2018
DOI: 10.5194/acp-18-10615-2018
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Status and future of numerical atmospheric aerosol prediction with a focus on data requirements

Abstract: Abstract. Numerical prediction of aerosol particle properties has become an important activity at many research and operational weather centers. This development is due to growing interest from a diverse set of stakeholders, such as air quality regulatory bodies, aviation and military authorities, solar energy plant managers, climate services providers, and health professionals. Owing to the complexity of atmospheric aerosol processes and their sensitivity to the underlying meteorological conditions, the predi… Show more

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Cited by 66 publications
(48 citation statements)
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“…These plans may include addition of aerosol species, update of emission inventories, addition/update of aerosol data assimilation, increased model resolution, improved parametrization of physical, chemical and/or optical properties and processes. These future plans also stress requirements for aerosol observations in the context of the operational activities carried out at various centres (Benedetti et al, 2018).…”
Section: Discussionmentioning
confidence: 99%
“…These plans may include addition of aerosol species, update of emission inventories, addition/update of aerosol data assimilation, increased model resolution, improved parametrization of physical, chemical and/or optical properties and processes. These future plans also stress requirements for aerosol observations in the context of the operational activities carried out at various centres (Benedetti et al, 2018).…”
Section: Discussionmentioning
confidence: 99%
“…These were developed and implemented at the request of users interested in data assimilation (DA) applications of the data set, as the spatial coverage and near-real-time availability of the data stream make it attractive for DA applications. Meaningful pixel-level uncertainty estimates are needed for DA in order that their information can be weighted alongside other elements of the system (Benedetti et al, 2018).…”
Section: A Note On Prognostic Pixel-level Uncertainty Estimatesmentioning
confidence: 99%
“…Raw data from the MISR instrument, which require detailed engineering information to interpret, are designated as level 0 and are not generally distributed except within the science data-processing stream (Bothwell et al, 2002). The level 0 files are reformatted into level 1A Hierarchical Data Format for the Earth Observing System (HDF-EOS) files that utilize the now legacy HDF4 data structure.…”
Section: Misr Terminologymentioning
confidence: 99%
“…The AGP files also contain the MISR DEM surface elevations and surface feature identifiers used to discriminate land and water (Nelson et al, 2013). Camera-viewing zenith and azimuth angles are obtained from the geometric parameters (GP_GMP) product (Bothwell et al, 2002;Nelson et al, 2013). Finally, the Terrestrial Atmosphere and Surface Climatology (TASC) data set provides monthly values of surface pressure, ozone, water vapor, snow and ice cover, and near-surface wind speed on a global 1 • by 1 • grid .…”
Section: Misr Terminologymentioning
confidence: 99%