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Assimilating atmospheric data into a terrestrial biosphere model: A case study of the seasonal cycle

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http://pubman.mpdl.mpg.de/cone/persons/resource/persons62428

Kaminski,  T.
Department Biogeochemical Systems, Prof. M. Heimann, Max Planck Institute for Biogeochemistry, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons62440

Knorr,  W.
Department Biogeochemical Synthesis, Prof. C. Prentice, Max Planck Institute for Biogeochemistry, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons62402

Heimann,  M.
Department Biogeochemical Systems, Prof. M. Heimann, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Citation

Kaminski, T., Knorr, W., Rayner, P. J., & Heimann, M. (2002). Assimilating atmospheric data into a terrestrial biosphere model: A case study of the seasonal cycle. Global Biogeochemical Cycles, 16(4), 1066. doi:10.1029/2001GB001463.


Cite as: http://hdl.handle.net/11858/00-001M-0000-000E-CF1C-3
Abstract
This paper demonstrates a new method of assimilating atmospheric concentration data into terrestrial biosphere models. Using a combination of adjoint and tangent linear models of both the underlying biosphere model and the atmospheric transport model, we directly infer optimal model parameters and their uncertainties. We also compute biospheric fluxes and their uncertainties arising from these parameters. We demonstrate the method using the Simple Diagnostic Biosphere Model (SDBM) and data on the seasonal cycle of CO2 from 41 observing sites. In the model, the light-use efficiency for several biomes is well-constrained by concentration observations. Optimal values generally increase with latitude as required to match the seasonal cycle. Modeled Q(10) values are poorly constrained unless local flux measurements are also used. Values also increase with latitude but are less than the commonly assumed value of 2.