For processing raw ADCP data in Python using the UHDAS pycurrents package (https://currents.soest.hawaii.edu/docs/adcp_doc/codas_setup/index.html).

ADCP_pycurrents_L1.py is based off of Jody Klymak's script (https://gist.github.com/jklymak/b39172bd0f7d008c81e32bf0a72e2f09). This version contains changes to variable names (following BODC conventions); addition of variables, variable and global attributes, and minimal ("L1") processing.

"L1" stands for "level 1 processing". This comprises:

• Corrections for magnetic declination
• Calculation of sea surface height from pressure values and latitude
• Flagging leading and trailing ensembles from before and after deployment and setting them to nan's
• Rotation into enu coordinates if this is not already the coordinate system of the dataset.

ADCP IOS header file.py produces an IOS Shell header file for each netCDF file that makes the netCDF file searchable on the IOS Water Properties website (https://www.waterproperties.ca/mainlogin.php?refer=/).

1. Before creating a virtual environment for the package, create a folder for the virtual environment and enter the folder in terminal, e.g. "test"
2. Create a virtual environment called "adcp37" with Python version 3.7:
   conda create -n adcp37 python=3.7
3. Activate the virtual environment:
   conda activate adcp37
4. Add the conda-forge to your channel:
   conda config --add channels conda-forge
   conda config --set channel_priority strict
5. Install required packages:
   conda install numpy scipy pip pandas netCDF4 xarray gsw
   pip install datetime
6. Clone pycurrents:
   hg clone --verbose http://currents.soest.hawaii.edu/hg/pycurrents
7. Install pycurrents:
   pip install -e ./pycurrents
8. Clone this pycurrents_ADCP_processing repository with git:
   git clone https://github.com/hhourston/pycurrents_ADCP_processing.git

• Linux (or Unix-like) environment

ADCP_pycurrents_L1.py uses the pycurrents package to open a raw ADCP file in Python and export it in netCDF file format. The script also uses a .csv metadata file for the raw ADCP file whose contents are combined with the raw data in the netCDF file, so that the netCDF file is self-describing. This metadata file is filled out by the user and a template can be found at https://github.com/hhourston/ADCP_processing_visualization/tree/master/ADCP_metadata_template.

A description of output data format can be found in the RDI Ocean Surveyor technical manual at http://www.teledynemarine.com/Documents/Brand%20Support/RD%20INSTRUMENTS/Technical%20Resources/Manuals%20and%20Guides/Ocean%20Surveyor_Observer/Ocean%20Surveyor%20Technical%20Manual_Apr18.pdf, starting on page 148.

ADCP_pycurrents_L1.py is based off of the gist, RdiToNetcdf.ipynb, by Jody Klymak (https://github.com/jklymak), and includes contributions from Di Wan (https://github.com/onedwd) and Eric Firing (https://github.com/efiring). add_var2nc.py was written by Di Wan.