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Operational Dust PredictionOver 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 challenges owing to the complexity of the system. At the centre of the problem is the vast range of scales required to fully account for all of the physical processes related to dust. Another limiting factor is the paucity of suitable dust observations available for model, evaluation and assimilation. This chapter discusses in detail numerical prediction of dust with examples from systems that are currently providing dust forecasts in near real-time or are part of international efforts to establish daily provision of dust forecasts based on multi-model ensembles. The various models are introduced and described along with an overview on the importance of dust prediction activities and a historical perspective. Assimilation and evaluation aspects in dust prediction are also discussed.
Document ID
20150002145
Acquisition Source
Goddard Space Flight Center
Document Type
Book Chapter
Authors
Benedetti, Angela
(European Centre for Medium-Range Weather Forecasts Reading, United Kingdom)
Baldasano, Jose M.
(Barcelona Supercomputing Center Barcelona, Spain)
Basart, Sara
(Barcelona Supercomputing Center Barcelona, Spain)
Benincasa, Francesco
(Barcelona Supercomputing Center Barcelona, Spain)
Boucher, Olivier
(Laboratoire de Meteorologie Dynamique Paris, France)
Brooks, Malcolm E.
(MET Office (Meteorological Office) Exeter, United Kingdom)
Chen, Jen-Ping
(National Taiwan Univ. Taipei, Taiwan, Province of China)
Colarco, Peter R.
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Gong, Sunlin
(Chinese Academy of Meteorological Sciences Beijing, China)
Huneeus, Nicolas
(Chile Univ. Santiago, Chile)
Jones, Luke
(European Centre for Medium-Range Weather Forecasts Reading, United Kingdom)
Lu, Sarah
(National Centers for Environmental Prediction College Park, MD, United States)
Menut, Laurent
(Laboratoire de Meteorologie Dynamique Paris, France)
Morcrette, Jean-Jacques
(European Centre for Medium-Range Weather Forecasts Reading, United Kingdom)
Mulcahy, Jane
(MET Office (Meteorological Office) Exeter, United Kingdom)
Nickovic, Slobodan
(Institute of Physics Belgrade, Macedonia)
Garcia-Pando, Carlos P.
(Columbia Univ. New York, NY, United States)
Reid, Jeffrey S.
(Naval Research Lab. Monterey, CA, United States)
Sekiyama, Thomas T.
(Japan Meteorological Agency Tsukuba, Japan)
Tanaka, Taichu Y.
(Japan Meteorological Agency Tsukuba, Japan)
Terradellas, Enric
(Agencia Estatal de Meteorologia Madrid, Spain)
Westphal, Douglas L.
(Naval Research Lab. Monterey, CA, United States)
Zhang, Xiao-Ye
(Chinese Academy of Meteorological Sciences Beijing, China)
Zhou, Chun-Hong
(Chinese Academy of Meteorological Sciences Beijing, China)
Date Acquired
February 25, 2015
Publication Date
June 28, 2014
Publication Information
Publication: Mineral Dust: A Key Player in the Earth System
Publisher: Springer
ISBN: 978-94-017-8978-3
Subject Category
Meteorology And Climatology
Report/Patent Number
GSFC-E-DAA-TN19201
Report Number: GSFC-E-DAA-TN19201
ISBN: 978-94-017-8978-3
Funding Number(s)
CONTRACT_GRANT: NNX14AB99A
Distribution Limits
Public
Copyright
Public Use Permitted.
Keywords
assimilation
mathematical models
dust
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