English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
 
 
DownloadE-Mail
  Status and future of numerical atmospheric aerosol prediction with a focus on data requirements

Benedetti, A., Reid, J. S., Knippertz, P., Marsham, J. H., Di Giuseppe, F., Remy, S., et al. (2018). Status and future of numerical atmospheric aerosol prediction with a focus on data requirements. Atmospheric Chemistry and Physics, 18, 10615-10643. doi:10.5194/acp-18-10615-2018.

Item is

Files

show Files
hide Files
:
acp-18-10615-2018.pdf (Publisher version), 1020KB
Name:
acp-18-10615-2018.pdf
Description:
Final Revised Paper
OA-Status:
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
-

Locators

show

Creators

show
hide
 Creators:
Benedetti, Angela1, Author
Reid, Jeffrey S.1, Author
Knippertz, Peter1, Author
Marsham, John H.1, Author
Di Giuseppe, Francesca1, Author
Remy, Samuel1, Author
Basart, Sara1, Author
Boucher, Olivier1, Author
Brooks, Ian M.1, Author
Menut, Laurent1, Author
Mona, Lucia1, Author
Laj, Paolo1, Author
Pappalardo, Gelsomina1, Author
Wiedensohler, Alfred1, Author
Baklanov, Alexander1, Author
Brooks, Malcolm1, Author
Colarco, Peter R.1, Author
Cuevas, Emilio1, Author
da Silva, Arlindo1, Author
Escribano, Jeronimo1, Author
Flemming, Johannes1, AuthorHuneeus, Nicolas1, AuthorJorba, Oriol1, AuthorKazadzis, Stelios1, AuthorKinne, Stefan2, Author           Popp, Thomas1, AuthorQuinn, Patricia K.1, AuthorSekiyama, Thomas T.1, AuthorTanaka, Taichu1, AuthorTerradellas, Enric1, Author more..
Affiliations:
1external, ou_persistent22              
2Observations and Process Studies, The Atmosphere in the Earth System, MPI for Meteorology, Max Planck Society, ou_913575              

Content

show
hide
Free keywords: OPTICAL DEPTH RETRIEVALS; VIIRS DAY/NIGHT BAND; REMOTE-SENSING OBSERVATIONS; SEA-SURFACE TEMPERATURE; SUMMERTIME WEST-AFRICA; FIRE RADIATIVE POWER; DATA ASSIMILATION; DUST EMISSION; MINERAL DUST; SAHELIAN DUST; Meteorology & Atmospheric Sciences;
 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.

Details

show
hide
Language(s): eng - English
 Dates: 20182018
 Publication Status: Issued
 Pages: 29
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: ISI: 000439936200002
DOI: 10.5194/acp-18-10615-2018
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Atmospheric Chemistry and Physics
  Abbreviation : ACP
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: Göttingen : Copernicus Publications
Pages: - Volume / Issue: 18 Sequence Number: - Start / End Page: 10615 - 10643 Identifier: ISSN: 1680-7316
CoNE: https://pure.mpg.de/cone/journals/resource/111030403014016