New Wave Model Data Available In Datahub

We are excited to share that we have just added five WAM Wave Model datasets to Planet OS Datahub. From local wind-induced waves to swell waves originating from distant weather systems, wave models provide critical information about our seas and oceans.

The WAM model has been operational in the international community since the early 90s after a long period of development under the WAMDIG (Wave Model Development and Implementation Group).

Wave Model Datasets For Different Regions

In practice, wave model data is usually difficult to access due to strange file formats, and it is hard to find information about the difference between the models. We aim to solve this problem by providing a uniform, easy to understand API for different models. In Planet OS Datahub, users can simply compare datasets by reviewing their detail pages, and get access to the data with a standard API call.

Use cases

  • Construction and management of offshore structures (e.g. offshore wind farms)
    Knowledge of the size and strength of waves helps to plan the expected resilience of offshore structures that are constantly influenced by the force of water. In addition, using the models one can better plan maintenance of offshore objects such as a wind turbines. For example, when the wave height exceeds a certain level, the ships can’t access the turbine.
  • Development of port and harbour related structures
    Similarly to the previous example, historical wave data is significant for building structures near or at the coast.
  • Shipping industry
    From large cargo ships to small yachts, they all depend on the state of the ocean and need to be constantly aware of expecte changes.
  • Surfers
    Surfers have developed some of the most detailed wave data applications. Combining local predictions with WAM model data enables to get more precise predictions.
  • Wave energy
    It has been predicted that wave energy will have great potential in the future and wave models would help to calculate expected power output.

Jupyter Notebook

I have published a Jupyter Notebook in GitHub that illustrates ways of using WAM models data via Planet OS Datahub API, including point and raster API options:

https://github.com/planet-os/notebooks/blob/master/api-examples/PlanetOS_WAve_Models.ipynb

In addition to this release, many other wave related datasets are available in Datahub. Find out more from these articles: