Investigating spatial differentiation of model parameters in a carbon cycle data assimilation system

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Better estimates of the net exchange of CO(2) between the atmosphere and the terrestrial biosphere are urgently needed to improve predictions of future CO(2) levels in the atmosphere. The carbon cycle data assimilation system (CCDAS) offers the capability of inversion, while it is at the same time based on a process model that can be used independent of observational data. CCDAS allows the assimilation of atmospheric CO(2) concentrations into the terrestrial biosphere model BETHY, constraining its process parameters via an adjoint approach. Here, we investigate the effect of spatial differentiation of a universal carbon balance parameter of BETHY on posterior net CO(2) fluxes and their uncertainties. The parameter, beta, determines the characteristics of the slowly decomposing soil carbon pool and represents processes that are difficult to model explicitly. Two cases are studied with an assimilation period of 1979 to 2003. In the base case, there is a separate beta for each plant functional type (PFT). In the regionalization case, beta is differentiated not only by PFT, but also according to each of 11 large continental regions as used by the TransCom project. We find that the choice of spatial differentiation has a profound impact not only on the posterior (optimized) fluxes and their uncertainties, but even more so on the spatial covariance of the uncertainties. Differences are most pronounced in tropical regions, where observations are sparse. While regionalization leads to an improved fit to the observations by about 20% compared to the base case, we notice large spatial variations in the posterior net CO(2) flux on a grid cell level. The results illustrate the need for universal process formulations in global-scale atmospheric CO(2) inversion studies, at least as long as the observational network is too sparse to resolve spatial fluctuations at the regional scale.


External organisations
  • University of Bristol
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Physical Geography
Original languageEnglish
Pages (from-to)GB2021
JournalGlobal Biogeochemical Cycles
Publication statusPublished - 2011
Publication categoryResearch