Improving the predictions of ecosystem carbon fluxes using the Ecosystem Demography model

Friday, 18 December 2015
Poster Hall (Moscone South)
Ashehad Ashween Ali1, Daniel Scott1, Ke Zhang2 and Paul R Moorcroft1, (1)Harvard University, Cambridge, MA, United States, (2)University of Oklahoma Norman Campus, Norman, OK, United States
Large uncertainties exist in terrestrial biosphere models projections of terrestrial carbon fluxes. One critical quantity that strongly influence the net ecosystem exchange of carbon between the land and the atmosphere via effects on photosynthesis and respiration is soil moisture.

In this study, we used newly-acquired information on root-zone soil moisture (RZSM) available from the AirMOSS P-band radar remote sensing instrument in conjunction with carbon and energy flux measurements from eddy-flux towers to constrain predictions from the Ecosystem Demography model version 2 (ED2) against 2 years of measurements from a series of sites across North America.

In comparison to the default model formulation, we found that the RZSM-constrained ED2 model improves the predictions of net ecosystem exchange, heat and water fluxes, as well as growth and mortality dynamics of trees. Overall, these results suggest that data-constrained parameterization of terrestrial biosphere models such as ED2 can be used to improve site-level ecosystem predictions, but also improve and scale-up predictions to regional and continental scales.