Chapter 10 Operational Dust Prediction

Over the last few years, numerical prediction of dust aerosol concentration has become prominent at several research and operational weather centres due to growing interest from diverse stakeholders, such as solar energy plant managers, health professionals, aviation and military authorities and policymakers. Dust prediction in numerical weather prediction-type models faces a number of A. Benedetti ( ) • L. Jones • J.-J. Morcrette European Centre for Medium-Range Weather Forecasts, Reading, UK e-mail: Angela.Benedetti@ecmwf.int; Luke.Jones@ecmwf.int; Jean-Jacques.Morcrette@ecmwf.int J.M. Baldasano • S. Basart • F. Benincasa Barcelona Supercomputer Center-Centro Nacional de Supercomputación (BSC-CNS), Barcelona, Spain e-mail: Jose.Baldasano@bsc.es; Sara.Basart@bsc.es; Francesco.Benincasa@bsc.es O. Boucher • L. Menut Laboratoire de Météorologie Dynamique, Paris, France e-mail: Olivier.Boucher@lmd.jussieu.fr; Menut@lmd.polytechnique.fr M.E. Brooks • J. Mulcahy Met Office, Exeter, UK e-mail: Malcolm.E.Brooks@metoffice.gov.uk; Jane.Mulcahy@metoffice.gov.uk J.-P. Chen Department of Atmospheric Science, National Taiwan University, Taipei, Taiwan e-mail: jpchen@as.ntu.edu.tw P.R. Colarco NASA Goddard Space Flight Center, Greenbelt, MD, USA e-mail: Peter.R.Colarco@nasa.gov P. Knippertz and J.-B.W. Stuut (eds.), Mineral Dust: A Key Player in the Earth System, DOI 10.1007/978-94-017-8978-3__10, © Springer ScienceCBusiness Media Dordrecht 2014 223 https://ntrs.nasa.gov/search.jsp?R=20150002145 2019-08-14T03:12:43+00:00Z