The Respondence of Wave on Sea Surface Temperature in the Context of Global Change

Several aspects of global climate change, e.g., the rise sea level and water temperature anomalies, suggest advantages studying wave distributions. In this study, WAVEWATCH-III (WW3) (version 6.07), which is a well-known numerical model, was employed for simulating waves over seas from 1993–2020. The European Centre Medium-Range Weather Forecasts (ECMWF), Copernicus Marine Environment Monitoring Service (CMEMS), current were used as forcing fields in WW3 model. validation modelling simulations against measurements National Data Buoy Center (NDBC) buoys Haiyang-2B (HY-2B) altimeter yielded root mean square error (RMSE) 0.49 m 0.63 m, with correlation (COR) 0.89 0.90, respectively. terms calculated by WW3-simulated waves, i.e., breaking nonbreaking radiation stress, Stokes drift, included simulation circulation model named Stony Brook Parallel Ocean Model (sbPOM). simulated 2005–2015 using high-quality Simple Assimilation (SODA) data. sbPOM-simulated results obtained Array Real-time Geostrophic Oceanography (Argo) RMSE 1.12 °C COR 0.99. By seasonal variation, interrelation currents, anomaly, significant heights (SWHs) strong Indian Ocean. areas, distribution consistent SWHs. monthly variation SWHs, surface elevation, anomalies revealed that upward trends SWHs 1993–2015 ocean. Ocean, obviously influenced SST wind stress. stress intensity enlarges growth wave-induced strengthen heat exchange at air–sea layer. It assumed oscillation had negative response to ocean 2005–2015. This feedback indicates could slow down amplitude warming.