Marine Heatwaves in a Changing Southern Ocean: Heat Budget Analysis in Modular Ocean Model v4p1 (ESM2M GFDL) and Causal Inference through Convergent Cross Mapping
[Description of methods used for collection/generation of data] For the heat budget analysis, we utilized temperature tendency terms available in the Modular Ocean Model version 4p1 (MOM4p1). Heat flux anomalies (in W m-2) for each term were averaged over a time step at a given ocean grid cell, foll...
| Autores: | , , , |
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| Tipo de recurso: | conjunto de datos |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/360285 |
| Acceso en línea: | http://hdl.handle.net/10261/360285 https://doi.org/10.20350/digitalCSIC/16360 |
| Access Level: | acceso abierto |
| Palabra clave: | Heat Budgets MOM4p1 Causal Inference Convergent Cross Mapping marine heatwaves |
| Sumario: | [Description of methods used for collection/generation of data] For the heat budget analysis, we utilized temperature tendency terms available in the Modular Ocean Model version 4p1 (MOM4p1). Heat flux anomalies (in W m-2) for each term were averaged over a time step at a given ocean grid cell, following Griffies et al. (2015). Subsequently, we calculated anomalies for each heat term relative to their seasonal cycles. These anoalies were then averaged separately over the days corresponding to the onset phase (i.e., heat build-up) and the decay phase (i.e., heat dissipation) of the marine heatwaves (MHWs). To study causal interactions between the physical variables (Max. SSTA, SIC, and MLD) and net primary production (NPP) rates, we applied Dynamic Empirical Modelling (EDM). Specifically, we utilised the Convergent Cross Mapping (CCM) method, as defined by Sugihara et al. (2012). Following a sensitivity test, we adjusted the time delays (τ) and embedding dimension (E) to 3 and 6, respectively. |
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