Advances in conceptual modelling of the variable nature of Dansgaard-Oeschger events
This study introduces a novel dynamical systems model designed to capture the highly non-periodic nature of Dansgaard-Oeschger (DO) events. Such events are difficult to model adequately due to their variable durations — some lasting around a century, while others span multiple millennia &a...
| Main Authors: | , , , , , |
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| Format: | Text |
| Language: | English |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://doi.org/10.5194/egusphere-2024-2156 https://egusphere.copernicus.org/preprints/2024/egusphere-2024-2156/ |
| Summary: | This study introduces a novel dynamical systems model designed to capture the highly non-periodic nature of Dansgaard-Oeschger (DO) events. Such events are difficult to model adequately due to their variable durations — some lasting around a century, while others span multiple millennia — and the occurrence of short precursor events that precede the longer DO events despite similar boundary climate conditions. Utilizing a simplified two-equation framework derived from the Stommel model, our approach integrates an internal control parameter which acts as a feedback parameter on the Antarctic Bottom Water (AABW) formation. Through both analytical and numerical methods, we establish a suitable parameter domain within which the newly adjusted models can accurately replicate the paleoclimatic records of DO events as described by summary statistics derived from ice-core data. The analysis also shows that without the novel control parameter, the model does not have a suitable parameter domain in which it can reproduce the wide range of event characteristics seen in the ice-core record. The study provides new insights into the underlying mechanisms driving these highly significant climate phenomena and the necessary timescale in which they are forced, by allowing the new model's parameters to vary through time. This allows our model to achieve unprecedented precision in capturing a realistic sequence of DO events with timing characteristics matching those of the observational record. This refined model not only enhances our understanding of the DO cycles but also demonstrates the potential of simple dynamical systems to simulate complex climate interactions. |
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