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

Estimation of ash injection in the atmosphere by basaltic volcanic plumes: the case of the Eyjafjallajökull 2010 eruption

During explosive eruptions, volcanic plumes inject ash into the atmosphere and may severely affect air traffic, as illustrated by the 2010 Eyjafjallajökull eruption. Quantitative estimates of ash injection can be deduced from the height reached by the volcanic plume on the basis of scaling laws inferred from models of powerful Plinian plumes. In less explosive basaltic eruptions, there is a partitioning of the magma influx between the atmospheric plume and an effusive lava flow on the ground. We link the height reached by the volcanic plume with the rate of ash injection in the atmosphere via a refined plume model that (1) includes a recently developed variable entrainment law and (2) accounts for mass partitioning between ground flow and plume. We compute the time evolution of the rate of injection of ash into the atmosphere for the Eyjafjallajökull eruption on the basis of satellite thermal images and plume heights and use the dispersion model of the Volcanic Ash Advisory Center of Toulouse to translate these numbers into hazard maps. The classical Plinian model would have overestimated ash injection by about 20% relative to the refined estimate, which does not jeopardize risk assessment. This small error was linked to effective fragmentation by intense interactions of magma with water derived from melting of ice and hence strong mass partitioning into the plume. For a less well fragmented basaltic dry eruption, the error may reach 1 order of magnitude and hence undermine the prediction of ash dispersion, which demonstrates the need to monitor both plume heights and ground flows during an explosive eruption

Evaluation of long-range transport and deposition of desert dust with the CTM MOCAGE

International audienceDesert dust modelling and forecasting attract growing interest, due to the numerous impacts of dusts on climate, numerical weather prediction, health, ecosystems, transportation, as well as on many industrial activities. The validation of numerical tools is a very important activity in this context, and we present here an example of such an effort, combining in situ (horizontal visibility in SYNOP messages, IMPROVE database) and remote-sensing data (satellite imagery, AERONET aerosol optical thickness data). Interestingly, these measurements are available routinely, and not only in the context of dedicated measurements campaign; thus, they can be used in an operational context to monitor the performances of operational forecasting systems. MOCAGE is the chemistry-transport model of Météo-France, used operationally to forecast the three-dimensional transport of dusts and their deposition. Two very long-range transport episodes of dust have been studied: one case of Saharan dust transported to East America through Asia and Pacific observed in November 2004 and one case of Saharan dust transported from West Africa to Caribbean Islands in May 2007. Episodes of geographical extension had seldom been studied, and they provide a very selective reference to compare the modelled desert dusts with. The representation of dusts in MOCAGE appears to be realistic in these two very different cases. In turn, the model simulations are used to make the link between the complementary information provided by the different measurements tools, providing a fully consistent picture of the entire episodes. The evolution of the aerosol size distribution during the episodes has also been studied. With no surprise, our study underlines that deposition processes are very sensitive to the size of dust particles. If the atmospheric cycle, in terms of mass, is very much under the influence of larger particles (some micrometres and above), only the finer particles actually travel over thousands of kilometres. This illustrates the need for an accurate representation of size distributions for this aerosol component in numerical models and advocates for using a size-resolved (bin) approach as sinks, and particularly, deposition do not affect the emitted log-normal distributions symmetrically on both sides of the median diameter. Overall, the results presented in this study provide an evaluation of Météo-France operational dust forecasting system MOCAGE

Evaluation of long-range transport and deposition of desert dust with the CTM MOCAGE

Desert dust modelling and forecasting attract growing interest, due to the numerous impacts of dusts on climate, numerical weather prediction, health, ecosystems, transportation, as well as on many industrial activities. The validation of numerical tools is a very important activity in this context, and we present here an example of such an effort, combining in situ (horizontal visibility in SYNOP messages, IMPROVE database) and remote-sensing data (satellite imagery, AERONET aerosol optical thickness data). Interestingly, these measurements are available routinely, and not only in the context of dedicated measurements campaign; thus, they can be used in an operational context to monitor the performances of operational forecasting systems. MOCAGE is the chemistry-transport model of Météo-France, used operationally to forecast the three-dimensional transport of dusts and their deposition. Two very long-range transport episodes of dust have been studied: one case of Saharan dust transported to East America through Asia and Pacific observed in November 2004 and one case of Saharan dust transported from West Africa to Caribbean Islands in May 2007. Episodes of geographical extension had seldom been studied, and they provide a very selective reference to compare the modelled desert dusts with. The representation of dusts in MOCAGE appears to be realistic in these two very different cases. In turn, the model simulations are used to make the link between the complementary information provided by the different measurements tools, providing a fully consistent picture of the entire episodes. The evolution of the aerosol size distribution during the episodes has also been studied. With no surprise, our study underlines that deposition processes are very sensitive to the size of dust particles. If the atmospheric cycle, in terms of mass, is very much under the influence of larger particles (some micrometres and above), only the finer particles actually travel over thousands of kilometres. This illustrates the need for an accurate representation of size distributions for this aerosol component in numerical models and advocates for using a size-resolved (bin) approach as sinks, and particularly, deposition do not affect the emitted log-normal distributions symmetrically on both sides of the median diameter. Overall, the results presented in this study provide an evaluation of Météo-France operational dust forecasting system MOCAGE

Preparing the assimilation of the future MTG‐IRS sounder into the mesoscale NWP AROME model

International audienceThe IRS (InfraRed Sounder) instrument is an infrared Fourier transform spectrometer that will be on board the Meteosat Third Generation series of the future EUMETSAT geostationary satellites. It will measure the radiance emitted by the Earth at the top of the atmosphere using 1960 channels. IRS will provide high spatial and temporal frequency 4D information on atmospheric temperature and humidity, winds, clouds, surfaces, as well as on the chemical composition of the atmosphere. The assimilation of these new observations represents a great challenge and opportunity for the improvement of Numerical Weather Prediction (NWP) forecast skill, especially for mesoscale models such as AROME at Météo‐France (Brousseau et al. 2016). The objectives of this study are to prepare for the assimilation of IRS in this system and to evaluate its impact on the forecasts when added to the currently assimilated observations. By using an Observing System Simulation Experiment (OSSE) constructed for a mesoscale NWP model. This OSSE framework makes use of synthetic observations of both IRS and the currently assimilated observing systems in AROME, constructed from a known and realistic state of the atmosphere. The latter, called the Nature Run, is derived from a long and uninterrupted forecast of the mesoscale model. These observations were assimilated and evaluated using a 1 h update cycle 3D‐Var data assimilation system over two‐month periods, one in the summer and one in the winter. This study demonstrates the benefits that can be expected from the assimilation of IRS observations into AROME NWP system. The assimilation of only 75 channels over oceans increases the total amount of observations used in the AROME 3D‐Var by about 50 %. The IRS impact in terms of forecast scores was evaluated and compared for the summer and winter periods. The main findings are that (i) over both periods the assimilation of these observations lead to statistically improved forecasts over the whole atmospheric column, (ii) for the summer season experiment, the forecast ranges up to +48h are improved, (iii) for the winter season experiment, the impact on the forecasts is globally positive but is smaller compared to the summer period and extends only to 24 h. Based on these results, it is foreseen that the addition of future IRS observations in the AROME NWP systems will significantly improve mesoscale weather forecasts