Tangents, adjoints and computational complexity in terrestrial carbon modelling

Authors

  • Ian Graham Enting

DOI:

https://doi.org/10.21914/anziamj.v52i0.3871

Keywords:

adjoint modelling

Abstract

Differentiation enters modelling through initialisation, calibration, sensitivity analysis and data assimilation. Automatic differentiation provides tools for augmenting models to calculate the derivatives. Adjoint transformations lead to computational gains in such analyses. The calculation of tangent models by operator overloading provides a reference case against which to assess such gains. This article uses a vector space representation to analyse how special localisation characteristics of the land surface within the earth system might change the computational complexity of calculating derivatives. References
  • B. D. Craven. Control and Optimization. Chapman and Hall, London, 1995.
  • I. G. Enting. Inverse Problems in Atmospheric Constituent Transport. CUP, Cambridge, UK, 2002.
  • I. G. Enting, D. M. Etheridge, and M. J. Fielding. A perturbation analysis of the climate benefit of geosequestration. Int. J. Greenhouse Gas Control, 2:289--296, 2008. doi:10.1016/j.ijggc.2008.02.005
  • R. Giering. Tangent linear and adjoint biogeochemical models. In P. Kasibhatla et al., editor, Inverse Methods in Global Biogeochemical Cycles. (Geophysical Monograph no. 114), pages 33--48. AGU, Washington, DC, 2000.
  • A. Griewank. Evaluating Derivatives: Principles and Techniques of Algorithmic Differentiation. SIAM, Philadelphia, 2000.
  • C. S. Potter, J. T. Randerson, C. B. Field, P. A. Matson, P. M. Vitousek, and H. A. Mooney. Terrestrial ecosystem production: A process model based on global satellite and surface data. Global Biogeochemical Cycles, 7:811--841, 1993. doi:10.1029/93GB02725
  • P. J. Rayner, M. Scholze, W. Knorr, T. Kaminski, R. Giering, and H. Widmann. Two decades of terrestrial carbon fluxes from a carbon cycle data assimilation system {(ccdas)}. Global Biogeochemical Cycles, 19:GB2026, 2005. doi:10.1029/2004GB002254
  • C. Rodenbeck. Estimating {co}$_2$ sources and sinks from atmospheric mixing ratio measurements using a global inversion of atmospheric transport. Max-Planck-Institut fur Biogeochemie: Technical Paper 6, 2005. http://www.bgc-jena.mpg.de/mpg/websiteBiogeochemie/Publikationen/Technical_Reports/tech_report6.pdf, 2005
  • W. Steffen, editor. Blueprint for Australian Carbon Cycle Research. Australian Greenhouse Office, Canberra, 2005. http://www.globalcarbonproject.org/global/pdf/Australia.CarbonBluePrint_2005.pdf
  • C. W. Straka. ADF95: Tool for automatic differentiation of a FORTRAN code designed for large numbers of independent variables. Comput. Phys. Commun., 168:123--139, 2005. doi:10.1016/j.cpc.2005.01.011
  • A. Tarantola. Inverse Problem Theory: Methods for Data Fitting and Model Parameter Estimation. SIAM, Philadelphia, 2005.
  • Y.-P. Wang, C. M. Trudinger, and I. G. Enting. A review of applications of model-data fusion to studies of terrestrial carbon fluxes at different scales. Agricultural and Forest Meteorology, 149:1829--1842, 2009. doi:10.1016/j.agrformet.2009.07.009

Published

2011-10-10

Issue

Section

Proceedings Computational Techniques and Applications Conference