gliderad2cp

gliderad2cp processes data from the Nortek AD2CP acoustic doppler current profiler (ADCP) mounted on a glider. gliderad2cp takes data from the ADCP unit and the glider and combines them to produce estimates of vertical shear of velocity. The gliderad2cp toolbox greatly simplifies file handling, integration of any glider data to ADCP data, and the complex trigonometry necessary to obtain high quality shear data. In particular, the integration of the Nortek AD2CP varies across glider manufacturers, either using alternating 3-beam configurations between up and down profiles (on the Seaglider or the Spray) or using 4 beams at all times (on the SeaExplorer). This python package allows users to easily load Nortek AD2CP netCDF files and pull the raw data to provide clean shear estimates with consistent processing and quality control independent of which glider they use. Finally, it provides a final referenced velocity profile and corrects for shear bias when the data permits.

Documentation is hosted at flow-lab.org/gliderad2cp/

Code is hosted on https://github.com/bastienqueste/gliderad2cp

Installation

gliderad2cp can be installed with pip

python -m pip install gliderad2cp

Usage

gliderad2cp requires 2 inputs:

A netcdf (.nc) file of Nortek AD2CP data as output by the Nortek MIDAS post-processing software. This software should be procured from Nortek.
Glider data in a timeseries csv or parquet file (.pqt) file with the following variables: ["time", "temperature", "salinity", "latitude", "pressure", "longitude", "profile_number", "declination", ]

N.B. if declination data are not present in the datafile, they can be added with the function process_adcp.get_declination.

The primary functionality of gliderad2cp is to produce a gridded dataset of velocity shear using data from the glider and AD2CP. This is achieved with two steps:

from gliderad2cp import process_adcp
adcp_file_path = "path/to/adcp/files"
glider_file_path = "path/to/glider/files"
ds_adcp, df_glider = process_adcp.shear_from_adcp(adcp_file_path, glider_file_path)
ds_shear = process_adcp.grid_shear(ds_adcp, df_glider)

shear_from_adcp Returns an xarray dataset of gridded ADCP data in 3 coordinate systems (beam, XYZ and ENU) and a pandas dataframe of glider data

grid_shear Combines the ADCP and glider data into a gridded xarray dataset with velocity shear binned on a per-glider profile basis at 1 m vertical resolution.

Additionally, the function velocity_from_shear can be used to estimate absolute velocity profiles:

ds_vel = process_adcp.velocity_from_shear(adcp_file_path, glider_file_path, ds_adcp, df_glider)

This requires estimates of speed through water and the following additional variables in the glider file: ["speed_vert", "speed_horz", "dead_reckoning", "nav_resource", "dive_number"]

Additional options

By default, the following options are used during processing:

default_options = {
            'debug_plots': True,
            'correctADCPHeading': True,
            'ADCP_discardFirstBins': 0,
            'ADCP_correlationThreshold': 70,
            'ADCP_amplitudeThreshold': 75,
            'ADCP_velocityThreshold': 0.8,
            'correctXshear': False,
            'correctYshear': False,
            'correctZshear': False,
            'correctZZshear': False,
            'ADCP_regrid_correlation_threshold': 20,
            'plots_directory': 'plots',
        }

These options can be changed by using the options kwarg in the relevant functions.

These utility functions can be controlled with much greater granularity by calling their constittuent functions individually. This process is detailed in the two example notebooks.

Notebooks

Notebook 01_calculate_velocity_shear.ipynb demonstrates the core functionality of gliderad2cp. It takes a glider timeseries and a netCDF file created by a Nortek MIDAS from AD2CP data and produces a gridded dataset of velocity shear

Notebook 02_integrate_velocity_shear.ipynb shows one method of integrating this velocity shear into earth relative absolute velocities.

Both notebooks use data hosted on zenodo, downloaded with pooch. The datasets can be downloaded here https://zenodo.org/record/8431329

Contributing

gliderad2cp welcomes contributions. Feel free to submit an Issue or Pull Request if you have recommendations or have experienced issues with the package. Please see the community guidelines, CONTRIBUTING.md and make use of the Issue and Pull Request templates.

naomikrauzig / gliderad2cp