Physical and biogeochemical forcing of oxygen and nitrate changes during El Niño/El Viejo and La Niña/La Vieja upper-ocean phases in the tropical eastern South Pacific along 86° W

Abstract. Temporal changes in the water mass distribution and biogeochemical signals in the tropical eastern South Pacific are investigated with the help of an extended optimum multi-parameter (OMP) analysis, a technique for inverse modeling of mixing and biogeochemical processes through a multidimensional least-square fit. Two ship occupations of a meridional section along 85°50' W from 14° S to 1° N are analysed during relatively warm (El Niño/El Viejo, March 1993) and cold (La Niña/La Vieja, February 2009) upper-ocean phases. The largest El Niño–Southern Oscillation (ENSO) impact was found in the water properties and water mass distribution in the upper 200 m north of 10° S. ENSO promotes the vertical motion of the oxygen minimum zone (OMZ) associated with the hypoxic equatorial subsurface water (ESSW). During a cold phase the core of the ESSW is found at shallower layers, replacing shallow (top 200 m) subtropical surface water (STW). The heave of isopycnals due to ENSO partially explains the intrusion of oxygen-rich and nutrient-poor antarctic intermediate water (AAIW) into the depth range of 150–500 m. The other cause of the AAIW increase at shallower depths is that this water mass flowed along shallower isopycnals in 2009. The shift in the vertical location of AAIW reaching the OMZ induces changes in the amount of oxygen advected and respired inside the OMZ: the larger the oxygen supply, the greater the respiration and the lower the nitrate loss through denitrification. Variations in the intensity of the zonal currents in the equatorial current system, which ventilates the OMZ from the west, are used to explain the patchy latitudinal changes of seawater properties observed along the repeated section. Significant changes reach down to 800 m, suggesting that decadal variability (Pacific decadal oscillation) is also a potential driver in the observed variability.