Modelling Aspects of Land-Atmosphere Interaction: Thermal Instability in Peatland Soils and Land Parameter Estimation Through Data Assimilation
Luke, Catherine M.
Date: 8 July 2011
Thesis or dissertation
Publisher
University of Exeter
Degree Title
PhD in Mathematics
Abstract
The land (or ‘terrestrial’) biosphere strongly influences the exchange of carbon,
energy and water between the land surface and the atmosphere. The size of the
land carbon store and the magnitude of the interannual variability of the carbon
exchange make models of the land surface a vital component in climate models.
This thesis ...
The land (or ‘terrestrial’) biosphere strongly influences the exchange of carbon,
energy and water between the land surface and the atmosphere. The size of the
land carbon store and the magnitude of the interannual variability of the carbon
exchange make models of the land surface a vital component in climate models.
This thesis addresses two aspects of land surface modelling: soil respiration and
phenology modelling, using different techniques with the goal of improving model
representation of land-atmosphere interaction. The release of heat associated with soil respiration is neglected in the vast majority
of large-scale models but may be critically important under certain circumstances.
In this thesis, the effect of this heat release is considered in two ways. Firstly, a
deliberately simple model for soil temperature and soil carbon, including biological
heating, is constructed to investigate the effect of thermal energy generated by
microbial respiration on soil temperature and soil carbon stocks, specifically in
organic soils. Secondly, the mechanism for biological self-heating is implemented
in the Joint UK Land Environment Simulator (JULES), in order to investigate the
impacts of the extra feedback in a complex model.
With the intention of improving estimates of the parameters governing modelled
land surface processes, a data assimilation system based on the JULES land surface
model is presented. The ADJULES data assimilation system uses information from the derivative of JULES (or adjoint) to search for a locally optimum parameter set
by calibrating against observations. In this thesis, ADJULES is used with satellite-derived
vegetation indices to improve the modelling of phenology in JULES.
Doctoral Theses
Doctoral College
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