Saatchi (CMS 2020): Bottom-up Spatial Estimates of Carbon Pools and Fluxes of Terrestrial Ecosystems Attributed to Land Use and Environmental Effects
Sassan Saatchi, Jet Propulsion Laboratory / Caltech, saatchi@jpl.nasa.gov (Presenter)
We propose to extend the existing integrated bottom-up carbon accounting infrastructure developed during CMS pilot projects (phase I & II) for estimating annual carbon pools and fluxes of the US forestlands to global forests and decadal time scales (1990-2022). Spatio-temporal machine learning (ML) algorithm trained by a large number of available ground observations from inventory data, and observations of structure from airborne and spaceborne sensors will characterize spatial vegetation carbon pools and uncertainty globally, while recently developed satellite observations of disturbance and recovery products will allow estimates of carbon losses and gains. These products will be integrated in carbon bookkeeping and assimilation models to provide spatial gross emissions and removals from land use and environmental factors to better understand the role of terrestrial vegetation in the global carbon budget. The proposed extension of our CMS pilot project will be one the most advanced bottom-up terrestrial carbon monitoring systems informing the global stocktake and national policies on carbon management and climate mitigation. Our goal is to improve transparency in estimates of global terrestrial carbon fluxes by integrating what are currently disparate approaches into a data-driven bottom-up framework to spatially estimate gross land use and environmental fluxes globally over the period 1990 to 2022.
Associated Project(s):
Poster Location ID: 13
Presentation Type: Poster
Session: Poster Session 1
Session Date: Wednesday (9/27) 1:15 PM