Status and future of numerical atmospheric aerosol prediction with a focus on data requirements
Authors: Benedetti Angela , Reid Jeffrey S. , Knippertz Peter , Marsham John H. , Di Giuseppe Francesca , Rémy Samuel , Basart Sara , Boucher Olivier , Brooks Ian M. , Menut Laurent , Mona Lucia , Laj Paolo , Pappalardo Gelsomina , Wiedensohler Alfred , Baklanov Alexander , Brooks Malcolm , Colarco Peter R. , Cuevas Emilio , da Silva Arlindo , Escribano Jeronimo , Flemming Johannes , Huneeus Nicolas , Jorba Oriol , Kazadzis Stelios , Kinne Stefan , Popp Thomas , Quinn Patricia K. , Sekiyama Thomas T. , Tanaka Taichu , Terradellas Enric 
Published: July 2018

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 prediction of aerosol particle
concentrations and properties in the numerical weather prediction (NWP) framework
faces a number of challenges. The modeling of numerous aerosol-related
parameters increases computational expense. Errors in aerosol prediction
concern all processes involved in the aerosol life cycle including (a) errors
on the source terms (for both anthropogenic and natural emissions),
(b) errors directly dependent on the meteorology (e.g., mixing, transport,
scavenging by precipitation), and (c) errors related to aerosol chemistry (e.g.,
nucleation, gas–aerosol partitioning, chemical transformation and growth,
hygroscopicity). Finally, there are fundamental uncertainties and significant
processing overhead in the diverse observations used for verification and
assimilation within these systems. Indeed, a significant component of aerosol
forecast development consists in streamlining aerosol-related observations
and reducing the most important errors through model development and data
assimilation. Aerosol particle observations from satellite- and ground-based
platforms have been crucial to guide model development of the recent years
and have been made more readily available for model evaluation and
assimilation. However, for the sustainability of the aerosol particle
prediction activities around the globe, it is crucial that quality aerosol
observations continue to be made available from different platforms (space,
near surface, and aircraft) and freely shared. This paper reviews current
requirements for aerosol observations in the context of the operational
activities carried out at various global and regional centers. While some of
the requirements are equally applicable to aerosol–climate, the focus here is
on global operational prediction of aerosol properties such as mass
concentrations and optical parameters. It is also recognized that the term
“requirements” is loosely used here given the diversity in global aerosol
observing systems and that utilized data are typically not from operational
sources. Most operational models are based on bulk schemes that do not
predict the size distribution of the aerosol particles. Others are based on a
mix of “bin” and bulk schemes with limited capability of simulating the size
information. However the next generation of aerosol operational models will
output both mass and number density concentration to provide a more complete
description of the aerosol population. A brief overview of the
state of the art is provided with an introduction on the importance of
aerosol prediction activities. The criteria on which the requirements for
aerosol observations are based are also outlined. Assimilation and evaluation
aspects are discussed from the perspective of the user requirements.