Tropical Atlantic Variability: Observations and Modeling
We review the state-of-the-art knowledge of Tropical Atlantic Variability (TAV). A well-developed observing system and sustained effort of the climate modeling community have improved our understanding of TAV. It is dominated by the seasonal cycle, for which some mechanisms have been identified. The...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-08-01
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| Series: | Atmosphere |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-4433/10/9/502 |
| _version_ | 1818983902571659264 |
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| author | William Cabos Alba de la Vara Shunya Koseki |
| author_facet | William Cabos Alba de la Vara Shunya Koseki |
| author_sort | William Cabos |
| collection | DOAJ |
| description | We review the state-of-the-art knowledge of Tropical Atlantic Variability (TAV). A well-developed observing system and sustained effort of the climate modeling community have improved our understanding of TAV. It is dominated by the seasonal cycle, for which some mechanisms have been identified. The interannual TAV presents a marked seasonality with three dominant modes: (i) the Atlantic Zonal Mode (AZM), (ii) the Atlantic Meridional Mode (AMM) and (iii) the variability in the Angola–Benguela Front (ABF). At longer time scales, the AMM is active and low-frequency variations in the strength, periodicity, and spatial structure of the AZM are observed. Also, changes in the mean position of the ABF occur. Climate models still show systematic biases in the simulated TAV. Their causes are model-dependent and relate to drawbacks in the physics of the models and to insufficient resolution of their atmospheric and oceanic components. The identified causes for the biases can have local or remote origin, involving the global ocean and atmospheric circulation. Although there is not a clear consensus regarding the role of model resolution in the representation of the TAV, eddy-resolving ocean models combined with atmospheric models with enhanced horizontal and vertical resolutions simulate smaller biases. |
| first_indexed | 2024-12-20T18:10:29Z |
| format | Article |
| id | doaj.art-05cc5fbfe8ee4fbcb131f758840fcb86 |
| institution | Directory Open Access Journal |
| issn | 2073-4433 |
| language | English |
| last_indexed | 2024-12-20T18:10:29Z |
| publishDate | 2019-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Atmosphere |
| spelling | doaj.art-05cc5fbfe8ee4fbcb131f758840fcb862022-12-21T19:30:29ZengMDPI AGAtmosphere2073-44332019-08-0110950210.3390/atmos10090502atmos10090502Tropical Atlantic Variability: Observations and ModelingWilliam Cabos0Alba de la Vara1Shunya Koseki2Department of Physics, University of Alcalá, 28805 Alcalá de Henares, SpainEnvironmental Sciences Institute, University of Castilla-La Mancha, Avenida Carlos III s/n, 45071 Toledo, SpainGeophysical Institute, University of Bergen and Bjerknes Centre for Climate Research, 5020 Bergen, NorwayWe review the state-of-the-art knowledge of Tropical Atlantic Variability (TAV). A well-developed observing system and sustained effort of the climate modeling community have improved our understanding of TAV. It is dominated by the seasonal cycle, for which some mechanisms have been identified. The interannual TAV presents a marked seasonality with three dominant modes: (i) the Atlantic Zonal Mode (AZM), (ii) the Atlantic Meridional Mode (AMM) and (iii) the variability in the Angola–Benguela Front (ABF). At longer time scales, the AMM is active and low-frequency variations in the strength, periodicity, and spatial structure of the AZM are observed. Also, changes in the mean position of the ABF occur. Climate models still show systematic biases in the simulated TAV. Their causes are model-dependent and relate to drawbacks in the physics of the models and to insufficient resolution of their atmospheric and oceanic components. The identified causes for the biases can have local or remote origin, involving the global ocean and atmospheric circulation. Although there is not a clear consensus regarding the role of model resolution in the representation of the TAV, eddy-resolving ocean models combined with atmospheric models with enhanced horizontal and vertical resolutions simulate smaller biases.https://www.mdpi.com/2073-4433/10/9/502Tropical Atlantic VariabilityTropical Atlantic climatesea-surface temperature biasesobservational dataclimate modeling |
| spellingShingle | William Cabos Alba de la Vara Shunya Koseki Tropical Atlantic Variability: Observations and Modeling Atmosphere Tropical Atlantic Variability Tropical Atlantic climate sea-surface temperature biases observational data climate modeling |
| title | Tropical Atlantic Variability: Observations and Modeling |
| title_full | Tropical Atlantic Variability: Observations and Modeling |
| title_fullStr | Tropical Atlantic Variability: Observations and Modeling |
| title_full_unstemmed | Tropical Atlantic Variability: Observations and Modeling |
| title_short | Tropical Atlantic Variability: Observations and Modeling |
| title_sort | tropical atlantic variability observations and modeling |
| topic | Tropical Atlantic Variability Tropical Atlantic climate sea-surface temperature biases observational data climate modeling |
| url | https://www.mdpi.com/2073-4433/10/9/502 |
| work_keys_str_mv | AT williamcabos tropicalatlanticvariabilityobservationsandmodeling AT albadelavara tropicalatlanticvariabilityobservationsandmodeling AT shunyakoseki tropicalatlanticvariabilityobservationsandmodeling |