Note: Single-source report; awaiting corroboration.
NASA scientists have developed an artificial intelligence tool to improve detection of harmful algal blooms in ocean waters. In a study published in AGU Earth and Space Science, the AI tool combined data from multiple satellites to identify blooms in western Florida and Southern California.
These severe blooms pose significant health risks and economic impacts to U.S. coastal communities. Florida locations such as Tampa Bay and Sarasota have faced recurring issues for decades. For example, the species Karenia brevis in Gulf waters produces harmful blooms that kill wildlife, foul beaches, and cause illness in swimmers. On the West Coast, blooms of Pseudo-nitzschia have poisoned dolphins, sea lions, and other marine animals. Toxins may also become airborne, affecting human respiratory health.
Health agencies conduct water testing and issue warnings or beach closures, but this process requires manual sampling and laboratory analysis, which can delay response. Pinpointing where to test before a bloom spreads remains difficult. NASA's Earth-observing satellites provide wide-area monitoring to help track blooms, and the new AI tool may enhance these efforts by guiding targeted water testing.
According to Michelle Gierach, a NASA Jet Propulsion Laboratory scientist and study coauthor, the AI tool could indicate when and where to collect water samples as blooms emerge, promote collaboration among experts, and support decision-making.
The satellites include NASA’s PACE satellite, which uses a hyperspectral sensor to characterize algal communities, and instruments like TROPOMI, which detect faint red fluorescence from species such as K. brevis during photosynthesis. The research combined observations from five missions or instruments to develop the AI detection approach.