Research Interests

I’m currently the NCEO Leader and Research Fellow for Earth System Model and Climate-Carbon Data Evaluation for the UK National Centre for Earth Observation (NCEO), based at the University of Leicester, UK.

My Research Interests include the following areas:

Earth System Model Evaluation

The evaluation of Earth System Models is vital to understanding their processes and feedbacks and the effect they may have on a changing future climate.

• A large number of Essential Climate Variables can now be observed from satellite data and the use of these for evaluating ESMs allows improved process understanding.
• Understanding of the uncertainty in the observations and how that should be accounted for in evaluating models.

Satellite Retrievals of Methane

I’m responsible for the development, production and evaluation of the University of Leicester GOSAT Proxy Methane Data product.

• Since the launch of the GOSAT satellite in 2009, these data have been produced by the UK National Centre for Earth Observation (NCEO) as part of the ESA Greenhouse Gas Climate Change Initiative (GHG-CCI) and Copernicus Climate Change Services (C3S) projects.
• With now over a decade of observations, many scientific studies have used these data to examine methane trends and emissions.

Understanding Wetland Methane Emissions

Wetland emissions contribute the largest uncertainties to the current global atmospheric CH₄ budget and how these emissions will change under future climate scenarios is still poorly understood.

• A large part of my research work has been focused on utilising satellite CH₄ observations to analysis and evaluate our understanding of wetland CH₄ emissions.

Monitoring Fire Emissions from Space

Biomass burning can be one of the most important disturbances to the Earth System.

• Significant transfer of ancient carbon into the atmosphere occurs when carbon-rich peatlands are subject to burning.
• The monitoring of the emission ratios between different species can provide information on the characteristics of the fuel being burnt.
• Satellite observations can aid in the evaluation of fire models and help better understand the processes and feedbacks between fire and the rest of the Earth System.

Machine Learning for Earth System Science

Machine Learning and Artificial Intelligence has a huge potential to revolutionise Earth System Science in the same way as it has in other scientific fields.

• Emulators can be trained to reproduce the behaviour of complex and computationally expensive physical models.
• “Explainable AI” can help us understand the complex relationships inherent in Earth System Models and gain insight into the underlying processes.

Satellite Retrievals of Biomass Burning Hydrocarbons

My PhD in the EOS Group at the University of Leicester, titled Satellite Observations of C₂H₂ and C₂H₆ in the Upper Troposphere, supervised by Professor John Remedios, focused on identifying organic compounds generated during biomass burning from space-based instrumentation and understanding their sources, distribution and transport within the atmosphere.

• Development of a novel technique to utilise thermal infrared emission spectra from satellite data in order to detect and analyse the distributions of biomass burning products in the upper troposphere.
• Extensive work performing optimal estimation retrievals in order to compare distributions.
• Highlights include: Successful detection of C₂H₂ and C₂H₆, characterisation of Asian Monsoon anticyclone chemical isolation, identification of deep convection and uplift of gases, identifying signature of C₂H₆ related to fossil fuel production