Loss functions and constraints improve sea surface height prediction
Peer-Reviewed Publication
Updates every hour. Last Updated: 22-Jan-2026 12:12 ET (22-Jan-2026 17:12 GMT/UTC)
Existing sea surface height prediction models require excessive computing power and training times and suffer from progressive error accumulation, limiting their accuracy to 14–15 days in the future. A team of researchers recently developed a lightweight deep learning model called GTU-Net with unique loss function and physical constraints that improve the reliability of medium- and long-range sea surface height predictions to improve long-term ocean monitoring, climate studies and operational ocean forecasting.
A research team led by Hiroshima University and Tokyo University of Agriculture and Technology have proposed a neuroendocrine mechanism in bony fish that signals ovulation from the ovaries to the brain, using the medaka fish as a model; the first step to elucidate the neural circuits for facilitation of sexual receptivity in female teleosts.
In a groundbreaking study of ancient ocean geochemistry, a Rutgers researcher and a former Rutgers graduate student have found evidence that the end of the latest ice age some 18,000 years ago, a period of rapid planetary warming, coincided with the emergence of salty water that had been trapped in the deep ocean.
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