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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
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...
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| Published in: | Geoscientific Model Development 2019-01, Vol.12 (1), p.33-67 |
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| Main Authors: | , , , , , , , , , , , , , , , , , , |
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| creator | Brasseur, Guy P Xie, Ying Petersen, Anna Katinka Bouarar, Idir Flemming, Johannes Gauss, Michael Jiang, Fei Kouznetsov, Rostislav Kranenburg, Richard Mijling, Bas Peuch, Vincent-Henri Pommier, Matthieu Segers, Arjo Sofiev, Mikhail Timmermans, Renske van der A, Ronald Walters, Stacy Xu, Jianming Zhou, Guangqiang |
| description | 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. |
| doi_str_mv | 10.5194/gmd-12-33-2019 |
| format | article |
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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.</description><identifier>ISSN: 1991-9603</identifier><identifier>ISSN: 1991-959X</identifier><identifier>ISSN: 1991-962X</identifier><identifier>EISSN: 1991-9603</identifier><identifier>EISSN: 1991-962X</identifier><identifier>DOI: 10.5194/gmd-12-33-2019</identifier><language>eng</language><publisher>Katlenburg-Lindau: Copernicus GmbH</publisher><subject>Air ; Air pollution ; Air quality ; Airborne particulates ; Algorithms ; Analysis ; Boundary conditions ; Chemical transport ; Chronic obstructive pulmonary disease ; Daily forecasts ; Documentation ; Emissions ; Ensemble forecasting ; Forecasting ; Forecasts and trends ; Intercomparison ; Nitrogen oxides ; Organic chemistry ; Oxides ; Ozone ; Partial differential equations ; Particulate matter ; Photochemicals ; Pollutants ; Suspended particulate matter ; Urban areas ; Weather ; Weather forecasting ; Websites</subject><ispartof>Geoscientific Model Development, 2019-01, Vol.12 (1), p.33-67</ispartof><rights>COPYRIGHT 2019 Copernicus GmbH</rights><rights>2019. This work is published under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c474t-2057fbee96d867fe46dd9b48d3367f7c63b916aedbc94603579a061d4e5b9f0c3</citedby><cites>FETCH-LOGICAL-c474t-2057fbee96d867fe46dd9b48d3367f7c63b916aedbc94603579a061d4e5b9f0c3</cites><orcidid>0000-0002-0077-5338 ; 0000-0003-4880-5329 ; 0000-0001-5140-0037 ; 0000-0001-6016-4363 ; 0000-0003-1396-0505 ; 0000-0003-1744-7565</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2162727439/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2162727439?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,777,781,25735,27906,27907,36994,44572,74876</link.rule.ids></links><search><creatorcontrib>Brasseur, Guy P</creatorcontrib><creatorcontrib>Xie, Ying</creatorcontrib><creatorcontrib>Petersen, Anna Katinka</creatorcontrib><creatorcontrib>Bouarar, Idir</creatorcontrib><creatorcontrib>Flemming, Johannes</creatorcontrib><creatorcontrib>Gauss, Michael</creatorcontrib><creatorcontrib>Jiang, Fei</creatorcontrib><creatorcontrib>Kouznetsov, Rostislav</creatorcontrib><creatorcontrib>Kranenburg, Richard</creatorcontrib><creatorcontrib>Mijling, Bas</creatorcontrib><creatorcontrib>Peuch, Vincent-Henri</creatorcontrib><creatorcontrib>Pommier, Matthieu</creatorcontrib><creatorcontrib>Segers, Arjo</creatorcontrib><creatorcontrib>Sofiev, Mikhail</creatorcontrib><creatorcontrib>Timmermans, Renske</creatorcontrib><creatorcontrib>van der A, Ronald</creatorcontrib><creatorcontrib>Walters, Stacy</creatorcontrib><creatorcontrib>Xu, Jianming</creatorcontrib><creatorcontrib>Zhou, Guangqiang</creatorcontrib><title>Ensemble forecasts of air quality in eastern China – Part 1: Model description and implementation of the MarcoPolo–Panda prediction system, version 1</title><title>Geoscientific Model Development</title><description>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.</description><subject>Air</subject><subject>Air pollution</subject><subject>Air quality</subject><subject>Airborne particulates</subject><subject>Algorithms</subject><subject>Analysis</subject><subject>Boundary conditions</subject><subject>Chemical transport</subject><subject>Chronic obstructive pulmonary disease</subject><subject>Daily forecasts</subject><subject>Documentation</subject><subject>Emissions</subject><subject>Ensemble forecasting</subject><subject>Forecasting</subject><subject>Forecasts and trends</subject><subject>Intercomparison</subject><subject>Nitrogen oxides</subject><subject>Organic chemistry</subject><subject>Oxides</subject><subject>Ozone</subject><subject>Partial differential equations</subject><subject>Particulate matter</subject><subject>Photochemicals</subject><subject>Pollutants</subject><subject>Suspended particulate matter</subject><subject>Urban areas</subject><subject>Weather</subject><subject>Weather 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Development</jtitle><date>2019-01-03</date><risdate>2019</risdate><volume>12</volume><issue>1</issue><spage>33</spage><epage>67</epage><pages>33-67</pages><issn>1991-9603</issn><issn>1991-959X</issn><issn>1991-962X</issn><eissn>1991-9603</eissn><eissn>1991-962X</eissn><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.</abstract><cop>Katlenburg-Lindau</cop><pub>Copernicus GmbH</pub><doi>10.5194/gmd-12-33-2019</doi><tpages>35</tpages><orcidid>https://orcid.org/0000-0002-0077-5338</orcidid><orcidid>https://orcid.org/0000-0003-4880-5329</orcidid><orcidid>https://orcid.org/0000-0001-5140-0037</orcidid><orcidid>https://orcid.org/0000-0001-6016-4363</orcidid><orcidid>https://orcid.org/0000-0003-1396-0505</orcidid><orcidid>https://orcid.org/0000-0003-1744-7565</orcidid><oa>free_for_read</oa></addata></record> |
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| identifier | ISSN: 1991-9603 |
| ispartof | Geoscientific Model Development, 2019-01, Vol.12 (1), p.33-67 |
| issn | 1991-9603 1991-959X 1991-962X 1991-9603 1991-962X |
| language | eng |
| recordid | cdi_proquest_journals_2162727439 |
| source | Publicly Available Content Database |
| subjects | Air Air pollution Air quality Airborne particulates Algorithms Analysis Boundary conditions Chemical transport Chronic obstructive pulmonary disease Daily forecasts Documentation Emissions Ensemble forecasting Forecasting Forecasts and trends Intercomparison Nitrogen oxides Organic chemistry Oxides Ozone Partial differential equations Particulate matter Photochemicals Pollutants Suspended particulate matter Urban areas Weather Weather forecasting Websites |
| title | Ensemble forecasts of air quality in eastern China – Part 1: Model description and implementation of the MarcoPolo–Panda prediction system, version 1 |
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