The tropical Atlantic exhibits significant ocean variability from daily to decadal time scales, driven by complex ocean dynamics and air-sea interactions. This session is devoted to advancing the understanding of these dynamics and their climatic impacts on both adjacent and remote regions, including their interactions with other tropical basins. In addition, we are interested in the effects of climate change and variability modes on the tropical Atlantic, with a particular focus on impacts on marine ecosystems.
Relevant ocean processes include upper and deep ocean circulation, eddies, tropical instability waves, mixing, and upwellings. For air-sea interactions, we welcome studies analyzing the seasonal cycle, marine heat waves, the development of variability modes on local to basin scale (e.g., Atlantic, Dakar and Benguela Niños, Atlantic Meridional Mode and South Atlantic Ocean Dipole) and interbasin teleconnections. Wind variations related to high-frequency events, cyclones, convective systems and those shaping air-sea coupled modes are encouraged.
Finally, we seek for studies that explore the causes and impacts of systematic model errors in simulating the local to regional Atlantic climate variability. Submissions based on direct observations, reanalysis, model simulations and machine learning techniques are welcome.
Relevant ocean processes include upper and deep ocean circulation, eddies, tropical instability waves, mixing, and upwellings. For air-sea interactions, we welcome studies analyzing the seasonal cycle, marine heat waves, the development of variability modes on local to basin scale (e.g., Atlantic, Dakar and Benguela Niños, Atlantic Meridional Mode and South Atlantic Ocean Dipole) and interbasin teleconnections. Wind variations related to high-frequency events, cyclones, convective systems and those shaping air-sea coupled modes are encouraged.
Finally, we seek for studies that explore the causes and impacts of systematic model errors in simulating the local to regional Atlantic climate variability. Submissions based on direct observations, reanalysis, model simulations and machine learning techniques are welcome.