final_program_abstracts[1]

11 IMSC Session Program
Climate variability and its effect on the terrestrial biosphere
Monday - Poster Session 9
Lindsay Collins and Clive Anderson
University of Sheffield, UK
Climate change is the most important environmental issue of the 21st century, with
profound societal impacts. International strategies to mitigate climate change rely on
predictions on the fluxes of greenhouse gases (especially carbon dioxide) between
atmosphere, oceans and the terrestrial biosphere. Of these fluxes, that between the
atmosphere and vegetation and soils is the most complex and the least well quantified.
A central strategy for estimating and predicting terrestrial carbon dynamics
encapsulates knowledge of ecological and soil processes in a computer model, known
as dynamic global vegetation model (DGVM), and uses the model to synthesise data
and process understanding to predict carbon fluxes. Climate variables are major
drivers of DGVMs and potentially a major source of uncertainty in derived carbon
flux estimates.
Here we bring together carbon modelling and statistical methods to identify the
sources of uncertainty in the DGVM carbon fluxes with respect to the climate and the
weather. The Sheffield Dynamic Global Vegetation Model (SDGVM) is used in this
study. Dynamic linear models are used to measure the variability in the climate across
the UK according to the SDGVM driving data. Bayesian sensitivity analysis is then
used in the framework of Gaussian process emulation to estimate the uncertainty in
the UK carbon flux estimates with respect to the climate and weather variability.
Abstracts 52