Quantifying uncertainty in the biospheric carbon flux for England and Wales

• Published in: Journal of the Royal Statistical Society. Series A, Statistics in society Vol. 171; no. 1; pp. 109 - 135
• Main Authors: Kennedy, Marc, Anderson, Clive, O'Hagan, Anthony, Lomas, Mark, Woodward, Ian, Gosling, John Paul, Heinemeyer, Andreas
• Format: Journal Article
• Language: English
• Published: Oxford, UK Oxford, UK : Blackwell Publishing Ltd 01.01.2008; Blackwell Publishing Ltd; Blackwell Publishing; Blackwell; Royal Statistical Society
• Series: Journal of the Royal Statistical Society Series A
• Subjects: Agricultural soils; Applications; Biosphere; Carbon; Carbon flux; Cell aggregates; Climate change; Climate models; Computer experiments; Data collection; Dynamic vegetation models; Emulation; England; Exact sciences and technology; Gaussian process; General topics; Global analysis, analysis on manifolds; Grasses; Grassland soils; Land cover; Mathematics; Meritocracy; Modeling; Multivariate analysis; Net biome productivity; Panel data; Probability and statistics; Sciences and techniques of general use; Sensitivity analysis; Standard deviation; Statistical analysis; Statistical methods; Statistics; Topology. Manifolds and cell complexes. Global analysis and analysis on manifolds; Uncertainty analysis; United Kingdom; Vegetation; Wales; England; United Kingdom; Great Britain; Europe; Wales; Correlation; Net biome productivity; Dynamic vegetation models; Computation code; Carbon flux; Multivariate analysis; Computer experiments; Emulation; Marginal distribution; Standard deviation; Dynamic model; Uncertainty analysis; Bayes estimation; Productivity; Sensitivity analysis; Prior distribution; Statistical association; Statistical estimation; Statistical method; Soils; Climate change; Gaussian process; Correlation analysis; Gaussian processes; Application
• ISSN: 0964-1998; 1467-985X
• DOI: 10.1111/j.1467-985X.2007.00489.x

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.