Atmospheric trace gas constituents and aerosols exert important influences on global-scale and regional-scale climate. Atmospheric chemistry determines the abundance and lifetime of many greenhouse gases. In the stratosphere, heterogeneous chemistry involving reactive chlorine causes ozone (O3) depletion while, in the troposphere, reactive gases such as carbon monoxide, nitrogen oxides, and volatile organic compounds (VOCs) perturb the climate indirectly by affecting the abundance of CH4 and tropospheric O3. Atmospheric chemistry also contributes to climate through its effects on aerosol formation.
The role of feedbacks is also being recognised. For example, climate change inﬂuences the timescale of stratospheric O3 recovery and may affect future tropospheric O3 through changes in vegetation and biogenic VOC emissions. As a result, there is a need to implement atmospheric chemistry in Earth System Models (ESMs) to understand and quantify interactions between climate, atmospheric composition, and other ES components such as vegetation.
Figure 1. Schematic showing the role of atmospheric composition in the Earth System.
The UK’s ESM for the 5th Coupled Model Intercomparison Project (CMIP5), HadGEM2-ES (Collins et al., 2011), included a representation of atmospheric chemistry (O’Connor et al., 2014) for the first time. UKESM1, however, has enhanced capability as a result of developments through the United Kingdom Chemistry and Aerosol (UKCA) collaborative project between the Met Office and its NERC/NCAS partners. These improvements include:
- Extension to the chemistry to include isoprene, a tropospheric O3 precursor whose emissions from vegetation are sensitive to climate and carbon dioxide.
- Extension to the chemistry to include heterogeneous ozone depletion chemistry in the stratosphere (Morgenstern et al., 2009).
- Inclusion of an interactive photolysis scheme, Fast-JX (Telford et al., 2013).
- Inclusion of an interactive biogenic VOC emissions scheme (Pacifico et al., 2011).
- Inclusion of an interactive emissions scheme from fires as a diagnostic (Mangeon et al., 2016).
Figure 2. A comparison of the annual cycle of O3 in UKESM1 (green), HadGEM2-ES (blue), a multi-model mean (red), individual ensemble members (grey) and observations (black).
A snapshot of the model performance can be seen in Figure 2 which shows a comparison of the annual cycle in O3 at different pressure levels for different latitude bands. In terms of the overall performance, a root mean square error (RMSE) for HadGEM2-ES and UKESM1 was calculated using modelled and observed monthly mean O3 concentrations at 750, 500, and 250 hPa and excluding the extra-tropics at 250 hPa; HadGEM2-ES had a RMSE of 7.7 ppbv (O’Connor et al., 2014) and UKESM1 has a RMSE error of 5.9 ppbv, both at the lower end of RMSEs from the multi-model ensemble of 5.1–18.0 ppbv (Stevenson et al., 2006). However, in the lower stratosphere of the extra-tropics, UKESM1 has a higher RMSE than HadGEM2-ES but HadGEM2-ES was largely constrained by observations in that region due to its absence of stratospheric heterogeneous chemistry.
Overall, UKESM1 represents a step change in capability in atmospheric chemistry and will provide a flagship model for contributing to the forthcoming Aerosol and Chemistry Model Intercomparison Project (Collins et al., 2017), and for underpinning investigative science in composition and climate.
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