cris.boxmetadata.label.title
Seasonal Variability of the Southern Tip of the Oxygen Minimum Zone in the Eastern South Pacific (30°-38°S): A Modeling Study
cris.boxmetadata.label.dateissued
01 browse.startsWith.months.december 2019
cris.boxmetadata.label.accesslevel
open access
cris.boxmetadata.label.resourcetype
journal article
cris.boxmetadata.label.authors
Pizarro-Koch M.
Pizarro O.
Dewitte B.
MONTES TORRES, IVONNE KATHERINE
Ramos M.
Paulmier A.
Garçon V.
cris.boxmetadata.label.publisher
Blackwell Publishing Ltd
cris.boxmetadata.label.abstract
We investigate the seasonal variability of the southern tip (30°–38°S) of the eastern South Pacific oxygen minimum zone (OMZ) based on a high horizontal resolution (1/12°) regional coupled physical-biogeochemical model simulation. The simulation is validated by available in situ observations and the OMZ seasonal variability is documented. The model OMZ, bounded by the contour of 45 μM, occupies a large volume (4.5x104 km3) during the beginning of austral winter and a minimum (3.5x104 km3) at the end of spring, just 1 and 2 months after the southward transport of the Peru-Chile Undercurrent (PCUC) is maximum and minimum, respectively. We showed that the PCUC significantly impacts the alongshore advection of dissolved oxygen (DO) modulating the OMZ seasonal variability. However, zonal transport of DO by meridionally alternating zonal jets and mesoscale eddy fluxes play also a major role in the seasonal and spatial variability of the OMZ. Consistently, a DO budget analysis reveals a significant contribution of advection terms to the rate of change of DO and the prominence of mesoscale variability within the seasonal cycle of these terms. Biogeochemical processes and horizontal and vertical mixing, associated with subgrid scale processes, play only a secondary role in the OMZ seasonal cycle. Overall, our study illustrates the interplay of mean and (mesoscale) eddy-induced transports of DO in shaping the OMZ and its seasonal cycle off Central Chile.
cris.boxmetadata.label.citationstartpage
8574
cris.boxmetadata.label.citationendpage
8604
cris.boxmetadata.label.volume
124
cris.boxmetadata.label.issue
12
cris.boxmetadata.label.language
English
cris.boxmetadata.label.ocdeknowledgeArea
Oceanografía, Hidrología, Recursos hídricos Astronomía Ingeniería oceanográfica
cris.boxmetadata.label.doi
cris.boxmetadata.label.scopusidentifier
2-s2.0-85076288734
cris.boxmetadata.label.source
Journal of Geophysical Research: Oceans
cris.boxmetadata.label.containerissn
21699275
cris.boxmetadata.label.sponsor
MP-K was supported by a Doctoral Scholarship from CONICYT (Ministry of Education, Chile). This study was partial funded by the FONDECYT projects: 11811872 leaded by OP, 1140845 leaded by MR and 1151185 leaded by BD. BD acknowledges support from Fondecyt (project 1190276). Funds from the Instituto Milenio de Oceanografía, Chile (ICM grant IC 120019), COPAS Sur-Austral CONICYT PIA APOYO CCTE AFB170006 and project CRN3070-IAI (US national science Foundation; grant GEO-11280040), and the financial support for MP-K internships at LEGOS and IGP from the REDOC.CTA (Red Doctoral en Ciencia, Tecnología y Ambiente, University of Concepción, Chile) are also acknowledged. BD, OP and MR also acknowledge supports from FONDECYT 1171861. The university of Concepcion and the “Fondo de Investigación Pesquera” (FIP; MOBIO-BIO program) provided in situ data. The authors acknowledge: MODIS-Aqua for providing SST and chlorophyll satellite data (http://oceancolor.gsfc.nasa.gov); AVISO for altimeter products (http://marine.copernicus.eu); CARS for climatological data (www.marine.csiro.au/~dunn/ cars2009/). Cruise data used in Figures, and and mooring data used in Figure are freely available under request to the Chilean National Center for Hydrographic and Oceanographic Data (Centro Nacional de Datos Hidrográficos y Oceanográficos de Chile; http://www.shoa.cl/n_cendhoc/). ROMS model code is available at http://www.croco-ocean.org. All input data set and configuration of our ROMS/BIOEBUS simulations are described in section and in the references therein. This work was granted access to the HPC resources of CALMIP supercomputing center at the Toulouse University under the allocations 2017-1044 and 2018-1044. MP‐K was supported by a Doctoral Scholarship from CONICYT (Ministry of Education, Chile). This study was partial funded by the FONDECYT projects: 11811872 leaded by OP, 1140845 leaded by MR and 1151185 leaded by BD. BD acknowledges support from Fondecyt (project 1190276). Funds from the Instituto Milenio de Oceanografía, Chile (ICM grant IC 120019), COPAS Sur‐Austral CONICYT PIA APOYO CCTE AFB170006 and project CRN3070‐IAI (US national science Foundation; grant GEO‐11280040), and the financial support for MP‐K internships at LEGOS and IGP from the REDOC.CTA (Red Doctoral en Ciencia, Tecnología y Ambiente, University of Concepción, Chile) are also acknowledged. BD, OP and MR also acknowledge supports from FONDECYT 1171861. The university of Concepcion and the “Fondo de Investigación Pesquera” (FIP; MOBIO‐BIO program) provided data. The authors acknowledge: MODIS‐Aqua for providing SST and chlorophyll satellite data (http://oceancolor.gsfc.nasa.gov); AVISO for altimeter products (http://marine.copernicus.eu); CARS for climatological data (www.marine.csiro.au/~dunn/ cars2009/). Cruise data used in Figures , and and mooring data used in Figure are freely available under request to the Chilean National Center for Hydrographic and Oceanographic Data (Centro Nacional de Datos Hidrográficos y Oceanográficos de Chile; http://www.shoa.cl/n_cendhoc/ ). ROMS model code is available at http://www.croco‐ocean.org . All input data set and configuration of our ROMS/BIOEBUS simulations are described in section and in the references therein. This work was granted access to the HPC resources of CALMIP supercomputing center at the Toulouse University under the allocations 2017‐1044 and 2018‐1044. in situ
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