Abstract
Abstract. 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 characterised 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.
Funder
Natural Environment Research Council
Cited by
38 articles.
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