Journal article

A review of applications of model-data fusion to studies of terrestrial carbon fluxes at different scales

Ying-Ping Wang, Cathy M Trudinger, Ian G Enting



Model-data fusion is defined as matching model prediction and observations by varying model parameters or states using statistical estimation. In this paper, we review the history of applications of various model-data fusion techniques in studies of terrestrial carbon fluxes in two approaches: top-down approaches that use measurements of global CO2 concentration and sometimes other atmospheric constituents to infer carbon fluxes from the land surface, and bottom-up approaches that estimate carbon fluxes using process-based models. We consider applications of model-data fusion in flux estimation, parameter estimation, model error analysis, experimental design and forecasting. Significant prog..

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University of Melbourne Researchers


Funding Acknowledgements

We thank the financial support of this work by CSIRO for YPW, CMT and IGE, the Australian Department of Climate Change for YPW and the Australian Research Council to the Centre of Excellence for Mathematics and Statistics of Complex Systems (MASCOS) for IGE. Dr Ray Leuning and Professor Yiqi Luo provided constructive comments on the paper.