Data Assimilation, Tipping Events, and the Importance of Underlying Dynamics. ...
Tipping points in a system have particular significance in the context of climate science. Events such as Amazon rainforest die-back, West African monsoon shift, and Arctic sea ice loss are all thought to have an underlying tipping point, beyond which the system will not recover. Mathematically, tip...
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| Format: | Doctoral or Postdoctoral Thesis |
| Language: | English |
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University of Surrey
2020
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| Online Access: | https://dx.doi.org/10.15126/thesis.900087 https://openresearch.surrey.ac.uk/esploro/outputs/doctoral/99593523502346 |
| Summary: | Tipping points in a system have particular significance in the context of climate science. Events such as Amazon rainforest die-back, West African monsoon shift, and Arctic sea ice loss are all thought to have an underlying tipping point, beyond which the system will not recover. Mathematically, tipping can be understood using a dynamical systems analysis of a model, and there are geophysical models which have been found to have a specific mathematical feature which can cause tipping (a saddle-node bifurcation). Empirical data suggests there are more such systems. Systems with this feature will have strongly non-linear behaviour close to the tipping point, which can cause issues for data assimilation methods. This thesis considers the effect of a saddle-node bifurcation in two strands: in the context of real-world tipping events, and; in the context of data assimilation. In the first strand, the effect of successive annual droughts on a carbon cycle model of a forest is considered. The resilience of the ... |
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