Processed and corrected CTD profile data from ASCA July 2016 (SEAmester I), collected on the SA Agulhas II voyage 020
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https://api.odp.saeon.ac.za/catalog/SAEON/go/10.15493/SAEON.EGAGASINI.24000008
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The Agulhas System Climate Array (ASCA) is a mooring array and is designed to provide long-term observations of the Agulhas Current's volume, heat and salt transport and its variability from mesoscale (eddies), through seasonal to interannual timescales. The ASCA shelf and tall moorings extend 200 km offshore along decending TOPEX/Jason satellite ground track # 96, through the core of the Agulhas Current, with CPIES measurements extending the array to 300 km offshore of Port Elizabeth. The data collected during the ASCA project have been obtained from various oceanographic instrumentation. This is the processed product from data collected by the shipborne CTD (Conductivity, Temperature, Depth) sensors for all depths at the following stations: 001, 002, 003, 004, 005, 006, 007, 008, 009, 010, 011, 012, 013, 014, 015, 016, 017, 018, 019 and 020. The salinity values obtained from the salinometer in DOI: 10.15493/SAEON.EGAGASINI.10000007 were higher than previously observed salinities across the ACT/ ASCA transect and for these reasons the uncorrected CTD data were used as the final product. Here we present a newly reprocessed version of the CTD data from ASCA July 2016. The CTD raw data were converted to scientific units using SBEDataProcessing software (ver 7.26.7.114). The following modules (SBEDataProcessing) were then run on the converted data using the recommended default values: Align CTD, Filter, Loop Edit and Cell Thermal Mass. The data were then split into the up cast and the down cast. The down cast data were then bin averaged on pressure, every 1dbar. These data differ from the previous version (DOI: 10.15493/SAEON.EGAGASINI.10000007) in that the salinity data have been reprocessed according to best practice methods. A few small spikes were observed in the data at depth and were removed.
提供机构:
South African Environmental Observation Network
创建时间:
2020-01-29



