scholarly journals Towards robust regional estimates of CO2 sources and sinks using atmospheric transport models

Nature ◽  
2002 ◽  
Vol 415 (6872) ◽  
pp. 626-630 ◽  
Author(s):  
Kevin Robert Gurney ◽  
Rachel M. Law ◽  
A. Scott Denning ◽  
Peter J. Rayner ◽  
David Baker ◽  
...  
Keyword(s):  
Atmospheric Transport ◽  
Transport Models ◽  
Sources And Sinks ◽  
Regional Estimates

scholarly journals Comparing atmospheric transport models for future regional inversions over Europe – Part 1: mapping the atmospheric CO<sub>2</sub> signals

2007 ◽  
Vol 7 (13) ◽  
pp. 3461-3479 ◽  
Author(s):  
C. Geels ◽  
M. Gloor ◽  
P. Ciais ◽  
P. Bousquet ◽  
P. Peylin ◽  
...  
Keyword(s):  
High Resolution ◽  
High Altitude ◽  
Large Scale ◽  
Fossil Fuel ◽  
Atmospheric Transport ◽  
Inverse Methods ◽  
Spatiotemporal Variability ◽  
Transport Models ◽  
Sources And Sinks ◽  
Low Altitude

Abstract. The CO2 source and sink distribution across Europe can be estimated in principle through inverse methods by combining CO2 observations and atmospheric transport models. Uncertainties of such estimates are mainly due to insufficient spatiotemporal coverage of CO2 observations and biases of the models. In order to assess the biases related to the use of different models the CO2 concentration field over Europe has been simulated with five different Eulerian atmospheric transport models as part of the EU-funded AEROCARB project, which has the main goal to estimate the carbon balance of Europe. In contrast to previous comparisons, here both global coarse-resolution and regional higher-resolution models are included. Continuous CO2 observations from continental, coastal and mountain sites as well as flasks sampled on aircrafts are used to evaluate the models' ability to capture the spatiotemporal variability and distribution of lower troposphere CO2 across Europe. 14CO2 is used in addition to evaluate separately fossil fuel signal predictions. The simulated concentrations show a large range of variation, with up to ~10 ppm higher surface concentrations over Western and Central Europe in the regional models with highest (mesoscale) spatial resolution. The simulation – data comparison reveals that generally high-resolution models are more successful than coarse models in capturing the amplitude and phasing of the observed short-term variability. At high-altitude stations the magnitude of the differences between observations and models and in between models is less pronounced, but the timing of the diurnal cycle is not well captured by the models. The data comparisons show also that the timing of the observed variability on hourly to daily time scales at low-altitude stations is generally well captured by all models. However, the amplitude of the variability tends to be underestimated. While daytime values are quite well predicted, nighttime values are generally underpredicted. This is a reflection of the different mixing regimes during day and night combined with different vertical resolution between models. In line with this finding, the agreement among models is increased when sampling in the afternoon hours only and when sampling the mixed portion of the PBL, which amounts to sampling at a few hundred meters above ground. The main recommendations resulting from the study for constraining land carbon sources and sinks using high-resolution concentration data and state-of-the art transport models through inverse methods are given in the following: 1) Low altitude stations are presently preferable in inverse studies. If high altitude stations are used then the model level that represents the specific sites should be applied, 2) at low altitude sites only the afternoon values of concentrations can be represented sufficiently well by current models and therefore afternoon values are more appropriate for constraining large-scale sources and sinks in combination with transport models, 3) even when using only afternoon values it is clear that data sampled several hundred meters above ground can be represented substantially more robustly in models than surface station records, which emphasize the use of tower data in inverse studies and finally 4) traditional large scale transport models seem not sufficient to resolve fine-scale features associated with fossil fuel emissions, as well as larger-scale features like the concentration distribution above the south-western Europe. It is therefore recommended to use higher resolution models for interpretation of continental data in future studies.

scholarly journals The importance of transport model uncertainties for the estimation of CO<sub>2</sub> sources and sinks using satellite measurements

2010 ◽  
Vol 10 (20) ◽  
pp. 9981-9992 ◽  
Author(s):  
S. Houweling ◽  
I. Aben ◽  
F.-M. Breon ◽  
F. Chevallier ◽  
N. Deutscher ◽  
...  
Keyword(s):  
Transport Model ◽  
Atmospheric Transport ◽  
A Priori ◽  
Model Errors ◽  
Tracer Transport ◽  
Satellite Measurements ◽  
Transport Models ◽  
Sources And Sinks ◽  
The Impact ◽  
Ppm Level

Abstract. This study presents a synthetic model intercomparison to investigate the importance of transport model errors for estimating the sources and sinks of CO2 using satellite measurements. The experiments were designed for testing the potential performance of the proposed CO2 lidar A-SCOPE, but also apply to other space borne missions that monitor total column CO2. The participating transport models IFS, LMDZ, TM3, and TM5 were run in forward and inverse mode using common a priori CO2 fluxes and initial concentrations. Forward simulations of column averaged CO2 (xCO2) mixing ratios vary between the models by σ=0.5 ppm over the continents and σ=0.27 ppm over the oceans. Despite the fact that the models agree on average on the sub-ppm level, these modest differences nevertheless lead to significant discrepancies in the inverted fluxes of 0.1 PgC/yr per 106 km2 over land and 0.03 PgC/yr per 106 km2 over the ocean. These transport model induced flux uncertainties exceed the target requirement that was formulated for the A-SCOPE mission of 0.02 PgC/yr per 106 km2, and could also limit the overall performance of other CO2 missions such as GOSAT. A variable, but overall encouraging agreement is found in comparison with FTS measurements at Park Falls, Darwin, Spitsbergen, and Bremen, although systematic differences are found exceeding the 0.5 ppm level. Because of this, our estimate of the impact of transport model uncerainty is likely to be conservative. It is concluded that to make use of the remote sensing technique for quantifying the sources and sinks of CO2 not only requires highly accurate satellite instruments, but also puts stringent requirements on the performance of atmospheric transport models. Improving the accuracy of these models should receive high priority, which calls for a closer collaboration between experts in atmospheric dynamics and tracer transport.

scholarly journals Comparing atmospheric transport models for future regional inversions over Europe. Part 1: Mapping the CO<sub>2</sub> atmospheric signals

2006 ◽  
Vol 6 (3) ◽  
pp. 3709-3756 ◽  
Author(s):  
C. Geels ◽  
M. Gloor ◽  
P. Ciais ◽  
P. Bousquet ◽  
P. Peylin ◽  
...  
Keyword(s):  
High Resolution ◽  
High Altitude ◽  
Large Scale ◽  
State Of The Art ◽  
Atmospheric Transport ◽  
Spatiotemporal Variability ◽  
Concentration Data ◽  
Transport Models ◽  
Sources And Sinks ◽  
Low Altitude

Abstract. The CO2 source and sink distribution across Europe can be estimated in principle through inverse methods by combining CO2 observations and atmospheric transport models. Uncertainties of such estimates are mainly due to insufficient spatiotemporal coverage of CO2 observations and biases of the models. In order to assess the biases related to the use of different models the CO2 concentration field over Europe has been simulated with five different Eulerian atmospheric transport models as part of the EU-funded AEROCARB project, which has the main goal to estimate the carbon balance of Europe. In contrast to previous comparisons, here both global coarse-resolution and regional higher-resolution models are included. Continuous CO2 observations from continental, coastal and mountain in-situ atmospheric stations as well as flask samples sampled on aircrafts are used to evaluate the models' ability to capture the spatiotemporal variability and distribution of lower troposphere CO2 across Europe. 14CO2 is used in addition to evaluate separately fossil fuel signal predictions. The simulated concentrations show a large range of variation, with up to ~10 ppm higher surface concentrations over Western and Central Europe in the regional models with highest (mesoscale) spatial resolution. The simulation – data comparison reveals that generally high-resolution models are more successful than coarse models in capturing the amplitude and phasing of the observed short-term variability. At high-altitude stations the magnitude of the differences between observations and models and in between models is less pronounced, but the timing of the diurnal cycle is not well captured by the models. The data comparisons show also that the timing of the observed variability on hourly to daily time scales at low-altitude stations is generally well captured by all models. However, the amplitude of the variability tends to be underestimated. While daytime values are quite well predicted, nighttime values are generally underpredicted. This is a reflection of the different mixing regimes during day and night combined with different vertical resolution between models. In line with this finding, the agreement among models is increased when sampling in the afternoon hours only and when sampling the mixed portion of the PBL, which amounts to sampling at a few hundred meters above ground. Main recommendations resulting from the study for constraining land carbon sources and sinks using high-resolution concentration data and state-of-the art transport models are therefore: 1) low altitude stations are preferable over high altitude stations as these locations are difficult to represent in state-of-the art models, 2) at low altitude stations only afternoon values can be represented sufficiently well to be used to constrain large-scale sources and sinks in combination with transport models, 3) even when using only afternoon values it is clear that data sampled several hundred meters above ground can be represented substantially more robust in models than surface station records, and finally 4) traditional large scale transport models seem not sufficient to resolve CO2 distributions over regions of the size of for example Spain and thus seem too coarse for interpretation of continental data.

scholarly journals Influence of two atmospheric transport models on inf erring sources and sinks of atmospheric CO2

Tellus B ◽  
1996 ◽  
Vol 48 (4) ◽  
pp. 568-582 ◽  
Author(s):  
P. Bousquet ◽  
P. Ciais ◽  
P. Monfray ◽  
Y. Balkanski ◽  
M. Ramonet ◽  
...  
Keyword(s):  
Atmospheric Transport ◽  
Atmospheric Co2 ◽  
Transport Models ◽  
Sources And Sinks

scholarly journals Influence of two atmospheric transport models on inferring sources and sinks of atmospheric CO2

Tellus B ◽  
1996 ◽  
Vol 48 (4) ◽  
pp. 568-582 ◽  
Author(s):  
P. BOUSQUET ◽  
P. CIAIS ◽  
P. MONFRAY ◽  
Y. BALKANSK1 ◽  
M. RAMONET ◽  
...  
Keyword(s):  
Atmospheric Transport ◽  
Atmospheric Co2 ◽  
Transport Models ◽  
Sources And Sinks

scholarly journals The importance of transport model uncertainties for the estimation of CO<sub>2</sub> sources and sinks using satellite measurements

2010 ◽  
Vol 10 (6) ◽  
pp. 14737-14769 ◽  
Author(s):  
S. Houweling ◽  
I. Aben ◽  
F.-M. Breon ◽  
F. Chevallier ◽  
N. Deutscher ◽  
...  
Keyword(s):  
Transport Model ◽  
Atmospheric Transport ◽  
Model Errors ◽  
Satellite Measurements ◽  
Transport Models ◽  
Sources And Sinks ◽  
Remote Sensing Technique ◽  
Mixing Ratios ◽  
Further Development ◽  
Ppm Level

Abstract. This study presents a synthetic model intercomparison to investigate the importance of transport model errors for estimating the sources and sinks of CO2 using satellite measurements. The experiments were designed for testing the potential performance of the proposed CO2 lidar A-SCOPE, but also apply to other space borne missions that monitor total column CO2. The participating transport models IFS, LMDZ, TM3, and TM5 were run in forward and inverse mode using common CO2 fluxes and initial concentrations. Simulated column averaged CO2 (xCO2) mixing ratios vary between the models by σ=0.5 ppm over the continents and σ=0.27 ppm over sea. A variable, but overall quite encouraging agreement is found in comparison with FTS measurements at Park Falls, Darwin, Spitsbergen, and Bremen. Despite the fact that the models agree on average on the sub-ppm level, these modest differences nevertheless lead to significant discrepancies in the inverted fluxes of 0.1 Pg C/yr per 106 km2 over land and 0.03 Pg C/yr per 106 km2 over the ocean. These transport model induced flux uncertainties exceed the target requirement that was formulated for the A-SCOPE mission of 0.02 Pg C/yr per 106 km2, and could also limit the overall performance of other CO2 missions such as GOSAT. It is concluded that to make use of the remote sensing technique for quantifying the sources and sinks of CO2 not only requires highly accurate satellite instruments, but also puts stringent requirements on the performance of atmospheric transport models. Further development of these models should receive high priority.

scholarly journals A review of approaches to estimate wildfire plume injection height within large scale atmospheric chemical transport models – Part 1

2015 ◽  
Vol 15 (6) ◽  
pp. 9767-9813 ◽  
Author(s):  
R. Paugam ◽  
M. Wooster ◽  
S. R. Freitas ◽  
M. Val Martin
Keyword(s):  
Large Scale ◽  
Atmospheric Transport ◽  
Source Region ◽  
Chemical Species ◽  
Chemical Conversion ◽  
Ambient Air ◽  
Transport Models ◽  
Fire Emissions ◽  
Fire Smoke ◽  
In Fire

Abstract. Landscape fires produce smoke containing a very wide variety of chemical species, both gases and aerosols. For larger, more intense fires that produce the greatest amounts of emissions per unit time, the smoke tends initially to be transported vertically or semi-vertically close by the source region, driven by the intense heat and convective energy released by the burning vegetation. The column of hot smoke rapidly entrains cooler ambient air, forming a rising plume within which the fire emissions are transported. This characteristics of this plume, and in particular the height to which it rises before releasing the majority of the smoke burden into the wider atmosphere, are important in terms of how the fire emissions are ultimately transported, since for example winds at different altitudes maybe quite different. This difference in atmospheric transport then may also affect the longevity, chemical conversion and fate of the plumes chemical consituents, with for example very high plume injection heights being associated with extreme long-range atmospheric transport. Here we review how such landscape-scale fire smoke plume injection heights are represented in larger scale atmospheric transport models aiming to represent the impacts of wildfire emissions on component of the Earth system. The use of satellite Earth observation (EO) data is commonly used for this, and detail the EO datasets capable of being used to remotely assess wildfire plume height distributions and the driving characteristics of the causal fires. We also discus both the physical mechanisms and dynamics taking place in fire plumes, and investigate the efficiency and limitations of currently available injection height parameterizations. Finally, we conclude by suggestion some future parameterization developments and ideas on EO data selection that maybe relevant to the instigation of enhanced methodologies aimed at injection height representation.

scholarly journals Designing optimal greenhouse gas observing networks that consider performance and cost

2014 ◽  
Vol 4 (2) ◽  
pp. 705-749
Author(s):  
D. D. Lucas ◽  
C. Yver Kwok ◽  
P. Cameron-Smith ◽  
H. Graven ◽  
D. Bergmann ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Atmospheric Transport ◽  
Pareto Frontier ◽  
Ghg Emissions ◽  
Emission Rates ◽  
Monitoring Networks ◽  
Transport Models ◽  
Hfc 134A ◽  
Scientific Accuracy ◽  
Better Than

Abstract. Emission rates of greenhouse gases (GHGs) entering into the atmosphere can be inferred using mathematical inverse approaches that combine observations from a network of stations with forward atmospheric transport models. Some locations for collecting observations are better than others for constraining GHG emissions through the inversion, but the best locations for the inversion may be inaccessible or limited by economic and other non-scientific factors. We present a method to design an optimal GHG observing network in the presence of multiple objectives that may be in conflict with each other. As a demonstration, we use our method to design a prototype network of six stations to monitor summertime emissions in California of the potent GHG 1,1,1,2-tetrafluoroethane (CH2FCF3, HFC-134a). We use a multiobjective genetic algorithm to evolve network configurations that seek to jointly maximize the scientific accuracy of the inferred HFC-134a emissions and minimize the associated costs of making the measurements. The genetic algorithm effectively determines a set of "optimal" observing networks for HFC-134a that satisfy both objectives (i.e., the Pareto frontier). The Pareto frontier is convex, and clearly shows the tradeoffs between performance and cost, and the diminishing returns in trading one for the other. Without difficulty, our method can be extended to design optimal networks to monitor two or more GHGs with different emissions patterns, or to incorporate other objectives and constraints that are important in the practical design of atmospheric monitoring networks.

scholarly journals An online emission module for atmospheric chemistry transport models: implementation in COSMO-GHG v5.6a and COSMO-ART v5.1-3.1

2020 ◽  
Vol 13 (5) ◽  
pp. 2379-2392 ◽  
Author(s):  
Michael Jähn ◽  
Gerrit Kuhlmann ◽  
Qing Mu ◽  
Jean-Matthieu Haussaire ◽  
David Ochsner ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Atmospheric Transport ◽  
Model Simulation ◽  
Vertical Scaling ◽  
Transport Models ◽  
Input Size ◽  
Modeling Systems ◽  
Fortran 90 ◽  
Processing Steps ◽  
Python Package

Abstract. Emission inventories serve as crucial input for atmospheric chemistry transport models. To make them usable for a model simulation, they have to be pre-processed and, traditionally, provided as input files at discrete model time steps. In this paper, we present an “online” approach, which produces a minimal number of input data read-in at the beginning of a simulation and which handles essential processing steps online during the simulation. For this purpose, a stand-alone Python package “emiproc” was developed, which projects the inventory data to the model grid and generates temporal and vertical scaling profiles for individual emission categories. The package is also able to produce “offline” emission files if desired. Furthermore, we outline the concept of the online emission module (written in Fortran 90) and demonstrate its implementation in two different atmospheric transport models: COSMO-GHG and COSMO-ART. Simulation results from both modeling systems show the equivalence of the online and offline procedure. While the model run time is very similar for both approaches, input size and pre-processing time are greatly reduced when online emissions are utilized.

Sign in / Sign up

Export Citation Format

Share Document