waters it decreased. Global mean sea level continued to rise during 2013, on pace with a trend of 3.2 mm yr-1 over the past two decades. A portion of this trend (0.5 mm yr-1) has been attributed to natural variability associated with the Pacific decadal oscillation as well as to ongoing contributions from the melting of glaciers and ice sheets and ocean warming. Global tropical cyclone frequency during 2013 was slightly above average with a total of 94 storms, although the North Atlantic Basin had its quietest hurricane season since 1994. In the Western North Pacific Basin, Super Typhoon Haiyan, the deadliest tropical cyclone of 2013, had 1-minute sustained winds estimated to be 170 kt (87.5 m s-1) on 7 November, the highest wind speed ever assigned to a tropical cyclone. High storm surge was also associated with Haiyan as it made landfall over the central Philippines, an area where sea level is currently at historic highs, increasing by 200 mm since 1970. In the atmosphere, carbon dioxide, methane, and nitrous oxide all continued to increase in 2013. As in previous years, each of these major greenhouse gases once again reached historic high concentrations. In the Arctic, carbon dioxide and methane increased at the same rate as the global increase. These increases are likely due to export from lower latitudes rather than a consequence of increases in Arctic sources, such as thawing permafrost. At Mauna Loa, Hawaii, for the first time since measurements began in 1958, the daily average mixing ratio of carbon dioxide exceeded 400 ppm on 9 May. The state of these variables, along with dozens of others, and the 2013 climate conditions of regions around the world are discussed in further detail in this 24th edition of the State of the Climate series. © 2014, American Meteorological Society. All rights reserved.

In this study we compare the diurnal variation in stratospheric ozone derived from free-running simulations of the Whole Atmosphere Community Climate Model (WACCM) and from reanalysis data of the atmospheric service MACC (Monitoring Atmospheric Composition and Climate) which both use a similar stratospheric chemistry module. We find good agreement between WACCM and the MACC reanalysis for the diurnal ozone variation in the high-latitude summer stratosphere based on photochemistry. In addition, we consult the ozone data product of the ERA-Interim reanalysis. The ERA-Interim reanalysis ozone system with its long-term ozone parametrization can not capture these diurnal variations in the upper stratosphere that are due to photochemistry. The good dynamics representations, however, reflects well dynamically induced ozone variations in the lower stratosphere. For the high-latitude winter stratosphere we describe a novel feature of diurnal variation in ozone where changes of up to 46.6% (3.3 ppmv) occur in monthly mean data. For this effect good agreement between the ERA-Interim reanalysis and the MACC reanalysis suggest quite similar diurnal advection processes of ozone. The free-running WACCM model seriously underestimates the role of diurnal advection processes at the polar vortex at the two tested resolutions. The intercomparison of the MACC reanalysis and the ERA-Interim reanalysis demonstrates how global reanalyses can benefit from a chemical representation held by a chemical transport model. The MACC reanalysis provides an unprecedented description of the dynamics and photochemistry of the diurnal variation of stratospheric ozone which is of high interest for ozone trend analysis and research on atmospheric tides. We confirm the diurnal variation in ozone at 5 hPa by observations of the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) experiment and selected sites of the Network for Detection of Atmospheric Composition Change (NDACC). The latter give valuable insight even to diurnal variation of ozone in the polar winter stratosphere.

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. © Author(s) 2013., SCOPUS: re.j, info:eu-repo/semantics/published

[1] The eruption of the Eyjafjallajokull volcano, Iceland, in April and May 2010 caused unprecedented disruptions of European air traffic showing that timely monitoring of volcanic ash and SO2 dispersion as well as the corresponding plume heights are important for aviation safety. This paper describes the observations of SO2 and BrO columns in the eruption plume and the determination of the SO2 plume height using the GOME-2 satellite instrument. During the eruptive period in May 2010, SO2 total columns of up to ∼20 DU and BrO columns of ∼7.7 × 1013 molec/cm2 were detected. The BrO/SO2 ratio estimated from the GOME-2 observations of the Eyjafjallajokull eruption varies from 1.1 × 10−4 to 2.1 × 10−4. The SO2 plume heights estimated from the GOME-2 observations on 5 May range from 8–13 km and mostly agree within 1–3 km with visual observations, radar data and modeling results. Furthermore, the GOME-2 SO2 observations are compared with in situ measurements of the DLR Falcon aircraft on 17 and 18 May 2010 and with Brewer instruments at Valentia, Ireland and Hohenpeissenberg, Germany. The SO2 columns derived from the Falcon profile measurements range from 0.6–4.7 DU and the comparison with the GOME-2 measurements shows a good agreement, mainly within 1 DU. The Brewer observations at Hohenpeissenberg also agree well with the GOME-2 measurements with a daily average SO2 column of ∼1.3 DU during the overpass of the SO2 cloud on 18 May, whereas the Brewer instrument at Valentia shows up to 50% higher SO2 columns (∼8 DU) on 11 May.

The severe wildfires in western Russia during July–August 2010 coincided with a strong heat wave and led to large emissions of aerosols and trace gases such as carbon monoxide (CO), hydrocarbons and nitrogen oxides into the troposphere. This extreme event is used to evaluate the ability of the global MACC (Monitoring Atmospheric Composition and Climate) atmospheric composition forecasting system to provide analyses of large-scale pollution episodes and to test the respective influence of a priori emission information and data assimilation on the results. Daily 4-day hindcasts were conducted using assimilated aerosol optical depth (AOD), CO, nitrogen dioxide (NO2) and ozone (O3) data from a range of satellite instruments. Daily fire emissions were used from the Global Fire Assimilation System (GFAS) version 1.0, derived from satellite fire radiative power retrievals. The impact of accurate wildfire emissions is dominant on the composition in the boundary layer, whereas the assimilation system influences concentrations throughout the troposphere, reflecting the vertical sensitivity of the satellite instruments. The application of the daily fire emissions reduces the area-average mean bias by 63% (for CO), 60% (O3) and 75% (NO2) during the first 24 h with respect to independent satellite observations, compared to a reference simulation with a multi-annual mean climatology of biomass burning emissions. When initial tracer concentrations are further constrained by data assimilation, biases are reduced by 87, 67 and 90%. The forecast accuracy, quantified by the mean bias up to 96 h lead time, was best for all compounds when using both the GFAS emissions and assimilation. The model simulations suggest an indirect positive impact of O3 and CO assimilation on hindcasts of NO2 via changes in the oxidizing capacity. However, the quality of local hindcasts was strongly dependent on the assumptions made for forecasted fire emissions. This was well visible from a relatively poor forecast accuracy quantified by the root mean square error, as well as the temporal correlation with respect to ground-based CO total column data and AOD. This calls for a more advanced method to forecast fire emissions than the currently adopted persistency approach. The combined analysis of fire radiative power observations, multiple trace gas and aerosol satellite observations, as provided by the MACC system, results in a detailed quantitative description of the impact of major fires on atmospheric composition, and demonstrate the capabilities for the real-time analysis and forecasts of large-scale fire events.

The 2008 Antarctic ozone hole was one of the largest and most long-lived in recent years. Predictions of the ozone hole were made in near-real time (NRT) and hindcast mode with the Integrated Forecast System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). The forecasts were carried out both with and without assimilation of satellite observations from multiple instruments to provide more realistic initial conditions. Three different chemistry schemes were applied for the description of stratospheric ozone chemistry: (i) a linearization of the ozone chemistry, (ii) the stratospheric chemical mechanism of the MOZART-3 chemical transport model (CTM) and (iii) the relaxation to a climatology as implemented in the TM5 CTM. The IFS uses the latter two schemes by means of a two-way coupled system. Without assimilation, the forecasts showed model-specific shortcomings in predicting start time, extent and duration of the ozone hole. The assimilation of satellite observations from the Microwave Limb Sounder (MLS), the Ozone Monitoring Instrument (OMI), the Solar Backscattering Ultraviolet radiometer (SBUV-2) and the SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY) led to a significant improvement of the forecasts when compared with total columns and vertical profiles from ozone sondes. The combined assimilation of observations from multiple instruments helped to overcome limitations of the ultraviolet (UV) sensors at low solar elevation over Antarctica. The assimilation of data from MLS was crucial to obtain a good agreement with the observed ozone profiles both in the polar stratosphere and troposphere. The ozone analyses by the three model configurations were very similar despite the different underlying chemistry schemes. During the chemically instigated development of the ozone hole, differences quickly developed in the initialized forecasts by the different schemes. The predictions of the ozone-hole closure, which is driven mainly by dynamical processes, benefited from the initialization over a much longer forecast length. The characteristics of the individual chemistry schemes became apparent after the third forecast day but the forecasts were still close to the respective analyses. The initialization with ozone analyses was beneficial up to at least 15 days.

Vertical profiles of CO taken from the MOZAIC aircraft database are used to globally evaluate the performance of the GEMS/MACC models, including the ECMWF-Integrated Forecasting System (IFS) model coupled to the CTM MOZART-3 with 4DVAR data assimilation for the year 2004. This study provides a unique opportunity to compare the performance of three offline CTMs (MOZART-3, MOCAGE and TM5) driven by the same meteorology as well as one coupled atmosphere/CTM model run with data assimilation, enabling us to assess the potential gain brought by the combination of online transport and the 4DVAR chemical satellite data assimilation. First we present a global analysis of observed CO seasonal averages and interannual variability for the years 2002–2007. Results show that despite the intense boreal forest fires that occurred during the summer in Alaska and Canada, the year 2004 had comparably lower tropospheric CO concentrations. Next we present a validation of CO estimates produced by the MACC models for 2004, including an assessment of their ability to transport pollutants originating from the Alaskan/Canadian wildfires. In general, all the models tend to underestimate CO. The coupled model and the CTMs perform best in Europe and the US where biases range from 0 to -25% in the free troposphere and from 0 to -50% in the surface and boundary layers (BL). Using the 4DVAR technique to assimilate MOPITT V4 CO significantly reduces biases by up to 50% in most regions. However none of the models, even the IFS-MOZART-3 coupled model with assimilation, are able to reproduce well the CO plumes originating from the Alaskan/Canadian wildfires at downwind locations in the eastern US and Europe. Sensitivity tests reveal that deficiencies in the fire emissions inventory and injection height play a role.

The implementation and application of a newly developed coupled system combining ECMWF's integrated forecast system (IFS) with global chemical transport models (CTMs) is presented. The main objective of the coupled system is to enable the IFS to simulate key chemical species without the necessity to invert the complex source and sink processes such as chemical reactions, emission and deposition. Thus satellite observations of atmospheric composition can be assimilated into the IFS using its 4D-VAR algorithm. In the coupled system, the IFS simulates only the transport of chemical species. The coupled CTM provides to the IFS the concentration tendencies due to emission injection, deposition and chemical conversion. The CTMs maintain their own transport schemes and are fed with meteorological data at hourly resolution from the IFS. The CTM used in the coupled system can be either MOZART-3, TM5 or MOCAGE. The coupling is achieved via the special-purpose OASIS4 software. The scientific integrity of the coupled system is proven by analysing the difference between stand-alone CTM simulations and the tracer fields in the coupled IFS. The IFS concentration fields match the CTM fields for about 48 h with the biggest differences occurring in the planetary boundary layer (PBL). The coupled system is a good test bed for process-oriented comparison of the coupled CTM. As an example, the vertical structure of chemical conversion and emission injection is studied for a ten day period over Central Europe for the three CTMs.

[1] The sulfur dioxide plumes released by the eruptions of the Icelandic volcanoes Eyjafjallajokull in May 2010 and Grimsvotn in May 2011 were studied using satellite observations from the Second Global Ozone Monitoring Experiment (GOME-2), Ozone Monitoring Instrument (OMI), and Scanning Imaging Absorption Spectrometer for Atmospheric Chartography and modeled with the Integrated Forecasting System of the European Centre for Medium-Range Weather Forecasts (ECMWF). The retrievals of SO2 total columns (TCSO2) were (i) used to estimate emission rate and injection height of the two eruptions and (ii) assimilated with ECMWF's four-dimensional variational data assimilation algorithm to obtain initial conditions for subsequent forecasts. The OMI retrievals provided the highest plume observation values, and GOME-2 had the best coverage. The emission parameters were estimated by comparing TCSO2 observations with an ensemble of test tracers injected at different heights. The applied methodology led to emission estimates of 0.25 Tg over 20 days in May 2010 and 0.32 Tg over 2 days in May 2011. The SO2 analyses produced by assimilating GOME-2 TCSO2 retrievals captured the plume maxima well but exaggerated the plume area. The injection height estimate was used during the assimilation to determine the height of the assimilated plume. Plume forecasts were evaluated by means of hit-rate and plume-size statistics for different TCSO2 thresholds. Plume forecasts using either the emission parameters or the SO2 analyses as initial conditions agreed reasonably with the observations, but using both led to the best forecast performance. The initialization with SO2 analysis fields improved, in particular, the forecast of the Grimsvotn plume after the end of the eruption. The developed forecast and assimilation system can be applied for near–real-time forecasting of volcanic SO2 plumes.

This study provides a comprehensive assessment of NO2 changes across the main European urban areas induced by the COVID-19 lockdown using satellite retrievals from the Tropospheric Monitoring Instrument (TROPOMI), surface site measurements and simulations from the Copernicus Atmospheric Monitoring Service (CAMS) regional ensemble of air quality models. Some recent TROPOMI-based estimates of NO2 changes have neglected the influence of weather variability between the reference and lockdown periods. Here we provide weather-normalized estimates based on a machine learning method (gradient boosting) along with an assessment of the biases that can be expected from methods that omit the influence of weather. We also compare the weather-normalized satellite NO2 column changes with both weather-normalized surface NO2 concentration changes and simulated changes by the CAMS regional ensemble, composed of 11 models, using recently published emission reductions induced by the lockdown. We show that all estimates show the same tendency on NO2 reductions. Locations where the lockdown was stricter show stronger reductions and, conversely, locations where softer measures were implemented show milder reductions in NO2 pollution levels. Regarding average reductions, estimates based on either satellite observations (−23 %) surface stations (−43 %) or models (−32 %) are presented, showing the importance of vertical sampling but also the horizontal representativeness. Surface station estimates are significantly changed when sampled to the TROPOMI overpasses (−37 %) pointing out the importance of the variability in time of such estimates. Observation based machine learning estimates show a stronger temporal variability than the model-based estimates.