The simulation of the coupled evolution of atmospheric dynamics, pollutant transport, chemical reactions and atmospheric composition is one of the most challenging tasks in environmental modelling, climate change studies, and weather forecasting for the next decades as they all involve strongly integrated processes. Weather strongly influences air quality (AQ) and atmospheric transport of hazardous materials, while atmospheric composition can influence both weather and climate by directly modifying the atmospheric radiation budget or indirectly affecting cloud formation. Until recently, however, due to the scientific complexities and lack of computational power, atmospheric chemistry and weather forecasting have developed as separate disciplines, leading to the development of separate modelling systems that are only loosely coupled.

The continuous increase in computer power has now reached a stage that enables us to perform online coupling of regional meteorological models with atmospheric chemical transport models. The focus on integrated systems is timely, since recent research has shown that meteorology and chemistry feedbacks are important in the context of many research areas and applications, including numerical weather prediction (NWP), AQ forecasting as well as climate and Earth system modelling. However, the relative importance of online integration and its priorities, requirements and levels of detail necessary for representing different processes and feedbacks can greatly vary for these related communities: (i) NWP, (ii) AQ forecasting and assessments, (iii) climate and earth system modelling. Additional applications are likely to benefit from online modelling, e.g.: simulation of volcanic ash or forest fire plumes, pollen warnings, dust storms, oil/gas fires, geo-engineering tests involving changes in the radiation balance.

The COST Action ES1004 – European framework for online integrated air quality and meteorology modelling (EuMetChem) – aims at paving the way towards a new generation of online integrated atmospheric chemical transport and meteorology modelling with two-way interactions between different atmospheric processes including dynamics, chemistry, clouds, radiation, boundary layer and emissions. As its first task, we summarise the current status of European modelling practices and experience with online coupled modelling of meteorology with atmospheric chemistry including feedback mechanisms and attempt reviewing the various issues connected to the different modules of such online coupled models but also providing recommendations for coping with them for the benefit of the modelling community at large

Abstract. Over the past several years, there has been a rapid development in the number and quality of global aerosol models intended for operational forecasting use. Indeed, most centers with global numerical weather prediction (NWP) capabilities have some program for aerosol prediction. These aerosol models typically have differences in their underlying meteorology as well as aerosol sources, sinks, microphysics and transformations. However, like similar diversity in aerosol climate models, the aerosol forecast models have fairly similar overall bulk error statistics for aerosol optical thickness (AOT)-one of the few aerosol metrics that is globally available. Experience in climate and weather prediction has shown that in situations such as this where there are several independent models, a multi-model ensemble or consensus will be top performing in many key error metrics. Further, multi-model ensembles provide a highly valuable tool for forecasters attempting to predict severe aerosol events. Here we present the first steps in developing a global multi-model aerosol forecasting ensemble intended for eventual operational and basic research use. Drawing from members of the International Cooperative for Aerosol Prediction (ICAP) latest generation of quasi-operational aerosol models, five day AOT forecasts are analyzed for December 2011 through November 2012 from four institutions: ECMWF, JMA, NASA GSFC, and NRL/FNMOC. For dust, we also include the NOAA NGAC product in our analysis. The Barcelona Supercomputing Centre (NMMC) and UK Met office dust product have also recent become available with ICAP, but have insufficient data to be included in this analysis period. A simple consensus ensemble of member and mean AOT fields for modal species (e.g., fine and coarse mode, and a separate dust ensemble) is used to create the ICAP Multi-Model Ensemble (ICAP-MME). The ICAP-MME is run daily at 0Z for 6 hourly forecasts out to 120 h. Basing metrics on comparisons to 21 regionally representative Aerosol Robotic Network (AERONET) sites, all models generally captured the basic aerosol features of the globe. However, there is an overall AOT low bias among models, particularly for high AOT events. Biomass burning regions have the most diversity in seasonal average AOT. The southern oceans, though low in AOT, nevertheless also have high diversity. In regard to root mean square error, as expected the ICAP-MME placed first over all models worldwide, and was typically first or second in ranking against all models at individual sites. These results are encouraging; as more global operational aerosol models come on line, we expect their inclusion in a robust operational multi-model ensemble will provide valuable aerosol forecasting guidance.

Abstract. Systematic measurements of dust concentration profiles at continental scale were recently made possible by the development of synergistic retrieval algorithms using combined lidar and sun photometer data and the establishment of robust remote-sensing networks in the framework of Aerosols, Clouds, and Trace gases Research InfraStructure Network (ACTRIS)/European Aerosol Research Lidar Network (EARLINET). We present a methodology for using these capabilities as a tool for examining the performance of dust transport models. The methodology includes considerations for the selection of a suitable dataset and appropriate metrics for the exploration of the results. The approach is demonstrated for four regional dust transport models (BSC-DREAM8b v2, NMMB/BSC-DUST, DREAMABOL, DREAM8-NMME-MACC) using dust observations performed at 10 ACTRIS/EARLINET stations. The observations, which include coincident multi-wavelength lidar and sun photometer measurements, were processed with the Lidar-Radiometer Inversion Code (LIRIC) to retrieve aerosol concentration profiles. The methodology proposed here shows advantages when compared to traditional evaluation techniques that utilize separately the available measurements such as separating the contribution of dust from other aerosol types on the lidar profiles and avoiding model assumptions related to the conversion of concentration fields to aerosol extinction values. When compared to LIRIC retrievals, the simulated dust vertical structures were found to be in good agreement for all models with correlation values between 0.5 and 0.7 in the 1 to 6 km range, where most of dust is typically observed. The absolute dust concentration was typically underestimated with mean bias values of −40 to −20 μg m−3 at 2 km, the altitude of maximum mean concentration. The reported differences among the models found in this comparison indicate the benefit of the systematic use of the proposed approach in future dust model evaluation studies.

Abstract. In the present work, atmospheric mineral dust from a MACC-II short reanalysis run for two years (2007–2008), has been evaluated over Northern Africa and Middle East using satellite aerosol products (from MISR, MODIS and OMI satellite sensors), ground-based AERONET data, in-situ PM10 concentrations from AMMA, and extinction vertical profiles from two ground-based lidars and CALIOP. The MACC-II aerosol optical depth (AOD) spatial and temporal (seasonal and interannual) variability shows good agreement with those provided by satellite sensors. The capability of the model to reproduce AOD, Ångström exponent (AE) and dust optical depth (DOD) from daily to seasonal time-scale is quantified over twenty-six AERONET stations located in eight geographically distinct regions by using statistical parameters. Overall DOD seasonal variation is fairly well simulated by MACC-II in all regions, although the correlation is significantly higher in dust transport regions than in dust source regions. The ability of MACC-II in reproducing dust vertical profiles has been assessed by comparing seasonal averaged extinction vertical profiles simulated by MACC-II under dust conditions with corresponding extinction profiles obtained with lidar instruments at M'Bour and Santa Cruz de Tenerife, and with CALIOP. We find a good agreement in dust layers structures and averaged extinction vertical profiles between MACC-II, the lidars and CALIOP above the marine boundary layer from 1 to 6 km. Surface dust daily mean concentrations from MACC-II reanalysis has been evaluated with daily averaged PM10 at three monitoring stations of the Sahelian Dust Transect. MACC-II correctly reproduces daily to interannual surface dust concentration variability, although it underestimates daily and monthly means all year long, especially in winter and early spring (dry season). MACC-II reproduces well the dust variability recorded along the station-transect which reflects the variability in dust emission by different Saharan sources, but fails in reproducing the sporadic and very strong dust events associated to mesoscale convective systems during the wet season.

Abstract-The elastic lidar equation contains two unknown atmospheric parameters, namely, the particulate optical extinction and backscatter coefficients, which are related through the lidar ratio (i.e., the particulate-extinction-to-backscatter ratio).