scholarly journals Supplementary material to "Calibrating a global atmospheric chemistry transport model using Gaussian process emulation and ground-level concentrations of ozone and carbon monoxide"

2021 ◽  
Author(s):  
Edmund Ryan ◽  
Oliver Wild
Keyword(s):  
Carbon Monoxide ◽  
Gaussian Process ◽  
Atmospheric Chemistry ◽  
Transport Model ◽  
Ground Level ◽  
Chemistry Transport Model ◽  
Gaussian Process Emulation ◽  
Supplementary Material

scholarly journals Calibrating a global atmospheric chemistry transport model using Gaussian process emulation and ground-level concentrations of ozone and carbon monoxide

2021 ◽  
Author(s):  
Edmund Ryan ◽  
Oliver Wild
Keyword(s):  
Carbon Monoxide ◽  
Gaussian Process ◽  
Atmospheric Chemistry ◽  
Dry Deposition ◽  
Ground Level ◽  
Atmospheric Composition ◽  
Transport Models ◽  
Representation Error ◽  
Spatial Coverage ◽  
Gaussian Process Emulation

Abstract. Atmospheric chemistry transport models are important tools to investigate the local, regional and global controls on atmospheric composition and air quality. To ensure that these models represent the atmosphere adequately it is important to compare their outputs with measurements. However, ground based measurements of atmospheric composition are typically sparsely distributed and representative of much smaller spatial scales than those resolved in models, and thus direct comparison incurs uncertainty. In this study, we investigate the feasibility of using observations of one or more atmospheric constituents to estimate parameters in chemistry transport models and to explore how these estimates and their uncertainties depend upon representation errors and the level of spatial coverage of the measurements. We apply Gaussian process emulation to explore the model parameter space and use monthly averaged ground-level concentrations of ozone (O3) and carbon monoxide (CO) from across Europe and the US. Using synthetic observations we find that the estimates of parameters with greatest influence on O3 and CO are unbiased, and the associated parameter uncertainties are low even at low spatial coverage or with high representation error. Using reanalysis data, we find that estimates of the most influential parameter – corresponding to the dry deposition process – are closer to its expected value using both O3 and CO data than using O3 alone. This is remarkable because it shows that while CO is largely unaffected by dry deposition, the additional constraints it provides are valuable for achieving unbiased estimates of the dry deposition parameter. In summary, these findings identify the level of spatial representation error and coverage needed to achieve good parameter estimates and highlight the benefits of using multiple constraints to calibrate atmospheric chemistry models.

scholarly journals Calibrating a global atmospheric chemistry transport model using Gaussian process emulation and ground-level concentrations of ozone and carbon monoxide

2021 ◽  
Vol 14 (9) ◽  
pp. 5373-5391
Author(s):  
Edmund Ryan ◽  
Oliver Wild
Keyword(s):  
Carbon Monoxide ◽  
Gaussian Process ◽  
Atmospheric Chemistry ◽  
Dry Deposition ◽  
Ground Level ◽  
Atmospheric Composition ◽  
Transport Models ◽  
Representation Error ◽  
Spatial Coverage ◽  
Gaussian Process Emulation

Abstract. Atmospheric chemistry transport models are important tools to investigate the local, regional and global controls on atmospheric composition and air quality. To ensure that these models represent the atmosphere adequately, it is important to compare their outputs with measurements. However, ground based measurements of atmospheric composition are typically sparsely distributed and representative of much smaller spatial scales than those resolved in models; thus, direct comparison incurs uncertainty. In this study, we investigate the feasibility of using observations of one or more atmospheric constituents to estimate parameters in chemistry transport models and to explore how these estimates and their uncertainties depend upon representation errors and the level of spatial coverage of the measurements. We apply Gaussian process emulation to explore the model parameter space and use monthly averaged ground-level concentrations of ozone (O3) and carbon monoxide (CO) from across Europe and the US. Using synthetic observations, we find that the estimates of parameters with greatest influence on O3 and CO are unbiased, and the associated parameter uncertainties are low even at low spatial coverage or with high representation error. Using reanalysis data, we find that estimates of the most influential parameter – corresponding to the dry deposition process – are closer to its expected value using both O3 and CO data than using O3 alone. This is remarkable because it shows that while CO is largely unaffected by dry deposition, the additional constraints it provides are valuable for achieving unbiased estimates of the dry deposition parameter. In summary, these findings identify the level of spatial representation error and coverage needed to achieve good parameter estimates and highlight the benefits of using multiple constraints to calibrate atmospheric chemistry transport models.

scholarly journals Ethane, ethyne and carbon monoxide concentrations in the upper troposphere and lower stratosphere from ACE and GEOS-Chem: a comparison study

2011 ◽  
Vol 11 (4) ◽  
pp. 13099-13139 ◽  
Author(s):  
G. González Abad ◽  
N. D. C. Allen ◽  
P. F. Bernath ◽  
C. D. Boone ◽  
S. D. McLeod ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Atmospheric Chemistry ◽  
Transport Model ◽  
Chemical Mechanism ◽  
Chemical Transport Model ◽  
Spectrometer Data ◽  
Chemistry Experiment ◽  
Global Mean ◽  
Tropospheric Concentrations ◽  
Good Agreement

Abstract. Near global upper tropospheric concentrations of carbon monoxide (CO), ethane (C2H6) and ethyne (C2H2) from ACE (Atmospheric Chemistry Experiment) Fourier transform spectrometer on board the Canadian satellite SCISAT-1 are presented and compared with the output from the Chemical Transport Model (CTM) GEOS-Chem. The retrievals of ethane and ethyne from ACE have been improved for this paper by using new sets of microwindows compared with those for previous versions of ACE data. With the improved ethyne retrieval we have been able to produce a near global upper tropospheric distribution of C2H2 from space. Carbon monoxide, ethane and ethyne concentrations retrieved using ACE spectra show the expected seasonality linked to variations in the anthropogenic emissions and destruction rates as well as seasonal biomass burning activity. The GEOS-Chem model was run using the dicarbonyl chemistry suite, an extended chemical mechanism in which ethyne is treated explicitly. Seasonal cycles observed from satellite data are well reproduced by the model output, however the simulated CO concentrations are found to be systematically biased low over the Northern Hemisphere. An average negative global mean bias of 12% and 7% of the model relative to the satellite observations has been found for CO and C2H6 respectively and a positive global mean bias of 1% has been found for C2H2. ACE data are compared for validation purposes with MkIV spectrometer data and Global Tropospheric Experiment (GTE) TRACE-A campaign data showing good agreement with all of them.

scholarly journals Modelling atmospheric OH-reactivity in a boreal forest ecosystem

2011 ◽  
Vol 11 (18) ◽  
pp. 9709-9719 ◽  
Author(s):  
D. Mogensen ◽  
S. Smolander ◽  
A. Sogachev ◽  
L. Zhou ◽  
V. Sinha ◽  
...  
Keyword(s):  
Boreal Forest ◽  
Gas Phase ◽  
Atmospheric Chemistry ◽  
Transport Model ◽  
Inorganic Compounds ◽  
Chemistry Transport Model ◽  
One Dimensional ◽  
Inorganic Species ◽  
Individual Contributions ◽  
The Individual

Abstract. We have modelled the total atmospheric OH-reactivity in a boreal forest and investigated the individual contributions from gas phase inorganic species, isoprene, monoterpenes, and methane along with other important VOCs. Daily and seasonal variation in OH-reactivity for the year 2008 was examined as well as the vertical OH-reactivity profile. We have used SOSA; a one dimensional vertical chemistry-transport model (Boy et al., 2011a) together with measurements from Hyytiälä, SMEAR II station, Southern Finland, conducted in August 2008. Model simulations only account for ~30–50% of the total measured OH sink, and in our opinion, the reason for missing OH-reactivity is due to unmeasured unknown BVOCs, and limitations in our knowledge of atmospheric chemistry including uncertainties in rate constants. Furthermore, we found that the OH-reactivity correlates with both organic and inorganic compounds and increases during summer. The summertime canopy level OH-reactivity peaks during night and the vertical OH-reactivity decreases with height.

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