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-D-FGAT (First Guess at Appropriate Time) method. The validation of O₃ and CO assimilated fields is done using self-consistency 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 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.

In this study we present a pre-operational forecasting assimilation system of different types of aerosols. This system has been developed within the chemistry-transport model of Météo-France, MOCAGE, and uses the assimilation of the Aerosol Optical Depth (AOD) from MODIS (Moderate Resolution Imaging Spectroradiometer) onboard both Terra and Aqua. It is based on the AOD assimilation system within the MOCAGE model. It operates on a daily basis with a global configuration of $1^{\circ }\times 1^{\circ }$ (longitude × latitude). The motivation of such a development is the capability to predict and anticipate extreme events and their impacts on the air quality and the aviation safety in the case of a huge volcanic eruption. The validation of the pre-operational system outputs has been done in terms of AOD compared against the global AERONET observations within two complete years (January 2018–December 2019). The comparison between both datasets shows that the correlation between the MODIS assimilated outputs and AERONET over the whole period of study is 0.77, whereas the biases and the RMSE (Root Mean Square Error) are 0.006 and 0.135, respectively. The ability of the pre-operational system to predict extreme events in near real time such as the desert dust transport and the propagation of the biomass burning was tested and evaluated. We particularly presented and documented the desert dust outbreak which occurred over Greece in late March 2018 as well as the wildfire event which happened on Australia between July 2019 and February 2020. We only presented these two events, but globally the assimilation chain has shown that it is capable of predicting desert dust events and biomass burning aerosols which happen all over the globe.

This paper presents the first results about the assimilation of CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) extinction coefficient measurements onboard the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) satellite in the MOCAGE (MOdèle de Chimie Atmosphérique à Grande Echelle) chemistry transport model of Météo-France. This assimilation module is an extension of the aerosol optical depth (AOD) assimilation system already presented by Sič et al. (2016). We focus on the period of the TRAQA (TRAnsport à longue distance et Qualité de l’Air dans le bassin méditerranéen) field campaign that took place during summer 2012. This period offers the opportunity to have access to a large set of aerosol observations from instrumented aircraft, balloons, satellite and ground-based stations. We evaluate the added value of CALIOP assimilation with respect to the model free run by comparing both fields to independent observations issued from the TRAQA field campaign. In this study we focus on the desert dust outbreak which happened during late June 2012 over the Mediterranean Basin (MB) during the TRAQA campaign. The comparison with the AERONET (Aerosol Robotic Network) AOD measurements shows that the assimilation of CALIOP lidar observations improves the statistics compared to the model free run. The correlation between AERONET and the model (assimilation) is 0.682 (0.753); the bias and the root mean square error (RMSE), due to CALIOP assimilation, are reduced from −0.063 to 0.048 and from 0.183 to 0.148, respectively. Compared to MODIS (Moderate-resolution Imaging Spectroradiometer) AOD observations, the model free run shows an underestimation of the AOD values, whereas the CALIOP assimilation corrects this underestimation and shows a quantitative good improvement in terms of AOD maps over the MB. The correlation between MODIS and the model (assimilation) during the dust outbreak is 0.47 (0.52), whereas the bias is −0.18 (−0.02) and the RMSE is 0.36 (0.30). The comparison of in situ aircraft and balloon measurements to both modelled and assimilated outputs shows that the CALIOP lidar assimilation highly improves the model aerosol field. The evaluation with the LOAC (Light Optical Particle Counter) measurements indicates that the aerosol vertical profiles are well simulated by the direct model but with a general underestimation of the aerosol number concentration, especially in the altitude range 2–5 km. The CALIOP assimilation improves these results by a factor of 2.5 to 5. Analysis of the vertical distribution of the desert aerosol concentration shows that the aerosol dust transport event is well captured by the model but with an underestimated intensity. The assimilation of CALIOP observations allows the improvement of the geographical representation of the event within the model as well as its intensity by a factor of 2 in the altitude range 1–5 km.

In the context of the Atmosphere Observing System (AOS) international program, a new-generation spaceborne lidar is expected to be in polar orbit for deriving new observations of aerosol and clouds. In this work, we analyze the added values of these new observations for characterizing aerosol vertical distribution. For this, synthetic observations are simulated using the BLISS lidar simulator in terms of the backscatter coefficient at 532 nm. We consider two types of lidar instruments, an elastic backscatter lidar instrument and a high spectral resolution lidar (HSRL). These simulations are performed with atmospheric profiles from a nature run (NR) modeled by the MOCAGE chemical transport model. In three case studies involving large events of different aerosol species, the added value of the HSRL channel (for measuring aerosol backscatter profiles with respect to simple backscatter measurements) is shown. Observations independent of an a priori lidar ratio assumption, as done typically for simple backscattering instruments, allow probing the vertical structures of aerosol layers without divergence, even in cases of intense episodes. A 5-day study in the case of desert dust completes the study of the added value of the HSRL channel with relative mean bias from the NR of the order of 1.5%. For low abundances, relative errors in the backscatter coefficient profiles may lay between +40% and −40%, with mean biases between +5% and −5%.

This paper presents the first results about the assimilation of CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) extinction coefficient measurements on-board the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) satellite in the chemistry transport model MOCAGE (Modèle de Chimie Atmosphérique à Grande Echelle) of Météo-France. This assimilation module is an extension of the Aerosol Optical Depth (AOD) assimilation system already presented by Sic et al. (2016). We focus on the period of TRAQA (TRAnsport à longue distance et Qualité de l’Air dans le bassin méditerranéen) field campaign that took place during the summer 2012. This period offers the opportunity to have access to a large set of aerosol observations from instrumented aircraft, balloons, satellite and ground-based stations. We evaluate the added value of CALIOP assimilation with respect to the model free run by comparing both fields to independent observations issued from the TRAQA field campaign. In this study we focus on the desert dust outbreak which happened during late June 2012 over the Mediterranean Basin (MB) during TRAQA campaign. The comparison with the AERONET (Aerosol Robotic Network) AOD measurements shows that the assimilation of CALIOP lidar observations improves the statistics compared to the model free run. The correlation between AERONET and the model (assimilation) is 0.682 (0.753), the bias and the RMSE, due to CALIOP assimilation, are reduced from −0.063 to 0.048 and from 0.183 to 0.148, respectively. Compared to MODIS (Moderate-resolution Imaging Spectroradiometer) AOD observations, the model free run shows an underestimation of the AOD values whereas the CALIOP assimilation corrects this underestimation and shows a quantitative good improvement in terms of AOD maps over the MB. The correlation between MODIS and the model (assimilation) during the dust outbreak is 0.47 (0.52), whereas the bias is −0.18 (−0.02) and the RMSE is 0.36 (0.30). The comparison of in-situ aircraft and balloon measurements to both modelled and assimilated outputs shows that the CALIOP lidar assimilation highly improves themodel aerosol field. The evaluation with the LOAC (Light Optical Particle Counter) measurements indicates that the aerosol vertical profiles are well simulated by the direct model but with a general underestimation of the aerosol number concentration especially in the altitude range 2–5 km. The CALIOP assimilation improves these results by a factor of 2.5 to 5. Analysis of the vertical distribution of the desert aerosol concentration shows that the aerosol dust transport event is well captured by the model but with an underestimated intensity. The assimilation of CALIOP observations allows the improvement of the geographical representation of the event within the model as well as its intensity by a factor of two in the altitude range 1–5 km.

In the context of the Atmospheric Observing System (AOS) international program, a new generation spaceborne lidar is expected to be in polar orbit for deriving new observations of aerosol and clouds. In this work, we analyze the added values of these new observations for characterizing aerosol vertical distribution. For this, synthetic observations are simulated using the BLISS lidar simulator in terms of backscatter coefficient at 532 nm. We consider two types of lidar instruments, an elastic backscatter lidar instrument and a high spectral resolution lidar (HSRL). These simulations are performed with atmospheric profiles from a Nature Run (NR) modeled by the MOCAGE Chemical Transport Model. In three case studies involving large events of different aerosol species, the added value of the HSRL channel for measuring aerosol backscatter profiles with respect to simple backscatter measurements is shown. Observations independent from an a-priori lidar Ratio assumption, as done typically for simple backscattering instruments, allows probing the vertical structure of aerosol layers without divergence, even in case of intense episodes. Relative error in the backscatter coefficient profiles are observed to lay between +40% and -40% for low abudancies, with mean biases between +5% and -5%. A 5-day study in the case of desert dust completes the study of the added value of the HSRL channel with relative mean bias from the NR of the order of 1.5%.