Accepted author manuscript, 733 KB, PDF document
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Accepted author manuscript
Licence: CC BY: Creative Commons Attribution 4.0 International License
Final published version
Licence: CC BY: Creative Commons Attribution 4.0 International License
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Global sensitivity analysis of chemistry-climate model budgets of tropospheric ozone and OH
T2 - Exploring model diversity
AU - Wild, Oliver
AU - Voulgarakis, Apostolos
AU - O'Connor, Fiona
AU - Lamarque, Jean-Francois
AU - Ryan, Edmund
AU - Lee, Lindsay
PY - 2020/4/3
Y1 - 2020/4/3
N2 - Projections of future atmospheric composition change and its impacts on air quality and climate depend heavily on chemistry-climate models that allow us to investigate the effects of changing emissions and meteorology. These models are imperfect as they rely on our understanding of the chemical, physical and dynamical processes governing atmospheric composition, on the approximations needed to represent these numerically, and on the limitations of the observations required to constrain them. Model intercomparison studies show substantial diversity in results that reflect underlying uncertainties, but little progress has been made in explaining the causes of this or in identifying the weaknesses in process understanding or representation that could lead to improved models and to better scientific understanding. Global sensitivity analysis provides a valuable method of identifying and quantifying the main causes of diversity in current models. For the first time, we apply Gaussian process emulation with three independent global chemistry transport models to quantify the sensitivity of ozone and hydroxyl radicals (OH) to important climate-relevant variables, poorly-characterized processes and uncertain emissions. We show a clear sensitivity of tropospheric ozone to atmospheric humidity and precursor emissions which is similar for the models, but find large differences between models for methane lifetime, highlighting substantial differences in the sensitivity of OH to primary and secondary production. This approach allows us to identify key areas where model improvements are required while providing valuable new insight into the processes driving tropospheric composition change.
AB - Projections of future atmospheric composition change and its impacts on air quality and climate depend heavily on chemistry-climate models that allow us to investigate the effects of changing emissions and meteorology. These models are imperfect as they rely on our understanding of the chemical, physical and dynamical processes governing atmospheric composition, on the approximations needed to represent these numerically, and on the limitations of the observations required to constrain them. Model intercomparison studies show substantial diversity in results that reflect underlying uncertainties, but little progress has been made in explaining the causes of this or in identifying the weaknesses in process understanding or representation that could lead to improved models and to better scientific understanding. Global sensitivity analysis provides a valuable method of identifying and quantifying the main causes of diversity in current models. For the first time, we apply Gaussian process emulation with three independent global chemistry transport models to quantify the sensitivity of ozone and hydroxyl radicals (OH) to important climate-relevant variables, poorly-characterized processes and uncertain emissions. We show a clear sensitivity of tropospheric ozone to atmospheric humidity and precursor emissions which is similar for the models, but find large differences between models for methane lifetime, highlighting substantial differences in the sensitivity of OH to primary and secondary production. This approach allows us to identify key areas where model improvements are required while providing valuable new insight into the processes driving tropospheric composition change.
KW - Ozone
KW - OH
KW - Tropospheric chemistry
KW - Modelling
KW - Uncertainty
KW - Sensitivity analysis
KW - Model intercomparison
M3 - Journal article
VL - 20
SP - 4047
EP - 4058
JO - Atmospheric Chemistry and Physics
JF - Atmospheric Chemistry and Physics
SN - 1680-7316
ER -