Search

CHIMERE is a chemistry-transport model designed for regional atmospheric composition. It can be used at a variety of scales from local to continental domains. However, due to the model design and its historical use as a regional model, major limitations had remained, hampering its use at hemispheric scale, due to the coordinate system used for transport as well as to missing processes that are important in regions outside Europe. Most of these limitations have been removed in the CHIMERE-2017 version, allowing its use in any region of the world and at any scale, from the scale of a single urban area up to hemispheric scale, with or without polar regions included. Other important improvements have been made in the treatment of the physical processes affecting aerosols and the emissions of mineral dust. From a computational point of view, the parallelization strategy of the model has also been updated in order to improve model numerical performance and reduce the code complexity. The present article describes all these changes. Statistical scores for a model simulation over continental Europe are presented, and a simulation of the circumpolar transport of volcanic ash plume from the Puyehue volcanic eruption in June 2011 in Chile provides a test case for the new model version at hemispheric scale.

The presence of airborne aerosols affects the meteorology as it induces a perturbation in the radiation budget, the number of cloud condensation nuclei and the cloud micro-physics. Those effects are difficult to model at regional scale as regional chemistry-transport models are usually driven by a distinct meteorological model or data. In this paper, the coupling of the CHIMERE chemistry-transport model with the WRF meteorological model using the OASIS3-MCT coupler is presented. WRF meteorological fields along with CHIMERE aerosol optical properties are exchanged through the coupler at a high frequency in order to model the aerosol–radiation interactions. The WRF-CHIMERE online model has a higher computational burden than both models run separately in offline mode (up to 42 % higher). This is mainly due to some additional computations made within the models such as more frequent calls to meteorology treatment routines or calls to optical properties computation routines. On the other hand, the overall time required to perform the OASIS3-MCT exchanges is not significant compared to the total duration of the simulations. The impact of the coupling is evaluated on a case study over Europe, northern Africa, the Middle East and western Asia during the summer of 2012, through comparisons of the offline and two online simulations (with and without the aerosol optical properties feedback) to observations of temperature, aerosol optical depth (AOD) and surface PM10 (particulate matter with diameters lower than 10 µm) concentrations. The result shows that using the optical properties feedback induces a radiative forcing (average forcing of −4.8 W m−2) which creates a perturbation in the average surface temperatures over desert areas (up to 2.6° locally) along with an increase in both AOD and PM10 concentrations.

The ADRIMED (Aerosol Direct Radiative Impact on the regional climate in the MEDiterranean region) project was dedicated to study the atmospheric composition during the summer 2013 in the European Mediterranean region. During its campaign experiment part, the WRF (Weather Research and Forecast Model) and CHIMERE models were used in the forecast mode in order to decide whether intensive observation periods should be triggered. Each day, a simulation of 4 days was performed, corresponding to (D-1) to (D+2) forecast leads. The goal of this study was to determine whether the model forecast spread is lower or greater than the model biases compared to observations. It is shown that the differences between observations and the model are always higher than those between the forecasts. Among all forcing types used in the chemistry-transport model, it is shown that the strong bias and other related low forecast scores are mainly due to the forecast accuracy of the wind speed, which is used both for the mineral dust emissions (a threshold process) and for the long-range transport of aerosol: the surface wind speed forecast spread can reach 50%, leading to mineral dust emission forecast spread of up to 30%. These variations are responsible for a moderate forecast spread of the surface PM10 (a few percentage points) and for a large spread (more than 50%) in the mineral dust concentration at higher altitudes, leading to a mean AOD (aerosol optical depth) forecast spread of ±10%.

This paper presents the first ensemble modelling experiment in relation to birch pollen in Europe. The seven-model European ensemble of MACC-ENS, tested in trial simulations over the flowering season of 2010, was run through the flowering season of 2013. The simulations have been compared with observations in 11 countries, all members of the European Aeroallergen Network, for both individual models and the ensemble mean and median. It is shown that the models successfully reproduced the timing of the very late season of 2013, generally within a couple of days from the observed start of the season. The end of the season was generally predicted later than observed, by 5 days or more, which is a known feature of the source term used in the study. Absolute pollen concentrations during the season were somewhat underestimated in the southern part of the birch habitat. In the northern part of Europe, a record-low pollen season was strongly overestimated by all models. The median of the multi-model ensemble demonstrated robust performance, successfully eliminating the impact of outliers, which was particularly useful since for most models this was the first experience of pollen forecasting.

Depending on the magnitude of their eruptions, volcanoes impact the atmosphere at various temporal and spatial scales. The volcanic source remains a major unknown to rigorously assess these impacts. At the scale of an eruption, the limited knowledge of source parameters, including time variations of erupted mass flux and emission profile, currently represents the greatest issue that limits the reliability of volcanic cloud forecasts. Today, a growing number of satellite and remote sensing observations of distant plumes are becoming available, bringing indirect information on these source terms. Here, we develop an inverse modelling approach combining satellite observations of the volcanic plume with an Eulerian regional chemistry-transport model (CHIMERE) to characterise the volcanic SO2 emissions during an eruptive crisis. The May 2010 eruption of Eyjafjallajökull is a perfect case study to apply this method as the volcano emitted substantial amounts of SO2 during more than a month. We take advantage of the SO2 column amounts provided by a vast set of IASI (Infrared Atmospheric Sounding Interferometer) satellite images to reconstruct retrospectively the time series of the mid-tropospheric SO2 flux emitted by the volcano with a temporal resolution of ~2 h, spanning the period from 1 to 12 May 2010. We show that no a priori knowledge on the SO2 flux is required for this reconstruction. The initialisation of chemistry-transport modelling with this reconstructed source allows for reliable simulation of the evolution of the long-lived tropospheric SO2 cloud over thousands of kilometres. Heterogeneities within the plume, which mainly result from the temporal variability of the emissions, are correctly tracked over a timescale of a week. The robustness of our approach is also demonstrated by the broad similarities between the SO2 flux history determined by this study and the ash discharge behaviour estimated by other means during the phases of high explosive activity at Eyjafjallajökull in May 2010. Finally, we show how a sequential IASI data assimilation allows for a substantial improvement in the forecasts of the location and concentration of the plume compared to an approach assuming constant flux at the source. As the SO2 flux is an important indicator of the volcanic activity, this approach is also of interest to monitor poorly instrumented volcanoes from space.

Tropospheric trace gas and aerosol pollutants have adverse effects on health, environment and climate. In order to quantify and mitigate such effects, a wide range of processes leading to the formation and transport of pollutants must be considered, understood and represented in numerical models. Regional scale pollution episodes result from the combination of several factors: high emissions (from anthropogenic or natural sources), stagnant meteorological conditions, kinetics and efficiency of the chemistry and the deposition. All these processes are highly variable in time and space, and their relative contribution to the pollutants budgets can be quantified with chemistry-transport models. The CHIMERE chemistry-transport model is dedicated to regional atmospheric pollution event studies. Since it has now reached a certain level a maturity, the new stable version, CHIMERE 2013, is described to provide a reference model paper. The successive developments of the model are reviewed on the basis of published investigations that are referenced in order to discuss the scientific choices and to provide an overview of the main results.

Five one-year air quality simulations over a domain covering Europe have been performed using the CHIMERE chemistry transport model and the EMEP emission dataset for Europe. These five simulations differ only by the representation of the effective emission heights for anthropogenic emissions: one has been run using the EMEP standard recommendations, three others with vertical injection profiles derived from the EMEP recommendations but multiplying the injection height by 0.75, 0.50 and 0.25, respectively, while the last one uses vertical profiles derived from the recent literature. It is shown that using injection heights lower than the EMEP recommendations leads to significantly improved simulation of background SO2, NO2 and O3 concentrations when compared to the Airbase station measurements.