scholarly journals Source-receptor matrix calculation for deposited mass with the Lagrangian particle dispersion model FLEXPART v10.2 in backward mode

2017 ◽  
Author(s):  
Sabine Eckhardt ◽  
Massimo Cassiani ◽  
Nikolaos Evangeliou ◽  
Espen Sollum ◽  
Ignacio Pisso ◽  
...  
Keyword(s):  
Dispersion Model ◽  
Ice Cores ◽  
Particle Dispersion ◽  
Lagrangian Particle ◽  
Mixing Ratios ◽  
Efficient Calculation ◽  
Wet Scavenging ◽  
Application Fields ◽  
Atmospheric Concentrations ◽  
Matrix Calculation

Abstract. Existing Lagrangian particle dispersion models are capable of establishing source-receptor relationships by running either forward or backward in time. For many applications, backward simulations can be computationally more efficient by several orders of magnitude. However, to date, the backward modelling capabilities have been limited to atmospheric concentrations or mixing ratios. In this paper, we extend the backward modelling technique to substances deposited at the Earth's surface by wet scavenging and dry deposition. This facilitates efficient calculation of emission sensitivities for deposition quantities, which opens new application fields such as the comprehensive analysis of measured deposition quantities, or of deposition recorded in snow samples or ice cores. This could also include inverse modelling of emission sources based on such measurements. We have tested the new scheme as implemented in the Lagrangian particle dispersion model FLEXPART v10.2 by comparing results from forward and backward calculations. We also present an example application for black carbon concentrations recorded in Arctic snow.

scholarly journals Source–receptor matrix calculation for deposited mass with the Lagrangian particle dispersion model FLEXPART v10.2 in backward mode

2017 ◽  
Vol 10 (12) ◽  
pp. 4605-4618 ◽  
Author(s):  
Sabine Eckhardt ◽  
Massimo Cassiani ◽  
Nikolaos Evangeliou ◽  
Espen Sollum ◽  
Ignacio Pisso ◽  
...  
Keyword(s):  
Dispersion Model ◽  
Measurement Data ◽  
Ice Cores ◽  
Particle Dispersion ◽  
Lagrangian Particle ◽  
Mixing Ratios ◽  
Efficient Calculation ◽  
Wet Scavenging ◽  
Application Fields ◽  
Atmospheric Concentrations

Abstract. Existing Lagrangian particle dispersion models are capable of establishing source–receptor relationships by running either forward or backward in time. For receptor-oriented studies such as interpretation of "point" measurement data, backward simulations can be computationally more efficient by several orders of magnitude. However, to date, the backward modelling capabilities have been limited to atmospheric concentrations or mixing ratios. In this paper, we extend the backward modelling technique to substances deposited at the Earth's surface by wet scavenging and dry deposition. This facilitates efficient calculation of emission sensitivities for deposition quantities at individual sites, which opens new application fields such as the comprehensive analysis of measured deposition quantities, or of deposition recorded in snow samples or ice cores. This could also include inverse modelling of emission sources based on such measurements. We have tested the new scheme as implemented in the Lagrangian particle dispersion model FLEXPART v10.2 by comparing results from forward and backward calculations. We also present an example application for black carbon concentrations recorded in Arctic snow.

scholarly journals Technical note: The Lagrangian particle dispersion model FLEXPART version 6.2

2005 ◽  
Vol 5 (9) ◽  
pp. 2461-2474 ◽  
Author(s):  
A. Stohl ◽  
C. Forster ◽  
A. Frank ◽  
P. Seibert ◽  
G. Wotawa
Keyword(s):  
Nuclear Power ◽  
Water Cycle ◽  
Atmospheric Transport ◽  
Dispersion Model ◽  
Particle Dispersion ◽  
Technical Note ◽  
Point Sources ◽  
Lagrangian Particle ◽  
Modeling And Analysis ◽  
Application Fields

Abstract. The Lagrangian particle dispersion model FLEXPART was originally (about 8 years ago) designed for calculating the long-range and mesoscale dispersion of air pollutants from point sources, such as after an accident in a nuclear power plant. In the meantime FLEXPART has evolved into a comprehensive tool for atmospheric transport modeling and analysis. Its application fields were extended from air pollution studies to other topics where atmospheric transport plays a role (e.g., exchange between the stratosphere and troposphere, or the global water cycle). It has evolved into a true community model that is now being used by at least 25 groups from 14 different countries and is seeing both operational and research applications. A user manual has been kept actual over the years and was distributed over an internet page along with the model's source code. In this note we provide a citeable technical description of FLEXPART's latest version (6.2).

scholarly journals Source-receptor matrix calculation with a Source-receptor matrix calculation with a backward mode

2003 ◽  
Vol 3 (4) ◽  
pp. 4515-4548 ◽  
Author(s):  
P. Seibert ◽  
A. Frank
Keyword(s):  
Wet Deposition ◽  
Short Distance ◽  
Dispersion Model ◽  
Radioactive Decay ◽  
Particle Dispersion ◽  
Lagrangian Particle ◽  
Linear Source ◽  
Dry And Wet Deposition ◽  
First Order ◽  
Matrix Calculation

Abstract. The possibility to calculate linear-source receptor relationships for the transport of atmospheric trace substances with a Lagrangian particle dispersion model (LPDM) running in backward mode is shown and presented with many tests and examples. The derivation includes the action of sources and of any first-order processes (transformation with prescribed rates, dry and wet deposition, radioactive decay, ...). The backward mode is computationally advantageous if the number of receptors is less than the number of sources considered. The combination of an LPDM with the backward (adjoint) methodology is especially attractive for the application to point measurements, which can be handled without artificial numerical diffusion. Practical hints are provided for source-receptor calculations with different settings, both in forward and backward mode. The equivalence of forward and backward calculations is shown in simple tests for release and sampling of particles, pure wet deposition, pure convective redistribution and realistic transport over a short distance. Furthermore, an application example explaining measurements of Cs-137 in Stockholm as transport from areas contaminated heavily in the Chernobyl disaster is included.

scholarly journals Technical note: The Lagrangian particle dispersion model FLEXPART version 6.2

2005 ◽  
Vol 5 (4) ◽  
pp. 4739-4799 ◽  
Author(s):  
A. Stohl ◽  
C. Forster ◽  
A. Frank ◽  
P. Seibert ◽  
G. Wotawa
Keyword(s):  
Nuclear Power ◽  
Water Cycle ◽  
Atmospheric Transport ◽  
Dispersion Model ◽  
Particle Dispersion ◽  
Technical Note ◽  
Point Sources ◽  
Lagrangian Particle ◽  
Modeling And Analysis ◽  
Application Fields

Abstract. The Lagrangian particle dispersion model FLEXPART was originally (about 8 years ago) designed for calculating the long-range and mesoscale dispersion of air pollutants from point sources, such as after an accident in a nuclear power plant. In the meantime FLEXPART has evolved into a comprehensive tool for atmospheric transport modeling and analysis. Its application fields were extended from air pollution studies to other topics where atmospheric transport plays a role (e.g., exchange between the stratosphere and troposphere, or the global water cycle). It has evolved into a true community model that is now being used by at least 25 groups from 14 different countries and is seeing both operational and research applications. A user manual has been kept actual over the years and was distributed over an internet page along with the model's source code. However, so far there was no citeable description of FLEXPART. In this note we provide a description of FLEXPART's latest version (6.2).

Inverse modeling of halocarbons: sensitivity to the baseline definition

2021 ◽  
Author(s):  
Martin Vojta ◽  
Rona Thompson ◽  
Christine Groot Zwaaftink ◽  
Andreas Stohl
Keyword(s):  
Atmospheric Chemistry ◽  
Inverse Modeling ◽  
Sulfur Hexafluoride ◽  
Dispersion Model ◽  
Particle Dispersion ◽  
Surface Fluxes ◽  
Lagrangian Particle ◽  
Global Fields ◽  
Mixing Ratios ◽  
Model Based

<p>The identification of the baseline is an important task in inverse modeling of greenhouse gases, as it represents the influence of atmospheric chemistry and transport and surface fluxes from outside the inversion domain, or flux contributions prior to the length of the backward calculation for Lagrangian models. When modeling halocarbons, observation-based approaches are often used to calculate the baseline, although model-based approaches are an alternative. Model-based methods need global unbiased fields of mixing ratios of the observed species, which are not always easy to get and which need to be interfaced with the model used for the inversion. To find the best way to identify the baseline and to investigate whether the usage of observation-based approaches is suitable for inverse modeling of halocarbons, we use and analyze a model-based and two frequently used observation-based methods to determine the baseline and investigate their influence on inversion results. The model-based method couples global fields of mixing ratios with backwards-trajectories at their point of termination. We simulate those global fields with a Lagrangian particle dispersion model, FLEXPART_CTM, that uses a nudging routine to relax model data to observed values. The second method under investigation is the robust estimation of baseline signal (REBS) method, that is purely based on statistical analysis of observations. The third analyzed method is also primarily observation-based, but uses model information to subtract prior simulated mixing ratios from selected observations. We apply those three methods to sulfur hexafluoride (SF<sub>6</sub>) and use the Bayesian inversion framework FLEXINVERT for the inverse modeling and the Lagrangian particle dispersion model FLEXPART to calculate the source-receptor-relationship used in the inversion.</p>

scholarly journals Source-receptor matrix calculation with a Lagrangian particle dispersion model in backward mode

2004 ◽  
Vol 4 (1) ◽  
pp. 51-63 ◽  
Author(s):  
P. Seibert ◽  
A. Frank
Keyword(s):  
Wet Deposition ◽  
Short Distance ◽  
Dispersion Model ◽  
Radioactive Decay ◽  
Particle Dispersion ◽  
Lagrangian Particle ◽  
Linear Source ◽  
Dry And Wet Deposition ◽  
First Order ◽  
Matrix Calculation

Abstract. The possibility to calculate linear-source receptor relationships for the transport of atmospheric trace substances with a Lagrangian particle dispersion model (LPDM) running in backward mode is shown and presented with many tests and examples. This mode requires only minor modifications of the forward LPDM. The derivation includes the action of sources and of any first-order processes (transformation with prescribed rates, dry and wet deposition, radioactive decay, etc.). The backward mode is computationally advantageous if the number of receptors is less than the number of sources considered. The combination of an LPDM with the backward (adjoint) methodology is especially attractive for the application to point measurements, which can be handled without artificial numerical diffusion. Practical hints are provided for source-receptor calculations with different settings, both in forward and backward mode. The equivalence of forward and backward calculations is shown in simple tests for release and sampling of particles, pure wet deposition, pure convective redistribution and realistic transport over a short distance. Furthermore, an application example explaining measurements of Cs-137 in Stockholm as transport from areas contaminated heavily in the Chernobyl disaster is included.

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