How it's made: In-House MetOcean Modelling: What You Need to Know

This is our last post covering Category Two: MetOcean Models in the How It’s Made series, To round-up this section, we’re looking at how the weather experts create their own in-house MetOcean models.

 

 

Download your copy of "How It’s Made: The Ultimate Guide to Weather Forecasting" below:


Download Now

 

 

Weather can have a massive impact on operations, safety, and profitability. According to HBR, adverse weather impacts the operating and financial performance of 70% of businesses worldwide. Therefore, knowing what the weather conditions are going to be in the coming hours, days, and weeks is critical. And having weather data that is more accurate, reliable, and relevant gives them the level of detail they need to make informed decisions.

Metocean models are a representation of the physical world around us. They use a coordinate system to map a geospatial grid of latitude and longitude coordinates onto the earth. Experts use metocean models to understand both the analyzed and forecasted metocean conditions for specific cells in the grid.

 

“Modelling is both an art and a science. Where science delivers the empirical formula that form the basis of the models themselves, it is up to the metocean modeler to simplify the complex world into an optimal configuration that ensures maximum quality while using as little resources as possible”
Sander Hulst
Senior Oceanographic Researcher
MeteoGroup

 

What is the difference between external and in-house metocean models?
 

External datasets, which are readily available in the market, are a valuable part of the forecaster's toolkit. However, they are just part of the puzzle. For example, wave spectra from ECWMF are available every 3 to 6 hours, which might not be the required temporal resolution for the specific use case In-house models can provide this higher resolution with insights for every hour - or even intra-hourly. The in-house models can also provide spatial resolution down to hundreds of meters.

It is clear that for some use-cases, external datasets alone are not enough. They need additional inputs to solve the challenge that the customer is facing. Custom model configurations allow experts to select source terms (physical equations) and grid resolutions for that particular use case. To translate global data to your specific area of interest, the experts nest one or more feature-resolving grids in regional grids and then the regional grids in the global grids. We call this physical downscaling, an alternative to statistical downscaling.

In-house models provide end users with direct access to new and improved methodologies and give them the chance to participate in the research and implementation of future models in ways that can specifically benefit their business.

Working with the experts, who know the models and your business, ensures that the guidance and advice you receive are tailored to your situation and requirements. You can focus on your priorities, confident that you have access to near real-time insight into how the weather conditions are developing and experts that understand what this data means for you.

 

How do the experts create a numerical metocean model?

 

Reliable forecasts are essential but complicated to produce. Taking the example of a specific oceanographic / wave model, we can see how the experts both produce the model and apply it to real life situations. (This approach applies to meteorological models as well).

At an offshore wind farm location off the Belgian coast, sandbanks can cause high or long waves to break early, or induce waves to bend.

These conditions make it harder to predict wave height, which is a real challenge for offshore projects in the area. In the past, forecasts have at times been half a meter off because sandbanks are not accounted for in the global wave models. This has obvious, huge implications for vessels working close to their safety threshold.

To provide accurate forecast for the offshore windfarm in such a challenging location, it required the development of an in-house model using an innovative approach. By coupling atmospheric forcing with in-house wave models, it not only looks at the conditions at sea but also incorporates the atmospheric winds that drive the waves. Furthermore it includes detailed tidal information, a prerequisite when working in shallow water. The model was calibrated both with local observations (in-situ) and remote sensing data. The model is run on a cloud based High Performance Cluster which ensures there’s always enough computing power for it to run and new models can be set up for any desired location around the world.

 

What is the added value of in-house metocean models?

 

Different models have different strengths. Where a coarse model is set up to perform well in the deep ocean, a more detailed model is required closer to shore.

The advantage of in-house modeling experts means that different models can be coupled: the output from one becoming the input for another. For instance, a regional WAVEWATCHIII model can be fed surface wind data computed by a regional WRF domain, of which both receive boundary conditions from a global grid.

Think about offshore companies that need to plan operations in marginal weather conditions. They benefit from specific inhouse models and combinations. In this case, a SWAN model run on a high-resolution grid can take spectral wave data from the regional WAVEWATCHIII, surface winds from WRF, tidal data from harmonic components, and ocean circulation data from Mercator, in order to properly capture, for instance, the wave-current interactions over complex seafloor features. The resulting dataset can provide unique insights in reigning and future conditions. These types of modeling is also crucial for innovative blue energy developments that depend on accurate tide and wave power data.

 

Accessing just the insight you need

 

In-house models are built for specific use cases or for specific locations. They aim to increase the forecast value parameters of specific data points, for example data points relating to waves for near shore work or specific offshore activities like cable laying.

It’s about supporting the end client at all stages of their work, with the data that they need. For offshore projects, for example, this typically means using coarse data for the tender phase, with detailed studies used for design phase and then using the same model grids for the operation and decommissioning phases.

In-house models provide end users with direct access to new and improved methodologies, and may even give them the chance to participate in the research and implementation of future models in ways that can specifically benefit their business.

Working with the experts, who know the models and your business, ensures that the guidance and advice you receive are tailored to your situation and requirements. You can focus on your priorities, confident that you have access to near real-time insight into how the weather conditions are developing and experts that understand what this data means for you.

 

Download your copy of "How It’s Made: The Ultimate Guide to Weather Forecasting" below:


Download Now

 

 

Modelling is both an art and a science. Where science delivers the empirical formula that form the basis of the models themselves, it is up to the metocean modeler to simplify the complex world into an optimal configuration that ensures maximum quality while using as little resources as possible


Sander Hulst


Senior Oceanographic Researcher
MeteoGroup