Saildrone’s surprise: Ocean robot discovers trigger causing forecast models to get it wrong

A sea-roving robot that sails into hurricanes has uncovered a missing link that will help improve hurricane forecast models.

A Saildrone uncrewed surface vehicle made a historical discovery on Sept. 30, 2021, when it sailed into the eyewall of Hurricane Sam.

The 23-foot drone ship showed us what it looks like inside a hurricane eyewall with over 100 mph winds and 30-foot high waves in a viral video.

In a recently published study, researchers have discovered another unexpected facet of the storm.

Saildrone measured surface ocean temperatures that had unexpectedly risen during the first half of the storm.

These changes were not captured by satellites or any other means of surveillance.

Accurate water temperatures are critical for forecast model predictions.

Models saw the water temps in front of Hurricane Sam cooler than they were — resulting in lower forecast intensity.

As it turned out “Sam turned out to be one of the longest and strongest hurricanes in our historical record,” said Andrew Chiodi, an oceanographer with NOAA’s Pacific Marine Environmental Laboratory who published data on the impressive Category 4 hurricane.

Sam ranked as the fifth longest-lived major Atlantic hurricane in the satellite era, packing a total of 7.75 days at or above Category 3 strength.

Hurricanes typically churn up colder water, but in this case, cold deep water was inverted by a layer of much warmer subsurface water. This trapped layer of warm water was upwelled to the surface by Hurricane Sam.

Models underestimated the flow of energy from the warm ocean into the eyewall by 12-17%.

Accurately knowing the amount of heat transfer from the upper ocean into the storm core will improve intensity forecasts.

The next step for Saildrone is to add new sensors to measure sea spray, which influences the exchange between ocean heat and hurricanes.

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