These data consist of raw echosounder observations collected during ACE (Leg1-Leg3) using an EK80 WBT operating at 12.5 kHz. The instrument was calibrated at South Georgia during the expedition (Leg 3) and corrections were applied prior to calculation of the volume backscattering strength (Sv). The signal-to-noise ratio (SNR) was analysed and was deemed very poor at depths greater than 1000 m. Therefore, only data collected between the transducer depth (8.4 m) and 1000 m were archived. Sv values within this depth range that had poor SNRs (<2) were deemed to be bad data and set to a value of NA. Observations were made using a pulse duration of 16.384 ms (c. 24 m) and are therefore not suitable for fine-scale studies (e.g. analysis of krill swarms). They are more suited to studies relating to large-scale biological features such as deep scattering layers.

Water column sonar data, the acoustic back-scatter from the near-surface to the seafloor, are used to assess physical and biological characteristics of the ocean including the spatial distribution of plankton, fish, methane seeps, and underwater oil plumes. In collaboration with NOAA's National Marine Fisheries Service (NMFS) and the University of Colorado Boulder, NOAA’s National Centers for Environmental Information (NCEI) established a national archive for water column sonar data. This project entails ensuring the long-term stewardship of well-documented water column sonar data, and enabling discovery and access to researchers and the public around the world. Data providers include NOAA National Marine Fisheries Service (NMFS), NOAA Office of Ocean Exploration and Research (OER), NOAA National Ocean Service (NOS), Rolling Deck to Repository (R2R), U.S. academic and private institutions, and international groups. This data set comprises the water-column sonar data archived at NCEI in a more readily accessible media. Data provided to NCEI are in their raw format. Processing routines are being applied to a subset of the archive, specifically focusing on Simrad EK60 single and multiple frequency datasets. Ping alignment, noise removal algorithms (De Robertis & Higgenbottom, 2007; Ryan et al., 2015), and bottom detection algorithms are applied to the raw data binned into one hour intervals using Echoview (Myriax, v.10). The processed data are exported as a CSV for each interval and each frequency.