Tropical wildfires account for up to 93% of global burnt area and approximately 85% of the resulting carbon emissions, yet are significantly under-represented in existing fire models. These models are predominantly process-based, require a multitude of input datasets, parameters and calculations, and are difficult to reproduce or use independently from a dynamic global vegetation model (DGVM). The aim of this thesis is to develop empirical parameterisations of tropical fire occurrence and spread that represent an improvement in accuracy over existing models and that can be easily implemented both as standalone models or within a DGVM. These models are based on well-documented relationships from the literature. An index of potential fire is produced based on the observed peak of fire activity at intermediate levels of productivity and aridity. This can be converted into expected fire counts using a simple, observation-derived parameter map. Fire sizes have been shown to follow an approximately fractal distribution in a range of ecosystems, which is used to develop a new burnt area model. Replacing the fire count and burnt area calculations of existing fire models with these new parameterisations improves the spatial distribution of the resulting estimates, while giving temporally comparable predictions to the original models. The magnitude of the resulting burnt area estimates is also improved. The use of empirical fire modelling is therefore a viable alternative to current process-based methods, and makes practical use of theories that are well-documented in the literature. These models require few input variables and can be easily incorporated into a DGVM. However, further work to improve the temporal accuracy and dynamicity of these models would be beneficial, as would a method to link these models to parameterisations of combustion and trace gas emissions.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:633966 |
| Date | January 2014 |
| Creators | Fletcher, Imogen Nancy |
| Contributors | Friedlingstein, Pierre; Aragão, Luiz |
| Publisher | University of Exeter |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/10871/16207 |
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