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Modeling weather in Shoreline simulations: methods and best practices

Summary: This article explains how to model weather in Shoreline simulations, detailing the different methods available for incorporating weather data into your simulations.

Modeling weather in Shoreline simulations

In Shoreline simulations, weather plays a crucial role in determining the accuracy of the results, especially for offshore wind projects. You can model weather in the following ways:

  1. Disabled: This option allows you to run simulations without any weather restrictions. It is useful for testing logic and troubleshooting weather files.

  2. Historical: This method utilizes the first year of your weather data for all simulation runs. It is beneficial for examining variability in results when using the same weather pattern across multiple simulations.

  3. Increment start year: With this approach, each simulation run begins with a different year from your weather file. This allows you to observe year-on-year variability in the results.

  4. Markov: This method generates synthetic weather data based on your existing dataset. It enables you to run more simulations than you have years of data, making it ideal for situations where your data is limited.

Weather matrix feature

If you utilize the weather matrix feature, you can create complex restrictions where operational limits change based on combinations of weather conditions, such as wind speed and wave height.

Conclusion

Modeling weather in Shoreline simulations can significantly enhance the accuracy of your results. By choosing the appropriate method for your simulations, you can effectively analyze the impact of weather on your projects.