Events

Atmospheric & Environmental Chemistry Seminars

Towards seamless carbon cycle prediction: from data assimilation to emergent constraints

Kevin Bowman, Engineering and Science Directorate Principal, NASA Jet Propulsion Laboratory

Apr 15, 2022
12:00 pm to 1:00 pm | Remote

Register here: https://harvard.zoom.us/meeting/register/tJcucO6srDgoGN1GFfS3HDyt57ah23r003CJ

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Abstract

The Paris Agreement was a watershed moment in providing a framework to address the mitigation of climate change.  The Global Stocktake is a bi-decadal process to assess progress in greenhouse gas emission reductions in light of climate feedbacks and response.   However, the relationship between emission commitments and concentration requirements is confounded by  complex natural and anthropogenic biogeochemical processes modulated by climate feedbacks.  

We investigate the prospects and challenges of mediating between emissions and concentrations along with the predictability of their trajectory. Our primary tool is the NASA Carbon Monitoring System Flux (CMS-Flux), which is an inverse modeling and data assimilation system that ingests a suite of observations  across the carbon cycle to attribute atmospheric carbon variability to anthropogenic and biogeochemical processes.

We use this tool to address an essential question for the Stocktake: the predictability of the  carbon cycle.  We look at this question through several angles.  We ingest data  into a  carbon cycle model using a Markov Chain Monte Carlo (MCMC) technique that explicitly incorporates non-Gaussian behavior and use those solutions to characterize the trajectory and predictability of terrestrial carbon dynamics.  We further consider the coevolution of air quality and carbon in conjunction with an advanced chemical data assimilation system in light of an environmental Kuznet curve to assess the predictability of carbon given air quality emissions.  We then consider predictability  and observability within a hierarchical emergent constraint (HEC) framework, which is used to constrain carbon-climate feedbacks.   These elements taken together are core components  of a carbon attribution and prediction system needed to assess the efficacy of carbon mitigation strategies in the presence of a changing climate. 

Contact
Contact:

Zhen Qu

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