Carbon Assimilation and Modelling of the European Land Surfaces

M. Scholze, P. Rayner, W. Knorr, T. Kaminski, R. Giering, and H. Widmann. Non-linear parameter optimisation of a terrestrial biosphere model using atm. CO2 observations: CCDAS. Geophysical Research Abstracts, 6:06281, 2004.
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M. Scholze, P. Rayner, W. Knorr, T. Kaminski, R. Giering, and H. Widmann. A global carbon cycle data assimilation system (CCDAS) to infer atmosphere-biosphere CO2 exchanges. Geophysical Research Abstracts, 6:07504, 2004. [ .pdf ] 

W. Knorr and J. Kattge. Inversion of terrestrial biosphere model parameter values against eddy covariance measurements using Monte Carlo sampling. submitted to Global Change Biology, 2004. [ .pdf ] 

T. Kaminski, R. Giering, M. Scholze, P. Rayner, and W. Knorr. A prototype of a data assimilation system based on automatic differentiation. Geophysical Research Abstracts, 5:11812, 2003. [ .ppt/.pdf | .pdf ] 

T. Kaminski, R. Giering, M. Scholze, P. Rayner, and W. Knorr. An example of an automatic differentiation-based modelling system. In V. Kumar, L. Gavrilova, C. J. K. Tan, and P. L'Ecuyer, editors, Computational Science - ICCSA 2003, International Conference Montreal, Canada, May 2003, Proceedings, Part II, volume 2668 of Lecture Notes in Computer Science, pages 95-104, Berlin, 2003. Springer. [ .ppt/.pdf | .pdf ]

The paper presents a prototype of a Carbon Cycle Data Assimilation System (CCDAS), which is composed of a terrestrial biosphere model (BETHY) coupled to an atmospheric transport model (TM2), corresponding derivative codes as well as a derivative-based optimisation routine. In calibration mode, we use first and second derivatives, to estimate model parameters and their uncertainties from atmospheric observations and their uncertainties. In prognostic mode, we use first derivatives, to map model parameters and their uncertainties onto prognostic quantities and their uncertainties.

 

M. Scholze. Model studies on the response of the terrestrial carbon cycle on climate change and variability. Examensarbeit, Max-Planck-Institut für Meteorologie, Hamburg, Germany, 2003. [ http | .pdf ]

M. Scholze, P. Rayner, W. Knorr, T. Kaminski, and R. Giering. A prototype Carbon Cycle Data Assimilation System (CCDAS): Inferring interannual variations of vegetation-atmosphere CO2 fluxes. Abstract CG62A-05. Eos Trans. AGU, 83(47), December 2002. [ .ppt/.pdf | http ] 

T. Kaminski, W. Knorr, P. Rayner, and M. Heimann. Assimilating atmospheric data into a terrestrial biosphere model: A case study of the seasonal cycle. Global Biogeochemical Cycles, 16(4):14-1-14-16, 2002. [ http | .ps.gz | .pdf ] 

T. Kaminski and M. Heimann. Inverse modeling of atmospheric carbon dioxide fluxes. Science, 294(5541):259, 2001. [ http | .ps.gz ] 

T. Kaminski, P. Rayner, M. Heimann, and I. Enting. On aggregation errors in atmospheric transport inversions. J. Geophys. Res., 106(D5):4703, 2001.
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Peter Rayner, Wolfgang Knorr, Marko Scholze, Ralf Giering, Thomas Kaminski, Martin Heimann, and Corinne Le Quere. Inferring terrestrial biosphere carbon fluxes from combined inversions of atmospheric transport and process-based terrestrial ecosystem models. In Proceedings of 6th Carbon dioxide conference at Sendai, pages 1015-1017, 2001. [ .pdf ]

This is the first document featuring the implementation of a carbon cycle data assimilation and prediction scheme, which is based on the terrestrial biosphere model BETHY

 

R. Giering. Tangent linear and adjoint biogeochemical models. In Prasad S. Kasibhatla, editor, Inverse Methods in Global Biogeochemical Cycles, volume 114, pages 33-48. American Geophysical Union, 2000.

 

M. Heimann and T. Kaminski. Inverse modeling approaches to infer surface trace gas fluxes from observed atmospheric mixing ratios. In A. F. Bouwman, editor, Approaches to scaling of trace gas fluxes in ecosystems, chapter 14, pages 275-295. Elsevier, Amsterdam, 1999. [ http | .ps.gz | .pdf ] 

T. Kaminski, M. Heimann, and R. Giering. A coarse grid three dimensional global inverse model of the atmospheric transport, 1, Adjoint model and Jacobian matrix. J. Geophys. Res., 104(D15):18,535-18,553, 1999. [ .ps.gz | .pdf ] 

T. Kaminski, M. Heimann, and R. Giering. A coarse grid three dimensional global inverse model of the atmospheric transport, 2, Inversion of the transport of CO₂ in the 1980s. J. Geophys. Res., 104(D15):18,555-18,581, 1999. [ .ps.gz | .pdf ] 

M. Heimann and T. Kaminski. Aktueller Forschungsschwerpunkt: Quellen und Senken des atmosphärischen Kohlendioxids. In Jahresbericht der MPG 1998. Max-Planck-Gesellschaft, Munich, Germany, 1999. [ .ps.gz | .pdf ] 

T. Kaminski, M. Heimann, and R. Giering. A matrix representation for an atmospheric transport model computed by its adjoint. In S.-E. Gryning and N. Chaumerliac, editors, Air Pollution Modelling and its Application XII, pages 247-255. Plenum Press, New York, 1998. [ .ps.gz ] 

T. Kaminski. On the benefit of the adjoint technique for inversion of the atmospheric transport employing carbon dioxide as an example of a passive tracer. PhD thesis, Max-Planck-Institut für Meteorologie, Hamburg, Germany, 1998.
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T. Kaminski, M. Heimann, and R. Giering. A global scale inversion of the transport of CO₂ based on a matrix representation of an atmospheric transport model. In R. Baum, I. Enting, R. Francey, M. Hopkins, and P. Holper, editors, Fifth International Carbon Dioxide Conference, pages 147-148. CSIRO Division of atmospheric research, Aspendale, Victoria, Australia, 1997. [ .ps.gz | .pdf ] 

T. Kaminski, R. Giering, and M. Heimann. Sensitivity of the seasonal cycle of CO₂ at remote monitoring stations with respect to seasonal surface exchange fluxes determined with the adjoint of an atmospheric transport model. Physics and Chemistry of the Earth, 21(5-6):457-462, 1996. [ .ps.gz | .pdf ]