"The oceans remain vastly under-monitored," said Gabriel Bousquet, an MIT postdoc who led the design of a unique robot as part of his graduate thesis. "In particular, it's very important to understand the Southern Ocean and how it is interacting with climate change. But it's very hard to get there." Bousquet and his team designed a hybrid vehicle that can both fly above tumultuous seas and sail on them when things are calmer. The vehicle uses one-third as much wind as an albatross would and travels ten times faster than a typical sailboat, making for a very efficient way to survey the vast areas of the planet's seas.

When Ernest Shackleton's ship Endurance succumbed to the Antarctic pack ice on November 21, 1915, he and his crew began one of the most gruelling survival attempts in history. Since the explorer led his 27 men to safety more than a century ago, there has been no sign of the ship. But now, in an echo of the golden age of exploration, the race is on to the Antarctic once more – as two rival expeditions hunt for the lost vessel. A British-led team from Scott Polar Research Institute at Cambridge University, along with universities in South Africa and New Zealand, plans to launch autonomous underwater vehicles almost two miles under the ice. The multi-million pound expedition will set out in January 2019 in research ship SA Agulhas II, The Times reported.

A thriving super colony of some 1.5 million Adelie penguins has been discovered on the remote Danger Islands in the east Antarctic, surprised scientists announced. Just 100 miles (160 kilometres) away in the west Antarctic, the same species is in decline due to sea ice melt blamed on global warming, they said. The first complete census revealed that the Danger Islands host more than 750,000 breeding pairs of Adelie penguins, more than the rest of the Antarctic Peninsula region combined, the team reported. It included the third and fourth-largest Adelie penguin colonies in the world. A thriving super colony of some 1.5 million Adelie penguins has been discovered on the remote Danger Islands in the east Antarctic, surprised scientists announced.

This story is part of our multi-part series looking at some of the big stories and bright ideas primed to make headlines in 2018. Moore's Law describes the exponential technological progress of computer chips. For the past 50 years, every 18 to 24 months, they have shrunk by about half in both size and cost. This enabled the creation of personal computers and cellphones--two devices that have become ubiquitous, which was unfathomable to the average person just 30 years ago. Rapid progress is being made in many fields, including robotics and artificial intelligence.

Climate projections continue to be marred by large uncertainties, which originate in processes that need to be parameterized, such as clouds, convection, and ecosystems. But rapid progress is now within reach. New computational tools and methods from data assimilation and machine learning make it possible to integrate global observations and local high-resolution simulations in an Earth system model (ESM) that systematically learns from both. Here we propose a blueprint for such an ESM. We outline how parameterization schemes can learn from global observations and targeted high-resolution simulations, for example, of clouds and convection, through matching low-order statistics between ESMs, observations, and high-resolution simulations. We illustrate learning algorithms for ESMs with a simple dynamical system that shares characteristics of the climate system; and we discuss the opportunities the proposed framework presents and the challenges that remain to realize it.

We now take it for granted that our machines can sense almost any space in the world, from deep sea trenches to the chambers of the human heart. Building on thousands of years of research in physics, war, and natural history, doctors in the 1940s began using ultrasound to scan human and animal bodies. Taking cues from dolphins and bats and Leonardo da Vinci's early echolocation experiments, naval scientists in the early 20th century learned how to detect mines and submarines with sonar. Early cathode ray studies by Wilhelm Röntgen, Nikola Tesla, and Thomas Edison led to the development of x-ray photography, which enabled radiologists to see broken bones, art historians to read the layers of an oil painting, and physicists to study crystalline structures. Revolutions in machine sensing have transformed fields like medicine and engineering and creative production, several times over. Now, finally, these technologies are reaching their apotheosis, converging in -- sound of balloon deflating -- the self-driving car! Sorry if I sound disappointed. According to hype, autonomous vehicles will ease congestion, shorten commutes, reduce fuel consumption, slow global warming, enhance accessibility, liberate parking spaces for better uses, and improve public health and social equity. 1 All well and good. Analysts predict that by 2050 self-driving cars will save 59,000 lives and 250 million commuting hours annually and support a new "passenger economy" worth $7 trillion USD. 2 Google's parent company Alphabet is positioning itself to lead that economy, with synergies among Waymo (self-driving cars), Waze (navigation), Sidewalk Labs (urban tech), and Google Maps, plus search and advertising (and maybe law enforcement and private security, too!).

The albatross is one of the most efficient travelers in the animal world, and one species - the wandering albatross - can fly almost 500 miles (804 kilometers) in a day with just an occasional flap of its wings. The birds have a large wingspan of up to 11 feet (3.4 meters) across to catch and ride the wind, and soar and dive between contrasting currents of air, a flight pattern called dynamic soaring - comparable to riding a sidewinding rollercoaster. Now, engineers at MIT have developed a new model to simulate this dynamic soaring, and have used it to identify the optimal flight pattern that an albatross should take in order to harvest the most wind and energy. They found that when an albatross banks or turns to dive down and soar up, it should do this in shallow arcs - keeping almost to a straight, forwards track. The researchers say that the new model will be useful in understanding how albatross flight patterns may change as wind patterns shift with changing climate, as well as inform the design of wind-propelled drones and gliders which could be used to perform long-duration, long-range monitoring missions in remote regions of the world.

To see the world through the eyes of a 40-ton polar whale it helps to use a little bug. At least that's what this satellite tracking tag resembles. We're crammed into an inflatable black rubber zodiac on a blustery day in Antarctica's Gerlache Strait, puttering toward a motionless humpback whale. A fist-sized camera with gangly grasshopper-like antennae and suction cup feet sits on a pole resting on scientist Ari Friedlaender's shoulders. Towering icebergs and glacier-draped mountains rise around us.

Scientists filming in the South Ocean off the coast of New Zealand captured this stunning footage of a blue whale eating a mass of krill. When you weigh 200 tons, even the smallest body movements require a lot of energy. That's why blue whales, Earth's largest animal, are picky eaters. Stunning new drone footage shows exactly how these massive mammals maneuver to feed on only the most nutritious patches of krill--providing insight on how they make these choices. Captured by a research team led by National Geographic Explorer Leigh Torres from Oregon State's Marine Mammal Institute, footage filmed in the Southern Ocean near New Zealand shows the moment a whale spots a patch of krill and sizes up whether it's worth expending energy.

Good weather seldom lasts more than a few hours off the coast of Antarctica, and after a remarkable day of cloudless fine conditions, the next day dawns grey and cold. The research vessel, Akademik Treshnikov, moves back from its parking spot against the glacier and sails to a nearby location, where the submarine is again launched. Instead of exploring the underside of the glacier, this time the focus is on marine life on the ocean floor. As the unmanned sub reaches a depth of 900m, a giant sponge resembling an enormous gourd looms into view. The four-man team operating the robotic sub manoeuvre it into place, and then using a robotic arm, lift the beautiful creature from its perch, and places it in one of the sampling boxes.