共 77 条
Variability in the coupling between sea surface temperature and wind stress in the global coastal ocean
被引:24
作者:
Wang, Yuntao
[1
,2
]
Castelao, Renato M.
[1
]
机构:
[1] Univ Georgia, Dept Marine Sci, Marine Sci Bldg, Athens, GA 30602 USA
[2] Natl Marine Fisheries Serv, NOAA, Silver Spring, MD USA
关键词:
Air-sea interaction;
Coupling coefficient;
SST;
SST gradient;
Fronts;
Wind stress;
CALIFORNIA CURRENT SYSTEM;
NUMERICAL WEATHER PREDICTION;
MESOSCALE EDDIES;
INTERANNUAL VARIABILITY;
SATELLITE MEASUREMENTS;
NORTHERN CALIFORNIA;
UPWELLING SYSTEM;
SEASONAL CYCLE;
SOUTHERN-OCEAN;
ARABIAN SEA;
D O I:
10.1016/j.csr.2016.07.011
中图分类号:
P7 [海洋学];
学科分类号:
0707 ;
摘要:
Mesoscale ocean-atmosphere interaction between sea surface temperature (SST) and wind stress throughout the global coastal ocean was investigated using 7 years of satellite observations. Coupling coefficients between crosswind SST gradients and wind stress curl and between downwind SST gradients and wind stress divergence were used to quantify spatial and temporal variability in the strength of the interaction. The use of a consistent data set and standardized methods allow for direct comparisons between coupling coefficients in the different coastal regions. The analysis reveals that strong coupling is observed in many mid-latitude regions throughout the world, especially in regions with strong fronts like Eastern and Western Boundary Currents. Most upwelling regions in Eastern Boundary Currents are characterized by strong seasonal variability in the strength of the coupling, which generally peaks during summer in mid latitudes and during winter at low latitudes. Seasonal variability in coastal regions along Western Boundary Currents is comparatively smaller. Intraseasonal variability is especially important in regions of strong eddy activity (e.g., Western Boundary Currents), being particularly relevant for the coupling between crosswind SST gradients and wind stress curl. Results from the analysis can be used to guide modeling studies, since it allows for the a priori identification of regions in which regional models need to properly represent the ocean-atmosphere interaction to accurately represent local variability. (C) 2016 Elsevier Ltd. All rights reserved.
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页码:88 / 96
页数:9
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