Forecasting the northern African dust outbreak towards Europe in April 2011: a model intercomparison

• Published in: Atmospheric Chemistry and Physics
• Main Authors: Huneeus, N., Basart, Sara, Baldasano Recio, José María
• Other Authors: Universitat Politècnica de Catalunya. Departament d'Enginyeria de Projectes i de la Construcció, Barcelona Supercomputing Center, Universitat Politècnica de Catalunya. GReCT - Grup de Recerca de Ciències de la Terra
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2016
• Subjects: Àrees temàtiques de la UPC::Desenvolupament humà i sostenible::Degradació ambiental::Contaminació atmosfèrica; Mineral dust; Air quality > Measurement; Atmospheric aerosols; Optical radar; Dust Storm; forecast models; Saharan dust; Aerosol Lidar; AERONET; CALIOP; Pols mineral; Aire > Qualitat > Mesurament; Aerosols atmosfèrics; Radar òptic; Merra; Fiedler; Huneeus; Aerosol Robotic Network
• Online Access: http://hdl.handle.net/2117/86592; https://doi.org/10.5194/acp-16-4967-2016

In the framework of theWorld Meteorological Organisation’s Sand and Dust Storm Warning Advisory and Assessment System, we evaluated the predictions of five state-of-the-art dust forecast models during an intense Saharan dust outbreak affecting western and northern Europe in April 2011. We assessed the capacity of the models to predict the evolution of the dust cloud with lead times of up to 72 h using observations of aerosol optical depth (AOD) from the AErosol RObotic NETwork (AERONET) and the Moderate Resolution Imaging Spectroradiometer (MODIS) and dust surface concentrations from a ground-based measurement network. In addition, the predicted vertical dust distribution was evaluated with vertical extinction profiles from the Cloud and Aerosol Lidar with Orthogonal Polarization (CALIOP). To assess the diversity in forecast capability among the models, the analysis was extended to wind field (both surface and profile), synoptic conditions, emissions and deposition fluxes. Models predict the onset and evolution of the AOD for all analysed lead times. On average, differences among the models are larger than differences among lead times for each individual model. In spite of large differences in emission and deposition, the models present comparable skill for AOD. In general, models are better in predicting AOD than near-surface dust concentration over the Iberian Peninsula. Models tend to underestimate the longrange transport towards northern Europe. Our analysis suggests that this is partly due to difficulties in simulating the vertical distribution dust and horizontal wind. Differences in the size distribution and wet scavenging efficiency may also account for model diversity in long-range transport. The authors acknowledge AERONET (http://aeronet.gsfc.nasa.gov) and thank the PIs of the AERONET stations used in this paper for maintaining the observation program and the AERONET-Europe TNA (EU-ACTRIS grant no. 262254) for contributing to calibration efforts. We also acknowledge the MERRA, CALIPSO and MODIS mission scientists and associated NASA personnel for the production of the data used in this research effort. MODIS data used in this paper were produced with the Giovanni online data system, developed and maintained by the NASA GES DISC. S. Basart acknowledges the Catalan Government (BE-DGR-2012) as well as the CICYT project (CGL2010-19652 and CGL2013-46736) and Severo Ochoa (SEV-2011-00067) programme of the Spanish Government. The NMMB/BSC-Dust and BSC-DREAM8b simulations were performed on the MareNostrum supercomputer hosted by BSC. Stephanie Fiedler acknowledges the funding of the European Research Council through the starting grant of Peter Knippertz (no. 257543). Nicolas Huneeus acknowledges FONDAP 15110009 and FONDECYT 1150873. The database on dust concentrations at ground level was produced in the framework of the Grant Agreement LIFE10 ENV/IT/327 from the LIFE Programme of the European Commission. J. Pey has been partially funded by a Ramon y Cajal Grant (RYC-2013-14159) from the Spanish Ministry of Economy and Competitiveness. Carlos Pérez García-Pando acknowledges the Department of Energy (DE-SC0006713) and the NASA Modeling, Analysis and Prediction Program. The work was partly funded within MACC-II by the European Commission under the EU Seventh Research Framework Programme, contract number 283576 and MACC-III by the European Community’s Horizon 2020 Programme under grant agreement no. 633080. Postprint (published version)