NASA

Five saildrones deployed from Barbados observed ocean-atmosphere interactions at the sub-mesoscale improve climate models and weather prediction.

Data collected by a fleet of saildrones deployed to the Arctic is being used to validate satellite remote sensing and help develop machine learning tools to estimate air-sea heat exchange.

Saildrone-ship-buoy comparisons were a key objective during NASA’s SPURS-2 field campaign, as highlighted by a paper published in a special issue of Oceanography.

Satellite imagery improves understanding of Earth’s systems, but in situ data is required for calibration, validation, and algorithm development.

Dr. Eric Lindstrom, Physical Oceanography Program Scientist at NASA, will oversee the new Saildrone Ocean Observing Network.

NASA’s S-MODE experiment leveraged instruments of the sea and sky to study how small-scale ocean dynamics impact Earth’s climate system.

The Saildrone Baja Campaign studied upwelling and frontal region dynamics, air-sea interactions, and diurnal warming effects along the US/Mexico coast.

Five saildrones were deployed from Barbados to join the EUREC4A/ATOMIC project, a massive international effort using air, space, surface, and sub-surface platforms to improve climate models and weather prediction.

The 5th annual Arctic mission, in partnership with NOAA and NASA, took a fleet of saildrones to a new frontier—the Arctic ice edge—to improve sea ice prediction and satellite algorithm development.

Six saildrones were deployed from Dutch Harbor, AK, to survey ongoing changes in the Arctic ecosystem in partnership with NOAA’s Pacific Marine Environmental Lab and Alaska Fisheries Science Center and NASA.