Quantifying uncertainty in the biospheric carbon flux for England and Wales

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Abstract:

Summary. 

A crucial issue in the current global warming debate is the effect of vegetation and soils on carbon dioxide (CO2) concentrations in the atmosphere. Vegetation can extract CO2 through photosynthesis, but respiration, decay of soil organic matter and disturbance effects such as fire return it to the atmosphere. The balance of these processes is the net carbon flux. To estimate the biospheric carbon flux for England and Wales, we address the statistical problem of inference for the sum of multiple outputs from a complex deterministic computer code whose input parameters are uncertain. The code is a process model which simulates the carbon dynamics of vegetation and soils, including the amount of carbon that is stored as a result of photosynthesis and the amount that is returned to the atmosphere through respiration. The aggregation of outputs corresponding to multiple sites and types of vegetation in a region gives an estimate of the total carbon flux for that region over a period of time. Expert prior opinions are elicited for marginal uncertainty about the relevant input parameters and for correlations of inputs between sites. A Gaussian process model is used to build emulators of the multiple code outputs and Bayesian uncertainty analysis is then used to propagate uncertainty in the input parameters through to uncertainty on the aggregated output. Numerical results are presented for England and Wales in the year 2000. It is estimated that vegetation and soils in England and Wales constituted a net sink of 7.55 Mt C (1 Mt C = 1012 g of carbon) in 2000, with standard deviation 0.56 Mt C resulting from the sources of uncertainty that are considered.

Keywords: Carbon flux; Climate change; Computer experiments; Dynamic vegetation models; Emulation; Gaussian process; Net biome productivity; Sensitivity analysis; Uncertainty analysis

Document Type: Research Article

DOI: http://dx.doi.org/10.1111/j.1467-985X.2007.00489.x

Affiliations: 1: University of Sheffield, UK 2: University of York, UK

Publication date: January 1, 2008

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