DataSheet_1_Spatio-temporal variability of surface turbulent heat flux feedback for mesoscale sea surface temperature anomaly in the global ocean.docx

• Main Authors: Man Yuan, Furong Li, Xiaohui Ma, Peiran Yang
• Format: Dataset
• Language: unknown
• Published: 2022
• Subjects: Oceanography; Marine Biology; Marine Geoscience; Biological Oceanography; Chemical Oceanography; Physical Oceanography; Marine Engineering; surface turbulent heat flux feedback; mesoscale; spatio-temporal variability; geographically and temporally weighted regression; marine atmospheric boundary layer adjustment; Antarctic; The Antarctic; Antarc*
• Online Access: https://doi.org/10.3389/fmars.2022.957796.s001; https://figshare.com/articles/dataset/DataSheet_1_Spatio-temporal_variability_of_surface_turbulent_heat_flux_feedback_for_mesoscale_sea_surface_temperature_anomaly_in_the_global_ocean_docx/21274152

The surface turbulent heat flux feedback α T plays an important role in the atmosphere–ocean coupling. However, spatio-temporal variability of α T for sea surface temperature anomaly (SSTA) at oceanic mesoscales in the global ocean remains poorly assessed. In this study, we tackle this issue using an advanced statistical model, i.e., the geographically and temporally weighted regression model. The estimated time-mean α T for mesoscale SSTA generally ranges from 10 to 50 W/(m 2 K) within 70°S–70°N, except in the Antarctic coastal region where its value drops to zero. The α T is larger in the tropics than in off-tropical regions and locally enhanced in the equatorial cold tongues, western boundary currents, and their extensions. The spatial structure α T is primarily attributed to the non-linearity in the Clausius–Clapeyron relation and inhomogeneity in the background wind speed, whereas adjustment of surface wind speed, air temperature, or moisture to mesoscale SSTA plays an important role in the regional variability. There is an evident seasonal cycle of α T in the tropics and under the northern hemisphere’s storm tracks. The former is due to the seasonally varying response of surface wind speed to mesoscale SSTA, and the latter results from the seasonality of atmospheric and oceanic background states. Our analysis reveals prominent spatio-temporal variability of α T for mesoscale SSTA governed by complicated dynamics.