Effects of Periodic Tidal Elevations on the Air-Sea Momentum and Turbulent Heat Fluxes in the East China Sea

ATMOSPHERE(2022)

Cited 2|Views10
No score
Abstract
Using bulk formulas, two-year platform (fastened to the seabed) hourly observations from 2016 to 2017 in the East China Sea (121.6 degrees E, 32.4 degrees N) are used to investigate the role of the tide-induced surface elevation in changing the fixed observational height and modifying the momentum and air-sea turbulent heat fluxes. The semidiurnal tide-dominated elevation anomalies ranging from -3.6 to 3.9 m change the fixed platform observational height. This change causes hourly differences in the wind stress and latent and sensible heat fluxes between estimates with and without considering surface elevation, with values ranging from -1.5 x 10(-3) Nm(-2), -10.2 Wm(-2), and -3.6 Wm(-2) to 2.2 x 10(-3) Nm(-2), 8.4 Wm(-2), and 4.6 Wm(-2), respectively. More significant differences occur during spring tides. The differences show weak dependence on the temperature, indicating weak seasonal variations. The mean (maximum) difference percentage relative to the mean magnitude is approximately 3.5% (7%), 1.5% (3%), and 1.5% (3%) for the wind stress and latent and sensible heat fluxes, respectively. The boundary layer stability (BLS) can convert from near-neutral conditions to stable and unstable states in response to tide-induced changes in the observational height, with a probability of occurrence of 2%. Wind anomalies play dominant roles in determining the hourly anomalies of the latent heat flux, regardless of the state of the BLS. Extreme cases, including the cold air outbreak in 2016, tropical cyclones Meranti in 2016, and Ampil in 2018, are also examined. This study will facilitate future observation-reanalysis comparisons in the studied coastal region where ocean-atmosphere-land interactive processes are significant.
More
Translated text
Key words
air-sea turbulent heat fluxes, tidal processes, wind stress, boundary layer stability, platform observations
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined