Improvement of ocean state estimation by assimilating mapped Argo drift data

Area of Science:

• Oceanography
• Data Assimilation
• Climate Science

Background:

• Ocean state estimation is crucial for understanding global oceanic circulation.
• Subsurface ocean currents play a significant role in heat and salt transport.
• Argo floats provide valuable subsurface oceanographic data.

Purpose of the Study:

• To investigate the impact of assimilating mapped subsurface ocean currents into a global ocean state estimation system.
• To assess the representativeness of volume transport estimations with and without Argo current data.
• To evaluate the effectiveness of subsurface current data in improving ocean circulation models.

Main Methods:

• Two global ocean state estimations were performed using the K7 four-dimensional variational data assimilation system.
• One estimation incorporated climatological geostrophic currents from Argo floats at 1000 dbar depth.
• Volume transport was assessed to evaluate the impact of assimilated current data.

Main Results:

• Assimilation of Argo subsurface current data had subtle impacts on estimated volume transports.
• The strongest effects were observed in the subtropical North Pacific.
• Corrections at 10°N involved offsetting wind stress curl and Rossby wave adjustment.

Conclusions:

• Subsurface ocean current data, even from a single depth, can effectively improve global oceanic circulation estimation.
• Data assimilation of Argo float data offers a valuable method for refining ocean circulation models.
• This study underscores the importance of incorporating diverse oceanographic datasets for accurate climate modeling.