Output data for extended optimum multiparameter analysis (OMP) SR3 2018

• Other Authors: Data Officer (distributor), IMAS Data Manager (hasAssociationWith), Institute for Marine and Antarctic Studies (IMAS), University of Tasmania (UTAS) (resourceProvider), Instituto de Investigaciones Marinas: Vigo, Pontevedra, ES (hasAssociationWith), Pardo, Paula Conde (hasPrincipalInvestigator), Traill, Christopher (author), Traill, Christopher (hasPrincipalInvestigator)
• Format: Dataset
• Language: unknown
• Published: University of Tasmania, Australia
• Subjects: oceans; BIOGEOCHEMICAL CYCLES; EARTH SCIENCE; OCEAN CHEMISTRY; DATA ANALYSIS AND VISUALIZATION; EARTH SCIENCE SERVICES; Marine Geoscience; EARTH SCIENCES; GEOLOGY; Chemical Oceanography; OCEANOGRAPHY; Bottom_Depth; Pressure (measured variable) in the water body exerted by overlying sea water only; Temperature of the water body; potential temperature; Practical salinity of the water body; Concentration of oxygen {O2} per unit mass of the water body; Concentration of silicate {SiO4} per unit mass of the water body; Concentration of phosphate {PO4} per unit mass of the water body; Concentration of nitrate {NO3} per unit mass of the water body; Subtropical Central Water; Subantarctic Mode Water; High Salinity Shelf Water; Antarctic Surface Water; Antarctic Intermediate Water; Circumpolar Deep Water; Antarctic Bottom Water; Pacific and Indian old Deep Water; Delta Oxygen; Global / Oceans | Global / Oceans | Southern Ocean; Antarctic; Southern Ocean; Pacific; Indian; Antarc*
• Online Access: https://researchdata.edu.au/output-extended-optimum-sr3-2018/2828961

Maintenance and Update Frequency: notPlanned Statement: The eOMP was parameterized following Pardo et al. (2017) and references below are provided in the accompanying manuscript and supplement by Traill et al. (2023). The eOMP was solved for the SWTs described in Table S1 and Delta-O value at each sample point using hydrographic and nutrient measurements described in section 2.2. The system was constrained to water mass mixing groups described in Table S2. To estimate the relative proportion of SWTs at each sample point, the set of equations is solved via a non-negative weighted least squares method through each of the 11 SWTs (Table S1) according to mixing groups (Pardo et al., 2017). Mixing groups (Table S2) further limit the contribution of SWTs at each sampling point to a subset of SWTs, reducing the unknowns at each sample point and increasing the degrees of freedom. Mixing groups are arranged according to the possible mixing interfaces between SWTs with continuity maintained by connecting mixing groups through one or more shared SWT (Table S2). The arrangement of mixing groups and SWT parameterization is derived from previously described hydrography along the SR3 transect (Sokolov & Rintoul, 2000; Sloyan & Rintoul, 2001b; Sokolov & Rintoul, 2009; Herraiz-Borreguero & Rintoul, 2011; Pardo et al., 2017) and in section S1.3. The SWTs’ conservative properties (θ and S) were defined based on the bibliography available (Table S1, Table S3). The values of the non-conservative variables of the SWTs (Table S3) were initially extrapolated from regression lines with θ and S (Poole & Tomczak, 1999) and then subjected to an iterative process inside the OMP in order to obtain the types that best fit the cruise data. In order to check the sensitivity of the model to variations in the environment and variations due to measurement errors (Leffanue & Tomczak, 2004), we’ve run a perturbation analysis of uncertainties (Lawson & Hanson, 1995). The uncertainties of the SWTs fractions and of ΔO ...