Information Services banner Edinburgh Research Archive The University of Edinburgh crest

Edinburgh Research Archive >
Geosciences, School of >
Global Change Research Institute >
Global Change Research Institute PhD thesis collection >

Please use this identifier to cite or link to this item: http://hdl.handle.net/1842/2201

This item has been viewed 17 times in the last year. View Statistics

Files in This Item:

File Description SizeFormat
PhD thesis MASTER 002.007.pdfOpen Access version3.2 MBAdobe PDFView/Open
Hill T C files.zipOriginal files are available to ERA administrators only2.29 MBZip file
Title: A modelling approach to carbon, water and energy feedbacks and interactions across the land-atmosphere interface.
Authors: Hill, Timothy C
Supervisor(s): Williams, Mat
Moncrieff, John
Woodward, Ian
Issue Date: 2007
Abstract: The climate is changing and the rate of this change is expected to increase. In the 20th century global surface temperatures rose by 0.6 (±0.2) K. Based on current model predictions, and economic forecasts, global temperature increases of 1.4 to 5.8 K are expected over the period 1990 – 2100. One of the main drivers for this temperature increase is the build up of CO2 in the atmosphere which has been increasing since pre-industrial times. Pre-industrial concentrations of CO2 were bounded between 180 ppm and 300 ppm, however the current concentrations of 380 ppm are far in excess of these bounds. Further more, forecasts indicates that a further doubling in the next century is a distinct possibility. However making predictions about the future climate is difficult. Predicting the trajectory that the climate will take uses assumptions of economic growth, technological advances and ecological and physical processes. If we are to make informed decisions regarding the future of the planet, we have to account not only for future anthropogenic emissions and land use, but we also have to identify the response of the Earth system. By its very nature the Earth is immensely complex; processes, interactions and feedbacks exist which operate on vastly different spatial and temporal scales. Each of these processes has an associated level of uncertainty. This uncertainty propagates through models and the processes and feedbacks they simulate. One of our jobs as environmental scientists is to quantify and then reduce these uncertainties. Consequently it is critical to quantify the interactions of the land-surface and the atmosphere. The role of the land-surface is critical to the response of the Earth’s climate. All general circulation models and regional scale models need representations of the land-surface. A lot of the work concerning the land-surface aims to determine the land-surface partitioning of energy, the evapotranspiration of water and if the land-surface is a sink or a source of CO2. To do achieve this we need to understand (1) the underlying processes governing the response of the land-surface, (2) the response of these processes to perturbations from climate change and humans, (3) the temporal and spatial heterogeneity in these processes, and (4) the feedbacks that land-surface processes have with the climate. In this thesis I use a coupled atmosphere-biosphere model to show current understanding of the carbon, water and energy dynamics of the biosphere and the atmosphere to be consistent with both PBL and stand-based measurements. I then use the CAB model to investigate the strength of different feedbacks between the atmosphere and biosphere. Finally the model is then used in a Monte Carlo Bayesian inversion scheme to invert atmospheric measurements to infer information about surface parameters.
Keywords: Geoscience
Climate modelling
URI: http://hdl.handle.net/1842/2201
Appears in Collections:Global Change Research Institute PhD thesis collection

Items in ERA are protected by copyright, with all rights reserved, unless otherwise indicated.

 

Valid XHTML 1.0! Unless explicitly stated otherwise, all material is copyright © The University of Edinburgh 2013, and/or the original authors. Privacy and Cookies Policy