Predicting future changes to the global carbon cycle (and therefore climate) and quantifying anthropogenic emissions of greenhouse gases (GHGs) both require an understanding of net GHGs emissions and uptake across a variety of spatial and temporal scales. This talk will explore some of the core scientific questions related to understanding GHG budgets through the lens of the statistical and computational challenges that arise. The focus will be on the use of atmospheric observations, and applications will include the natural and anthropogenic components of the methane and carbon dioxide budgets. The discussion will include issues related to the solution of spatiotemporal inverse problems, uncertainty quantification, data fusion, gap filling, and issues of “big data” arising from the use of satellite observations.
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