For the eighth year in a row, the world’s oceans absorbed a record-breaking amount of heat in 2025. It was equivalent to the energy it would take to boil 2 billion Olympic swimming pools.

A deep learning (DL) model, based on a transformer architecture, is trained on a climate-model dataset and compared with a standard linear inverse model (LIM) in the tropical Pacific. We show that the DL model produces more accurate forecasts compared to the LIM when tested on a reanalysis dataset. We then assess the ability of an ensemble Kalman filter to reconstruct the monthly-averaged upper ocean from a noisy set of 24 sea-surface temperature observations designed to mimic existing coral proxy measurements, and compare results for the DL model and LIM. Due to signal damping in the DL model, we implement a novel inflation technique by adding noise from hindcast experiments. Results show that assimilating observations with the DL model yields better reconstructions than the LIM for observation averaging times ranging from one month to one year. The improved reconstruction is due to the enhanced predictive capabilities of the DL model, which map the memory of past observations to future assimilation times.

Sea surface temperature (SST) is an essential climate variable that can be measured via ground truth, remote sensing, or hybrid model methodologies. Here, we celebrate SST surveillance progress via the application of a few relevant technological advances from the late 20th and early 21st century. We further develop our existing water cycle observation framework, Flux to Flow (F2F), to fuse AMSR-E and MODIS into a higher resolution product with the goal of capturing gradients and filling cloud gaps that are otherwise unavailable. Our neural network architecture is constrained to a deep convolutional residual regressive neural network. We utilize three snapshots of twelve monthly SST measurements in 2010 as measured by the passive microwave radiometer AMSR-E, the visible and infrared monitoring MODIS instrument, and the in situ Argo dataset ISAS. The performance of the platform and success of this approach is evaluated using the root mean squared error (RMSE) metric. We determine that the 1:1 configuration of input and output data and a large observation region is too challenging for the single compute node and dcrrnn structure as is. When constrained to a single 100 x 100 pixel region and a small training dataset, the algorithm improves from the baseline experiment covering a much larger geography. For next discrete steps, we envision the consideration of a large input range with a very small output range. Furthermore, we see the need to integrate land and sea variables before performing computer vision tasks like those within. Finally, we see parallelization as necessary to overcome the compute obstacles we encountered.

An amphibious, 'shape-shifting' drone has been created that's worthy of its own James Bond film. The'dual robot' drone, called MEDUSA (Multi-Environment Dual robot for Underwater Sample Acquisition), is able to fly through the air and land on water in order to quickly collect samples for scientific studies. It has a pod tethered to it that can be deployed underwater remotely at hard-to-reach aquatic environments. Engineers at Imperial College London use the drone to measure lake water for signs of microorganisms and algal blooms, which can pose hazards to human health. In the future, it could be used to monitor climate clues like temperature changes in Arctic seas.

In estimations of ocean heat content – important when assessing and predicting the effects of climate change – calculations have often presented the rate of warming as a gradual rise from the mid 20th century to today. However, new research from UC Santa Barbara scientists Timothy DeVries and Aaron Bagnell could overturn that assumption, suggesting the ocean maintained a relatively steady temperature throughout most of the 20th century, before embarking on a steep rise. The newly discovered dynamics may have significant implications for what we might expect in the future. "There wasn't an onset of an imbalance until about 1990, which is later than most estimates," said DeVries, an associate professor in the Department of Geography, and a co-author on a paper that appears in the journal Nature Communications. According to the study, the period from 1950 to1990 saw temperature fluctuations in the water column but no net warming.

A comprehensive new study of North Atlantic right whales has found the species is significantly smaller and less healthy than southern right whales and could be wiped out in the next 20 years without intervention. The study, the largest of its kind, was organized by Dr. Fredrik Christiansen or Aarhus University in Denmark and involved 12 research institutions across five countries. The team used a fleet of drones to capture images of right whales in the North Atlantic and three major regions in the southern hemisphere. A team of researchers organized by Dr. Fredrik Christiansen or Aarhus University in Denmark used drones to photograph right whales around the world and found North Atlantic right whales are far smaller and less healthy than their southern hemisphere counterparts Using a technique called'aerial photogrammetry,' the team correlated basic information about whale width and length to make determinations about the general health of the whales. In an interview with National Geographic, Christiansen said the team was shocked to find the North Atlantic right whales'looked like a runway…you could basically set up a tent on their backs.'

The dreaded El Niño strikes the globe every 2 to 7 years. As warm waters in the tropical Pacific Ocean shift eastward and trade winds weaken, the weather pattern ripples through the atmosphere, causing drought in southern Africa, wildfires in South America, and flooding on North America's Pacific coast. Climate scientists have struggled to predict El Niño events more than 1 year in advance, but artificial intelligence (AI) can now extend forecasts to 18 months, according to a new study. The work could help people in threatened regions better prepare for droughts and floods, for example by choosing which crops to plant, says William Hsieh, a retired climate scientist in Victoria, Canada, who worked on early El Niño forecasts but who was not involved in the current study. Longer forecasts could have "large economic benefits," he says.

LONDON - The world's oceans are rising in temperature faster than previously believed as they absorb most of the world's growing climate-changing emissions, scientists said Thursday. Ocean heat -- recorded by thousands of floating robots -- has been setting records repeatedly over the last decade, with 2018 expected to be the hottest year yet, displacing the 2017 record, according to an analysis by the Chinese Academy of Sciences. That is driving sea level rise, as oceans warm and expand, and helping fuel more intense hurricanes and other extreme weather, scientists warn. The warming, measured since 1960, is faster than predicted by scientists in a 2013 Intergovernmental Panel on Climate Change report that looked at ocean warming, according to the study, published this week in the journal Science. "It's mainly driven by the accumulation of greenhouse gases such as carbon dioxide in the atmosphere due to human activities," said Lijing Cheng, a lead author of the study from the Chinese Academy of Sciences.

The world's oceans are rising in temperature faster than previously believed as they absorb most of the world's growing climate-changing emissions, scientists said Thursday. Ocean heat - recorded by thousands of floating robots - has been setting records repeatedly over the last decade, with 2018 expected to be the hottest year yet, displacing the 2017 record, according to an analysis by the Chinese Academy of Sciences. That is driving sea level rise, as oceans warm and expand, and helping fuel more intense hurricanes and other extreme weather, scientists warn. The world s oceans are rising in temperature faster than previously believed as they absorb most of the world's growing climate-changing emissions, scientists have said. Ocean heating is critical marker of climate change because an estimated 93 percent of the excess solar energy trapped by greenhouse gases accumulates in the world's oceans.