Application of Adjoint Data Assimilation Method to Atmospheric Aerosol Transport Problems

Xu, Minjie; Fu, Kai; Lv, Xianqing

doi:10.1155/2017/5865403

Cited by 3 publications

(3 citation statements)

References 32 publications

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“…Based on (13), we can get the gradient of the cost function on the initial conditions of pollutant concentration 0 , , [22] …”

Section: Advances In Mathematical Physicsmentioning

confidence: 99%

“…Douglas Jr. and Russell [19] proposed characteristic method to solve convection-diffusion equations; Shen et al [20] presented a characteristic finite difference method and its stability and convergence were analyzed; Fu and Liang [21] developed a conservative characteristic finite difference method to predict the distribution of atmospheric aerosols; Xu et al [22] used the adjoint assimilation method with the characteristic finite difference scheme to solve aerosol transport problems.…”

Section: Introductionmentioning

confidence: 99%

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A Study of the Transport of Marine Pollutants Using Adjoint Method of Data Assimilation with Method of Characteristics

et al. 2018

Advances in Mathematical Physics

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An adjoint method of data assimilation with the characteristic finite difference (CFD) scheme is applied to marine pollutant transport problems and the temporal and spatial distribution of marine pollutants are simulated. Numerical tests of twodimensional problems of pollutant transport with two different schemes indicate that the error of CFD is smaller than that of central difference scheme (CDS). Then the inversion experiments of the initial field and the source and sink terms of pollutants are carried out. Applying CFD in the adjoint method of data assimilation cannot only reduce simulation error to get a good inversion but can also enable larger time step size to decrease computation time and improve the calculation efficiency.

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“…Based on (13), we can get the gradient of the cost function on the initial conditions of pollutant concentration 0 , , [22] …”

Section: Advances In Mathematical Physicsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Study of the Transport of Marine Pollutants Using Adjoint Method of Data Assimilation with Method of Characteristics

et al. 2018

Advances in Mathematical Physics

Self Cite

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“…Spatial interpolation techniques are essential for estimating PM 2.5 variations. Many interpolation methods, such as kriging and Cressman interpolations, have been widely used in atmospheric subjects [8,9,12,13,14]. Lee et al [12] developed a space-time geostatistical kriging model to predict PM 2.5 fields over continental United States and found the kriging estimate was more accurate for locations near monitoring stations.…”

Section: Introductionmentioning

confidence: 99%

Application of the Orthogonal Polynomial Fitting Method in Estimating PM2.5 Concentrations in Central and Southern Regions of China

Liu

Wang

et al. 2019

IJERPH

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Sufficient and accurate air pollutant data are essential to analyze and control air contamination problems. An orthogonal polynomial fitting (OPF) method using Chebyshev basis functions is introduced to produce spatial distributions of fine particle (PM2.5) concentrations in central and southern regions of China. Idealized twin experiments (IE1 and IE2) are designed to validate the feasibility of the OPF method. IE1 is designed in accordance with the most common distribution of PM2.5 concentrations in China, whereas IE2 represents a common distribution in spring and autumn. In both idealized experiments, prescribed distributions are successfully estimated by the OPF method with smaller errors than kriging or Cressman interpolations. In practical experiments, cross-validation is employed to assess the interpolation results. Distributions of PM2.5 concentrations are well improved when OPF is applied. This suggests that errors decrease when the fitting order increases and arrives at the minimum when both orders reach 6. Results calculated by the OPF method are more accurate than kriging and Cressman interpolations if appropriate fitting orders are selected in practical experiments.

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Advancing Three-Dimensional Coupled Water Quality Model of Marine Ranches: Model Development, Global Sensitivity Analysis, and Optimization Based on Observation System

Liu

Jiang

Zhao

et al. 2022

JMSE

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Marine ranching is a stock enhancement project that has been an important part of aquaculture in China. Due to the lack of scientific management, disasters have occurred, resulting in millions of economic losses. Based on the observation system of marine ranches, a three-dimensional water quality model of marine ranches was developed to study the spatio-temporal variation of key ecological indicators, including the concentrations of chlorophyll-a, zooplankton, detritus, nutrients, and dissolved oxygen (DO). The model is coupled offline with the residual current, temperature, and salinity simulated by a regional oceanic modeling system (ROMS). The conservative characteristic finite difference (C-CFD) scheme is introduced to solve the equations, which guarantees model stability and mass conservation and allows for a larger time step compared to traditional difference schemes. In state-of-the-art water quality models, the biogeochemical processes are parameterized. Due to the complexity of the water quality model, a combination of global sensitivity analysis (GSA) and the adjoint method is introduced as the methodology to optimize the model parameters. Morris’ sampling method is implemented as the GSA method to find out the key factors of the water quality model. The optimization of sensitive parameters with the adjoint method significantly improves the model precision, while the other parameters can be set as empirical values. The results indicate that the combination of GSA and the adjoint method is efficient in the parameter optimization of the water quality model. The model is applicable in marine ranches.

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Application of Adjoint Data Assimilation Method to Atmospheric Aerosol Transport Problems

Cited by 3 publications

References 32 publications

A Study of the Transport of Marine Pollutants Using Adjoint Method of Data Assimilation with Method of Characteristics

A Study of the Transport of Marine Pollutants Using Adjoint Method of Data Assimilation with Method of Characteristics

Application of the Orthogonal Polynomial Fitting Method in Estimating PM2.5 Concentrations in Central and Southern Regions of China

Advancing Three-Dimensional Coupled Water Quality Model of Marine Ranches: Model Development, Global Sensitivity Analysis, and Optimization Based on Observation System

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