Application of Adjoint Data Assimilation Method to Atmospheric Aerosol Transport Problems
We propose combining the adjoint assimilation method with characteristic finite difference scheme (CFD) to solve the aerosol transport problems, which can predict the distribution of atmospheric aerosols efficiently by using large time steps. Firstly, the characteristic finite difference scheme (CFD...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2017-01-01
|
| Series: | Advances in Mathematical Physics |
| Online Access: | http://dx.doi.org/10.1155/2017/5865403 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832547579892596736 |
|---|---|
| author | Minjie Xu Kai Fu Xianqing Lv |
| author_facet | Minjie Xu Kai Fu Xianqing Lv |
| author_sort | Minjie Xu |
| collection | DOAJ |
| description | We propose combining the adjoint assimilation method with characteristic finite difference scheme (CFD) to solve the aerosol transport problems, which can predict the distribution of atmospheric aerosols efficiently by using large time steps. Firstly, the characteristic finite difference scheme (CFD) is tested to compute the Gaussian hump using large time step sizes and is compared with the first-order upwind scheme (US1) using small time steps; the US1 method gets E2 error of 0.2887 using Δt=1/450, while CFD method gets a much smaller E2 of 0.2280 using a much larger time step Δt=1/45. Then, the initial distribution of PM2.5 concentration is inverted by the adjoint assimilation method with CFD and US1. The adjoint assimilation method with CFD gets better accuracy than adjoint assimilation method with US1 while adjoint assimilation method with CFD costs much less computational time. Further, a real case of PM2.5 concentration distribution in China during the APEC 2014 is simulated by using adjoint assimilation method with CFD. The simulation results are in good agreement with the observed values. The adjoint assimilation method with CFD can solve large scale aerosol transport problem efficiently. |
| format | Article |
| id | doaj-art-74d686d02d064d2cabdc21db8185af2c |
| institution | Kabale University |
| issn | 1687-9120 1687-9139 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Mathematical Physics |
| spelling | doaj-art-74d686d02d064d2cabdc21db8185af2c2025-02-03T06:44:01ZengWileyAdvances in Mathematical Physics1687-91201687-91392017-01-01201710.1155/2017/58654035865403Application of Adjoint Data Assimilation Method to Atmospheric Aerosol Transport ProblemsMinjie Xu0Kai Fu1Xianqing Lv2Physical Oceanography Laboratory, Ocean University of China, Qingdao 266100, ChinaSchool of Mathematical Science, Ocean University of China, Qingdao 266100, ChinaPhysical Oceanography Laboratory, Ocean University of China, Qingdao 266100, ChinaWe propose combining the adjoint assimilation method with characteristic finite difference scheme (CFD) to solve the aerosol transport problems, which can predict the distribution of atmospheric aerosols efficiently by using large time steps. Firstly, the characteristic finite difference scheme (CFD) is tested to compute the Gaussian hump using large time step sizes and is compared with the first-order upwind scheme (US1) using small time steps; the US1 method gets E2 error of 0.2887 using Δt=1/450, while CFD method gets a much smaller E2 of 0.2280 using a much larger time step Δt=1/45. Then, the initial distribution of PM2.5 concentration is inverted by the adjoint assimilation method with CFD and US1. The adjoint assimilation method with CFD gets better accuracy than adjoint assimilation method with US1 while adjoint assimilation method with CFD costs much less computational time. Further, a real case of PM2.5 concentration distribution in China during the APEC 2014 is simulated by using adjoint assimilation method with CFD. The simulation results are in good agreement with the observed values. The adjoint assimilation method with CFD can solve large scale aerosol transport problem efficiently.http://dx.doi.org/10.1155/2017/5865403 |
| spellingShingle | Minjie Xu Kai Fu Xianqing Lv Application of Adjoint Data Assimilation Method to Atmospheric Aerosol Transport Problems Advances in Mathematical Physics |
| title | Application of Adjoint Data Assimilation Method to Atmospheric Aerosol Transport Problems |
| title_full | Application of Adjoint Data Assimilation Method to Atmospheric Aerosol Transport Problems |
| title_fullStr | Application of Adjoint Data Assimilation Method to Atmospheric Aerosol Transport Problems |
| title_full_unstemmed | Application of Adjoint Data Assimilation Method to Atmospheric Aerosol Transport Problems |
| title_short | Application of Adjoint Data Assimilation Method to Atmospheric Aerosol Transport Problems |
| title_sort | application of adjoint data assimilation method to atmospheric aerosol transport problems |
| url | http://dx.doi.org/10.1155/2017/5865403 |
| work_keys_str_mv | AT minjiexu applicationofadjointdataassimilationmethodtoatmosphericaerosoltransportproblems AT kaifu applicationofadjointdataassimilationmethodtoatmosphericaerosoltransportproblems AT xianqinglv applicationofadjointdataassimilationmethodtoatmosphericaerosoltransportproblems |