Échanges en surface dans le modèle de chimie transport multi-échelles MOCAGE

Les échanges en surface dans le Modèle de Chimie Transport (MCT) multi-échelles MOCAGE de Météo-France comprennent à la fois les flux d'émissions et de dépôt sec d'espèces gazeuses. Une interface 2D a été développée entre MOCAGE et le modèle de prévisions météorologiques opérationnel français ARPEGE dans le but de calculer des flux à la surface réalistesPour les émissions, un inventaire global est employé pour le moment; cet inventaire a été construit essentiellement à partir des inventaires des programmes IGAC/GEIA (International Global Atmospheric Chemistry / Global Emission Inventory Activity) et EDGAR (Emission Database for Global Atmospheric Research qui ont des résolutions temporelles annuelles, sai-sonnières ou mensuelles et une résolution spatiale de un degré.Le dépôt sec d'espèces gazeuses, y compris l'ozone, le dioxyde de soufre, les composés azotés, les composés organiques à longue et à courte durée de vie, a été paramétrisé selon [Wesely, 1989]. Le modèle calcule la vitesse de dépôt à partir de valeurs de trois résistances en série, les résistances aérodynamique, laminaire et de la surface. Ces résistances sont calculées en utilisant les champs de surface d'ARPEGE. Les champs liés à la végétation, tels l'indice foliaire, sont prescrits avec une résolution de un degré sur le globe et de cinq minutes sur l'Europe. Un certain nombre de modifications a été apporté à la paramétrisation de [Wesely, 1989], par exemple pour la formulation de la résistance stomatale et celle de la résistance de surface sur les surfaces mouillées. Les valeurs calculées de vitesse de dépôt ont été comparées à des observations et leurs distributions spatiales et temporelles ont été analysées sur deux saisons opposées (hiver et été, sur les différents domaines de MOCAGE, de résolution allant de 2 degrés pour le globe à 0.25 degrés pour la France.Surface exchanges considered in the MOCAGE multiscale Chemistry and Transport Model (CTM) of Météo-France include both emissions and dry deposition of gaseous species. To compute realistic time-dependent fluxes at the surface, a 2D interface between MOCAGE and ARPEGE, the French operational numerical weather prediction model, was developed.With regard to emissions, a default global inventory is presently employed. Built mainly from the IGAC/GEIA (International Global Atmospheric Chemistry / Global Emission Inventory Activity) and the EDGAR (Emission Database for Global Atmospheric Research programs, this inventory has an annual, seasonal or monthly temporal resolution, and a degree-by-degree spatial resolution.Dry deposition of gaseous species, including ozone, sulfur dioxide, nitrogen-containing com-pounds, long-lived and short-lived intermediates organic compounds, were parameterised ac-cording to [Wesely, 1989]. The model calculates dry deposition velocities from three resistances in series: aerodynamic, laminar, and surface. These resistances are computed using the surface fields obtained from the analyses or forecasts of ARPEGE. Vegetation fields such as the Leaf Area Index are prescribed with a one-degree spatial resolution at the global scale, and a five-minute resolution over Europe. A number of modifications was incorporated into the original surface resistance scheme (e.g., the formulation of stomatal resistance and surface resistance over wet surfaces. Calculated dry deposition velocities were compared to observations, and the spatial and temporal distributions were analysed for two different seasons (summer and winter) using the varions MOCAGE domains of varying resolutions (from 2 degrees over the globe to 0.25 degrees over France)

How realistic are air quality hindcasts driven by forcings from climate model simulations?

Predicting how European air quality could evolve over the next decades in the context of changing climate requires the use of climate models to produce results that can be averaged in a climatologically and statistically sound manner. This is a very different approach from the one that is generally used for air quality hindcasts for the present period; analysed meteorological fields are used to represent specifically each date and hour. Differences arise both from the fact that a climate model run results in a pure model output, with no influence from observations (which are useful to correct for a range of errors), and that in a "climate" set-up, simulations on a given day, month or even season cannot be related to any specific period of time (but can just be interpreted in a climatological sense). Hence, although an air quality model can be thoroughly validated in a "realistic" set-up using analysed meteorological fields, the question remains of how far its outputs can be interpreted in a "climate" set-up. For this purpose, we focus on Europe and on the current decade using three 5-yr simulations performed with the multiscale chemistry-transport model MOCAGE and use meteorological forcings either from operational meteorological analyses or from climate simulations. We investigate how statistical skill indicators compare in the different simulations, discriminating also the effects of meteorology on atmospheric fields (winds, temperature, humidity, pressure, etc.) and on the dependent emissions and deposition processes (volatile organic compound emissions, deposition velocities, etc.). Our results show in particular how differing boundary layer heights and deposition velocities affect horizontal and vertical distributions of species. When the model is driven by operational analyses, the simulation accurately reproduces the observed values of O<sub>3</sub>, NO<sub>x</sub>, SO<sub>2</sub> and, with some bias that can be explained by the set-up, PM<sub>10</sub>. We study how the simulations driven by climate forcings differ, both due to the realism of the forcings (lack of data assimilated and lower resolution) and due to the lack of representation of the actual chronology of events. We conclude that the indicators such as mean bias, mean normalized bias, RMSE and deviation standards can be used to interpret the results with some confidence as well as the health-related indicators such as the number of days of exceedance of regulatory thresholds. These metrics are thus considered to be suitable for the interpretation of simulations of the future evolution of European air quality

A linear CO chemistry parameterization in a chemistry-transport model: evaluation and application to data assimilation

This paper presents an evaluation of a new linear parameterization valid for the troposphere and the stratosphere, based on a first order approximation of the carbon monoxide (CO) continuity equation. This linear scheme (hereinafter noted LINCO) has been implemented in the 3-D Chemical Transport Model (CTM) MOCAGE (MOdèle de Chimie Atmospherique Grande Echelle). First, a one and a half years of LINCO simulation has been compared to output obtained from a detailed chemical scheme output. The mean differences between both schemes are about ±25 ppbv (part per billion by volume) or 15% in the troposphere and ±10 ppbv or 100% in the stratosphere. Second, LINCO has been compared to diverse observations from satellite instruments covering the troposphere (Measurements Of Pollution In The Troposphere: MOPITT) and the stratosphere (Microwave Limb Sounder: MLS) and also from aircraft (Measurements of ozone and water vapour by Airbus in-service aircraft: MOZAIC programme) mostly flying in the upper troposphere and lower stratosphere (UTLS). In the troposphere, the LINCO seasonal variations as well as the vertical and horizontal distributions are quite close to MOPITT CO observations. However, a bias of ~−40 ppbv is observed at 700 Pa between LINCO and MOPITT. In the stratosphere, MLS and LINCO present similar large-scale patterns, except over the poles where the CO concentration is underestimated by the model. In the UTLS, LINCO presents small biases less than 2% compared to independent MOZAIC profiles. Third, we assimilated MOPITT CO using a variational 3D-FGAT (First Guess at Appropriate Time) method in conjunction with MOCAGE for a long run of one and a half years. The data assimilation greatly improves the vertical CO distribution in the troposphere from 700 to 350 hPa compared to independent MOZAIC profiles. At 146 hPa, the assimilated CO distribution is also improved compared to MLS observations by reducing the bias up to a factor of 2 in the tropics. This study confirms that the linear scheme is able to simulate reasonably well the CO distribution in the troposphere and in the lower stratosphere. Therefore, the low computing cost of the linear scheme opens new perspectives to make free runs and CO data assimilation runs at high resolution and over periods of several years

Equilibrium of sinks and sources of sulphate over Europe: comparison between a six-year simulation and EMEP observations

Sulphate distributions were simulated with a global chemistry transport model. A chemical scheme describing the sulphur cycle and the parameterisations of the main sinks for sulphate aerosols were included in the model. A six-year simulation was conducted from the years 2000 to 2005, driven by the ECMWF operational analyses. Emissions come from an inventory representative of the year 2000. This paper focuses on the analysis of the sulphate sinks and sources over Europe for the entire period of simulation. The Sulphate burden shows a marked annual cycle, which is the result of the annual variations of the aqueous and gaseous chemistry. Regionally, the monthly mean aerosol burden can vary by a factor of 2 from one year to another, because of different weather conditions, driving chemistry, transport and wet deposition of sulphate aerosols. Sulphate ground concentrations, scavenging fluxes and precipitation modelled were compared with observations. The model represents quite well sulphate fields over Europe, but has a general tendency to overestimate sulphate ground concentrations, in particular over Northern Europe. We assume that it is linked to the representation of the scavenging fluxes, which are underestimated. We suggest that uncertainties in modelled precipitation explain only partially the underestimation of the scavenging fluxes in the model

A new version of the CNRM Chemistry-Climate Model, CNRM-CCM: description and improvements from the CCMVal-2 simulations

This paper presents a new version of the Météo-France CNRM Chemistry-Climate Model, so-called CNRM-CCM. It includes some fundamental changes from the previous version (CNRM-ACM) which was extensively evaluated in the context of the CCMVal-2 validation activity. The most notable changes concern the radiative code of the GCM, and the inclusion of the detailed stratospheric chemistry of our Chemistry-Transport model MOCAGE on-line within the GCM. A 47-yr transient simulation (1960–2006) is the basis of our analysis. CNRM-CCM generates satisfactory dynamical and chemical fields in the stratosphere. Several shortcomings of CNRM-ACM simulations for CCMVal-2 that resulted from an erroneous representation of the impact of volcanic aerosols as well as from transport deficiencies have been eliminated. <br><br> Remaining problems concern the upper stratosphere (5 to 1 hPa) where temperatures are too high, and where there are biases in the NO<sub>2</sub>, N<sub>2</sub>O<sub>5</sub> and O<sub>3</sub> mixing ratios. In contrast, temperatures at the tropical tropopause are too cold. These issues are addressed through the implementation of a more accurate radiation scheme at short wavelengths. Despite these problems we show that this new CNRM CCM is a useful tool to study chemistry-climate applications

Global model simulations of air pollution during the 2003 European heat wave

Three global Chemistry Transport Models - MOZART, MOCAGE, and TM5 - as well as MOZART coupled to the IFS meteorological model including assimilation of ozone (O-3) 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 similar to 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 O-3 in this model. Results from sensitivity simulations indicate that an increase of the horizontal resolution to around 1 degrees x1 degrees and potential uncertainties in European anthropogenic emissions or in long-range transport of pollution cannot completely account for the underestimation of CO and O-3 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

The value of satellite observations in the analysis and short-range prediction of Asian dust

Asian dust is a seasonal meteorological phenomenon which affects east Asia, and has severe consequences on the air quality of China, North and South Korea and Japan. Despite the continental extent, the prediction of severe episodes and the anticipation of their consequences is challenging. Three 1-year experiments were run to assess the skill of the model of the European Centre for Medium-Range Weather Forecasts (ECMWF) in monitoring Asian dust and understand its relative contribution to the aerosol load over China. Data used were the Moderate Resolution Imaging Spectroradiometer (MODIS) Dark Target and the Deep Blue aerosol optical depth (AOD). In particular the experiments aimed at understanding the added value of data assimilation runs over a model run without any aerosol data. The year 2013 was chosen as representative of the availability of independent AOD data from two established ground-based networks (AERONET, Aerosol Robotic Network, and CARSNET, China Aerosol Remote Sensing Network), which could be used to evaluate experiments. Particulate matter (PM) data from the China Environmental Protection Agency were also used in the evaluation. Results show that the assimilation of satellite AOD data is beneficial to predict the extent and magnitude of desert dust events and to improve the short-range forecast of such events. The availability of observations from the MODIS Deep Blue algorithm over bright surfaces is an asset, allowing for a better localization of the sources and definition of the dust events. In general both experiments constrained by data assimilation perform better than the unconstrained experiment, generally showing smaller normalized mean bias and fractional gross error with respect to the independent verification datasets. The impact of the assimilated satellite observations is larger at analysis time, but lasts into the forecast up to 48&thinsp;h. The performance of the global model in terms of particulate matter does not show the same degree of skill as the performance in terms of optical depth. Despite this, the global model is able to capture some regional pollution patterns. This indicates that the global model analyses may be used as boundary conditions for regional air quality models at higher resolution, enhancing their performance in situations in which part of the pollution may have originated from large-scale mechanisms. While assimilation is not a substitute for model development and characterization of the emission sources, results indicate that it can play a role in delivering improved monitoring of Asian dust optical depth.</p

A new chemistry-climate tropospheric and stratospheric model MOCAGE-Climat: evaluation of the present-day climatology and sensitivity to surface processes

International audienceWe present the chemistry-climate configuration of the Météo-France Chemistry and Transport Model, MOCAGE-Climat. MOCAGE-Climat is a state-of-the-art model that simulates the global distribution of ozone and its precursors (82 chemical species) both in the troposphere and the stratosphere, up to the mid-mesosphere (~70 km). Surface processes (emissions, dry deposition), convection, and scavenging are explicitly described in the model that has been driven by the ECMWF operational analyses of the period 2000–2005, on T21 and T42 horizontal grids and 60 hybrid vertical levels, with and without a procedure that reduces calculations in the boundary layer, and with on-line or climatological deposition velocities. Model outputs have been compared to available observations, both from satellites (TOMS, HALOE, SMR, SCIAMACHY, MOPITT) and in-situ instrument measurements (ozone sondes, MOZAIC and aircraft campaigns) at climatological timescales. The distribution of long-lived species is in fair agreement with observations in the stratosphere putting apart shortcomings linked to the large-scale circulation. The variability of the ozone column, both spatially and temporarily, is satisfactory. However, the too fast Brewer-Dobson circulation accumulates too much ozone in the lower to mid-stratosphere at the end of winter. Ozone in the UTLS region does not show any systematic bias. In the troposphere better agreement with ozone sonde measurements is obtained at mid and high latitudes than in the tropics and differences with observations are the lowest in summer. Simulations using a simplified boundary layer lead to ozone differences between the model and the observations up to the mid-troposphere. NOx in the lowest troposphere is in general overestimated, especially in the winter months over the northern hemisphere, which might result from a positive bias in OH. Dry deposition fluxes of O3 and nitrogen species are within the range of values reported by recent inter-comparison model exercises. The use of climatological deposition velocities versus deposition velocities calculated on-line had greatest impact on HNO3 and NO2 in the troposphere

Global model simulations of air pollution during the 2003 European heat wave

Three global Chemistry Transport Models – MOZART, MOCAGE, and TM5 – as well as MOZART coupled to the IFS meteorological model including assimilation of ozone (O&lt;sub&gt;3&lt;/sub&gt;) 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 &amp;minus;25% (except ~5% for MOCAGE) in the case of ozone and from &amp;minus;80% to &amp;minus;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 O&lt;sub&gt;3&lt;/sub&gt; in this model. Results from sensitivity simulations indicate that an increase of the horizontal resolution to around 1&amp;deg;&amp;times;1&amp;deg; and potential uncertainties in European anthropogenic emissions or in long-range transport of pollution cannot completely account for the underestimation of CO and O&lt;sub&gt;3&lt;/sub&gt; 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