The CAMS reanalysis of atmospheric composition

Inness, Antje; Ades, Melanie; Agustı́-Panareda, Anna; Barré, Jérôme; Benedictow, Anna; Blechschmidt, Anne-Marlene; Dominguez, Juan J.; Engelen, Richard; Eskes, Henk; Flemming, Johannes; Huijnen, Vincent; Jones, Luke; Kipling, Zak; Massart, Sébastien; Parrington, Mark; Peuch, Vincent-Henri; Razinger, Miha; Rémy, Samuel; Schulz, Mıchael; Suttie, Martin

doi:10.5194/acp-2018-1078

Cited by 55 publications

(77 citation statements)

References 40 publications

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“…Stratospheric ozone chemistry in IFS (CB05) is parameterized by a linear ozone scheme (Cariolle & Déqué, 1986; Cariolle & Teyssèdre, 2007). This combination allows a realistic representation of tropospheric and stratospheric ozone concentrations (Huijnen et al, 2020; Inness et al, 2019). The chemistry module of the IFS together with its emissions is documented in more detail in Flemming et al (2015) and Flemming et al (2017) and the updates used in the CAMS reanalysis in Inness et al (2019).…”

Section: Data Setsmentioning

confidence: 99%

Exceptionally Low Arctic Stratospheric Ozone in Spring 2020 as Seen in the CAMS Reanalysis

et al. 2020

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A reanalysis data set produced by the Copernicus Atmosphere Monitoring service (CAMS reanalysis, 2003 to present day) augmented by ERA5 data for the years before 2003 is used to describe the evolution of the 2020 Arctic ozone season and to compare it with years back to 1979. Ozone columns over large parts of the Arctic reached record low values in March and April 2020 because of an exceptionally strong, cold, and persistent Arctic polar vortex. Minimum ozone columns were below 250 DU for most of March and the first half of April, with the lowest values of 211 DU in the CAMS reanalysis found on 18 March. Such low values are extremely unusual for the Arctic. The previous years with similarly strong Arctic ozone depletion were 2011 and 1997 with minimum values of 232 and 217 DU, respectively. The performance of the CAMS ozone analysis is assessed by comparison with ozonesonde data and found to agree well with the independent observations. We find a clear sign of chemical ozone destruction with ozone severely depleted in a layer between 80 and 50 hPa in late March and early April when partial pressure values below 2 mPa were observed. Profiles from the limb sounders Atmospheric Chemistry Experiment‐Fourier Transform Spectrometer (ACE‐FTS) and Microwave Limb Sounder (MLS) show clear signs of chlorine activation and the presence of polar stratospheric clouds. Monthly mean ozone columns in March 2020 were up to 180 DU or 40% lower than the CAMS climatology (2003–2019) while values for 2011 and 1997 were lower by 31% and 35%, respectively.

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Section: Data Setsmentioning

confidence: 99%

Exceptionally Low Arctic Stratospheric Ozone in Spring 2020 as Seen in the CAMS Reanalysis

et al. 2020

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“…The accuracy of the total AOT in the CAMSiRA reanalysis is discussed in Flemming et al (2017) and Inness et al (2018) in 10 terms of global and regional bias and correlation against surface observations. Since the AOT computed from the climatology of mass mixing ratio discussed in this work is based on the same reanalysis, it has the same mean bias when evaluated over a 9 https://doi.org/10.5194/gmd-2019-149 Preprint.…”

Section: Verification Of the Climatological Aerosol Distribution Agaimentioning

confidence: 99%

“…We identify as likely contributors to this bias (i) possible incorrect vertical distribution of all aerosols (including absorbing types) in the forecast model driven in part by the operator splitting of convective transport and scavenging, (ii) a tendency for the assimilation to assign far too much positive increment to black carbon in the tropics, (iii) errors in the emission for organic and black carbon aerosols and (iv) too large absorption in the optical properties associated to the biomass burning species. These problems are currently being addressed and improvements have been incorporated in the most recent CAMS reanalysis (Inness et al, 2018). (Geer, 2016).…”

Section: Impact On Forecast Errors and Skillmentioning

confidence: 99%

An aerosol climatology for global models based on the tropospheric aerosol scheme in the Integrated Forecasting System of ECMWF

Bozzo¹,

Benedetti²,

Flemming³

et al. 2019

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Abstract. An aerosol climatology to represent aerosols in the radiation schemes of Global Atmospheric Models was recently developed. We derived the climatology from a reanalysis of atmospheric composition produced by the Copernicus Atmosphere Monitoring Service (CAMS). As an example of application into a global atmospheric model, we discuss the technical aspects of the implementation in the Integrated Forecasting System of European Centre for Medium Range Weather Forecasts (ECMWF-IFS) and the impact of the new climatology on the medium-range weather forecasts and one-year simulations. The new aerosol climatology was derived by combining a set of model simulation with constrained meteorological conditions and an atmospheric composition reanalysis for the period 2003–2014 produced by the IFS. The aerosol fields of the re-analysis are constrained by assimilating Aerosol optical thickness (AOT) retrievals product by the MODIS instruments. In a further step, we used modelled aerosol fields to correct the aerosol speciation and the vertical profiles of the aerosol reanalysis fields. The new climatology provides the monthly-mean mass mixing ratio of five aerosol species constrained by assimilated MODIS AOT. Using the new climatology in the ECMWF-IFS leads to changes in direct aerosol radiative effect compared to the climatology previously implemented, which have a small, but non-negligible impact on the forecast skill of large-scale weather patterns in the medium-range. However, details of the regional distribution of aerosol radiative forcing can have a large local impact. This is the case for the area of the Arabian Peninsula and the northern Indian Ocean. Here changes in the radiative forcing of the mineral dust significantly improve the Summer Monsoon circulation.

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“…The octahedral grid is used for all simulations, except for the lowest resolution simulation at 80 km which uses a reduced linear Gaussian grid as in the ERA-Interim and CAMS re-analysis (Inness et al, 2018). The time steps are also dependent on the horizontal resolution and range from 7.5 minutes to 45 minutes.…”

Section: Global Atmospheric Co 2 Simulationsmentioning

confidence: 99%

Modelling CO2 weather – why horizontal resolution matters

Agustı́-Panareda¹,

Diamantakis²,

Massart³

et al. 2019

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Abstract. Climate change mitigation efforts require information on the current greenhouse gas atmospheric concentrations and their sources and sinks. Carbon dioxide (CO2) is the most abundant anthropogenic greenhouse gas. Its variability in the atmosphere is modulated by the synergy between weather and CO2 surface fluxes, often referred to as CO2 weather. It is interpreted with the help of global or regional numerical transport models, with horizontal resolutions ranging from a few hundreds of km to a few km. Changes in the model horizontal resolution affect not only atmospheric transport, but also the representation of topography and surface CO2 fluxes. This paper assesses the impact of horizontal resolution on the simulated atmospheric CO2 variability with a numerical weather prediction model. The simulations are performed using the Copernicus Atmosphere Monitoring Service (CAMS) CO2 forecasting system at different resolutions from 9&#8201;km to 80&#8201;km and are evaluated using in situ atmospheric surface measurements and atmospheric column-mean observations of CO2, as well as radiosonde and SYNOP observations of the winds. The results indicate that both diurnal and day-to-day variability of atmospheric CO2 are generally better represented at high resolution, as shown by a reduction in the errors in simulated wind and CO2. Mountain stations display the largest improvements at high resolution as they directly benefit from the more realistic orography. In addition, the CO2 spatial gradients are generally improved with increasing resolution for both stations near the surface and those observing the total column, as the overall inter-station error is also reduced in magnitude. However, close to emission hotspots, the high resolution can also lead to a deterioration of the simulation skill, highlighting uncertainties in the high resolution fluxes that are more diffuse at lower resolutions. We conclude that increasing horizontal resolution matters for modelling CO2 weather because it has the potential to bring together improvements in the surface representation of both winds and CO2 fluxes, as well as an expected reduction in numerical errors of transport. Modelling applications like atmospheric inversion systems to estimate surface fluxes will only be able to benefit fully from upgrades in horizontal resolution if the topography, winds and prior flux distribution are also upgraded accordingly. It is clear from the results that an additional increase in resolution might reduce errors even further. However, the horizontal resolution sensitivity tests indicate that the change in the CO2 and wind modelling error with resolution is not linear, making it difficult to extrapolate the results beyond the tested resolutions. Finally, we show that the high resolution simulations are useful for the assessment of the small-scale variability of CO2 which cannot be represented in coarser resolution models. These representativeness errors need to be considered when assimilating in situ data and high resolution satellite data such as Greenhouse gases Observing Satellite (GOSAT), Orbiting Carbon Observatory-2 (OCO-2), the Chinese Carbon Dioxide Observation Satellite Mission (TanSat) and future missions such as the Geostationary Carbon Observatory (GeoCarb) and the Sentinel satellite constellation for CO2. For these reasons, the high resolution CO2 simulations provided by the CAMS in real-time can be useful to estimate such small-scale variability in real time, as well as providing boundary conditions for regional modelling studies and supporting field experiments.

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The CAMS reanalysis of atmospheric composition

Cited by 55 publications

References 40 publications

Exceptionally Low Arctic Stratospheric Ozone in Spring 2020 as Seen in the CAMS Reanalysis

Exceptionally Low Arctic Stratospheric Ozone in Spring 2020 as Seen in the CAMS Reanalysis

An aerosol climatology for global models based on the tropospheric aerosol scheme in the Integrated Forecasting System of ECMWF

Modelling CO<sub>2</sub> weather – why horizontal resolution matters

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The CAMS reanalysis of atmospheric composition

Cited by 55 publications

References 40 publications

Exceptionally Low Arctic Stratospheric Ozone in Spring 2020 as Seen in the CAMS Reanalysis

Exceptionally Low Arctic Stratospheric Ozone in Spring 2020 as Seen in the CAMS Reanalysis

An aerosol climatology for global models based on the tropospheric aerosol scheme in the Integrated Forecasting System of ECMWF

Modelling CO&lt;sub&gt;2&lt;/sub&gt; weather – why horizontal resolution matters

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Modelling CO<sub>2</sub> weather – why horizontal resolution matters