Linguistic and Scientific
Harmonies of the Quran

Representation learning has proven to be a powerful methodology in a wide variety of machine learning applications. For atmospheric dynamics, however, it has so far not been considered, arguably due to the lack of large-scale, labeled datasets that could be used for training. In this work, we show that the difficulty is benign and introduce a self-supervised learning task that defines a categorical loss for a wide variety of unlabeled atmospheric datasets. Specifically, we train a neural network

Representation learning has proven to be a powerful methodology in a wide variety of machine learning applications. For atmospheric dynamics, however, it has so far not been considered, arguably due to the lack of large-scale, labeled datasets that could be used for training. In this work, we show that the difficulty is benign and introduce a self-supervised learning task that defines a categorical loss for a wide variety of unlabeled atmospheric datasets. Specifically, we train a neural network

Earth’s oceans reached their highest heat levels on record in 2025, absorbing vast amounts of excess energy from the atmosphere. This steady buildup has accelerated since the 1990s and is now driving stronger storms, heavier rainfall, and rising sea levels. While surface temperatures fluctuate year to year, the ocean’s long-term warming trend shows no sign of slowing.

Earth’s oceans reached their highest heat levels on record in 2025, absorbing vast amounts of excess energy from the atmosphere. This steady buildup has accelerated since the 1990s and is now driving stronger storms, heavier rainfall, and rising sea levels. While surface temperatures fluctuate year to year, the ocean’s long-term warming trend shows no sign of slowing.

Earth’s oceans reached their highest heat levels on record in 2025, absorbing vast amounts of excess energy from the atmosphere. This steady buildup has accelerated since the 1990s and is now driving stronger storms, heavier rainfall, and rising sea levels. While surface temperatures fluctuate year to year, the ocean’s long-term warming trend shows no sign of slowing.

Microscopic ocean algae produce a huge share of Earth’s oxygen—but they need iron to do it. New field research shows that when iron is scarce, phytoplankton waste energy and photosynthesis falters. Climate-driven changes may reduce iron delivery to the oceans, weakening the base of marine food chains. Over time, this could mean fewer krill and fewer whales, seals, and penguins.

Microscopic ocean algae produce a huge share of Earth’s oxygen—but they need iron to do it. New field research shows that when iron is scarce, phytoplankton waste energy and photosynthesis falters. Climate-driven changes may reduce iron delivery to the oceans, weakening the base of marine food chains. Over time, this could mean fewer krill and fewer whales, seals, and penguins.

Microscopic ocean algae produce a huge share of Earth’s oxygen—but they need iron to do it. New field research shows that when iron is scarce, phytoplankton waste energy and photosynthesis falters. Climate-driven changes may reduce iron delivery to the oceans, weakening the base of marine food chains. Over time, this could mean fewer krill and fewer whales, seals, and penguins.

When a huge earthquake struck near Kamchatka, the SWOT satellite captured an unprecedented, high-resolution view of the resulting tsunami as it crossed the Pacific. The data revealed the waves were far more complex and scattered than scientists expected, overturning the idea that large tsunamis travel as a single, stable wave. Ocean sensors confirmed the quake’s rupture was longer than earlier models suggested. Together, the findings could reshape how tsunamis are modeled and predicted.

When a huge earthquake struck near Kamchatka, the SWOT satellite captured an unprecedented, high-resolution view of the resulting tsunami as it crossed the Pacific. The data revealed the waves were far more complex and scattered than scientists expected, overturning the idea that large tsunamis travel as a single, stable wave. Ocean sensors confirmed the quake’s rupture was longer than earlier models suggested. Together, the findings could reshape how tsunamis are modeled and predicted.

When a huge earthquake struck near Kamchatka, the SWOT satellite captured an unprecedented, high-resolution view of the resulting tsunami as it crossed the Pacific. The data revealed the waves were far more complex and scattered than scientists expected, overturning the idea that large tsunamis travel as a single, stable wave. Ocean sensors confirmed the quake’s rupture was longer than earlier models suggested. Together, the findings could reshape how tsunamis are modeled and predicted.

A meltwater lake that formed in the mid-1990s on Greenland’s 79°N Glacier has been draining in sudden, dramatic bursts through cracks and vertical ice shafts. These events have accelerated in recent years, creating strange triangular fracture patterns and flooding the glacier’s base with water in just hours. Some drainages even pushed the ice upward from below, like a blister forming under the glacier. Scientists now wonder whether the glacier can ever return to its previous seasonal rhythm.

A meltwater lake that formed in the mid-1990s on Greenland’s 79°N Glacier has been draining in sudden, dramatic bursts through cracks and vertical ice shafts. These events have accelerated in recent years, creating strange triangular fracture patterns and flooding the glacier’s base with water in just hours. Some drainages even pushed the ice upward from below, like a blister forming under the glacier. Scientists now wonder whether the glacier can ever return to its previous seasonal rhythm.

A meltwater lake that formed in the mid-1990s on Greenland’s 79°N Glacier has been draining in sudden, dramatic bursts through cracks and vertical ice shafts. These events have accelerated in recent years, creating strange triangular fracture patterns and flooding the glacier’s base with water in just hours. Some drainages even pushed the ice upward from below, like a blister forming under the glacier. Scientists now wonder whether the glacier can ever return to its previous seasonal rhythm.

Scientists have uncovered why big predators like sharks spend so much time in the ocean’s twilight zone. The answer lies with mid-sized fish such as the bigscale pomfret, which live deep during the day and rise at night to feed, linking deep and surface food webs. Using satellite tags, researchers tracked these hard-to-study fish for the first time. Their movements shift with water clarity, potentially altering entire ocean food chains.