By Dr. Craig Summers

Ship routing based on reducing weather resistance lowers fuel costs and helps to meet emissions requirements (such as the Carbon Intensity Indicator, or CII, grading) and reduce carbon taxes. Weather routing for ships is currently done using satellite weather forecasts, which can be unreliable.

We are entering a new era, where connected internet of things (IoT) sensors provide weather maps based on measurement, not on forecast models. Unlike satellite forecasts, ship wind measurements are actual measurements of precise wind speed and direction. SailTimer has compared satellite forecasts against 103,000 measurements of wind direction on ships and weather buoys. The results show that satellite forecasts have an average error in wind direction of +/-35°.

The SailTimer database is a crowdsourcing platform that pulls from yachts in coastal areas and public sources offshore, including ships, weather buoys and drift sensors. Compared to satellite forecasts, SailTimer offers more accurate measurements of wind data to improve voyage optimization. The crowdsourced data can verify the accuracy of satellite forecasts.

Case Study: Container Ship from Busan to Los Angeles

Having more accurate weather data helps ships to continuously monitor arrival time. The common logic is that weather routing can take the ship around bad weather to arrive on time with lowered fuel costs and emissions.

A study done in South Korea by Kim and Roh (2020) provides data on seven repeated containership trips from Busan to Los Angeles. The fuel consumption data along the route is from March to June 2014, with a ship that carries 4,600-TEU containers.

The Kim and Roh study shows that boat speed has a much larger effect on fuel consumption than good/bad weather. Fuel consumption more than doubled to about 2.5 times as much when the boat speed was increased from 12.2 to 20.6 kt., for example. Changing course to reduce the weather resistance also does not usually help because it trades off against much larger distances.

Therefore, crowdsourced weather data from vessels up ahead may be most useful for going as slow as possible. You can’t go as slow as possible without accurate weather data. If the ship is approaching a wind zone where the weather load is going to increase fuel consumption by 7 percent, with accurate weather data, the routing software could then work backward from the arrival time to define boat speeds that will reduce fuel consumption by more than 7 percent.

It seems common practice for a ship to travel at its normal cruising speed on every trip, regardless of the weather—better to sail quickly and get there early than risk being late. This is the traditional strategy of “sail fast, then anchor.” But with this strategy, 50 percent of all container vessels arrive more than 8 hr. late, according to eeSea. The arrival times web page for the Port of Halifax, Canada, confirms this. Vessel scheduling starts more than a month ahead and is continuously updated based on ship location and congestion in previous ports. It shows about half of the ship arrivals in red, indicating arrival more than a day late.

Knowing that satellite weather forecasts have an average error of +/-35° in wind direction, it is easy to see how these delays can happen. More accurate measurements of wind and sea state from ships up ahead can help manage vessel speed to arrive on time. Avoiding excess speed also has a monetary savings by reducing fuel costs, as well as lowering greenhouse gas emissions for regulatory compliance.

Conceptually, the goal is to be able to determine the probability of arriving on time at the lowest speed possible through each wind zone. Crowdsourced data from other ships in upcoming wind zones is therefore useful for reducing uncertainty in the arrival time.

 

 

SailTimer Red-Green Trust Maps

Ships are only able to conserve fuel by reducing speed if they have confidence that they will arrive at the expected time given the sea state up ahead. There are not enough ships offshore to provide crowdsourced blanket coverage, but monitoring crowdsourced data from ships up ahead as they move around helps to show which satellite forecast model is most accurate at a particular location and time.

SailTimer’s interface is designed to be intuitive and easy to interpret at a glance. The green dots are locations where the satellite GRIB forecast is consistent with actual wind measurements from ships (with a threshold of less than 30° error). The red dots show locations where the satellite forecast is not verified by actual measurements (and has more than 30° error).

Using this Red-Green Map, a ship captain can check wind and sea state with actual measurements in real time from ships up ahead. The captain can see where the forecast is accurate, with a visual indicator of when and where the ship can slow-steam to reduce fuel consumption.

Crowdsourcing Data via Air Link

SailTimer’s low-cost Air Link sends real-time measurements of wind direction and wind speed from a vessel to an online database. The Air Link could also send boat performance data, such as RPMs and fuel consumption; information for CII grading; and sensor data for predictive maintenance.

Crowdsourced weather data is a public good that benefits the whole industry, and no one company is large enough to create this network independently. The more ships providing real-time data on wind and sea state, the more accurate the arrival time and boat speed calculations. When the arrival time calculations are more accurate, the vessel can take the most direct route while slowing down as often as possible to reduce fuel costs and emissions to arrive on time.

Conclusion

If you want to go slow, you need better weather data. You can’t always slow down because you can’t tell if you will be too early or too late. With accurate crowdsourced marine weather data, a ship can arrive more accurately on time at a speed that optimizes fuel consumption.

More accurate data from crowdsourced measurements on other vessels has two main benefits. The direct benefit is that the calculations of arrival time are more reliable, allowing improved reductions in fuel costs and emissions. The indirect benefit is that, if captains trust the data and routing, they will use them more, which also reduces fuel costs and emissions. Voyage optimization services that have more reliable results will get more customers.

There may be occasional situations where it is worthwhile to take a longer course around a storm in order to reduce weather resistance and fuel consumption, but simply slowing down on the direct route can have a far larger reduction in fuel costs and emissions. From the Kim and Roh study, we calculated that there were no alternate routes that could achieve the expected 3 percent fuel savings that is often claimed for satellite weather routing. But we did calculate that if the ship reduced its speed from 21 to an average of 13.7 kt., there was a 55 percent reduction in fuel costs and related greenhouse gas emissions.

SailTimer Red-Green Maps indicate where the satellite forecast model matches actual wind measurements from ships. The Red-Green Map provides an intuitive interface that shows whether the weather routing is reliable (green areas) or not (red areas).

The Red-Green Maps evolved from discussion with companies making weather-routing software. We discovered that one of their major problems is that they are selling expensive software, but ship captains often don’t trust the satellite weather forecast and, hence, don’t trust the weather routing calculations. So, using more accurate data would create more trust, better results and better profits.

Time-series modeling of crowdsourced ship measurements may help to clarify how weather systems are changing, as ships up ahead continue on their paths. Crowdsourced data from ships may also be a better foundation for machine learning to predict weather than satellite forecasts.

Weather routing companies can use our Red-Green Maps to know the predictive accuracy of satellite weather zones up ahead, calculate different possible speed combinations along the route, and achieve the lowest fuel consumption and emissions. The more crowdsourced measurements there are, the more accurate the estimated arrival time will be, enabling the ship to slow down as much as possible for optimal fuel and emissions management.

Reducing boat speed can produce a dramatically large reduction in fuel costs and emissions. If there is enough time to slow down, fuel consumption can be reduced by up to 55 percent, as we calculated. Greenhouse gas emissions would lower proportionately. If the estimated annual worldwide vessel fuel costs of $157 billion are reduced by up to 55 percent, simply slowing down has a value across the global industry of $86 billion annually.

Acknowledgments

The author would like to thank Net Zero Atlantic in Halifax, Canada, for its financial support for this project (#300-700-014).

References

For a list of references, contact: CS@sailtimer.co.

Dr. Craig Summers is the founder and CTO of SailTimer Inc. in Halifax, Canada.