NASA-developed AI Could Help Track Harmful Algae

NASA scientists have developed an artificial intelligence tool to take on a longstanding challenge in ocean waters. In a study recently published in AGU Earth and Space Science, researchers reported the tool was able to fuse data from. The institutional report frames the development in practical terms and ties it to the broader mission or observing effort.

That matters because Earth science becomes stronger when local observations can be placed inside a broader physical pattern that spans time and geography. The planet operates as a coupled system in which atmospheric, oceanic, cryospheric and solid-Earth processes interact across timescales from days to millions of years. A measurement that captures one variable at one location and one moment has limited interpretive value until it is embedded in the longer series and wider spatial coverage that allow natural variability to be separated from forced change. To do that, we’re going to bring all our NASA assets to the table. ” Media Contacts Andrew Wang / Andrew Good Jet Propulsion Laboratory, Pasadena, Calif. 420 miles (676.5 km) from Earth What does PACE do. Jet Propulsion Laboratory.

21, 2024, by the Ocean Color Instrument on NASA’s PACE satellite. In a study recently published in AGU Earth and Space Science, researchers reported the tool was able to fuse data from multiple satellites and detect harmful algal blooms that.

The National Oceanic and Atmospheric Administration (NOAA) works with states and other local partners to issue harmful algal bloom forecasts, like weather forecasts, during bloom. NASA’s Earth-orbiting satellites already track harmful algal blooms with their unique global view.

It can also drive collaboration between specialists, fostering new ways to conduct the science and deliver decision-support products. A hyperspectral sensor aboard NASA’s Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite, for example, can identify algal communities by their size, shape, and pigment.

The broader interest lies in linking the observation to climatic, geophysical or environmental dynamics that extend well beyond the immediate event or location. Earth science is unusual in that its most important questions operate on timescales that no single research career can observe directly, making the archival record, whether in ice, sediment, rock or satellite data, as important as any new measurement. Results that can be embedded in that record, and that either confirm or challenge the patterns it reveals, carry disproportionate scientific weight.

The study team, consisting of Gierach, Kelly Luis of NASA JPL, and research data scientist Nick LaHaye of Spatial Informatics Group, brought together findings from five space. Applying self-supervised AI to massive streams of satellite data is rapidly becoming a powerful tool for generating actionable ocean intelligence,” said Nadya Vinogradova Shiffer.

Because the account originates with NASA News Releases, it functions best as a primary institutional report that is close to the data and operations, not as independent scientific validation. Institutional communications are produced by organizations with legitimate interests in presenting their work in a favorable light, which does not make them unreliable but does make them partial. Details that complicate the narrative, including instrument limitations, unexpected failures and results below projections, tend to be minimized relative to progress messages. Technical documentation and peer-reviewed publications, where they exist, provide the complementary layer that institutional releases cannot substitute.

The next step is to place the result inside longer time series and to compare it with independent instruments and independent sites. Earth system observations gain most of their interpretive power from network density and temporal depth, not from any single measurement however precise. Model simulations that assimilate the new data will help clarify whether the observation fits comfortably within known natural variability or represents a shift that existing models do not reproduce.

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