Abstract
Abstract. In the framework of the World 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 long-range 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.
Highlights
Desert dust, the largest contributor to the global aerosol burden after sea salt (Textor et al, 2006; Huneeus et al, 2013), plays an important role in the climate system, the chemical composition of the atmosphere and the ocean biogeochemical cycles (Jickells et al, 2005; Aumont et al, 2008, Mahowald et al, 2009; Schulz et al, 2012; Gallisai et al, 2014)
Some evidence exists for increased mortality when dust aerosols are present in particulate matter with a radius smaller than 10 μm (PM10) (Jiménez et al, 2010; Karanasiou et al, 2012), and dust storms have been associated with epidemics of meningococcal meningitis in the African Sahel (Agier et al, 2013; Pérez García-Pando et al, 2014a, b)
We examine the performance of five state-of-the-art dust forecast models in predicting the intense Saharan dust outbreak transporting dust over western Europe to Scandinavia between 5 and 11 April 2011
Summary
The largest contributor to the global aerosol burden after sea salt (Textor et al, 2006; Huneeus et al, 2013), plays an important role in the climate system, the chemical composition of the atmosphere (see, e.g., Sokolik et al, 2001; Tegen, 2003; Balkanski et al, 2007; Bauer and Koch, 2005) and the ocean biogeochemical cycles (Jickells et al, 2005; Aumont et al, 2008, Mahowald et al, 2009; Schulz et al, 2012; Gallisai et al, 2014) Besides their climate effect, dust aerosols degrade air quality over large regions of the globe (see, e.g., Kim et al, 2001; Ozer et al, 2007; Querol et al, 2009; Pey et al, 2013) and often disproportionately reduce visibility close to source regions, impacting transportation (road vehicles and airports), military operations and photovoltaic energy production (see, e.g., SchroedterHomscheidt et al, 2013). While NWP benefits from advanced nearreal-time observations systems and well-established protocols for the evaluation of forecast products, similar procedures for aerosol forecasting are at their beginning (Reid et al, 2011)
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