Mohanty, Sweety, Kazempour, Daniyal, Patara, Lavinia and Kröger, Peer (2023) Interactive Detection and Visualization of Ocean Carbon Regimes. [Paper] In: 18th International Symposium on Spatial and Temporal Data, SSTD 2023. , 23.-25.08.2023, Calgary, Canada . Proceedings of the 18th International Symposium on Spatial and Temporal Data. ; pp. 171-174 . DOI 10.1145/3609956.3609973.

Full text not available from this repository. (Contact)

Abstract

Our research focuses on the detection of ocean carbon uptake regimes that are critical in the context of comprehending climate change. One observation among geoscientific data in Earth System Sciences is that the datasets often contain local and distinct statistical distributions posing a major challenge in applying clustering algorithms for data analysis. The use of global parameters in many clustering algorithms is often inadequate to capture such local distributions. In this study, we propose a novel tool to detect and visualize oceanic carbon uptake clusters. We implement a distance-variance selection method (augmented by BIC scores) on agglomerative hierarchical clustering constructed upon a regional multivariate linear regression model set. Instead of relying on a global distance, users can select the local distance and variance thresholds on our tool to detect the connections on the dendrograms that stand as potential clusters by considering both compactness and similarity.

Document Type:	Conference or Workshop Item (Paper)
Keywords:	dendrograms; multivariate-linear regression; ocean carbon regime
Research affiliation:	OceanRep > GEOMAR > FB1 Ocean Circulation and Climate Dynamics > FB1-OD Ocean Dynamics
Publisher:	Association for Computing Machinery
Related URLs:	Data link SCOPUS
Projects:	Opendap
Expeditions/Models/Experiments:	Numerical Model ORCA025.L46.LIM2vp.CFCSF6.MOPS.JRA.LP04-KLP002.hind
International?:	Yes
Date Deposited:	28 Sep 2023 11:08
Last Modified:	28 Nov 2023 15:06
URI:	https://oceanrep.geomar.de/id/eprint/59226

Actions (login required)

View Item