Model-data fusion at scales from site to globe: Uncertainty assessment, network design and multiple data constraints
Abstract
Accurate prediction and diagnoses of ecosystem-atmosphere carbon dioxide fluxes remain challenging problems. Multiple data constraints are needed to make substantial progress in both diagnosis and prediction of fluxes. Assimilation of the complex data sets with the potential to constrain flux estimates over large spatial and temporal scales raises is statistically, scientifically and computationally challenging. We present ongoing efforts to synthesize flux measurements with a variety of complementary measurements at scales from sites to regions to the globe. A variety of models are required to take advantage of complementary data sets and to span large regions. We also present progress in uncertainty assessment and observational network design, both of which can be addressed using a combination of statistical techniques and understanding of the nature of the data and models employed. Ongoing work includes efforts to improve predictive skill of models at points using flux tower and carbon pool data, to improve diagnosis of fluxes over regions using flux tower and atmospheric CO2 measurements, and to improve diagnosis and prediction of fluxes at global scales using atmospheric CO2, flux tower measurements, and ocean carbon measurements. We also discuss scientific needs and opportunities in this growing field of research.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2009
- Bibcode:
- 2009AGUFM.B44A..01D
- Keywords:
-
- 0426 BIOGEOSCIENCES / Biosphere/atmosphere interactions;
- 0428 BIOGEOSCIENCES / Carbon cycling;
- 0434 BIOGEOSCIENCES / Data sets