Automatic characterisation of Dansgaard-Oeschger events in palaeoclimate ice records

• Type: Summary of Presentation in an International Conference
• Date: 2023

Authors

Barbosa, SM (Author) FCUP; Maria Eduarda Silva (Author) FEP; Dias, N (Author) Other; Rousseau, D (Author) Other

Conference proceedings International

Title: EGU General Assembly 2023, Vienna

EGU General Assembly 2023

Vienna, 2023

Other information

Authenticus ID: P-00X-XVC

DOI: 10.5194/egusphere-egu23-3612

Abstract (EN): <jats:p>Greenland ice core records display abrupt transitions, designated as Dansgaard-Oeschger (DO) events, characterised by episodes of rapid warming (typically decades) followed by a slower cooling. The identification of abrupt transitions is hindered by the typical low resolution and small size of paleoclimate records, and their significant temporal variability. Furthermore, the amplitude and duration of the DO events varies substantially along the last glacial period, which further hinders the objective identification of abrupt transitions from ice core records Automatic, purely data-driven methods, have the potential to foster the identification of abrupt transitions in palaeoclimate time series in an objective way, complementing the traditional identification of transitions by visual inspection of the time series.In this study we apply an algorithmic time series method, the Matrix Profile approach, to the analysis of the NGRIP Greenland ice core record, focusing on:- the ability of the method to retrieve in an automatic way abrupt transitions, by comparing the anomalies identified by the matrix profile method with the expert-based identification of DO events;- the characterisation of DO events, by classifying DO events in terms of shape and identifying events with similar warming/cooling temporal patternThe results for the NGRIP time series show that the matrix profile approach struggles to retrieve all the abrupt transitions that are identified by experts as DO events, the main limitation arising from the diversity in length of DO events and the method&#8217;s dependence on fixed-size sub-sequences within the time series. However, the matrix profile method is able to characterise the similarity of shape patterns between DO events in an objective and consistent way.</jats:p>

Language: English

Type (Professor's evaluation): Scientific