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This paper presents observing system simulation experiments (OSSEs) to compare the relative capabilities of two geostationary thermal infrared (TIR) instruments to measure ozone (O3) and carbon monoxide (CO) for monitoring air quality (AQ) over Europe. The primary motivation of this study is to use OSSEs to assess how these infrared instruments can constrain different errors affecting AQ hindcasts and forecasts (emissions, meteorology, initial condition and the 3 parameters together). The first instrument (GEO-TIR) has a configuration optimized to monitor O3 and CO in the lowermost troposphere (LmT; defined to be the atmosphere between the surface and 3 km), and the second instrument (GEO-TIR2) is designed to monitor temperature and humidity. Both instruments measure radiances in the same spectral TIR band. Results show that GEO-TIR could have a significant impact (GEO-TIR is closer to the reference atmosphere than GEO-TIR2) on the analyses of O3 and CO LmT column. The information added by the measurements for both instruments is mainly over the Mediterranean Basin and some impact can be found over the Atlantic Ocean and Northern Europe. The impact of GEO-TIR is mainly above 1 km for O3 and CO but can also improve the surface analyses for CO. The analyses of GEO-TIR2 show low impact for O3 LmT column but a significant impact (although still lower than for GEO-TIR) for CO above 1 km. The results of this study indicate the beneficial impact from an infrared instrument (GEO-TIR) with a capability for monitoring O3 and CO concentrations in the LmT, and quantify the value of this information for constraining AQ models.

The behavior of the extratropical transition layer (ExTL) is investigated using a chemistry transport model (CTM) and analyses derived from assimilation of MLS (Microwave Limb Sounder) O3 and MOPITT (Measurements Of Pollution In The Troposphere) CO data. We firstly focus on a stratosphere–troposphere exchange (STE) case study that occurred on 15 August 2007 over the British Isles (50° N, 10° W). We evaluate the effect of data assimilation on the O3–CO correlations. It is shown that data assimilation disrupts the relationship in the transition region. When MLS O3 is assimilated, CO and O3 values are not consistent between each other, leading to unphysical correlations at the STE location. When MLS O3 and MOPITT CO assimilated fields are taken into account in the diagnostics the relationship happens to be more physical. We then use O3–CO correlations to quantify the effect of data assimilation on the height and depth of the ExTL. When the free-model run O3 and CO fields are used in the diagnostics, the ExTL distribution is found 1.1 km above the thermal tropopause and is 2.6 km wide (2σ). MOPITT CO analyses only slightly sharpen (by −0.02 km) and lower (by −0.2 km) the ExTL distribution. MLS O3 analyses provide an expansion (by +0.9 km) of the ExTL distribution, suggesting a more intense O3 mixing. However, the MLS O3 analyses ExTL distribution shows a maximum close to the thermal tropopause and a mean location closer to the thermal tropopause (+0.45 km). When MLS O3 and MOPITT CO analyses are used together, the ExTL shows a mean location that is the closest to the thermal tropopause (+0.16 km). We also extend the study at the global scale on 15 August 2007 and for the month of August 2007. MOPITT CO analyses still show a narrower chemical transition between stratosphere and troposphere than the free-model run. MLS O3 analyses move the ExTL toward the troposphere and broaden it. When MLS O3 analyses and MOPITT CO analyses are used together, the ExTL matches the thermal tropopause poleward of 50°.

The PCW (Polar Communications and Weather) mission is a dual satellite mission with each satellite in a highly eccentric orbit with apogee ~ 42,000 km and a period (to be decided) in the 12-24 hour range to deliver continuous communications and meteorological data over the Arctic and environs. At and near apogee the viewing is quasi-geostationary due to the slow satellite motion. The operational meteorological instrument is a 21-channel spectral imager with UV, visible, NIR and MIR channels similar to MODIS and ABI. The PHEMOS WCA (Weather, Climate and Air quality) mission is an atmospheric science complement to the operational PCW mission. The PHEMOS WCA instrument package consists of FTS and UVS imaging sounders with viewing range of ~4.5 degrees or a Field of Regard (FoR) ~ 3400x3400 km2 from near apogee. The spatial resolution at apogee of each imaging sounder is targeted to be 10Ã--10 km2 or better and the image repeat time is targeted at ~ 2 hours or better. The FTS has 4 bands that span the MIR and NIR. The MIR bands cover 700-1500 cm-1 and 1800-2700 cm-1 with a spectral resolution of 0.25 cm-1 i,e, a similar spectral resolution to IASI. They should provide vertical tropospheric profiles of temperature and water vapour in addition to partial columns of other gases of interest for air quality such as O3, CO, HCN, CH3OH, etc and also CO2 and CH4. The two NIR bands cover 5990-6010 cm-1 (0.25 cm-1) and 13060-13168 cm-1 (0.5 cm-1) and target columns of CO2 and CH4 and the O2-A band for surface pressure, aerosol OD and albedo. The UVS is an imaging spectrometer that covers the spectral range of 280 â€" 650 nm with 0.9 nm resolution and targets the tropospheric column densities of O3 and NO2. It is also planned to obtain the tropospheric columns of BrO, SO2, HCHO and (HCO)2 and the aerosol index (AI) as well as stratospheric columns of O3, NO2 and BrO. The quasi-stationary viewing will provide the ability to measure the diurnal behavior of atmospheric properties under the satellites and the ability to provide data for weather forecasting and also chemical data assimilation. Important goals for PHEMOS-WCA include measurement of meteorological and air quality data and the measurement of changes in CO2 and CH4 throughout the day-lit hours in the NIR near apogee (see FTS poster). In addition, the imaging design is to be sufficiently flexible so that it can be directed at special events possibly with the FoR reduced to have more rapid spatial coverage. In this paper we will outline the scientific objectives, status of retrieval algorithms and also the viewing geometry necessary with 2 satellites. PHEMOS WCA Phase A study was completed in March 2012. It was funded by the Canadian Space Agency (CSA).

Numerical models that combine weather forecasting and atmospheric chemistry are here referred to as chemical weather forecasting models. Eighteen operational chemical weather forecasting models on regional and continental scales in Europe are described and compared in this article. Topics discussed in this article include how weather forecasting and atmospheric chemistry models are integrated into chemical weather forecasting systems, how physical processes are incorporated into the models through parameterization schemes, how the model architecture affects the predicted variables, and how air chemistry and aerosol processes are formulated. In addition, we discuss sensitivity analysis and evaluation of the models, user operational requirements, such as model availability and documentation, and output availability and dissemination. In this manner, this article allows for the evaluation of the relative strengths and weaknesses of the various modelling systems and modelling approaches. Finally, this article highlights the most prominent gaps of knowledge for chemical weather forecasting models and suggests potential priorities for future research directions, for the following selected focus areas: emission inventories, the integration of numerical weather prediction and atmospheric chemical transport models, boundary conditions and nesting of models, data assimilation of the various chemical species, improved understanding and parameterization of physical processes, better evaluation of models against data and the construction of model ensembles. © 2012 Author(s).

This paper describes the capabilities of a nadir thermal infrared (TIR) sensor proposed for deployment onboard a geostationary platform to monitor ozone (O3) and carbon monoxide (CO) for air quality (AQ) purposes. To assess the capabilities of this sensor we perform idealized retrieval studies considering typical atmospheric profiles of O3 and CO over Europe with different instrument configuration (signal to noise ratio, SNR, and spectral sampling interval, SSI) using the KOPRA forward model and the KOPRA-fit retrieval scheme. We then select a configuration, referred to as GEO-TIR, optimized for providing information in the lowermost troposphere (LmT; 0–3 km in height). For the GEO-TIR configuration we obtain ~1.5 degrees of freedom for O3 and ~2 for CO at altitudes between 0 and 15 km. The error budget of GEO-TIR, calculated using the principal contributions to the error (namely, temperature, measurement error, smoothing error) shows that information in the LmT can be achieved by GEO-TIR. We also retrieve analogous profiles from another geostationary infrared instrument with SNR and SSI similar to the Meteosat Third Generation Infrared Sounder (MTG-IRS) which is dedicated to numerical weather prediction, referred to as GEO-TIR2. We quantify the added value of GEO-TIR over GEO-TIR2 for a realistic atmosphere, simulated using the chemistry transport model MOCAGE (MOd`ele de Chimie Atmospherique `a Grande Echelle). Results show that GEO-TIR is able to capture well the spatial and temporal variability in the LmT for both O3 and CO. These results also provide evidence of the significant added value in the LmT of GEO-TIR compared to GEO-TIR2 by showing GEO-TIR is closer to MOCAGE than GEO-TIR2 for various statistical parameters (correlation, bias, standard deviation).

International audience; The goal of this study is to assess the simulations of the distribution of the reactive gases using satellite observations. It will further help to assess the emission inventories used in simulations. This work is the part of the European 7th framework project MACC (Monitoring Atmopsheric Composition and Climate). Within MACC, several anthropogenic emission inventories have been updated, however, we will focus only on CO, NO2, HCHO and SO2 emission distributions. We will evaluate the distribution of these reactive and precursor gases as calculated by three chemistry transport models involved in MACC project i.e. MOZART, TM5 and MOCAGE. These simulation outputs are evaluated by comparing with ground based and satellite observations. We will present a case study focusing mainly on SO2 emissions from non-ferrous metal smelting industry located in Peru ( Ilo and La Oroya smelters) and in Siberia (Norilsk smelter). We will discuss the methodology we have used to improve the emissions from these smelters by using satellite observations of SO2 from SCIAMACHY instrument onboard ENVISAT-1. We will show that a significant improvement has been obtained in the MOZART simulation outputs when the updated SO2 emission fields are used by the model.

Vertical profiles of CO taken from the MOZAIC aircraft database are used to present (1) a global analysis of CO seasonal averages and interannual variability for the years 2002–2007 and (2) a global 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. Seasonal averages and interannual variability from several MOZAIC sites representing different regions of the world show that CO concentrations are highest and most variable during the winter season. The inter-regional variability is significant with concentrations increasing eastward from Europe to Japan. The impact of the intense boreal fires, particularly in Russia, during the fall of 2002 on the Northern Hemisphere CO concentrations throughout the troposphere is well represented by the MOZAIC data. A global validation of the GEMS/MACC GRG models which include three stand-alone CTMs (MOZART, MOCAGE and TM5) and the coupled ECMWF Integrated Forecasting System (IFS)/MOZART model with and without MOPITT CO data assimilation show that the models have a tendency to underestimate CO. The models 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). The biases are largest in the winter and during the daytime when emissions are highest, indicating that current inventories are too low. Data assimilation is shown to reduce biases by up to 25% in some regions. The models are not able to reproduce well the CO plumes originating from the Alaskan/Canadian wildfires at downwind locations in the eastern US and Europe, not even with assimilation. Sensitivity tests reveal that this is mainly due to deficiencies in the fire emissions inventory and injection height.

Three global Chemistry Transport Models ĝ€" MOZART, MOCAGE, and TM5 ĝ€" 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 2ĝ€"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.

International audience; This paper presents a comprehensive characterization of a very deep stratospheric intrusion which occurred over the British Isles on 15 August 2007. The signature of this event is diagnosed using ozonesonde measurements over Lerwick, UK (60.14 N, 1.19 W) and is also well characterized using meteorological analyses from the global operational weather prediction model of Météo-France, ARPEGE. Modelled as well as assimilated fields of both ozone (O3) and carbon monoxide (CO) have been used in order to better document this event. O3 and CO from Aura/MLS and Terra/MOPITT instruments, respectively, are assimilated into the three-dimensional chemical transport model MOCAGE of Météo-France using a variational 3-DFGAT (First Guess at Appropriate Time) method. The validation of O3 and CO assimilated fields is done using selfconsistency diagnostics and by comparison with independent observations such as MOZAIC (O3 and CO), AIRS (CO) and OMI (O3). It particularly shows in the upper troposphere and lower stratosphere region that the assimilated fields are closer to MOZAIC than the free model run. The O3 bias between MOZAIC and the analyses is −11.5 ppbv with a RMS of 22.4 ppbv and a correlation coefficient of 0.93, whereas between MOZAIC and the free model run, the corresponding values are 33 ppbv, 38.5 ppbv and 0.83, respectively. In the same way, for CO, the bias, RMS and correlation coefficient between MOZAIC and the analyses are −3.16 ppbv, 13 ppbv and 0.79, respectively, whereas between MOZAIC and the free model run, the corresponding values are 33 ppbv, 38.5 ppbv and 0.83, respectively. In the same way, for CO, the bias, RMS and correlation coefficient between MOZAIC and the analyses are −3.16 ppbv, 13 ppbv and 0.79, respectively, whereas between MOZAIC and the free model they are 6.3 ppbv, 16.6 ppbv and 0.71, respectively. The paper also presents a demonstration of the capability of O3 and CO assimilated fields to better describe a stratosphere-troposphere exchange (STE) event in comparison with the free run modelled O3 and CO fields. Although the assimilation of MLS data improves the distribution of O3 above the tropopause compared to the free model run, it is not sufficient to reproduce the STE event well. Assimilated MOPITT CO allows a better qualitative description of the stratospheric intrusion event. The MOPITT CO analyses appear more promising than the MLS O3 analyses in terms of their ability to capture a deep STE event. Therefore, the results of this study open the perspectives for using MOPITT CO in the STE studies.

We present a comparison of tropospheric NO2 from OMI measurements to the median of an ensemble of Regional Air Quality (RAQ) models, and an intercomparison of the contributing RAQ models and two global models for the period July 2008-June 2009 over Europe. The model forecasts were produced routinely on a daily basis in the context of the European GEMS ("Global and regional Earth-system (atmosphere) Monitoring using Satellite and in-situ data") project. The tropospheric vertical column of the RAQ ensemble median shows a spatial distribution which agrees well with the OMI NO2 observations, with a correlation low r=0.8. This is higher than the correlations from any one of the individual RAQ models, which supports the use of a model ensemble approach for regional air pollution forecasting. The global models show high correlations compared to OMI, but with significantly less spatial detail, due to their coarser resolution. Deviations in the tropospheric NO2 columns of individual RAQ models from the mean were in the range of 20-34% in winter and 40-62% in summer, suggesting that the RAQ ensemble prediction is relatively more uncertain in the summer months. The ensemble median shows a stronger seasonal cycle of NO2 columns than OMI, and the ensemble is on average 50% below the OMI observations in summer, whereas in winter the bias is small. On the other hand the ensemble median shows a somewhat weaker seasonal cycle than NO2 surface observations from the Dutch Air Quality Network, and on average a negative bias of 14%. Full profile information was available for two RAQ models and for the global models. For these models the retrieval averaging kernel was applied. Minor differences are found for area-averaged model columns with and without applying the kernel, which shows that the impact of replacing the a priori profiles by the RAQ model profiles is on average small. However, the contrast between major hotspots and rural areas is stronger for the direct modeled vertical columns than the columns where the averaging kernels are applied, related to a larger relative contribution of the free troposphere and the coarse horizontal resolution in the a priori profiles compared to the RAQ models. In line with validation results reported in the literature, summertime concentrations in the lowermost boundary layer in the a priori profiles from the DOMINO product are significantly larger than the RAQ model concentrations and surface observations over the Netherlands. This affects the profile shape, and contributes to a high bias in OMI tropospheric columns over polluted regions. The global models indicate that the upper troposphere may contribute significantly to the total column and it is important to account for this in comparisons with RAQ models. A combination of upper troposphere model biases, the a priori profile effects and DOMINO product retrieval issues could explain the discrepancy observed between the OMI observations and the ensemble median in summer.

We present a comparison of tropospheric NO2 from OMI measurements to the median of an ensemble of Regional Air Quality (RAQ) models, and an intercomparison of the contributing RAQ models and two global models for the period July 2008–June 2009 over Europe. The model forecasts were produced routinely on a daily basis in the context of the European GEMS ("Global and regional Earth-system (atmosphere) Monitoring using Satellite and in-situ data") project. The tropospheric vertical column of the RAQ ensemble median shows a spatial distribution which agrees well with the OMI NO2 observations, with a correlation r=0.8. This is higher than the correlations from any one of the individual RAQ models, which supports the use of a model ensemble approach for regional air pollution forecasting. The global models show high correlations compared to OMI, but with significantly less spatial detail, due to their coarser resolution. Deviations in the tropospheric NO2 columns of individual RAQ models from the mean were in the range of 20–34% in winter and 40–62% in summer, suggesting that the RAQ ensemble prediction is relatively more uncertain in the summer months. The ensemble median shows a stronger seasonal cycle of NO2 columns than OMI, and the ensemble is on average 50% below the OMI observations in summer, whereas in winter the bias is small. On the other hand the ensemble median shows a somewhat weaker seasonal cycle than NO2 surface observations from the Dutch Air Quality Network, and on average a negative bias of 14%. Full profile information was available for two RAQ models and for the global models. For these models the retrieval averaging kernel was applied. Minor differences are found for area-averaged model columns with and without applying the kernel, which shows that the impact of replacing the a priori profiles by the RAQ model profiles is on average small. However, the contrast between major hotspots and rural areas is stronger for the direct modeled vertical columns than the columns where the averaging kernels are applied, related to a larger relative contribution of the free troposphere and the coarse horizontal resolution in the a priori profiles compared to the RAQ models. In line with validation results reported in the literature, summertime concentrations in the lowermost boundary layer in the a priori profiles from the DOMINO product are significantly larger than the RAQ model concentrations and surface observations over the Netherlands. This affects the profile shape, and contributes to a high bias in OMI tropospheric columns over polluted regions. The global models indicate that the upper troposphere may contribute significantly to the total column and it is important to account for this in comparisons with RAQ models. A combination of upper troposphere model biases, the a priori profile effects and DOMINO product retrieval issues could explain the discrepancy observed between the OMI observations and the ensemble median in summer.

International audience; Within the African Monsoon Multidisciplinary Analysis (AMMA), we investigate the impact of nitrogen oxides produced by lightning (LiNOx) and convective transport during the West African Monsoon (WAM) upon the composition of the upper troposphere (UT) in the tropics. For this purpose, we have performed simulations with 4 state-of-the-art chemistry transport models involved within AMMA, namely MOCAGE, TM4, LMDz-INCA and p-TOMCAT. The model intercomparison is complemented with an evaluation of the simulations based on both spaceborne and airborne observations. The baseline simulations show important differences between the UT CO and O3 distributions simulated by each of the 4 models when compared to measurements from the MOZAIC program and fom the Aura/MLS spaceborne sensor. We show that such model discrepancies can be explained by differences in the convective transport parameterizations and, more particularly, the altitude reached by convective updrafts (ranging between ~200-125 hPa). Concerning UT O3, the models exhibit a good agreement with the main observed features. Nevertheless the majority of models simulate low O3 concentrations compared to both MOZAIC and Aura/MLS observations south of the equator, and rather high concentrations in the Northern Hemisphere. Sensitivity studies are performed to quantify the effect of deep convective transport and the influence of LiNOx production on the UT composition. These clearly indicate that the CO maxima and the elevated O3 concentrations south of the equator are due to convective uplift of air masses impacted by Southern African biomass burning, in agreement with previous studies. Moreover, during the WAM, LiNOx from Africa are responsible for the highest UT O3 enhancements (10-20 ppbv) over the tropical Atlantic between 10° S-20° N. Differences between models are primarily due to the performance of the parameterizations used to simulate lightning activity which are evaluated using spaceborne observations of flash frequency. Combined with comparisons of in-situ NO measurements we show that the models producing the highest amounts of LiNOx over Africa during the WAM (INCA and p-TOMCAT) capture observed NO profiles with the best accuracy, although they both overestimate lightning activity over the Sahel.