Earth's oxygenated history

We simulated Earth with oxygen concentrations between 1000 times less than the present atmospheric level (PAL), and up to 1.5 PAL.

Using WACCM6, we simulated the Earth with 1000 times less than the present atmospheric level (PAL) of oxygen, all the way up to 1.5 times PAL. We found lower ozone columns compared to previous 1D and 3D modelling, meaning that more ultraviolet radiation than previously anticipated could have reached the surface during the Proterozoic. See the following paper for more details: Cooke G. J., Marsh D. R., Walsh C., Black B. and Lamarque J.-F. 2022. A revised lower estimate of ozone columns during Earth’s oxygenated history. R. Soc. open sci.9211165211165. http://doi.org/10.1098/rsos.211165.

Tidally locked exoplanets: TRAPPIST-1e case study

Degenerate interpretations of O3 spectral features in exoplanet atmosphere observations due to stellar UV uncertainties: a 3D case study with TRAPPIST-1e

We simulated 10 different scenarios: 5 cases with one incoming stellar spectrum, and 5 cases with another. One of these was from Peacock et al. (2019), and the other from Wilson et al. (2021). The latter has much lower ultraviolet (UV) emission than the former. UV emission is important for atmospheric chemistry and the habitability of the surface.

More UV emission allows increased photolysis of atmospheric constituents, including O2. O2 photolysis produces O3 through the three body reaction O2 + O + M --> O3 + M, where M is any third body (usually O2 or N2 on Earth).

Predicting future exoplanet observations

What would these exopanets look like through current and next generation telescopes?

Cooke et al. (2023), Variability due to climate and chemistry in observations of oxygenated Earth-analogue exoplanets has been published in MNRAS. We investigated the annual and seasonal variability in observations of oxygenated Earth-like exoplanets with next generation telescope concepts (LUVOIR and HabEx). Large variations in planetary brightness occur. Depending on the telescope used and its coronagraph, confirming annual and/or seasonal variability may be possible. We found that clouds, chemistry and surface albedo are all important when considering temporal variability. 3D chemistry climate models are crucial tools for predicting future observations and the detection possibilities that future missions may yield.

Code developments

Open-source python code in Jupyter Notebook on GitHub.

I have developed two Jupyter Notebooks which are both ongoing projects.

One is the Stellar Wind and Irradiance Module (SWIM). This code takes a spectra from the Mega-MUSCLES survey and scales that spectra to a particular exoplanet around the star you have chosen. It also rebins the spectra based on your model of choice. It is easy to use and the user only needs to clone the GitHub repository. All options are given in drop down menus.

The other is a Jupyter Notebook that uses drop down menus to select different types of climate plots from 3D climate data. The user can then plot different variables such as surface sea ice fraction, the atmospheric temperature, and the atmospheric ozone mixing ratio.