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 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 Inversion of long-lived trace gas emissions using combined Eulerian and Lagrangian chemical transport models

2011 ◽  
Vol 11 (18) ◽  
pp. 9887-9898 ◽  
Author(s):  
M. Rigby ◽  
A. J. Manning ◽  
R. G. Prinn
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Transport Model ◽  
Initial Conditions ◽  
Dispersion Model ◽  
Chemical Transport ◽  
Particle Dispersion ◽  
Global Network ◽  
Lagrangian Model ◽  
Chemical Transport Model

Abstract. We present a method for estimating emissions of long-lived trace gases from a sparse global network of high-frequency observatories, using both a global Eulerian chemical transport model and Lagrangian particle dispersion model. Emissions are derived in a single step after determining sensitivities of the observations to initial conditions, the high-resolution emissions field close to observation points, and larger regions further from the measurements. This method has the several advantages over inversions using one type of model alone, in that: high-resolution simulations can be carried out in limited domains close to the measurement sites, with lower resolution being used further from them; the influence of errors due to aggregation of emissions close to the measurement sites can be minimized; assumptions about boundary conditions to the Lagrangian model do not need to be made, since the entire emissions field is estimated; any combination of appropriate models can be used, with no code modification. Because the sensitivity to the entire emissions field is derived, the estimation can be carried out using traditional statistical methods without the need for multiple steps in the inversion. We demonstrate the utility of this approach by determining global SF6 emissions using measurements from the Advanced Global Atmospheric Gases Experiment (AGAGE) between 2007 and 2009. The global total and large-scale patterns of the derived emissions agree well with previous studies, whilst allowing emissions to be determined at higher resolution than has previously been possible, and improving the agreement between the modeled and observed mole fractions at some sites.

scholarly journals A joint data assimilation system (Tan-Tracker) to simultaneously estimate surface CO<sub>2</sub> fluxes and 3-D atmospheric CO<sub>2</sub> concentrations from observations

2014 ◽  
Vol 14 (23) ◽  
pp. 13281-13293 ◽  
Author(s):  
X. Tian ◽  
Z. Xie ◽  
Y. Liu ◽  
Z. Cai ◽  
Y. Fu ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Transport Model ◽  
Surface Fluxes ◽  
Atmospheric Co2 ◽  
Simultaneous Estimation ◽  
Co2 Fluxes ◽  
Co2 Concentrations ◽  
Atmospheric Co2 Concentrations ◽  
Data Assimilation System ◽  
Assimilation System

Abstract. We have developed a novel framework ("Tan-Tracker") for assimilating observations of atmospheric CO2 concentrations, based on the POD-based (proper orthogonal decomposition) ensemble four-dimensional variational data assimilation method (PODEn4DVar). The high flexibility and the high computational efficiency of the PODEn4DVar approach allow us to include both the atmospheric CO2 concentrations and the surface CO2 fluxes as part of the large state vector to be simultaneously estimated from assimilation of atmospheric CO2 observations. Compared to most modern top-down flux inversion approaches, where only surface fluxes are considered as control variables, one major advantage of our joint data assimilation system is that, in principle, no assumption on perfect transport models is needed. In addition, the possibility for Tan-Tracker to use a complete dynamic model to consistently describe the time evolution of CO2 surface fluxes (CFs) and the atmospheric CO2 concentrations represents a better use of observation information for recycling the analyses at each assimilation step in order to improve the forecasts for the following assimilations. An experimental Tan-Tracker system has been built based on a complete augmented dynamical model, where (1) the surface atmosphere CO2 exchanges are prescribed by using a persistent forecasting model for the scaling factors of the first-guess net CO2 surface fluxes and (2) the atmospheric CO2 transport is simulated by using the GEOS-Chem three-dimensional global chemistry transport model. Observing system simulation experiments (OSSEs) for assimilating synthetic in situ observations of surface CO2 concentrations are carefully designed to evaluate the effectiveness of the Tan-Tracker system. In particular, detailed comparisons are made with its simplified version (referred to as TT-S) with only CFs taken as the prognostic variables. It is found that our Tan-Tracker system is capable of outperforming TT-S with higher assimilation precision for both CO2 concentrations and CO2 fluxes, mainly due to the simultaneous estimation of CO2 concentrations and CFs in our Tan-Tracker data assimilation system. A experiment for assimilating the real dry-air column CO2 retrievals (XCO2) from the Japanese Greenhouse Gases Observation Satellite (GOSAT) further demonstrates its potential wide applications.

scholarly journals Inversion of long-lived trace gas emissions using combined Eulerian and Lagrangian chemical transport models

2011 ◽  
Vol 11 (5) ◽  
pp. 14689-14717 ◽  
Author(s):  
M. Rigby ◽  
A. J. Manning ◽  
R. G. Prinn
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Transport Model ◽  
Initial Conditions ◽  
Dispersion Model ◽  
Chemical Transport ◽  
Particle Dispersion ◽  
Global Network ◽  
Lagrangian Model ◽  
Chemical Transport Model

Abstract. We present a method for estimating emissions of long-lived trace gases from a sparse global network of high-frequency observatories, using both a global Eulerian chemical transport model and Lagrangian particle dispersion model. Emissions are derived in a single step after determining sensitivities of the observations to initial conditions, the high-resolution emissions field close to observation points, and larger regions further from the measurements. This method has the several advantages over inversions using one type of model alone, in that: high-resolution simulations can be carried out in limited domains close to the measurement sites, with lower resolution being used further from them; the influence of errors due to aggregation of emissions close to the measurement sites can be minimized; assumptions about boundary conditions to the Lagrangian model do not need to be made, since the entire emissions field is estimated; any combination of appropriate models can be used, with no code modification. Because the sensitivity to the entire emissions field is derived, the estimation can be carried out using traditional statistical methods without the need for multiple steps in the inversion. We demonstrate the utility of this approach by determining global SF6 emissions using measurements from the Advanced Global Atmospheric Gases Experiment (AGAGE) between 2007 and 2009. The global total and large-scale patterns of the derived emissions agree well with previous studies, whilst allowing emissions to be determined at higher resolution than has previously been possible, and improving the agreement between the modeled and observed mole fractions at some sites.

Sources and Sinks of Atmospheric CO2

1992 ◽  
Vol 40 (5) ◽  
pp. 407 ◽  
Author(s):  
JA Taylor ◽  
J Lloyd
Keyword(s):  
Climate Change ◽  
Biomass Burning ◽  
Transport Model ◽  
Atmospheric Co2 ◽  
Tropical Rainforests ◽  
Co2 Uptake ◽  
Tracer Transport ◽  
Intergovernmental Panel ◽  
Co2 Concentrations ◽  
Atmospheric Co2 Concentrations

The biosphere plays an important role in determining the sources, sinks, levels and rates of change of atmospheric CO2 concentrations. Significant uncertainties remain in estimates of the fluxes of CO2 from biomass burning and deforestation, and uptake and storage of CO2 by the biosphere arising from increased atmospheric CO2 concentrations. Calculation of probable rates of carbon sequestration for the major ecosystem complexes and global 3-D tracer transport model runs indicate the possibility that a significant net CO2 uptake (> 1 Pg C yr-1), a CO2 'fertilisation effect', may be occurring in tropical rainforests, effectively accounting for much of the 'missing sink'. This sink may currently balance much of the CO2 added to the atmosphere from deforestation and biomass burning. Interestingly, CO2 released from biomass burning may itself be playing an important role in enhanced carbon storage by tropical rainforests. This has important implications for predicting future CO2 concentrations. If tropical rainforest destruction continues then much of the CO2 stored as a result of the CO2 'fertilisation effect' will be rereleased to the atmosphere and much of the 'missing sink' will disappear. These effects have not been considered in the IPCC (Intergovernmental Panel on Climate Change) projections of future atmospheric CO2 concentrations. Predictions which take account of the combined effects of deforestation, the return of carbon previously stored through the CO2 'fertilisation effect' and the loss of a large proportion of the 'missing sink' as a result of deforestation, would result in much higher predicted concentrations and rates of increase of atmospheric CO2 and, as a consequence, accelerated rates of climate change.

scholarly journals Los Angeles megacity: a high-resolution land–atmosphere modelling system for urban CO<sub>2</sub> emissions

2016 ◽  
Vol 16 (14) ◽  
pp. 9019-9045 ◽  
Author(s):  
Sha Feng ◽  
Thomas Lauvaux ◽  
Sally Newman ◽  
Preeti Rao ◽  
Ravan Ahmadov ◽  
...  
Keyword(s):  
High Resolution ◽  
Los Angeles ◽  
Co2 Emission ◽  
Fossil Fuel ◽  
Meteorological Data ◽  
Atmospheric Co2 ◽  
Co2 Concentrations ◽  
Emissions Modelling ◽  
Atmospheric Co2 Concentrations ◽  
Modelling System

Abstract. Megacities are major sources of anthropogenic fossil fuel CO2 (FFCO2) emissions. The spatial extents of these large urban systems cover areas of 10 000 km2 or more with complex topography and changing landscapes. We present a high-resolution land–atmosphere modelling system for urban CO2 emissions over the Los Angeles (LA) megacity area. The Weather Research and Forecasting (WRF)-Chem model was coupled to a very high-resolution FFCO2 emission product, Hestia-LA, to simulate atmospheric CO2 concentrations across the LA megacity at spatial resolutions as fine as  ∼  1 km. We evaluated multiple WRF configurations, selecting one that minimized errors in wind speed, wind direction, and boundary layer height as evaluated by its performance against meteorological data collected during the CalNex-LA campaign (May–June 2010). Our results show no significant difference between moderate-resolution (4 km) and high-resolution (1.3 km) simulations when evaluated against surface meteorological data, but the high-resolution configurations better resolved planetary boundary layer heights and vertical gradients in the horizontal mean winds. We coupled our WRF configuration with the Vulcan 2.2 (10 km resolution) and Hestia-LA (1.3 km resolution) fossil fuel CO2 emission products to evaluate the impact of the spatial resolution of the CO2 emission products and the meteorological transport model on the representation of spatiotemporal variability in simulated atmospheric CO2 concentrations. We find that high spatial resolution in the fossil fuel CO2 emissions is more important than in the atmospheric model to capture CO2 concentration variability across the LA megacity. Finally, we present a novel approach that employs simultaneous correlations of the simulated atmospheric CO2 fields to qualitatively evaluate the greenhouse gas measurement network over the LA megacity. Spatial correlations in the atmospheric CO2 fields reflect the coverage of individual measurement sites when a statistically significant number of sites observe emissions from a specific source or location. We conclude that elevated atmospheric CO2 concentrations over the LA megacity are composed of multiple fine-scale plumes rather than a single homogenous urban dome. Furthermore, we conclude that FFCO2 emissions monitoring in the LA megacity requires FFCO2 emissions modelling with  ∼  1 km resolution because coarser-resolution emissions modelling tends to overestimate the observational constraints on the emissions estimates.

scholarly journals Technical note: A high-resolution inverse modelling technique for estimating surface CO<sub>2</sub> fluxes based on the NIES-TM – FLEXPART coupled transport model and its adjoint

2020 ◽  
Author(s):  
Shamil Maksyutov ◽  
Tomohiro Oda ◽  
Makoto Saito ◽  
Rajesh Janardanan ◽  
Dmitry Belikov ◽  
...  
Keyword(s):  
High Resolution ◽  
Transport Model ◽  
Dispersion Model ◽  
Surface Flux ◽  
Particle Dispersion ◽  
Anthropogenic Emissions ◽  
Coupled Transport ◽  
Tracer Transport ◽  
Flux Corrections

Abstract. We developed a high-resolution surface flux inversion system based on the global Lagrangian–Eulerian coupled tracer transport model composed of National Institute for Environmental Studies Transport Model (NIES-TM) and FLEXible PARTicle dispersion model (FLEXPART). The inversion system is named NTFVAR (NIES-TM-FLEXPART-variational) as it applies variational optimisation to estimate surface fluxes. We tested the system by estimating optimized corrections to natural surface CO2 fluxes to achieve best fit to atmospheric CO2 data collected by the global in-situ network, as a necessary step towards capability of estimating anthropogenic CO2 emissions. We employ the Lagrangian particle dispersion model (LPDM) FLEXPART to calculate the surface flux footprints of CO2 observations at a 0.1° × 0.1° spatial resolution. The LPDM is coupled to a global atmospheric tracer transport model (NIES-TM). Our inversion technique uses an adjoint of the coupled transport model in an iterative optimization procedure. The flux error covariance operator is being implemented via implicit diffusion. Biweekly flux corrections to prior flux fields were estimated for the years 2010–2012 from in-situ CO2 data included in the Observation Package (ObsPack) dataset. High-resolution prior flux fields were prepared using Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC) for fossil fuel combustion, Global Fire Assimilation System (GFAS) for biomass burning, the Vegetation Integrative SImulator for Trace gases (VISIT) model for terrestrial biosphere exchange and Ocean Tracer Transport Model (OTTM) for oceanic exchange. The terrestrial biospheric flux field was constructed using a vegetation mosaic map and separate simulation of CO2 fluxes at daily time step by the VISIT model for each vegetation type. The prior flux uncertainty for terrestrial biosphere was scaled proportionally to the monthly mean Gross Primary Production (GPP) by the Moderate Resolution Imaging Spectroradiometer (MODIS) MOD17 product. The inverse system calculates flux corrections to the prior fluxes in the form of a relatively smooth field multiplied by high-resolution patterns of the prior flux uncertainties for land and ocean, following the coastlines and vegetation productivity gradients. The resulting flux estimates improve fit to the observations at continuous observations sites, reproducing both the seasonal variation and short-term concentration variability, including high CO2 concentration events associated with anthropogenic emissions. The use of high-resolution atmospheric transport in global CO2 flux inversion has the advantage of better resolving the transport from the mix of the anthropogenic and biospheric sources in densely populated continental regions and shows potential for better separation between fluxes from terrestrial ecosystems and strong localised sources such as anthropogenic emissions and forest fires. Further improvements in the modelling system are needed as the posterior fit is better than that by the National Oceanic and Atmospheric Administration (NOAA) CarbonTracker only for a fraction of the monitoring sites, mostly at coastal and island locations experiencing mix of background and local flux signals.

scholarly journals European source and sink areas of CO<sub>2</sub> retrieved from Lagrangian transport model interpretation of combined O<sub>2</sub> and CO<sub>2</sub> measurements at the high alpine research station Jungfraujoch

2011 ◽  
Vol 11 (15) ◽  
pp. 8017-8036 ◽  
Author(s):  
C. Uglietti ◽  
M. Leuenberger ◽  
D. Brunner
Keyword(s):  
Transport Model ◽  
Dispersion Model ◽  
Seasonal Pattern ◽  
Particle Dispersion ◽  
Research Station ◽  
Co2 Uptake ◽  
Air Masses ◽  
Background Values ◽  
Co2 Concentrations ◽  
Source And Sink

Abstract. The University of Bern monitors carbon dioxide (CO2) and oxygen (O2) at the High Altitude Research Station Jungfraujoch since the year 2000 by means of flasks sampling and since 2005 using a continuous in situ measurement system. This study investigates the transport of CO2 and O2 towards Jungfraujoch using backward Lagrangian Particle Dispersion Model (LPDM) simulations and utilizes CO2 and O2 signatures to classify air masses. By investigating the simulated transport patterns associated with distinct CO2 concentrations it is possible to decipher different source and sink areas over Europe. The highest CO2 concentrations, for example, were observed in winter during pollution episodes when air was transported from Northeastern Europe towards the Alps, or during south Foehn events with rapid uplift of polluted air from Northern Italy, as demonstrated in two case studies. To study the importance of air-sea exchange for variations in O2 concentrations at Jungfraujoch the correlation between CO2 and APO (Atmospheric Potential Oxygen) deviations from a seasonally varying background was analyzed. Anomalously high APO concentrations were clearly associated with air masses originating from the Atlantic Ocean, whereas low APO concentrations were found in air masses advected either from the east from the Eurasian continent in summer, or from the Eastern Mediterranean in winter. Those air masses with low APO in summer were also strongly depleted in CO2 suggesting a combination of CO2 uptake by vegetation and O2 uptake by dry summer soils. Other subsets of points in the APO-CO2 scatter plot investigated with respect to air mass origin included CO2 and APO background values and points with regular APO but anomalous CO2 concentrations. Background values were associated with free tropospheric air masses with little contact with the boundary layer during the last few days, while high or low CO2 concentrations reflect the various levels of influence of anthropogenic emissions and the biosphere. The pronounced cycles of CO2 and O2 exchanges with the biosphere and the ocean cause clusters of points and lead to a seasonal pattern.

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.

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