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 ◽  
...  

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.

2006 ◽  
Vol 6 (3) ◽  
pp. 3709-3756 ◽  
Author(s):  
C. Geels ◽  
M. Gloor ◽  
P. Ciais ◽  
P. Bousquet ◽  
P. Peylin ◽  
...  

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.


2015 ◽  
Vol 15 (6) ◽  
pp. 9767-9813 ◽  
Author(s):  
R. Paugam ◽  
M. Wooster ◽  
S. R. Freitas ◽  
M. Val Martin

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.


Elem Sci Anth ◽  
2018 ◽  
Vol 6 ◽  
Author(s):  
Kai Wu ◽  
Thomas Lauvaux ◽  
Kenneth J. Davis ◽  
Aijun Deng ◽  
Israel Lopez Coto ◽  
...  

The Indianapolis Flux Experiment aims to utilize a variety of atmospheric measurements and a high-resolution inversion system to estimate the temporal and spatial variation of anthropogenic greenhouse gas emissions from an urban environment. We present a Bayesian inversion system solving for fossil fuel and biogenic CO2 fluxes over the city of Indianapolis, IN. Both components were described at 1 km resolution to represent point sources and fine-scale structures such as highways in the a priori fluxes. With a series of Observing System Simulation Experiments, we evaluate the sensitivity of inverse flux estimates to various measurement deployment strategies and errors. We also test the impacts of flux error structures, biogenic CO2 fluxes and atmospheric transport errors on estimating fossil fuel CO2 emissions and their uncertainties. The results indicate that high-accuracy and high-precision measurements produce significant improvement in fossil fuel CO2 flux estimates. Systematic measurement errors of 1 ppm produce significantly biased inverse solutions, degrading the accuracy of retrieved emissions by about 1 µmol m–2 s–1 compared to the spatially averaged anthropogenic CO2 emissions of 5 µmol m–2 s–1. The presence of biogenic CO2 fluxes (similar magnitude to the anthropogenic fluxes) limits our ability to correct for random and systematic emission errors. However, assimilating continuous fossil fuel CO2 measurements with 1 ppm random error in addition to total CO2 measurements can partially compensate for the interference from biogenic CO2 fluxes. Moreover, systematic and random flux errors can be further reduced by reducing model-data mismatch errors caused by atmospheric transport uncertainty. Finally, the precision of the inverse flux estimate is highly sensitive to the correlation length scale in the prior emission errors. This work suggests that improved fossil fuel CO2 measurement technology, and better understanding of both prior flux and atmospheric transport errors are essential to improve the accuracy and precision of high-resolution urban CO2 flux estimates.


2019 ◽  
Vol 19 (5) ◽  
pp. 2991-3006 ◽  
Author(s):  
Kieran Brophy ◽  
Heather Graven ◽  
Alistair J. Manning ◽  
Emily White ◽  
Tim Arnold ◽  
...  

Abstract. Atmospheric inverse modelling has become an increasingly useful tool for evaluating emissions of greenhouse gases including methane, nitrous oxide, and synthetic gases such as hydrofluorocarbons (HFCs). Atmospheric inversions for emissions of CO2 from fossil fuel combustion (ffCO2) are currently being developed. The aim of this paper is to investigate potential errors and uncertainties related to the spatial and temporal prior representation of emissions and modelled atmospheric transport for the inversion of ffCO2 emissions in the US state of California. We perform simulation experiments based on a network of ground-based observations of CO2 concentration and radiocarbon in CO2 (a tracer of ffCO2), combining prior (bottom-up) emission models and transport models currently used in many atmospheric studies. The potential effect of errors in the spatial and temporal distribution of prior emission estimates is investigated in experiments by using perturbed versions of the emission estimates used to create the pseudo-data. The potential effect of transport error was investigated by using three different atmospheric transport models for the prior and pseudo-data simulations. We find that the magnitude of biases in posterior total state emissions arising from errors in the spatial and temporal distribution in prior emissions in these experiments are 1 %–15 % of posterior total state emissions and are generally smaller than the 2σ uncertainty in posterior emissions. Transport error in these experiments introduces biases of −10 % to +6 % into posterior total state emissions. Our results indicate that uncertainties in posterior total state ffCO2 estimates arising from the choice of prior emissions or atmospheric transport model are on the order of 15 % or less for the ground-based network in California we consider. We highlight the need for temporal variations to be included in prior emissions and for continuing efforts to evaluate and improve the representation of atmospheric transport for regional ffCO2 inversions.


Nature ◽  
2002 ◽  
Vol 415 (6872) ◽  
pp. 626-630 ◽  
Author(s):  
Kevin Robert Gurney ◽  
Rachel M. Law ◽  
A. Scott Denning ◽  
Peter J. Rayner ◽  
David Baker ◽  
...  

2010 ◽  
Vol 10 (20) ◽  
pp. 9981-9992 ◽  
Author(s):  
S. Houweling ◽  
I. Aben ◽  
F.-M. Breon ◽  
F. Chevallier ◽  
N. Deutscher ◽  
...  

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.


2019 ◽  
Vol 491 (2) ◽  
pp. 1600-1621
Author(s):  
Yi Mao ◽  
Jun Koda ◽  
Paul R Shapiro ◽  
Ilian T Iliev ◽  
Garrelt Mellema ◽  
...  

ABSTRACT Cosmic reionization was driven by the imbalance between early sources and sinks of ionizing radiation, both of which were dominated by small-scale structure and are thus usually treated in cosmological reionization simulations by subgrid modelling. The recombination rate of intergalactic hydrogen is customarily boosted by a subgrid clumping factor, 〈n2〉/〈n〉2, which corrects for unresolved fluctuations in gas density n on scales below the grid-spacing of coarse-grained simulations. We investigate in detail the impact of this inhomogeneous subgrid clumping on reionization and its observables, as follows: (1) Previous attempts generally underestimated the clumping factor because of insufficient mass resolution. We perform a high-resolution N-body simulation that resolves haloes down to the pre-reionization Jeans mass to derive the time-dependent, spatially varying local clumping factor and a fitting formula for its correlation with local overdensity. (2) We then perform a large-scale N-body and radiative transfer simulation that accounts for this inhomogeneous subgrid clumping by applying this clumping factor-overdensity correlation. Boosting recombination significantly slows the expansion of ionized regions, which delays completion of reionization and suppresses 21 cm power spectra on large scales in the later stages of reionization. (3) We also consider a simplified prescription in which the globally averaged, time-evolving clumping factor from the same high-resolution N-body simulation is applied uniformly to all cells in the reionization simulation, instead. Observables computed with this model agree fairly well with those from the inhomogeneous clumping model, e.g. predicting 21 cm power spectra to within 20 per cent error, suggesting it may be a useful approximation.


2017 ◽  
Author(s):  
Yu Liu ◽  
Nicolas Gruber ◽  
Dominik Brunner

Abstract. The emission of CO2 from the burning of fossil fuel is a prime determinant of variations in atmospheric CO2. Here, we simulate this fossil fuel signal together with the natural and background components with a regional high-resolution atmospheric transport model for central and southern Europe considering separately the emissions from different sectors and countries on the basis of emission inventories and hourly emission time functions. The simulated variations in atmospheric CO2 agree very well with observation-based estimates, although the observed variance is slightly underestimated, particularly for the fossil fuel component. Despite relatively rapid atmospheric mixing, the simulated fossil fuel signal reveals distinct annual mean structures deep into the troposphere reflecting the spatially dense aggregation of most emissions. The fossil fuel signal accounts for more than half of the total (fossil fuel + biospheric + background) temporal variations in atmospheric CO2 in most areas of northern and western central Europe, with the largest variations occurring on diurnal timescales owing to the combination of diurnal variations in emissions and atmospheric mixing/transport out of the surface layer. Their co-variance leads to a fossil-fuel diurnal rectifier effect with a magnitude as large as 9 ppm compared to a case with time-constant emissions. The spatial pattern of CO2 from the different sectors largely reflects the distribution and relative magnitude of the corresponding emissions, with power plant emissions leaving the most distinguished mark. An exception is southern and western Europe, where the emissions from the transportation sector dominate the fossil fuel signal. Most of the fossil fuel CO2 remains within the country responsible for the emission, although in smaller countries, up to 80 % of the fossil fuel signal can come from abroad. A fossil fuel emission reduction of 30 % is clearly detectable for a surface-based observing system for atmospheric CO2, while it is beyond the edge of detectability for the current generation of satellites with the exception of a few hotspot sites. Changes in variability in atmospheric CO2 might open an additional door for the monitoring and verification of changes in fossil fuel emissions, primarily for surface based systems.


2018 ◽  
Author(s):  
Kieran Brophy ◽  
Heather Graven ◽  
Alistair J. Manning ◽  
Emily White ◽  
Tim Arnold ◽  
...  

Abstract. Atmospheric inverse modelling has become an increasingly useful tool for evaluating emissions of greenhouse gases including methane, nitrous oxide and synthetic gases such as hydrofluorocarbons (HFCs). Atmospheric inversions for emissions of CO2 from fossil fuel combustion (ffCO2) are currently being developed. The aim of this paper is to investigate potential errors and uncertainties related to the spatial and temporal prior representation of emissions and modelled atmospheric transport for the inversion of ffCO2 emissions in the U.S. state of California. We perform simulation experiments based on a network of ground-based observations of CO2 concentration and radiocarbon in CO2 (a tracer of ffCO2), combining prior (bottom-up) emission models and transport models currently used in many atmospheric studies. The potential effect of errors in the spatial and temporal distribution of prior emission estimates is investigated in experiments by using perturbed versions of the emissions estimates used to create the pseudo data. The potential effect of transport error was investigated by using three different atmospheric transport models for the prior and pseudo data simulations. We find that the magnitude of biases in posterior state-total emissions arising from errors in the spatial and temporal distribution in prior emissions in these experiments are 1–15 % of posterior state-total emissions, and generally smaller than the 2-σ uncertainty in posterior emissions. Transport error in these experiments introduces biases of −10 % to +6 % in posterior state-total emissions. Our results indicate that uncertainties in posterior state-total ffCO2 estimates arising from the choice of prior emissions or atmospheric transport model are on the order of 15 % or less for the ground-based network in California we consider. We highlight the need for temporal variations to be included in prior emissions, and for continuing efforts to evaluate and improve the representation of atmospheric transport for regional ffCO2 inversions.


2020 ◽  
Author(s):  
Dominik Brunner ◽  
Jean-Matthieu Haussaire ◽  
Julia Marshall ◽  
Arjo Segers ◽  
Hugo Denier van der Gon ◽  
...  

&lt;p&gt;Emissions of carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;) will have to be drastically reduced in the coming decades to reach the goal of the Paris Agreement to limit the global temperature increase to no more than 2&amp;#176;C. To support this process, Europe is planning to establish a CO&lt;sub&gt;2&lt;/sub&gt; anthropogenic emission monitoring system, which will assist countries, cities and facility operators in monitoring their emissions and evaluating the progress towards their reduction targets. The system will combine measurements from ground-based networks with observations from a new constellation of CO&lt;sub&gt;2&lt;/sub&gt; satellites, which will provide high-resolution images of total column CO&lt;sub&gt;2&lt;/sub&gt; allowing tracking the plumes of large emission sources. A suite of atmospheric transport modelling systems will assimilate these observations and inversely estimate emissions from the continental to the country scale and down to the scale of individual cities and power plants.&lt;/p&gt;&lt;p&gt;In the European project &quot;CO&lt;sub&gt;2&lt;/sub&gt; Human Emissions&quot; (CHE), the components of such a modelling framework are explored, which includes the generation of a library of realistic atmospheric CO&lt;sub&gt;2&lt;/sub&gt; simulations. These &quot;nature runs&quot; are obtained by running global and regional atmospheric transport models at the highest possible resolution affordable today and using state-of-the-art inputs of anthropogenic emissions and natural CO&lt;sub&gt;2&lt;/sub&gt; fluxes. The library includes global simulations at 9 km x 9 km resolution with the CAMS-IFS model, European simulations at 5 km x 5 km resolution with WRF-GHG, COSMO-GHG and LOTOS-EUROS, and high-resolution simulations at 1 km x 1 km over the city of Berlin and several power plants with COSMO-GHG and LOTOS-EUROS.&lt;/p&gt;&lt;p&gt;Here we analyse and compare the model simulations to address the following questions: How realistically are atmospheric gradients in CO&lt;sub&gt;2&lt;/sub&gt; caused by spatial and temporal variations in biospheric and anthropogenic fluxes and by atmospheric dynamics represented at the different model resolutions? What resolution is required to resolve the plumes of individual cities and power plants? How large are the differences in near surface and total column CO&lt;sub&gt;2&lt;/sub&gt; due to uncertainties in atmospheric transport including uncertainties in vertical mixing? Information on transport uncertainties is derived from an ensemble of CAMS-IFS simulations and from the spread between the individual models.&lt;/p&gt;&lt;p&gt;Answering these questions is critical for the design of a future operational capacity to monitor anthropogenic CO&lt;sub&gt;2&lt;/sub&gt; emissions, which should optimally support decision makers at facility, city, and country scale as well as the global stocktake process of the Paris Agreement.&lt;/p&gt;


Sign in / Sign up

Export Citation Format

Share Document