ADCP's on gliders: features and applications.

Miguel Costa Tenreiro1, Enric Pallas Sanz1, Marco Julio Ulloa2, Jose Ochoa3, Thomas Meunier4, Angel Ruiz Angulo5, Julio Sheinbaum6, Julio Candela1, Simó Cusí7 and Sebastian Cisneros6, (1)Center for Scientific Research and Higher Education at Ensenada, Physical Oceanography, Ensenada, BJ, Mexico, (2)Instituto Politécnico Nacional, CICATA, Altamira, TM, Mexico, (3)CICESE, Ensenada, Baja Calif, Mexico, (4)WHOI, Physical Oceanography, Woods Hole, MA, United States, (5)Icelandic Meteorological Office, Reykjavik, Iceland, (6)CICESE, Physical Oceanography, Ensenada, BJ, Mexico, (7)Center for Scientific Research and Higher Education at Ensenada, Ensenada, BJ, Mexico
Abstract:
GMOG (Group of Monitoring the Ocean with Gliders) has been continuously monitoring Gulf of Mexico waters for the past three years using a fleet of seven highly instrumented Seagliders. The group has successfully finished 18 missions where physical and biochemical properties of the Gulf of Mexico have been measured with very high resolution. Together with CTD and biogeochemical sensors, an Acoustic Doppler Current Profiler (ADCP) have been mounted on GMOG’s Seaglider fleet. General dynamical features observed in three particular missions will be discussed: two current jets at the periphery of a cyclonic (mission 0008) and anticyclonic (mission 0011) regions observed in two virtual-mooring experiments near a deep water mooring deployed in the western Gulf of Mexico; and the vertical structure of the Campeche Gyre (mission 0017) is observed with different ADCP configurations and glider flight modes. The gliders were equipped with ADCPs for comparison/validation with the mooring data. GMOG’s capability to measure currents in near-real time using autonomous platforms and the relevance of acquiring horizontal velocity data to improve ocean circulation forecasts will be discussed. Near-real time velocity data sets provide nowadays crucial information to be assimilated by numerical modelers. Also targeted observations of horizontal velocity data are of great interest to understand coupled physical and biological processes, in particular, it will be shown that diel vertical migration can be detected from a moving platform.