scholarly journals Adjoint of the global Eulerian–Lagrangian coupled atmospheric transport model (A-GELCA v1.0): development and validation

2016 ◽  
Vol 9 (2) ◽  
pp. 749-764 ◽  
Author(s):  
Dmitry A. Belikov ◽  
Shamil Maksyutov ◽  
Alexey Yaremchuk ◽  
Alexander Ganshin ◽  
Thomas Kaminski ◽  
...  
Keyword(s):  
Message Passing ◽  
Message Passing Interface ◽  
Automatic Differentiation ◽  
Transport Model ◽  
Dispersion Model ◽  
Three Dimensional ◽  
Coupled Model ◽  
Particle Dispersion ◽  
Surface Fluxes ◽  
Eulerian Model

Abstract. We present the development of the Adjoint of the Global Eulerian–Lagrangian Coupled Atmospheric (A-GELCA) model that consists of the National Institute for Environmental Studies (NIES) model as an Eulerian three-dimensional transport model (TM), and FLEXPART (FLEXible PARTicle dispersion model) as the Lagrangian Particle Dispersion Model (LPDM). The forward tangent linear and adjoint components of the Eulerian model were constructed directly from the original NIES TM code using an automatic differentiation tool known as TAF (Transformation of Algorithms in Fortran; http://www.FastOpt.com), with additional manual pre- and post-processing aimed at improving transparency and clarity of the code and optimizing the performance of the computing, including MPI (Message Passing Interface). The Lagrangian component did not require any code modification, as LPDMs are self-adjoint and track a significant number of particles backward in time in order to calculate the sensitivity of the observations to the neighboring emission areas. The constructed Eulerian adjoint was coupled with the Lagrangian component at a time boundary in the global domain. The simulations presented in this work were performed using the A-GELCA model in forward and adjoint modes. The forward simulation shows that the coupled model improves reproduction of the seasonal cycle and short-term variability of CO2. Mean bias and standard deviation for five of the six Siberian sites considered decrease roughly by 1 ppm when using the coupled model. The adjoint of the Eulerian model was shown, through several numerical tests, to be very accurate (within machine epsilon with mismatch around to ±6 e−14) compared to direct forward sensitivity calculations. The developed adjoint of the coupled model combines the flux conservation and stability of an Eulerian discrete adjoint formulation with the flexibility, accuracy, and high resolution of a Lagrangian backward trajectory formulation. A-GELCA will be incorporated into a variational inversion system designed to optimize surface fluxes of greenhouse gases.

scholarly journals Adjoint of the Global Eulerian–Lagrangian Coupled Atmospheric transport model (A-GELCA v1.0): development and validation

2015 ◽  
Vol 8 (7) ◽  
pp. 5983-6019
Author(s):  
D. A. Belikov ◽  
S. Maksyutov ◽  
A. Yaremchuk ◽  
A. Ganshin ◽  
T. Kaminski ◽  
...  
Keyword(s):  
Message Passing ◽  
Message Passing Interface ◽  
Automatic Differentiation ◽  
Transport Model ◽  
Dispersion Model ◽  
Three Dimensional ◽  
Coupled Model ◽  
Particle Dispersion ◽  
Limiting Factors ◽  
Eulerian Model

Abstract. We present the development of the Adjoint of the Global Eulerian–Lagrangian Coupled Atmospheric (A-GELCA) model that consists of the National Institute for Environmental Studies (NIES) model as an Eulerian three-dimensional transport model (TM), and FLEXPART (FLEXible PARTicle dispersion model) as the Lagrangian plume diffusion model (LPDM). The tangent and adjoint components of the Eulerian model were constructed directly from the original NIES TM code using an automatic differentiation tool known as TAF (Transformation of Algorithms in Fortran; http://www.FastOpt.com), with additional manual pre- and post-processing aimed at improving the performance of the computing, including MPI (Message Passing Interface). As results, the adjoint of Eulerian model is discrete. Construction of the adjoint of the Lagrangian component did not require any code modification, as LPDMs are able to track a significant number of particles back in time and thereby calculate the sensitivity of observations to the neighboring emissions areas. Eulerian and Lagrangian adjoint components were coupled at the time boundary in the global domain.The results are verified using a series of test experiments. The forward simulation shown the coupled model is effective in reproducing the seasonal cycle and short-term variability of CO2 even in the case of multiple limiting factors, such as high uncertainty of fluxes and the low resolution of the Eulerian model. The adjoint model demonstrates the high accuracy compared to direct forward sensitivity calculations and fast performance. The developed adjoint of the coupled model combines the flux conservation and stability of an Eulerian discrete adjoint formulation with the flexibility, accuracy, and high resolution of a Lagrangian backward trajectory formulation.

scholarly journals Simulation of variability in atmospheric carbon dioxide using a global coupled Eulerian – Lagrangian transport model

2011 ◽  
Vol 4 (2) ◽  
pp. 317-324 ◽  
Author(s):  
Y. Koyama ◽  
S. Maksyutov ◽  
H. Mukai ◽  
K. Thoning ◽  
P. Tans
Keyword(s):  
Atmospheric Chemistry ◽  
Transport Model ◽  
Dispersion Model ◽  
Regional Scale ◽  
Coupled Model ◽  
Particle Dispersion ◽  
Atmospheric Composition ◽  
Tracer Transport ◽  
Eulerian Model ◽  
Co2 Concentrations

Abstract. This study assesses the advantages of using a coupled atmospheric-tracer transport model, comprising a global Eulerian model and a global Lagrangian particle dispersion model, to improve the reproducibility of tracer-gas variations affected by the near-field surface emissions and transport around observation sites. The ability to resolve variability in atmospheric composition on an hourly time-scale and a spatial scale of several kilometers would be beneficial for analyzing data from continuous ground-based monitoring and from upcoming space-based observations. The coupled model yields an increase in the horizontal resolution of transport and fluxes, and has been tested in regional-scale studies of atmospheric chemistry. By applying the Lagrangian component to the global domain, we extend this approach to the global scale, thereby enabling computationally efficient global inverse modeling and data assimilation. To validate the coupled model, we compare model-simulated CO2 concentrations with continuous observations at three sites: two operated by the National Oceanic and Atmospheric Administration, USA, and one operated by the National Institute for Environmental Studies, Japan. As the goal of this study is limited to introducing the new modeling approach, we selected a transport simulation at these three sites to demonstrate how the model may perform at various geographical areas. The coupled model provides improved agreement between modeled and observed CO2 concentrations in comparison to the Eulerian model. In an area where variability in CO2 concentration is dominated by a fossil fuel signal, the correlation coefficient between modeled and observed concentrations increases by between 0.05 to 0.1 from the original values of 0.5–0.6 achieved with the Eulerian model.

scholarly journals Pollutant transport in coastal areas with and without background wind

1997 ◽  
Vol 15 (4) ◽  
pp. 476-486 ◽  
Author(s):  
J. Camps ◽  
J. Massons ◽  
M. R. Soler ◽  
E. C. Nickerson
Keyword(s):  
Large Scale ◽  
Dispersion Model ◽  
Three Dimensional ◽  
Coastal Region ◽  
Coupled Model ◽  
Pollutant Dispersion ◽  
Particle Dispersion ◽  
Background Wind ◽  
Meteorological Model ◽  
Pollutant Concentrations

Abstract. A three-dimensional meteorological model and a Lagrangian particle dispersion model are used to study the effects of a uniform large-scale wind on the dispersion of a non-reactive pollutant in a coastal region with complex terrain. Simulations are carried out both with and without a background wind. A comparison between model results and measured data (wind and pollutant concentrations) indicates that the coupled model system provides a useful mechanism for analyzing pollutant dispersion in coastal regions.

scholarly journals Study of the footprints of short-term variation in XCO<sub>2</sub> observed by TCCON sites using NIES and FLEXPART atmospheric transport models

2016 ◽  
Author(s):  
D. A. Belikov ◽  
S. Maksyutov ◽  
A. Ganshin ◽  
R. Zhuravlev ◽  
N. M. Deutscher ◽  
...  
Keyword(s):  
Near Infrared ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Dispersion Model ◽  
Three Dimensional ◽  
Temporal Variations ◽  
Particle Dispersion ◽  
Bias Reduction ◽  
Total Carbon ◽  
Short Term

Abstract. The Total Carbon Column Observing Network (TCCON) is a network of ground-based Fourier Transform Spectrometers (FTS) that record near-infrared (NIR) spectra of the Sun. From these spectra, accurate and precise observations of CO2 column-averaged dry-air mole fraction (denoted XCO2) are retrieved. TCCON FTS observations have previously been used to validate satellite estimations of XCO2; however, our knowledge of the short-term spatial and temporal variations in XCO2 surrounding the TCCON sites is limited. In this work, we use the National Institute for Environmental Studies (NIES) Eulerian three-dimensional transport model and the FLEXPART (FLEXible PARTicle) Lagrangian Particle Dispersion Model (LPDM) to determine the footprints of short-term variations in XCO2 observed by operational, past, future, and possible TCCON sites. We propose a footprint-based method for the colocation of satellite and TCCON XCO2 observations, and estimate the performance of the method using the NIES model and five GOSAT XCO2 product datasets. Comparison of the proposed approach with a standard geographic method shows higher number of colocation points and average bias reduction up to 0.15 ppm for a subset of 16 stations for the period from January 2010 to January 2014. Case studies of the Darwin and La Réunion sites reveal that when the footprint area is rather curved, non-uniform and significantly different from a geographical rectangular area, the differences between these approaches are more noticeable. This emphasizes that the colocation is sensitive to local meteorological conditions and flux distributions.

scholarly journals A global coupled Eulerian-Lagrangian model and 1 × 1 km CO<sub>2</sub> surface flux dataset for high-resolution atmospheric CO<sub>2</sub> transport simulations

2011 ◽  
Vol 4 (3) ◽  
pp. 2047-2080 ◽  
Author(s):  
A. Ganshin ◽  
T. Oda ◽  
M. Saito ◽  
S. Maksyutov ◽  
V. Valsala ◽  
...  
Keyword(s):  
High Resolution ◽  
High Frequency ◽  
Transport Model ◽  
Dispersion Model ◽  
Particle Dispersion ◽  
Surface Fluxes ◽  
Atmospheric Co2 ◽  
Lagrangian Model ◽  
Co2 Concentrations ◽  
Atmospheric Co2 Concentrations

Abstract. We designed a method to simulate atmospheric CO2 concentrations at several continuous observation sites around the globe using surface fluxes at a very high spatial resolution. The simulations presented in this study were performed using a Lagrangian particle dispersion model coupled to a global atmospheric tracer transport model with prescribed global surface CO2 flux maps at a 1 × 1 km resolution. The surface fluxes used in the simulations were prepared by assembling the individual components of terrestrial, oceanic and fossil fuel CO2 fluxes. This experimental setup (i.e., a transport model running at a medium resolution, coupled to a high-resolution Lagrangian particle dispersion model together with global surface fluxes at a very high resolution), which was designed to represent high-frequency variations in atmospheric CO2 concentration, has not been reported at a global scale previously. Two sensitivity experiments were performed: (a) using the global transport model without coupling to the Lagrangian dispersion model, and (b) using the coupled model with a reduced resolution of surface fluxes, in order to evaluate the performance of Eulerian-Lagrangian coupling and the role of high-resolution fluxes in simulating high-frequency variations in atmospheric CO2 concentrations. A correlation analysis between observed and simulated atmospheric CO2 concentrations at selected locations revealed that the inclusion of both Eulerian-Lagrangian coupling and high-resolution fluxes improves the high-frequency simulations of the model. The results highlight the potential of a coupled Eulerian-Lagrangian model in simulating high-frequency atmospheric CO2 concentrations at many locations worldwide. The model performs well in representing observations of atmospheric CO2 concentrations at high spatial and temporal resolutions, especially for coastal sites and sites located close to sources of large anthropogenic emissions. While this study focused on simulations of CO2 concentrations, the model could be used for other atmospheric compounds with known estimated emissions.

scholarly journals Simulation of atmospheric carbon dioxide variability with a global coupled Eulerian-Lagrangian transport model

2010 ◽  
Vol 3 (4) ◽  
pp. 2051-2070
Author(s):  
Y. Koyama ◽  
S. Maksyutov ◽  
H. Mukai ◽  
K. Thoning ◽  
P. Tans
Keyword(s):  
Atmospheric Chemistry ◽  
Transport Model ◽  
Regional Scale ◽  
Coupled Model ◽  
Particle Dispersion ◽  
Atmospheric Composition ◽  
Small Subset ◽  
Tracer Transport ◽  
Eulerian Model ◽  
Co2 Concentrations

Abstract. This study assesses the advantages of using a coupled atmospheric-tracer transport model, comprising a global Eulerian model and a global Lagrangian particle dispersion model, for reproducibility of tracer gas variation affected by near field around observation sites. The ability to resolve variability in atmospheric composition on an hourly time scale and a spatial scale of several kilometers would be beneficial for analyzing data from continuous ground-based monitoring and upcoming space-based observations. The coupled model yields increased horizontal resolution of transport and fluxes, and has been tested in regional-scale studies of atmospheric chemistry. By applying the Lagrangian component to the global domain, we extend this approach to the global scale, thereby enabling global inverse modeling and data assimilation. To validate the coupled model, we compare model-simulated CO2 concentrations with continuous observations at two sites operated by the National Oceanic and Atmospheric Administration, USA and one site operated by National Institute for Environmental Studies, Japan. As the purpose of this study is limited to demonstration of the new modeling approach, we select a small subset of 3 sites to highlight use of the model in various geographical areas. To explore the capability of the coupled model in simulating synoptic-scale meteorological phenomena, we calculate the correlation coefficients and variance ratios between deseasonalized model-simulated and observed CO2 concentrations. Compared with the Eulerian model alone, the coupled model yields improved agreement between modeled and observed CO2 concentrations.

scholarly journals Study of the footprints of short-term variation in XCO<sub>2</sub> observed by TCCON sites using NIES and FLEXPART atmospheric transport models

2017 ◽  
Vol 17 (1) ◽  
pp. 143-157 ◽  
Author(s):  
Dmitry A. Belikov ◽  
Shamil Maksyutov ◽  
Alexander Ganshin ◽  
Ruslan Zhuravlev ◽  
Nicholas M. Deutscher ◽  
...  
Keyword(s):  
Near Infrared ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Dispersion Model ◽  
Three Dimensional ◽  
Temporal Variations ◽  
Particle Dispersion ◽  
Bias Reduction ◽  
Total Carbon ◽  
Short Term

Abstract. The Total Carbon Column Observing Network (TCCON) is a network of ground-based Fourier transform spectrometers (FTSs) that record near-infrared (NIR) spectra of the sun. From these spectra, accurate and precise observations of CO2 column-averaged dry-air mole fractions (denoted XCO2) are retrieved. TCCON FTS observations have previously been used to validate satellite estimations of XCO2; however, our knowledge of the short-term spatial and temporal variations in XCO2 surrounding the TCCON sites is limited. In this work, we use the National Institute for Environmental Studies (NIES) Eulerian three-dimensional transport model and the FLEXPART (FLEXible PARTicle dispersion model) Lagrangian particle dispersion model (LPDM) to determine the footprints of short-term variations in XCO2 observed by operational, past, future and possible TCCON sites. We propose a footprint-based method for the collocation of satellite and TCCON XCO2 observations and estimate the performance of the method using the NIES model and five GOSAT (Greenhouse Gases Observing Satellite) XCO2 product data sets. Comparison of the proposed approach with a standard geographic method shows a higher number of collocation points and an average bias reduction up to 0.15 ppm for a subset of 16 stations for the period from January 2010 to January 2014. Case studies of the Darwin and Reunion Island sites reveal that when the footprint area is rather curved, non-uniform and significantly different from a geographical rectangular area, the differences between these approaches are more noticeable. This emphasises that the collocation is sensitive to local meteorological conditions and flux distributions.

scholarly journals Mesoscale circulations over complex terrain in the Valencia coastal region, Spain – Part 2: Modeling CO<sub>2</sub> transport using idealized surface fluxes

2007 ◽  
Vol 7 (7) ◽  
pp. 1851-1868 ◽  
Author(s):  
G. Pérez-Landa ◽  
P. Ciais ◽  
G. Gangoiti ◽  
J. L. Palau ◽  
A. Carrara ◽  
...  
Keyword(s):  
Complex Terrain ◽  
Transport Model ◽  
Mesoscale Model ◽  
Atmospheric Transport ◽  
Dispersion Model ◽  
Coastal Region ◽  
Net Ecosystem Exchange ◽  
Co2 Concentration ◽  
Particle Dispersion ◽  
Surface Fluxes

Abstract. Vertical profiles of CO2 concentration were collected during an intensive summer campaign in a coastal complex-terrain region within the frame of the European Project RECAB (Regional Assessment and Modelling of the Carbon Balance in Europe). The region presents marked diurnal mesoscale circulation patterns. These circulations result in a specific coupling between atmospherically transported CO2 and its surface fluxes. To understand the effects of this interaction on the spatial variability of the observed CO2 concentrations, we applied a high-resolution transport simulation to an idealized model of land biotic fluxes. The regional Net Ecosystem Exchange fluxes were extrapolated for different land-use classes by using a set of eddy-covariance measurements. The atmospheric transport model is a Lagrangian particle dispersion model, driven by a simulation of the RAMS mesoscale model. Our simulations were able to successfully reproduce some of the processes controlling the mesoscale transport of CO2. A semi-quantitative comparison between simulations and data allowed us to characterize how the coupling between mesoscale transport and surface fluxes produced CO2 spatial gradients in the domain. Temporal averages in the simulated CO2 field show a covariance between flux and transport consisting of: 1) horizontally, a CO2 deficit over land, mirrored by a CO2 excess over the sea and 2) vertically, the prevalence of a mean CO2 depletion between 500 and 2000 m, and a permanent build-up of CO2 in the lower levels.

scholarly journals A global coupled Eulerian-Lagrangian model and 1 × 1 km CO<sub>2</sub> surface flux dataset for high-resolution atmospheric CO<sub>2</sub> transport simulations

2012 ◽  
Vol 5 (1) ◽  
pp. 231-243 ◽  
Author(s):  
A. Ganshin ◽  
T. Oda ◽  
M. Saito ◽  
S. Maksyutov ◽  
V. Valsala ◽  
...  
Keyword(s):  
High Resolution ◽  
High Frequency ◽  
Transport Model ◽  
Dispersion Model ◽  
Particle Dispersion ◽  
Surface Fluxes ◽  
Atmospheric Co2 ◽  
Lagrangian Model ◽  
Co2 Concentrations ◽  
Atmospheric Co2 Concentrations

Abstract. We designed a method to simulate atmospheric CO2 concentrations at several continuous observation sites around the globe using surface fluxes at a very high spatial resolution. The simulations presented in this study were performed using the Global Eulerian-Lagrangian Coupled Atmospheric model (GELCA), comprising a Lagrangian particle dispersion model coupled to a global atmospheric tracer transport model with prescribed global surface CO2 flux maps at a 1 × 1 km resolution. The surface fluxes used in the simulations were prepared by assembling the individual components of terrestrial, oceanic and fossil fuel CO2 fluxes. This experimental setup (i.e. a transport model running at a medium resolution, coupled to a high-resolution Lagrangian particle dispersion model together with global surface fluxes at a very high resolution), which was designed to represent high-frequency variations in atmospheric CO2 concentration, has not been reported at a global scale previously. Two sensitivity experiments were performed: (a) using the global transport model without coupling to the Lagrangian dispersion model, and (b) using the coupled model with a reduced resolution of surface fluxes, in order to evaluate the performance of Eulerian-Lagrangian coupling and the role of high-resolution fluxes in simulating high-frequency variations in atmospheric CO2 concentrations. A correlation analysis between observed and simulated atmospheric CO2 concentrations at selected locations revealed that the inclusion of both Eulerian-Lagrangian coupling and high-resolution fluxes improves the high-frequency simulations of the model. The results highlight the potential of a coupled Eulerian-Lagrangian model in simulating high-frequency atmospheric CO2 concentrations at many locations worldwide. The model performs well in representing observations of atmospheric CO2 concentrations at high spatial and temporal resolutions, especially for coastal sites and sites located close to sources of large anthropogenic emissions. While this study focused on simulations of CO2 concentrations, the model could be used for other atmospheric compounds with known estimated emissions.

scholarly journals Greenhouse gas network design using backward Lagrangian particle dispersion modelling − Part 1: Methodology and Australian test case

2014 ◽  
Vol 14 (17) ◽  
pp. 9363-9378 ◽  
Author(s):  
T. Ziehn ◽  
A. Nickless ◽  
P. J. Rayner ◽  
R. M. Law ◽  
G. Roff ◽  
...  
Keyword(s):  
Network Design ◽  
Fossil Fuel ◽  
Dispersion Model ◽  
Surface Flux ◽  
Particle Dispersion ◽  
Surface Fluxes ◽  
Test Case ◽  
Lagrangian Particle ◽  
Gas Network ◽  
Australian Continent

Abstract. This paper describes the generation of optimal atmospheric measurement networks for determining carbon dioxide fluxes over Australia using inverse methods. A Lagrangian particle dispersion model is used in reverse mode together with a Bayesian inverse modelling framework to calculate the relationship between weekly surface fluxes, comprising contributions from the biosphere and fossil fuel combustion, and hourly concentration observations for the Australian continent. Meteorological driving fields are provided by the regional version of the Australian Community Climate and Earth System Simulator (ACCESS) at 12 km resolution at an hourly timescale. Prior uncertainties are derived on a weekly timescale for biosphere fluxes and fossil fuel emissions from high-resolution model runs using the Community Atmosphere Biosphere Land Exchange (CABLE) model and the Fossil Fuel Data Assimilation System (FFDAS) respectively. The influence from outside the modelled domain is investigated, but proves to be negligible for the network design. Existing ground-based measurement stations in Australia are assessed in terms of their ability to constrain local flux estimates from the land. We find that the six stations that are currently operational are already able to reduce the uncertainties on surface flux estimates by about 30%. A candidate list of 59 stations is generated based on logistic constraints and an incremental optimisation scheme is used to extend the network of existing stations. In order to achieve an uncertainty reduction of about 50%, we need to double the number of measurement stations in Australia. Assuming equal data uncertainties for all sites, new stations would be mainly located in the northern and eastern part of the continent.

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