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pH glider

Tools for processing and plotting glider data with a pH sensor on-board.

Author: Lori Garzio (lgarzio@marine.rutgers.edu)

NOTE: this repo is under development

Installation Instructions

Add the channel conda-forge to your .condarc. You can find out more about conda-forge from their website: https://conda-forge.org/

conda config --add channels conda-forge

Clone the phglider repository

git clone https://github.com/lgarzio/phglider.git

Change your current working directory to the location that you downloaded phglider.

cd /Users/garzio/Documents/repo/phglider/

Create conda environment from the included environment.yml file:

conda env create -f environment.yml

Once the environment is done building, activate the environment:

conda activate phglider

Install the toolbox to the conda environment from the root directory of the phglider toolbox:

pip install .

The toolbox should now be installed to your conda environment.

Delayed Mode Glider Data Processing Steps

  1. download_ds.py: Download the delayed-mode dataset to your local machine from the RUCOOL ERDDAP server.

  2. ta_sal_regression.py: Calculate the best fit TA-salinity linear regression from discrete samples.

  3. process_phglider.py: Process delayed-mode pH glider data.

    1. Apply QARTOD QC flags (downloaded in the files) to CTD and DO data.
    2. Apply CTD hysteresis test flags.
    3. Run location QARTOD test.
    4. Convert pH voltages of 0.0 to nan.
    5. Apply CTD thermal lag correction.
    6. Interpolate (method=linear) pressure and remove data where pressure <1 dbar.
    7. Interpolate (method=linear) temperature and salinity.
    8. Remove interpolated data for profiles that failed hysteresis tests.
    9. Calculate pH from original and corrected voltages and interpolated CTD data.
    10. Calculate Total Alkalinity from interpolated salinity using a linear relationship determined from in-situ water sampling.
    11. Run ioos_qc gross range test on additional variables defined in the gross_range.yml config file, and apply test results to data.
    12. Run ioos_qc spike test on pH and corrected pH, and apply test results to data.
    13. Calculate CO2SYS variables using TA, corrected pH, interpolated salinity, interpolated temperature, interpolated pressure.
    14. Convert oxygen concentration to mg/L.

  4. plot_grouped_profiles_ph_qc.py: Plot corrected pH profiles with QARTOD gross range and spike tests applied.

  5. plot_phvars.py: Plot short sections of data for pH variables for QC.

  6. compare_glider_discrete.py: Compare glider data to discrete water samples collected during glider deployment and recovery.

  7. Create configuration files for the deployment.

  8. glider_to_dac_ncei.py: Format dataset to upload to the IOOS glider DAC and NCEI OA data portal.

  9. plot_ncei.py: Plot xsections of the data in the NCEI dataset before submitting files to the NCEI OA data portal.

CTD Thermal Lag

Originally written in Matlab by Daniel Wang and translated to Python by Jack Slater at the Virginia Institute of Marine Science. Code adapted for pH glider datasets.

See https://github.com/truedichotomy/CTD_thermal_lag for original code.

Citations

Humphreys, M. P., Gregor, L., Pierrot, D., van Heuven, S. M. A. C., Lewis, E. R., and Wallace, D. W. R. (2020). PyCO2SYS: marine carbonate system calculations in Python. Zenodo. doi:10.5281/zenodo.3744275.

Lewis, E. and Wallace, D. W. R. (1998) Program Developed for CO2 System Calculations, ORNL/CDIAC-105, Carbon Dioxide Inf. Anal. Cent., Oak Ridge Natl. Lab., Oak Ridge, Tenn., 38 pp., https://salish-sea.pnnl.gov/media/ORNL-CDIAC-105.pdf

Saba, G.K., Wright‐Fairbanks, E., Chen, B., Cai, W.‐J., Barnard, A. H., Jones, C. P., et al. (2019). The development and validation of a profiling glider deep ISFET‐based pH sensor for high resolution observations of coastal and ocean acidification. Frontiers in Marine Science, 6. https://doi.org/10.3389/fmars.2019.00664