The role of weather observations in forecasts for offshore projects
Whether you’re working on a wind farm construction, an oil rig, or dredging navigation channels, it’s no surprise that the weather impacts your work. This has always been the case for offshore companies. And, it not just about execution, weather impacts on every phase of an offshore project.
As a result, monitoring the weather is part of many people’s daily routine at work. They do this to understand the safety risks for crew, how the weather can impact operations, and understand the steps required to keep projects running profitably.
Meteorologists are also observing the weather on a daily basis because they need to know what is happening now to forecast what the weather will do. But where weather experts differ from casual observers is the scale of their observations. They rely on weather observation networks, drawing on a broad range of high-quality data from multiple sources to ensure they know what is happening.
When it comes to observations, these are particularly important during the project start-up and execution phases. For example, the offshore company briefs what they’re trying to achieve to their weather company; such as, they need a 72-hour weather window to complete a job from start to finish.
The weather company can then make a recommendation based on the weather data. Often this is an active role, joining daily briefing calls with the logistics, operations, and project teams. It ensures that, after issuing the forecast, the weather experts can explain it in more detail and share their confidence in the forecast. The decision of whether to work or not will still lie with the offshore company, but the weather company will help them identify when to work and when to stop based on conditions.
Then, after the work starts, it’s about continuous monitoring of the weather, querying any discrepancies, monitoring confidence in the forecast, and establishing if it's marginal or continuous and helping them analyze the false alarms. Accurate weather data, which enables operations in the margins, can help uncover additional weather windows to work.
There are two main types of observation networks used to help create a weather forecast:
1. Physical locations - e.g., weather stations (on land) and buoys (on water), which measure conditions in their precise location
2. Remote observations - e.g., radars and lightning detectors (horizontally on land) and satellites (from above), these measure conditions in a radius around the location
"MeteoGroup uses observations weather stations, radar, satellite and lightning networks worldwide to analyze the actual weather conditions, to adjust the forecast for the next hours and to validate and statistically correct our forecasts using a quality checked archive of observations"
– Wim van den Berg
Senior meteorological consultant | Weather Tech Team
For the offshore industry, the weather experts typically rely on observation data from weather stations, gathering it from many sources. This can include observations from private networks, which are provided by customers on site to give highly-localized weather forecast.
The experts also supplement the observation data from weather stations with observations from satellite and lightning.
Weather stations provide observation data readings of atmospheric conditions at their physical location. The data provided will depend on where the station is based. Marine buoys, for instance, will give nautical weather information like wave height. Weather stations on oil rigs provide local data for offshore operations.
Observation data is available from organizations operating networks of weather stations. Some information is even accessible as open data; however, the level of detail and accuracy of this observation data varies.
How do weather experts improve the data from weather stations?
Weather experts will only use reliable data sources. Where possible, they invest in multiple sources to correlate results. This approach helps to improve the location coverage and quality of data. They will also complete the observational data from weather stations with other sources to create an accurate view.
Weather station data can be categorized into three quality bands: High, moderate and uncertain. These bands help identify which sources are more likely to be accurate and reliable.
Characteristics: Data is provided from reliable sources, with quality assurance
Types of weather station: Includes primary networks, operated by National Meteorological Services; weather station networks owned and operated by private weather companies; and secondary networks, operated by National Meteorological Institutes
Type: Moderate quality
Characteristics: Data comes from a secondary source, with no agreed service level
Types of weather station: Reports provided by airports; reports provided from wind farms, offshore platforms or ships; providers with their own observation network
Type: Uncertain quality
Characteristics: Data comes from a source without any quality assurance or service level
Types of weather station: Consumer weather stations participating in open networks like Wunderground or Netatmo; Connected devices like autonomous vehicles; road/rail condition sensors; or webcam data
Data from weather stations is used alongside data from other observational networks, to help weather experts determine the weather forecast for the next hours.
They’ll use this data to identify situations where the weather can pose a risk to safety, impact on the day-to-day operations, and understand the steps required to keep the business running profitably
The data alone is not enough to determine the forecast, it’s the combination of data and subject matter expertise that creates an accurate forecast.
A weather satellite monitors the conditions of the atmosphere, clouds, and the Earth’s surface. Images are taken either by the infrared spectrum, which allows cloud coverage to be observed at all time; or by the visible spectrum, which requires daylight but provides a more realistic visualization.
How do weather experts improve the data from weather satellites?
Weather experts will process the satellite data, combining data from multiple satellite sources to create a global view. They also integrate it with data from other observation sources, to provide a complete picture of what is happening.
Satellite data can help forecasters support businesses and industries in many ways. In particular, in offshore, it’s beneficial for predicting squalls: short, heavy bursts of weather that result in the rapid onset of near to zero visibility and strong gusty winds. Knowing when squalls will occur is critical for offshore companies because they have a significant impact on operations.
During a thunderstorm, every lightning strike creates electromagnetic waves that travels through the atmosphere at the speed of light. Ground-based (terrestrial) antenna networks can detect these waves. Regional networks play a vital role in accurately identifying lightning with terrestrial systems and satellites. Lightning can also be detected by satellites – while terrestrial networks have a higher level of accuracy, satellite data offers better coverage over the ocean.
How do weather experts improve the data from lightning?
Weather experts improve the data by using their own end-to-end lightning data-processing system; they can offer near real-time visualization of the data, across different parameters. They also combine the lightning data with weather radar to help identify active thunderstorms.
Creating forecasts from observation data
The knowledge and experience of weather experts enhance the data gathered from weather observation networks. Their skills mean they can bring together multiple data sources, to improve the observation data and use this to provide a complete picture of what the forecast for the next few hours. Where forecast accuracy is critical, these experts are what differentiates between good enough to great.
Weather data can be an effective driver for cost-savings in offshore. To support your projects and ensure they’re successful, it’s critical that your team understands how accurate weather data can help you to optimize operations, by increasing the days you work on a project and decreasing project costs.
Want to learn more? Visit our Offshore Knowledge Base.
MeteoGroup uses observations weather stations, radar, satellite and lightning networks worldwide to analyze the actual weather conditions, to adjust the forecast for the next hours and to validate and statistically correct our forecasts using a quality checked archive of observations.