TIES Webinar Series on Data Science for Environmental Sciences (DSES)

The International Environmetrics Society (TIES) has launched a new TIES Webinar Series on Data Science for Environmental Sciences (DSES).

Our next webinar will be on May 19, at 6 pm CT (UTC-6, US)

For colleagues who live in Australia, it means May 20, at 9 am AEST (UTC+10).

You can virtually access the webinar and register via our website: www.environmetrics.xyz

Speaker: Andrew Zammit-Mangion, University of Wollongong, Australia.

Title: Bayesian inference on carbon dioxide surface fluxes using satellite data

Abstract: Carbon dioxide (CO2) is one of several greenhouse gases that trap heat in Earth’s lower atmosphere. Locations across Earth’s surface where CO2 is added to or removed from the atmosphere are known as sources and sinks, and the rate at which this happens is known as flux. In this talk I present WOMBAT (the WOllongong Methodology for Bayesian Assimilation of Trace-gases), a fully Bayesian hierarchical statistical framework for estimating CO2 global fluxes from satellite data. WOMBAT extends the current state-of-the-art through the consideration of a correlated error term, the capacity for online bias correction, and the provision of uncertainty quantification on all unknowns that appear in the Bayesian statistical model. Using the GEOS-Chem atmospheric transport model, we show that WOMBAT is able to obtain posterior means and variances on non-fossil-fuel CO2 fluxes from Orbiting Carbon Observatory-2 (OCO-2) data that are comparable to those from an international Model Intercomparison Project (MIP). We also find that WOMBAT’s predictions of out-of-sample retrievals obtained from the Total Column Carbon Observing Network are, for the most part, more accurate than those made by the MIP participants.

Bio: Andrew Zammit-Mangion is Associate Professor with the School of Mathematics and Applied Statistics at the University of Wollongong, Australia, with expertise in the field of spatio-temporal statistics and its application to the environmental sciences. He is recipient of the 2020 Abdel El-Shaarawi Early Investigator's Award from The International Environmetrics Society (TIES) and the 2022 ENVR Early Investigator Award from the American Statistical Association (ASA) Section on Statistics and the Environment.