scholarly journals Ocean Plastic Assimilator v0.2: assimilation of plastic concentration data into Lagrangian dispersion models

2021 ◽  
Vol 14 (7) ◽  
pp. 4769-4780
Author(s):  
Axel Peytavin ◽  
Bruno Sainte-Rose ◽  
Gael Forget ◽  
Jean-Michel Campin
Keyword(s):  
Dispersion Model ◽  
Simulated Data ◽  
Circulation Model ◽  
Particle Dispersion ◽  
Dispersion Models ◽  
Concentration Data ◽  
Suitable Candidate ◽  
Real World Applications ◽  
Lagrangian Dispersion ◽  
Assimilation Scheme

Abstract. A numerical scheme to perform data assimilation of concentration measurements in Lagrangian models is presented, along with its first implementation called Ocean Plastic Assimilator, which aims to improve predictions of the distributions of plastics over the oceans. This scheme uses an ensemble method over a set of particle dispersion simulations. At each step, concentration observations are assimilated across the ensemble members by switching back and forth between Eulerian and Lagrangian representations. We design two experiments to assess the scheme efficacy and efficiency when assimilating simulated data in a simple double-gyre model. Analysis convergence is observed with higher accuracy when lowering observation variance or using a circulation model closer to the real circulation. Results show that the distribution of the mass of plastics in an area can effectively be improved with this simple assimilation scheme. Direct application to a real ocean dispersion model of the Great Pacific Garbage Patch is presented with simulated observations, which gives similarly encouraging results. Thus, this method is considered a suitable candidate for creating a tool to assimilate plastic concentration observations in real-world applications to estimate and forecast plastic distributions in the oceans. Finally, several improvements that could further enhance the method efficiency are identified.

scholarly journals Ocean Plastic Assimilator v0.1: Assimilation of Plastics Concentration Data Into Lagrangian Dispersion Models

2021 ◽  
Author(s):  
Axel Peytavin ◽  
Bruno Sainte-Rose ◽  
Gael Forget ◽  
Jean-Michel Campin
Keyword(s):  
Numerical Scheme ◽  
Simulated Data ◽  
Circulation Model ◽  
Particle Dispersion ◽  
Dispersion Models ◽  
Concentration Data ◽  
Suitable Candidate ◽  
Real World Applications ◽  
Lagrangian Dispersion ◽  
Assimilation Scheme

Abstract. A numerical scheme to perform data assimilation of concentration measurements in Lagrangian models is presented, along with its first implementation called Ocean Plastic Assimilator, which aims at improving predictions of plastics distributions over the oceans. This scheme uses an ensemble method over a set of particle dispersion simulations. At each step, concentration observations are assimilated across the ensemble members by switching back and forth between Eulerian and Lagrangian representations. We design two experiments to assess the scheme efficacy and efficiency when assimilating simulated data in a simple double gyre model. Analysis convergence is observed with higher accuracy when lowering observation variance or using a more suitable circulation model. Results show that the distribution of plastic mass in an area can effectively be approached with this simple assimilation scheme. Thus, this method is considered a suitable candidate for creating a tool to assimilate plastic concentration observations in real-world applications to forecast plastic distributions in the oceans. Finally, several improvements that could further enhance the method efficiency are identified.

Development of a Hybrid Turbulent Particle Dispersion Model and Implementation in the Gasflow Code

2008 ◽  
Author(s):  
Zhanjie Xu ◽  
John R. Travis ◽  
Wolfgang Breitung
Keyword(s):  
Dispersion Model ◽  
Separated Flow ◽  
Particle Dispersion ◽  
Turbulent Dispersion ◽  
Vacuum Vessel ◽  
Dispersion Models ◽  
Proposed Model ◽  
Dust Mobilization ◽  
Decaying Turbulence ◽  
Turbulent Particle Dispersion

Dust mobilization in a vacuum vessel is one of the key issues endangering the security of the International Thermonuclear Experimental Reactor (ITER), in case of Loss of Vacuum Accidents (LOVA). The turbulent behavior of particles in turbulent flows has to be modeled for successful numerical simulations about particle mobilization. In this study a Lagrangian approach is adopted to formulate the particle transport especially for dust-dilute flows mostly encountered in the vacuum vessel of ITER. Based on the logic frame of the approach and the used Computational Fluid Dynamic (CFD) computer code in the study, a hybrid turbulent particle dispersion model is proposed. The hybrid model features both a deterministic separated flow (DSF) model and a stochastic separated flow (SSF) model, which are two popular turbulent dispersion models applied in particle simulations, and takes the advantages of the both models. The proposed model is implemented into the particle model of the CFD code successfully and the simulation results are verified against experimental data. The verifications manifest the validities of the proposed model. In this paper general information about the work of dust mobilization is introduced and the particle turbulent dispersion models are reviewed briefly at first. The hybrid model is then proposed based on the SSF model. An experiment about particle dispersions in an advective wind channel flow with decaying turbulence in the streamwise direction is reviewed in the third section. In the following section about model verification, the decaying turbulence parameters in the channel flow are verified against experimental data as the first step, the parameters about the particle dispersions in the verified flow field are then verified against the data. The work is concluded finally.

Development of a Hybrid Turbulent Particle Dispersion Model and Implementation in the Gasflow Code

2008 ◽  
Vol 131 (1) ◽  
Author(s):  
Zhanjie Xu ◽  
John R. Travis ◽  
Wolfgang Breitung
Keyword(s):  
Dispersion Model ◽  
Separated Flow ◽  
Particle Dispersion ◽  
Turbulent Dispersion ◽  
Vacuum Vessel ◽  
Dispersion Models ◽  
Proposed Model ◽  
Dust Mobilization ◽  
Decaying Turbulence ◽  
Turbulent Particle Dispersion

Dust mobilization in a vacuum vessel is one of the key issues endangering the security of the International Thermonuclear Experimental Reactor (ITER) in case of loss of vacuum accidents. The turbulent behavior of particles in turbulent flows has to be modeled for successful numerical simulations about particle mobilization. In this study a Lagrangian approach is adopted to formulate the particle transport especially for dust-dilute flows mostly encountered in the vacuum vessel of ITER. Based on the logic frame of the approach and the used computational fluid dynamics (CFD) computer code in the study, a hybrid turbulent particle dispersion model is proposed. The hybrid model features both a deterministic separated flow model and a stochastic separated flow (SSF) model, which are two popular turbulent dispersion models applied in particle simulations, and takes the advantages of the both models. The proposed model is implemented into the particle model of the CFD code successfully and the simulation results are verified against the experimental data. The verifications manifest the validities of the proposed model. In this paper general information about the work of dust mobilization is introduced and the particle turbulent dispersion models are reviewed briefly at first. The hybrid model is then proposed based on the SSF model. An experiment about particle dispersions in an advective wind channel flow with decaying turbulence in the streamwise direction is reviewed in the third section. In the following section about model verification, the decaying turbulence parameters in the channel flow are verified against the experimental data as the first step, and the parameters about the particle dispersions in the verified flow field are then verified against the data. The work is concluded finally.

scholarly journals Data-Driven Hazardous Gas Dispersion Modeling Using the Integration of Particle Filtering and Error Propagation Detection

2018 ◽  
Vol 15 (8) ◽  
pp. 1640 ◽  
Author(s):  
Zhengqiu Zhu ◽  
Sihang Qiu ◽  
Bin Chen ◽  
Rongxiao Wang ◽  
Xiaogang Qiu
Keyword(s):  
Particle Filtering ◽  
Error Propagation ◽  
Dispersion Model ◽  
Data Driven ◽  
Dispersion Modeling ◽  
Dispersion Models ◽  
Concentration Data ◽  
Gas Dispersion ◽  
Computational Errors ◽  
Hazardous Gas

The accurate prediction of hazardous gas dispersion process is essential to air quality monitoring and the emergency management of contaminant gas leakage incidents in a chemical cluster. Conventional Gaussian-based dispersion models can seldom give accurate predictions due to inaccurate input parameters and the computational errors. In order to improve the prediction accuracy of a dispersion model, a data-driven air dispersion modeling method based on data assimilation is proposed by applying particle filter to Gaussian-based dispersion model. The core of the method is continually updating dispersion coefficients by assimilating observed data into the model during the calculation process. Another contribution of this paper is that error propagation detection rules are proposed to evaluate their effects since the measured and computational errors are inevitable. So environmental protection authorities can be informed to what extent the model output is of high confidence. To test the feasibility of our method, a numerical experiment utilizing the SF6 concentration data sampled from an Indianapolis field study is conducted. Results of accuracy analysis and error inspection imply that Gaussian dispersion models based on particle filtering and error propagation detection have better performance than traditional dispersion models in practice though sacrificing some computational efficiency.

scholarly journals Selected results of a model validation exercise

2009 ◽  
Vol 3 (1) ◽  
pp. 13-16 ◽  
Author(s):  
M. Piringer ◽  
K. Baumann-Stanzer
Keyword(s):  
Model Validation ◽  
Dispersion Model ◽  
Concentration Data ◽  
Gaussian Models ◽  
Lagrangian Models ◽  
Flat Terrain ◽  
Lagrangian Dispersion ◽  
Environmental Programme ◽  
Undisturbed Flow

Abstract. The concentration fields calculated with three Gaussian models and one Lagrangian dispersion model are validated against a set of SF6 concentration data provided by the German environmental programme BWPLUS. The source was a pig fattening unit in fairly flat terrain. The results reveal that, in flat terrain with steady undisturbed flow, the use of Gauss models is still justified, whereas Lagrangian models should be used whenever the flow is modified by obstacles or topography.

scholarly journals The Use of Gaussian Mixture Models with Atmospheric Lagrangian Particle Dispersion Models for Density Estimation and Feature Identification

Atmosphere ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1369
Author(s):  
Alice Crawford
Keyword(s):  
Mixture Models ◽  
Density Estimation ◽  
Mixture Model ◽  
Gaussian Mixture Models ◽  
Gaussian Mixture ◽  
Particle Dispersion ◽  
Dispersion Models ◽  
Feature Identification ◽  
Lagrangian Particle ◽  
Concentration Data

Atmospheric Lagrangian particle dispersion models, LPDM, simulate the dispersion of passive tracers in the atmosphere. At the most basic level, model output consists of the position of computational particles and the amount of mass they represent. In order to obtain concentration values, this information is then converted to a mass distribution via density estimation. To date, density estimation is performed with a nonparametric method so that output consists of gridded concentration data. Here we introduce the use of Gaussian mixture models, GMM, for density estimation. We compare to the histogram or bin counting method for a tracer experiment and simulation of a large volcanic ash cloud. We also demonstrate the use of the mixture model for automatic identification of features in a complex plume such as is produced by a large volcanic eruption. We conclude that use of a mixture model for density estimation and feature identification has potential to be very useful.

scholarly journals Large-Scale Atmospheric Dispersal Simulations Identify Likely Airborne Incursion Routes of Wheat Stem Rust Into Ethiopia

2017 ◽  
Vol 107 (10) ◽  
pp. 1175-1186 ◽  
Author(s):  
M. Meyer ◽  
L. Burgin ◽  
M. C. Hort ◽  
D. P. Hodson ◽  
C. A. Gilligan
Keyword(s):  
Stem Rust ◽  
Large Scale ◽  
Dispersion Model ◽  
Fungal Spores ◽  
Disease Outbreaks ◽  
Particle Dispersion ◽  
East African ◽  
Wheat Stem Rust ◽  
Sub Saharan ◽  
African Rift

In recent years, severe wheat stem rust epidemics hit Ethiopia, sub-Saharan Africa’s largest wheat-producing country. These were caused by race TKTTF (Digalu race) of the pathogen Puccinia graminis f. sp. tritici, which, in Ethiopia, was first detected at the beginning of August 2012. We use the incursion of this new pathogen race as a case study to determine likely airborne origins of fungal spores on regional and continental scales by means of a Lagrangian particle dispersion model (LPDM). Two different techniques, LPDM simulations forward and backward in time, are compared. The effects of release altitudes in time-backward simulations and P. graminis f. sp. tritici urediniospore viability functions in time-forward simulations are analyzed. Results suggest Yemen as the most likely origin but, also, point to other possible sources in the Middle East and the East African Rift Valley. This is plausible in light of available field surveys and phylogenetic data on TKTTF isolates from Ethiopia and other countries. Independent of the case involving TKTTF, we assess long-term dispersal trends (>10 years) to obtain quantitative estimates of the risk of exotic P. graminis f. sp. tritici spore transport (of any race) into Ethiopia for different ‘what-if’ scenarios of disease outbreaks in potential source countries in different months of the wheat season.

scholarly journals Quantitative evaluation of numerical integration schemes for Lagrangian particle dispersion models

2016 ◽  
Author(s):  
Huda Mohd. Ramli ◽  
J. Gavin Esler
Keyword(s):  
Planck Equation ◽  
Particle Dispersion ◽  
Test Problems ◽  
Hermite Function ◽  
Dispersion Models ◽  
Lagrangian Particle ◽  
Integration Schemes ◽  
Fokker Planck Equation ◽  
Long Time ◽  
Fokker Planck

Abstract. A rigorous methodology for the evaluation of integration schemes for Lagrangian particle dispersion models (LPDMs) is presented. A series of one-dimensional test problems are introduced, for which the Fokker-Planck equation is solved numerically using a finite-difference discretisation in physical space, and a Hermite function expansion in velocity space. Numerical convergence errors in the Fokker-Planck equation solutions are shown to be much less than the statistical error associated with a practical-sized ensemble (N = 106) of LPDM solutions, hence the former can be used to validate the latter. The test problems are then used to evaluate commonly used LPDM integration schemes. The results allow for optimal time-step selection for each scheme, given a required level of accuracy. The following recommendations are made for use in operational models. First, if computational constraints require the use of moderate to long time steps it is more accurate to solve the random displacement model approximation to the LPDM, rather than use existing schemes designed for long time-steps. Second, useful gains in numerical accuracy can be obtained, at moderate additional computational cost, by using the relatively simple "small-noise" scheme of Honeycutt.

scholarly journals Atmospheric rivers moisture sources from a Lagrangian perspective

2016 ◽  
Vol 7 (2) ◽  
pp. 371-384 ◽  
Author(s):  
Alexandre M. Ramos ◽  
Raquel Nieto ◽  
Ricardo Tomé ◽  
Luis Gimeno ◽  
Ricardo M. Trigo ◽  
...  
Keyword(s):  
North Atlantic ◽  
Dispersion Model ◽  
Local Maximum ◽  
Detection Algorithm ◽  
Ocean Basin ◽  
Particle Dispersion ◽  
Western Coast ◽  
Moisture Uptake ◽  
Lagrangian Analysis ◽  
Data Set

Abstract. An automated atmospheric river (AR) detection algorithm is used for the North Atlantic Ocean basin, allowing the identification of the major ARs affecting western European coasts between 1979 and 2012 over the winter half-year (October to March). The entire western coast of Europe was divided into five domains, namely the Iberian Peninsula (9.75° W, 36–43.75° N), France (4.5° W, 43.75–50° N), UK (4.5° W, 50–59° N), southern Scandinavia and the Netherlands (5.25° E, 50–59° N), and northern Scandinavia (5.25° E, 59–70° N). Following the identification of the main ARs that made landfall in western Europe, a Lagrangian analysis was then applied in order to identify the main areas where the moisture uptake was anomalous and contributed to the ARs reaching each domain. The Lagrangian data set used was obtained from the FLEXPART (FLEXible PARTicle dispersion) model global simulation from 1979 to 2012 and was forced by ERA-Interim reanalysis on a 1° latitude–longitude grid. The results show that, in general, for all regions considered, the major climatological areas for the anomalous moisture uptake extend along the subtropical North Atlantic, from the Florida Peninsula (northward of 20° N) to each sink region, with the nearest coast to each sink region always appearing as a local maximum. In addition, during AR events the Atlantic subtropical source is reinforced and displaced, with a slight northward movement of the sources found when the sink region is positioned at higher latitudes. In conclusion, the results confirm not only the anomalous advection of moisture linked to ARs from subtropical ocean areas but also the existence of a tropical source, together with midlatitude anomaly sources at some locations closer to AR landfalls.

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