Spotter Data Archive

Data in this archive is to be used in accordance with the Sofar Ocean Spotter Data Archive License.

This repository is for getting started with the Sofar Spotter data archive using Python. The S3 bucket with the files (zarr and netCDF) can be viewed here.

Example scripts are provided in the examples/ directory to get started with the data.

Data Overview

This archive includes two datasets - one containing bulk wave parameters and the other containing wave spectra from the Sofar Spotter global buoy network, named spotter_data_bulk* and spotter_data_spectra*, respectively. Two versions of each dataset are available, one as a traditional NetCDF (.nc) and one in Zarr format (_zarr/). Data utilizes trajectory as a primary dimension in order to concatentate multiple records of varying length.

spotter_data_bulk

Dimensions of the data are index (count in full record) and trajectory (ID associated with buoy).

Data variables include latitude, longitude, meanDirection, meanDirectionalSpread, meanPeriod, peakDirection, peakDirectionalSpread, peakPeriod, and significantWaveHeight with coordinate index (i.e. all observations in record concatenated in one long array). An additional variable rowsize has the dimension trajectory, and describes how many observations from a given buoy. rowsize can then be used to slice the observations by trajectory (buoy ID). See examples/spotter_bulk.ipynb for an example of how to use this variable.

spotter_data_spectra

Dimensions of the data are index (count in full record), frequency (Hz), and trajectory (ID associated with buoy).

Data variables include variance_density, a1 , a2,b1, b2, latitude, longitude, rowsize, significantWaveHeight, and u10 (windspeed at 10 m). See Spotter Technical Manual for details on wave spectra definitions from directional wave buoys like Spotter.

Setup

To get started, in your terminal,

via ssh:

git clone [email protected]:sofarocean/spotter-data-archive.git  # for ssh clone

or if you prefer https:

git clone https://github.com/sofarocean/spotter-data-archive.git

# (optional, set up python environment)
python3 -m venv ./.venv
source ./.venv/bin/activate  # this activates the new environment

# install dependencies that are listed in requirements.txt
pip3 install -r requirements.txt

Running Jupyter notebooks

In your terminal, with your environment activated,

jupyter notebook

This should open a directory navigator in your browser where you can navigate to examples/ and select an .ipynb notebook.

If you encounter an error when importing packages related to the Python package libproj, install the following in your virtual environment.

brew install gdal

Make sure to restart terminal/Jupyter Notebook before attempting to rerun the scripts.

Contributing

We encourage community contribution of example scripts and specific analysis done using this dataset via pull request. Contact [email protected] with any questions.