
WAVEWATCH III data in Python¶
About¶
The bmi_wavewatch3 Python package provides both a command line interface and a programming interface for downloading and working with WAVEWATCH III data.
bmi_wavewatch3 provides access to the following raster data sources,
30 year wave hindcast Phase 1
30 year wave hindcast Phase 2
Production hindcast Singlegrid
Production hindcast Multigrid
All data sources provide both global and regional grids.
Installation¶
bmi_wavewatch3 can be installed by running pip install bmi-wavewatch3
. It requires Python >= 3.8 to run.
If you simply can’t wait for the latest release, you can install bmi_wavewatch3 directly from GitHub,
$ pip install git+https://github.com/csdms/bmi-wavewatch3
bmi_wavewatch3 is also available through conda, conda install bmi-wavewatch3 -c conda-forge
.
Usage¶
To get started, you can download WAVEWATCH III data by date with the ww3 command (use ww3 –help to print a brief message),
$ ww3 fetch "2010-05-22"
You can also do this through Python,
>>> from bmi_wavewatch3 import WaveWatch3
>>> WaveWatch3.fetch("2010-05-22")
The bmi_wavewatch3 package provides the WaveWatch3
class for downloading data and
presenting it as an xarray Dataset.
>>> from bmi_wavewatch3 import WaveWatch3
>>> ww3 = WaveWatch3("2010-05-22")
>>> ww3.data
<xarray.Dataset>
...
Use the inc
method to advance in time month-by-month,
>>> ww3.date
'2010-05-22'
>>> ww3.inc()
'2010-06-22'
>>> ww3.data.time
<xarray.DataArray 'time' ()>
array('2010-06-01T00:00:00.000000000', dtype='datetime64[ns]')
...
This will download new datasets as necessary and load the new data into the data
attribute.
Note
If the new data are not cached on you computer, you will notice a delay while the new
data are download. If the lazy
flag is set, the download will only occur once you
try to access the data (i.e. ww3.data
), otherwise the data are downloaded
as soon as the date is set.
Example¶
Plot data from the command line¶
Running the following from the command line will plot the variable significant wave height
from the WAVEWATCH III at_4m grid. Note that the time of day (in this case, 15:00) is
separated from the date with a T
(i.e. times can be given as YYYY-MM-DDTHH
)
$ ww3 plot --grid=at_4m --data-var=swh "2010-09-15T15"

Plot data from Python¶
This example is similar to the previous but uses the bmi_wavewatch3 Python interface.
>>> from bmi_wavewatch3 import WaveWatch3
>>> ww3 = WaveWatch3("2009-11-08")
The data can be accessed as an xarray Dataset through the data
attribute.
>>> ww3.data
<xarray.Dataset>
Dimensions: (step: 241, latitude: 311, longitude: 720)
Coordinates:
time datetime64[ns] 2009-11-01
* step (step) timedelta64[ns] 0 days 00:00:00 ... 30 days 00:00:00
surface float64 1.0
* latitude (latitude) float64 77.5 77.0 76.5 76.0 ... -76.5 -77.0 -77.5
* longitude (longitude) float64 0.0 0.5 1.0 1.5 ... 358.0 358.5 359.0 359.5
valid_time (step) datetime64[ns] dask.array<chunksize=(241,), meta=np.ndarray>
Data variables:
dirpw (step, latitude, longitude) float32 dask.array<chunksize=(241, 311, 720), meta=np.ndarray>
perpw (step, latitude, longitude) float32 dask.array<chunksize=(241, 311, 720), meta=np.ndarray>
swh (step, latitude, longitude) float32 dask.array<chunksize=(241, 311, 720), meta=np.ndarray>
u (step, latitude, longitude) float32 dask.array<chunksize=(241, 311, 720), meta=np.ndarray>
v (step, latitude, longitude) float32 dask.array<chunksize=(241, 311, 720), meta=np.ndarray>
Attributes:
GRIB_edition: 2
GRIB_centre: kwbc
GRIB_centreDescription: US National Weather Service - NCEP
GRIB_subCentre: 0
Conventions: CF-1.7
institution: US National Weather Service - NCEP
history: 2022-06-08T16:08 GRIB to CDM+CF via cfgrib-0.9.1...
The step
attribute points to the current time slice into the data (i.e number of three hour increments
since the start of the month),
>>> ww3.step
56
>>> ww3.data.swh[ww3.step, :, :].plot()

Release Notes¶
0.2.0 (2022-06-17)¶
New Features¶
Added a new subcommand, plot, to the ww3 command-line program.
ww3 plot
with download (if the data files are not already cached) and create a plot of the requested data. (#13)
Bug Fixes¶
Fixed a bug in the reporting of an error caused by an invalide datatime string. (#13)
0.1.1 (2022-06-10)¶
Other Changes and Additions¶
Set up GitHub Action to create a source distribution and push it to TestPyPI. This action is only run if the version tag is a prerelease version (i.e. the version string ends with
[ab][0-9]+
). (#10)Set up GitHub Action to create a source distribution and push it to PyPI. This action is only run if the version tag is a release version (i.e. the version string doesn’t end with
[ab][0-9]+
). (#11)
0.1.1b1 (2022-06-09)¶
New Features¶
Added
ww3
command line interface to download WaveWatch III data by date, region and quantity (significant wave height, wind speed, etc.). (#1)Added
WaveWatch3
class, which is the main access point for users of this package. This class downloads WaveWatch III data files (if not already cached) and provides a view of the data as an xarray Dataset. Users can then advance through the data month-by-month, downloading additional data as necessary. (#3)Added the
ww3 clean
subcommand that removes cached data files. (#4)Added
BMIWaveWatch3
class to provide a Basic Model Interface for the wavewatch3 package. (#5)Added additional WaveWatch III data sources from which users can fraw data from. (#6)
Added
fetch
method to WaveWatch3 to mimic the command line programww3 fetch
. (#7)Added additional data sources from which to retreive data from. Available data sources now include: Phase 1, Phase 2, Multigrid, Multigrid-extended, and Multigrid-thredds. (#7)
Added
ww3 info
command to print information (e.g. available grids, quantities, etc.) about data sources. (#7)Added a
step
property toWaveWatch3
to track the current time slice of the data cube. This property is also settable so that a user can use it to advance throught the data (additional data are downloaded in the background as needed). (#8)Dates can now be specified as iso-formatted date/time strings. For example, “1944-06-06T06:30”. (#8)
Rename package to
bmi_wavewatch3
. This follows the convention used by other CSDMS data components. (#9)
Documentation Enhancements¶
Added package description, installation, usage, and an example to the documentation. (#8)
Other Changes and Additions¶
Set up continuous integration using GitHub actions. This includes tests to ensure that the code is styled according to black, is free of lint, and passes all unit tests. (#2)
Added more unit tests, particularly for data sources. (#7)
Added a GitHub action to build the sphinx-based documentation as part of the continuous integration. (#8)
Better error reporting for the command line interface for HTTP errors when retreiving data as well as input validation. (#8)
Set up GitHub Action to create a source distribution and push it to TestPyPI. This action is only run if the version tag is a prerelease version (i.e. the version string ends with
[ab][0-9]+
). (#10)
Credits¶
Development Lead¶
Eric Hutton (@mcflugen)
Contributors¶
None yet. Why not be the first?
The MIT License (MIT)¶
Copyright (c) 2022 Community Surface Dynamics Modeling System
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.