The High Order Conservative Method for the Parameters Estimation in a PM2.5 Transport Adjoint Model

المؤلفون المشاركون

Zhang, Jicai
Li, Ning
Fu, Kai
Liu, Yongzhi
Lv, Xianqing

المصدر

Advances in Meteorology

العدد

المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-13، 13ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2017-12-25

دولة النشر

مصر

عدد الصفحات

13

التخصصات الرئيسية

الفيزياء

الملخص 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.

نمط استشهاد جمعية علماء النفس الأمريكية (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

نمط استشهاد الجمعية الأمريكية للغات الحديثة (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

نمط استشهاد الجمعية الطبية الأمريكية (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

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1122667