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  Ensemble forecasts of air quality in eastern China - Part 1: Model description and implementation of the MarcoPolo-Panda prediction system, version 1

Brasseur, G. P., Xie, Y., Petersen, K., Bouarar, I., Flemming, J., Gauss, M., et al. (2019). Ensemble forecasts of air quality in eastern China - Part 1: Model description and implementation of the MarcoPolo-Panda prediction system, version 1. Geoscientific Model Development, 12, 33-67. doi:10.5194/gmd-12-33-2019.

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gmd-12-33-2019.pdf (Publisher version), 9MB
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gmd-12-33-2019.pdf
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Final Revised Paper
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 Creators:
Brasseur, Guy P.1, Author                 
Xie, Ying2, Author
Petersen, Katinka1, Author           
Bouarar, Idir1, Author           
Flemming, Johannes2, Author
Gauss, Michael2, Author
Jiang, Fei2, Author
Kouznetsov, Rostislav2, Author
Kranenburg, Richard2, Author
Mijling, Bas2, Author
Peuch, Vincent-Henri2, Author
Pommier, Matthieu2, Author
Segers, Arjo2, Author
Sofiev, Mikhail2, Author
Timmermans, Renske2, Author
van der A, Ronald2, Author
Walters, Stacy2, Author
Xu, Jianming2, Author
Zhou, Guangqiang2, Author
Affiliations:
1Environmental Modelling, MPI for Meteorology, Max Planck Society, ou_2149681              
2external, ou_persistent22              

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Free keywords: SECONDARY ORGANIC AEROSOL; TROPOSPHERIC CHEMISTRY; TRANSPORT MODEL; SURFACE OZONE; EMISSIONS; DISPERSION; FRAMEWORK; EUROPE; UNCERTAINTIES; ASSIMILATIONGeology;
 Abstract: An operational multi-model forecasting system for air quality including nine different chemical transport models has been developed and provides daily forecasts of ozone, nitrogen oxides, and particulate matter for the 37 largest urban areas of China (population higher than 3 million in 2010). These individual forecasts as well as the mean and median concentrations for the next 3 days are displayed on a publicly accessible website (http://www.marcopolo-panda. eu, last access: 7 December 2018). The paper describes the forecasting system and shows some selected illustrative examples of air quality predictions. It presents an intercomparison of the different forecasts performed during a given period of time (1-15 March 2017) and highlights recurrent differences between the model output as well as systematic biases that appear in the median concentration values. Pathways to improve the forecasts by the multi-model system are suggested.

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Language(s): eng - English
 Dates: 2018-072018-102019-01-032019-01-03
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: ISI: 000455006200001
DOI: 10.5194/gmd-12-33-2019
 Degree: -

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Title: Geoscientific Model Development
  Other : Geosci. Model Dev.
  Abbreviation : GMD
Source Genre: Journal
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Publ. Info: Göttingen : Copernicus Publ.
Pages: - Volume / Issue: 12 Sequence Number: - Start / End Page: 33 - 67 Identifier: ISSN: 1991-959X
CoNE: https://pure.mpg.de/cone/journals/resource/1991-959X