Resolving the evolution of organic carbon stocks from joint assimilation of satellite-informed biomass and CMS-Flux CO2 flux estimates.
Abstract
Understanding the processes regulating the net carbon (C) exchange across terrestrial ecosystems is a challenging task, largely due to uncertainties in the magnitude of terrestrial C stocks and their dynamic responses to climate variability and disturbance. Ultimately, an integrated mechanistic understanding of climate forcings on uptake and respiration fluxes, their legacy effects on the terrestrial C balance, and ultimately an accurate knowledge on the evolution of live biomass and dead organic C stocks is needed understand and predict the net land C sink. A major limitation in resolving these terrestrial C dynamics has been the virtual impossibility of direct soil C stock measurements on a global scale; however, global-scale time resolved measurements of both net C fluxes and biomass provide an unprecedented opportunity to indirectly constrain estimates of the evolution of the dead organic C store dynamics across terrestrial ecosystems. Here we use the CARbon DAta-MOdel fraMework (CARDAMOM) Bayesian model-data fusion approach - constrained by (i) a near-decadal record CO2 fluxes (derived from OCO-2 and GOSAT measurements of atmospheric CO2), (ii) recently derived global annually-resolved biomass datasets, and (iii) ancillary observations, including MODIS leaf area, solar-induced fluorescence, as well as top-down atmospheric and CO surface fluxes - to resolve the annual-to-decadal C cycle dynamics and their underlying processes. In particular, we find that the combined flux-biomass observational constrains lead to substantial quantitative insights into the year-to-year imbalance of the dead organic C stocks as well as quantitative insights into associated process controls, both of which are critical for improving predictions of the land sink in the coming decades.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2019
- Bibcode:
- 2019AGUFM.B13H2604B
- Keywords:
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- 0414 Biogeochemical cycles;
- processes;
- and modeling;
- BIOGEOSCIENCES;
- 0428 Carbon cycling;
- BIOGEOSCIENCES;
- 0480 Remote sensing;
- BIOGEOSCIENCES