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The High Order Conservative Method for the Parameters Estimation in a PM2.5 Transport Adjoint Model
Joint Authors
Zhang, Jicai
Li, Ning
Fu, Kai
Liu, Yongzhi
Lv, Xianqing
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-12-25
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
We propose to apply Piecewise Parabolic Method (PPM), a high order and conservative interpolation, for the parameters estimation in a PM2.5 transport adjoint model.
Numerical experiments are taken to show the accuracy of PPM in space and its ability to increase the well-posedness of the inverse problem.
Based on the obtained results, the PPM provides better interpolation quality by employing much fewer independent points.
Meanwhile, this method is still well-behaved in the case of insufficient observations.
In twin experiments, two prescribed parameters, including the initial condition (IC) and the source and sink (SS), are successfully estimated by the PPM with lower interpolation errors than the Cressman interpolation.
In practical experiments, simulation results show good agreement with the observations of the period when the 21th APEC summit took place.
American Psychological Association (APA)
Li, Ning& Liu, Yongzhi& Lv, Xianqing& Zhang, Jicai& Fu, Kai. 2017. The High Order Conservative Method for the Parameters Estimation in a PM2.5 Transport Adjoint Model. Advances in Meteorology،Vol. 2017, no. 2017, pp.1-13.
https://search.emarefa.net/detail/BIM-1122667
Modern Language Association (MLA)
Li, Ning…[et al.]. The High Order Conservative Method for the Parameters Estimation in a PM2.5 Transport Adjoint Model. Advances in Meteorology No. 2017 (2017), pp.1-13.
https://search.emarefa.net/detail/BIM-1122667
American Medical Association (AMA)
Li, Ning& Liu, Yongzhi& Lv, Xianqing& Zhang, Jicai& Fu, Kai. The High Order Conservative Method for the Parameters Estimation in a PM2.5 Transport Adjoint Model. Advances in Meteorology. 2017. Vol. 2017, no. 2017, pp.1-13.
https://search.emarefa.net/detail/BIM-1122667
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1122667