Seasonal Variations in Eddy-Induced Atmospheric Perturbations in the South China Sea.

Autor: NINGNING ZHANG, JIAN LAN, YI YU, YOUGUANG ZHANG, YIJUN HE
Předmět:
Zdroj: Journal of Climate; Jan2024, Vol. 37 Issue 2, p551-567, 17p
Abstrakt: This study investigates the impact of eddy-induced sea surface temperature (SST) anomalies on the overlying atmosphere in the South China Sea, utilizing observational and reanalysis datasets. The results reveal that SST anomalies caused by anticyclonic or cyclonic eddies have a significant impact on the acceleration or deceleration of surface winds, with a stronger response in summer compared to winter. Moreover, atmospheric responses, such as heat flux, precipitation, and marine atmospheric boundary layer (MABL) depth above anticyclonic or cyclonic eddies, exhibit in-phase seasonal variations as surface winds. The study also explores the mechanisms leading to atmospheric response, pointing toward the vertical mixing mechanism as the dominant cause, supported by both the in-phase relationship between SST and surface wind anomalies and the linear relationship between the wind stress divergence anomaly and downwind SST gradient anomaly. Seasonal variations in coupling intensity are attributed to varying background atmospheric conditions, with more effective vertical turbulence mixing and stronger coupling intensity caused by more unstable MABL and enhanced largescale vertical wind shear during summer than winter. Besides, the atmosphere above eddies is under a quasi-equilibrium condition, in which the surface wind stress increases monotonically with the depth of MABL. Given that the MABL depth response to eddy-induced SST anomaly is stronger in summer than in winter, it is reasonable to expect a more intense wind response during this season. Thus, the MABL depth coupling works together with the vertical mixing mechanism to explain the proportional relationship between SST and wind anomalies, and why the atmospheric response is stronger in summer than in winter. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index