Inversion of Atmospheric CO 2 Concentrations
309
capability and scientifi c understanding in the development of techniques that extract
the signifi cance of these data. Understanding the carbon cycle, with its characteristic
“complex systems” features of feedbacks, nonlinearity, and multiple timescales, creates a need to go beyond “business-as-usual” analyses.
ACKNOWLEDGMENTS
The Centre of Excellence for Mathematics and Statistics of Complex Systems
(MASCOS) is funded by the Australian Research Council. The author’s fellowship
at MASCOS is supported in part by CSIRO. Nathan Clisby of MASCOS provided
helpful comments on the manuscript. As with my book, the present account draws
on the work of many collaborators, both from CSIRO (and a number formerly with
CSIRO) and beyond. Particular thanks are due to Prof. Inez Fung. My recent thinking on trace gas inversions has been greatly stimulated by the lecturers and students
at the 2006 MSRI-NCAR workshop on Carbon Data Assimilation.
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