Wednesday, December 12, 2018

Sails make a comeback as shipping tries to go green

Car manufacturer, Groupe Renault, is partnering with French designer and operator of cargo sailing ships, NeoLine, to reduce the carbon footprint of the Group’s supply chain.
NeoLine has designed a 136-meter ro-ro with 4,200 square meters of sail area it says has the potential to reduce CO2 emissions by up to 90 percent through the use of wind power primarily, combined with a cost-cutting speed and optimized energy mix. commission the vessels by 2020-2021 on a pilot route joining Saint-Nazaire in France, the U.S. Eastern seaboard and Saint-Pierre and Miquelon (off the coast of Newfoundland in Canada).

From The Sentinel by Kelvin Chan

As the shipping industry faces pressure to cut climate-altering greenhouse gases, one answer is blowing in the wind.

European and U.S. tech companies, including one backed by airplane maker Airbus, are pitching futuristic sails to help cargo ships harness the free and endless supply of wind power.
While they sometimes don't even look like sails -- some are shaped like spinning columns -- they represent a cheap and reliable way to reduce CO2 emissions for an industry that depends on a particularly dirty form of fossil fuels.

The merchant shipping industry releases 2.2% of the world’s carbon emissions, about the same as Germany, and the International Maritime Organization estimates that could increase up to 250% by 2050 if no action is taken.
Finnish company Norsepower may have a solution in the spinning cylinders they’ve designed for ships to harness wind power and produce forward thrust.
The result is a ship that needs less fuel to travel the seas - a major boost to the industry that transports 90% of international trade.
VICE News took a ride on the Estraden, a cargo ship fitted with Norsepower Rotor Sails, to see the technology that can reduce a ship’s carbon emissions by 1000 tons per year.
If all 50,000 merchant ships adopted Norsepower Rotor Sails, the costs saved on fuel would be over $7 billion a year, and the emissions prevented would equal more than 12 coal fired power plants.
While zero emission ships could be achieved using Rotor Sails paired with other alternative fuel sources, the economic incentives haven’t been strong enough to mobilize the industry just yet.
But strides such as those taken by Norsepower could help kickstart a widescale greening of the industry.

"It's an old technology," said Tuomas Riski, the CEO of Finland's Norsepower, which added its "rotor sail" technology for the first time to a tanker in August.
"Our vision is that sails are coming back to the seas."

Denmark's Maersk Tankers is using its Maersk Pelican oil tanker to test Norsepower's 30 meter (98 foot) deck-mounted spinning columns, which convert wind into thrust based on an idea first floated nearly a century ago.

Separately, A.P. Moller-Maersk, which shares the same owner and is the world's biggest container shipping company, pledged this week to cut carbon emissions to zero by 2050, which will require developing commercially viable carbon neutral vessels by the end of next decade.

This is Enercon's E-Ship 1 128m cargo vessel built in 2010 designed for the transportation of wind turbine components. She is a most unusual looking ship featuring four 27m tall Flettner Rotor Sails which rotate rapidly, due to the magnus effect this design helps reduce engine fuel costs with greater efficiency.

The shipping sector's interest in "sail tech" and other ideas took on greater urgency after the International Maritime Organization, the U.N.'s maritime agency, reached an agreement in April to slash emissions by 50 percent by 2050.

Transport's contribution to earth-warming emissions are in focus as negotiators in Katowice, Poland, gather for U.N. talks to hash out the details of the 2015 Paris accord on curbing global warming.

Beluga Projects SkySails

Shipping, like aviation, isn't covered by the Paris agreement because of the difficulty attributing their emissions to individual nations, but environmental activists say industry efforts are needed.
Ships belch out nearly 1 billion tons of carbon dioxide a year, accounting for 2-3 percent of global greenhouse gases. The emissions are projected to grow between 50 to 250 percent by 2050 if no action is taken.

Notoriously resistant to change, the shipping industry is facing up to the need to cut its use of cheap but dirty "bunker fuel" that powers the global fleet of 50,000 vessels -- the backbone of world trade.

The IMO is taking aim more broadly at pollution, requiring ships to start using low-sulfur fuel in 2020 and sending ship owners scrambling to invest in smokestack scrubbers, which clean exhaust, or looking at cleaner but pricier distillate fuels.

The GoodShipping Program is the world’s first initiative to decarbonize container shipping by changing the marine fuel mix – switching from heavy fuel oil towards sustainable marine fuel.
The Program enables cargo owners to make a change: their footprint from shipping will be reduced significantly, regardless of existing contracts, cargo routes and volumes.

A Dutch group, the Goodshipping Program , is trying biofuel, which is made from organic matter.
It refueled a container vessel in September with 22,000 liters of used cooking oil, cutting carbon dioxide emissions by 40 tons.

In Norway, efforts to electrify maritime vessels are gathering pace, highlighted by the launch of the world's first all-electric passenger ferry, Future of the Fjords, in April.
Chemical maker Yara is meanwhile planning to build a battery-powered autonomous container ship to ferry fertilizer between plant and port.
Ship owners have to move with the times, said Bjorn Tore Orvik, Yara's project leader.
Building a conventional fossil-fueled vessel "is a bigger risk than actually looking to new technologies ... because if new legislation suddenly appears then your ship is out of date," said Orvik.

Batteries are effective for coastal shipping, though not for long-distance sea voyages, so the industry will need to consider other "energy carriers" generated from renewable power, such as hydrogen or ammonia, said Jan Kjetil Paulsen, an advisor at the Bellona Foundation, an environmental non-government organization.
Wind power is also feasible, especially if vessels sail more slowly.
"That is where the big challenge lies today," said Paulsen.

The performance of the EcoFlettner, which has been tested on the MV Fehn Pollux since July, clearly exceeds the expectations of the scientists.
“The data we have evaluated so far signifcantly outmatch those of our model calculations,” says Professor Michael Vahs, who has been researching the topic of wind propulsion for seagoing vessels at the University of Applied Science Emden / Leer for more than 15 years.
“In perfect conditions, this prototype delivers more thrust than the main engine.”
15 companies from around Leer have been involved in the development and construction of the sailing system. The whole project is funded by the EU and coordinated by Mariko in Leer.
The rotor is 18 meters high and has a diameter of three meters.
After lengthy test runs ashore, the rotor is now being tested under real conditions aboard 90- meter-long multi-purpose freighter MV Fehn Pollux.
On board MV Fehn Pollux more than 50 different data are continuously collected and computed in real time by the Flettner control system on the bridge.
The computer uses the data to calculate the optimum settings for the rotor under the current conditions.

Wind power looks to hold the most promise.
The technology behind Norsepower's rotor sails, also known as Flettner rotors, is based on the principle that airflow speeds up on one side of a spinning object and slows on the other.
That creates a force that can be harnessed.

Rotor sails can generate thrust even from wind coming from the side of a ship.
German engineer Anton Flettner pioneered the idea in the 1920s but the concept languished because it couldn't compete with cheap oil.
On a windy day, Norsepower says rotors can replace up to 50 percent of a ship's engine propulsion. Overall, the company says it can cut fuel consumption by 7 to 10 percent.

Maersk Pelican: Trialling a pair of Norsepower Rotors under trading conditions

Maersk Tankers said the rotor sails have helped the Pelican use less engine power or go faster on its travels across, resulting in better fuel efficiency, though it didn't give specific figures.

One big problem with rotors is they get in the way of port cranes that load and unload cargo.
To get around that, U.S. startup Magnuss has developed a retractable version.
The New York-based company is raising $10 million to build its concept, which involves two 50-foot (15-meter) steel cylinders that retract below deck.
"It's just a better mousetrap," said CEO James Rhodes, who says his target market is the "Panamax" size bulk cargo ships carrying iron ore, coal or grain.

High tech versions of conventional sails are also on the drawing board.
Spain's bound4blue's aircraft wing-like sail and collapses like an accordion, according to a video of a scaled-down version from a recent trade fair.
The first two will be installed next year followed by five more in 2020.
The company is in talks with 15 more ship owners from across Europe, Japan, China and the U.S. to install its technology, said co-founder Cristina Aleixendrei.

Links :

Tuesday, December 11, 2018

Can Artificial Intelligence help build better, smarter climate models?

A computer simulation of carbon dioxide movement in the atmosphere.
The ‘Cloud Brain’ might make it possible to tighten up the uncertainties of how the climate will respond to rising carbon dioxide.

From e360 by Nicola Jones

Researchers have been frustrated by the variability of computer models in predicting the earth’s climate future.
Now, some scientists are trying to utilize the latest advances in artificial intelligence to focus in on clouds and other factors that may provide a clearer view.

Look at a digital map of the world with pixels that are more than 50 miles on a side and you’ll see a hazy picture: whole cities swallowed up into a single dot; Vancouver Island and the Great Lakes just one pixel wide.
You won’t see farmer’s fields, or patches of forest, or clouds.
Yet this is the view that many climate models have of our planet when trying to see centuries into the future, because that’s all the detail that computers can handle.
Turn up the resolution knob and even massive supercomputers grind to a slow crawl.
“You’d just be waiting for the results for way too long; years probably,” says Michael Pritchard, a next-generation climate modeler at the University of California, Irvine.
“And no one else would get to use the supercomputer.”

Earth recently experienced its largest annual increases in atmospheric carbon dioxide levels in at least 2,000 years.
These exchanges vary from year to year, and scientists are using OCO-2 data to uncover the reasons.
The many and varied uses of OCO-2 data will continue to be essential to understanding the dynamics of carbon dioxide across our planet and will help contribute to improved long-term climate forecasting.
NASA has released a video that explains the study, shows changing level of CO2

The problem isn’t just academic: It means we have a blurry view of the future.
It is hard to know if, importantly, a warmer world will bring more low-lying clouds that shield Earth from the sun, cooling the planet, or fewer of them, warming it up.
For this reason and more, the roughly 20 models run for the last assessment of the Intergovernmental Panel on Climate Change (IPCC) disagree with each other profoundly: Double the carbon dioxide in the atmosphere and one model says we’ll see a 1.5 degree Celsius bump; another says it will be 4.5 degrees C.
“It’s super annoying,” Pritchard says.
That factor of three is huge — it could make all the difference to people living on flooding coastlines or trying to grow crops in semi-arid lands.

Pritchard and a small group of other climate modelers are now trying to address the problem by improving models with artificial intelligence.
(Pritchard and his colleagues affectionately call their AI system the “Cloud Brain.”) Not only is AI smart; it’s efficient.
And that, for climate modelers, might make all the difference.

Computer hardware has gotten exponentially faster and smarter — today’s supercomputers handle about a billion billion operations per second, compared to a thousand billion in the 1990s.
Meanwhile a parallel revolution is going on in computer coding.
For decades, computer scientists and sci-fi writers have been dreaming about artificial intelligence: computer programs that can learn and behave like real people.
Starting around 2010, computer scientists took a huge leap forward with a technique called machine learning, specifically “deep learning,” which mimics the complex network of neurons in the human brain.

Traditional computer programming is great for tasks that follow rules: if x, then y.
But it struggles with more intuitive tasks for which we don’t really have a rule book, like translating languages, understanding the nuances of speech, or describing what’s in an image.
This is where machine learning excels.
The idea is old, but two recent developments finally made it practical — faster computers, and a vast amount of data for machines to learn from.
The internet is now flooded with pre-translated text and user-labelled photographs that are perfect for training a machine-learning program.

Companies like Microsoft and Google jumped on deep learning starting in the early 2010s, and have used it in recent years to power everything from voice recognition on smart phones to image searches on the internet.
Scientists have started to pick up these techniques too.
Medical researchers have used it to find patterns in datasets of proteins and molecules to guess which ones might make good drug candidates, for example.
And now deep learning is starting to stretch into climate science and environmental projects.

Researchers hope incorporating artificial intelligence into climate models will further understanding of how clouds, shown here over Bangladesh, will act in a warmer world.
Typical global climate models have pixel sizes far too large to see individual clouds or storm fronts.
The ‘Cloud Brain’ tends to get confused when given scenarios outside its training, such as a much warmer world.
NASA/International Space Station

Microsoft’s AI for Earth project, for example, is throwing serious money at dozens of ventures that do everything from making homes “smarter” in their use of energy for heating and cooling, to making better maps for precision conservation efforts.
A team at the National Energy Research Scientific Computing Center in Berkeley is using deep learning to analyze the vast reams of simulated climate data being produced by climate models, drawing lines around features like cyclones the way a human weather forecaster might do.
Claire Monteleoni at the University of Colorado, Boulder, is using AI to help decide which climate models are better than others at certain tasks, so their results can be weighed more heavily.

But what Pritchard and a handful of others are doing is more fundamental: inserting machine learning code right into the heart of climate models themselves, so they can capture tiny details in a way that is hundreds of times more efficient than traditional computer programming.
For now they’re focused on clouds — hence the name “Cloud Brain” — though the technique can be used on other small-scale phenomena.
That means it might be possible to tighten up the uncertainties of how the climate will respond to rising carbon dioxide, giving us a clearer picture of how clouds might shift and how temperatures and rainfall might vary — and how lives will likely to be affected from one small place to the next.

So far these attempts to hammer deep learning code into climate models are in the early stages, and it’s unclear if they’ll revolutionize model-making or fall flat.

The problem that the Cloud Brain tackles is a mismatch between what climate scientists understand and what computers can model — particularly with regard to clouds, which play a huge role in determining temperature.

While some aspects of cloud behavior are still hard to capture with algorithms, researchers generally know the physics of how water evaporates, condenses, forms droplets, and rains out.
They’ve written down the equations that describe all that, and can run small-scale, short-term models that show clouds evolving over short time periods with grid boxes just a few miles wide.
Such models can be used to see if clouds will grow wispier, letting in more sunlight, or cool the ground by shielding the sun.
But try to stick that much detail into a global-scale, long-term climate model, and it will go about a million times slower.
The general rule of thumb, says Chris Bretherton at the University of Washington, is if you want to cut your grid box dimensions in half, the computation will take 10 times as long.
“It’s not easy to make a model much more detailed,” he says.

The supercomputers that crunch these models cost somewhere in the realm of $100 million to build, says David Randall, a Colorado State University climate modeler; a month’s-worth of time on such a machine could cost millions.
Those fees don’t actually show up in an invoice for any given researcher; they’re paid by institutions, governments, and grants.
But the financial investment means there’s real competition for computer time.
For this reason, typical global climate models like the ones used thus far in IPCC reports have pixel sizes tens of miles wide — far too large to see individual clouds or even storm fronts.

The trick that Pritchard and others are attempting is to train deep learning systems with data from short-term runs of fine-scale cloud models.
This lets the AI basically develop an intuitive sense for how clouds work.
That AI can then be jimmied into a bigger-pixel global climate model, to shove more realistic cloud behavior into something that’s cheap and fast enough to run.

Pritchard and his two colleagues trained their Cloud Brain on high-resolution cloud model results, and then tested it to see if it would produce the same simulated climates as the slower, high-resolution model.
It did, even getting details like extreme rainfalls right, while running about 20 times faster.

Others — including Bretherton, a former colleague of Pritchard’s, and Paul O’Gorman, a climate researcher at MIT, are doing similar work.
The details of the strategies vary, but the general idea — using machine learning to create a more-efficient programming hack to emulate clouds on a small scale — is the same.
The approach could likewise be used to help large global models incorporate other fine features, like miles-wide eddies in the ocean that bedevil ocean current models, and the features of mountain ranges that create rain shadows.

The scientists face some major hurdles.
The fact that machine learning works almost intuitively, rather than following a rulebook, makes these programs computationally efficient.
But it also means that mankind’s hard-won understanding about the physics of gravitational forces, temperature gradients, and everything else, gets set aside.
That’s philosophically hard to swallow for many scientists, and also means that the resulting model might not be very flexible: Train an AI system on oceanic climates and stick it over the Himalayas and it might give nonsense results.
O’Gorman’s results hint that his AI can adapt to cooler climates but not warmer ones.
And Cloud Brain tends to get confused when given scenarios outside its training, such as a much warmer world.
“The model just blows up,” says Pritchard.
“It’s a little delicate right now.” Another disconcerting issue with deep learning is that it’s not transparent about why it’s doing what it’s doing, or why it comes to the results that it does.
“Basically it’s a black box; you push a bunch of numbers in one end and a bunch of numbers come out the other end,” says Philip Rasch, chief climate scientist at the Pacific Northwest National Laboratory.
“You don’t know why it’s producing the answers it’s producing.”

“In the end, we want to predict something that no one has observed,” says Caltech’s Tapio Schneider.
“This is hard for deep learning.”
For all these reasons, Schneider and his team are taking a different approach.
He is sticking to physics-based models, and using a simpler variant of machine learning to help tune the models.
He also plans to use real data about temperature, precipitation, and more as a training dataset.
“That’s more limited information than model data,” he says.
“But hopefully we get something that’s more predictive of reality when the climate changes.” Schneider’s well-funded effort, called the Climate Machine, was announced this summer but hasn’t yet been built.
No one yet knows how the strategy will pan out.

 Using a combination of cloud data, such as this satellite observation of a tropical storm over South America, and "machine learning" could help to fine-tune climate models. 
The ‘Cloud Brain’ tends to get confused when given scenarios outside its training, such as a much warmer world. 
NASA/Goddart Space Flight Center/Scientific Visualization Studio

The utility of these models for predicting the future climate is the biggest uncertainty.
“That’s the elephant in the room,” says Pritchard, who remains optimistic that he can do it, but accepts that we’ll simply have to wait and see.
Randall, who is watching the developments with interest from the sidelines, is also hopeful.
“We’re not there yet,” he says, “but I believe it will be very useful.”

Climate scientist Drew Schindell of Duke University, who isn’t working with machine learning himself, agrees.
“The difficulty with all of these things is we don’t know that the physics that’s important to short-term climate are the same processes important to long-term climate change,” he says.
Train an AI system on short-term data, in other words, and it might not get the long-term forecast right.
“Nevertheless,” he adds, “it’s a good effort, and a good thing to do.
It’s almost certain it will allow us to improve coarse-grid models.”

In all these efforts, deep learning might be a solution for areas of the climate picture for which we don’t understand the physics.
No one has yet devised equations for how microbes in the ocean feed into the carbon cycle and in turn impact climate change, notes Pritchard.
So, since there isn’t a rulebook, AI could be the most promising way forward.
“If you humbly admit it’s beyond the scope of our physics, then deep learning becomes really attractive,” Pritchard says.

Bretherton makes the bullish prediction that in about three years a major climate-modeling center will incorporate machine learning.
If his forecast prevails, global-scale models will be capable of paying better attention to fine details — including the clouds overhead.
And that would mean a far clearer picture of our future climate.

Links :

Monday, December 10, 2018

How ordinary ship traffic could help map the uncharted Arctic Ocean seafloor

A cargo ship sails through multi-year ice in Canada’s the Northwest Passage.
(Timothy Keane / Fednav)

From Arctic Today by Melody Schreiber

Equipping every ship that enters the Arctic with sensors could help fill critical gaps in maritime charts.

Throughout world, the ocean floor’s details remain largely a mystery; less than 10 percent has been mapped using modern sonar technology.
Even in the United States, which has some of the best maritime maps in the world, only one-third of the ocean and coastal waters have been mapped to modern standards.

This map shows unique ship visits to Arctic waters
between September 1, 2009, and December 31, 2016.

But perhaps the starkest gaps in knowledge are in the Arctic.
Only 4.7 percent of the Arctic has been mapped to modern standards.

“Especially when you get up north, the percentage of charts that are basically based on Royal Navy surveys from the 19th century is terrifying — or should be terrifying,” said David Titley, a retired U.S. Navy Rear Admiral who directs the Center for Solutions to Weather and Climate Risk at the Pennsylvania State University.
Titley spoke alongside several other maritime experts at a recent Woodrow Wilson Center event on marine policy, highlighting the need for improved oceanic maps.

 GeoGarage nautical raster chart coverage with material from international Hydrographic Offices
red : US NOAA / grey : Canada CHS /  black : Denmark Greenland DGA / yellow ; Norway NHS

 GeoGarage nautical raster chart coverage (NGA material)

 Catalogue of charts from
Department of Navigation and Oceanography of the Russian Federation

When he was on active duty in the Navy, Titley said, “we were finding sea mounts that we had no idea were there.
And conversely, we were getting rid of sea mounts on charts that weren’t there.”
The problem, he said, comes down to accumulating — and managing — data. But there could be an intriguing solution: crowdsourcing.
“How does every ship become a sensor?” Titley asks.
Ships outfitted with sensors could provide the very information they need to travel more effectively.

Each ship would collect information on oceans, atmosphere, ecosystems, pollutants and more.
As the ships traverse the ocean, they would help improve existing maps and information about the waters they tread.

Maps are becoming more important as shipping activity increases — both around the world and in the Arctic.

In August, the Russian research ship Akademik Ioffe ran aground in Canada’s Arctic. In 2015, the Finnish icebreaker Fennica ripped a three-foot gash in its hull — while sailing within the relatively better charted waters of Alaska’s Dutch Harbor.

“The traditional way that we have supplied these ships with information — with nautical charts and predicted tides and tide tables, and weather over radio facts — are not anywhere near close to being what’s necessary,” said Rear Admiral Shep Smith, director of NOAA’s Office of Coast Survey.
The “next generation of services” would go much further, predicting the water level, salinity, and other information with more precision and detail.
One of NOAA’s top priorities, Smith said, is “the broad baseline mapping of the ocean — including the hydrography, the depth and form of the sea floor, and oceanography.”
Such maps are necessary to support development, including transportation, offshore energy, fishing and stewardship of natural resources, he said.

 A team of engineers and students from the University of New Hampshire’s Center for Coastal and Ocean Mapping recently returned from a voyage that deployed the first autonomous (robotic) surface vessel — the Bathymetric Explorer and Navigator (BEN) — from a NOAA ship far above the Arctic Circle. Credit: Courtesy Christina Belton, NOAA

In NOAA’s records of U.S. waters and coasts, they have at least one piece of information on only 41 percent of the ocean.
“The other 59 percent, there’s potentially a gold mine of economically important information in there,” he continued. “Or environmentally important information.”
NOAA struggles even to model how water moves in the ocean without more information, he said.

They are turning to crowdsourcing, satellite-derived bathymetry — and the idea of turning every ship into a sensor.
Projects like Seabed 2030 — a worldwide effort to map the seabed — will be crucial to these efforts, Smith said.
“It’s hard to map the bottom of the ocean,” said Rear Admiral Jon White, president and CEO of the Consortium for Ocean Leadership.
“It’s like trying to map your backyard with ants, with the ships that we have.”

However, he said, the technology to do so is improving.
“There are great opportunities for the people who understand this technology, to make new ways, better ways to actually map it faster,” White said.
Moving forward, he said, both federal investment and public-private partnerships should focus on “getting every ship to be a sensor in the ocean.”
That effort will be crucial for accomplishing “all the things that we’re trying to do in the maritime environment,” he said.


Sunday, December 9, 2018

Pearl Harbor WWII maps

On the 77th anniversary of the attack on Pearl Harbor:
Japanese Commander Mitsuo Fuchida’s after-action damage assessment map of the 1941 attack, which was presented to Emperor Hirohito

Japanese map of Pearl Harbor that was found in a captured midget sub after the attack
77 years ago the Empire of Japan attacked the US Pacific Fleet at Pearl Harbor.

 by Brenda Lewis & Rupert Matthews 
This map and aerial photo show the catastrophic damage to Battleship Row.source : National Geographic

 NOAA map 19366 with the GeoGarage platform

Links :

Saturday, December 8, 2018

Bathymetry in Australia

Flythrough movie of Gifford Marine Park, which is located 600 km east of Brisbane, Australia.
The park is situated about halfway along the Lord Howe Rise seamount chain on the western flank of the Lord Howe Rise. 
Seamounts along this chain formed from Miocene volcanism via a migrating magma source (“hotspot”) after the opening of the Tasman Sea. 
Two large, flat-topped volcanic seamounts dominate the park. 
Their gently sloping summits have accumulated veneers of sediment, which in places have formed fields of bedforms. 
Steep cliffs, debris and large mass movement scars encircle each seamount, and contrast with the lower gradient abyssal plains from which they rise. 
Spanning over 3 km of ocean depths, the seamounts are likely to serve multiple and important roles as breeding locations, resting areas, navigational landmarks or supplementary feeding grounds for some cetaceans (e.g. humpback whales, sperm whales). 
They may also act as important aggregation points for other highly migratory pelagic species. 
The bathymetry shown here was collected on two surveys - the first in 2007 by Geoscience Australia and the second in 2017 by Geoscience Australia in collaboration with the Japan Agency for Marine-Earth Science and Technology. 
The Gifford Marine Park has also been the focus of a study undertaken by the Marine Biodiversity Hub as part of the National Environmental Science Program.

Flythrough movie of Perth Canyon Marine Park, southwest Western Australia showing seafloor bathymetry and marine life that occurs within the park.
The park encompasses a diversity of geomorphic features, ranging from gently sloping soft sediment plains to near-vertical towering cliffs of exposed bedrock.
This geodiversity extends from the head of Perth Canyon at the shelf break to the slope-confined submarine canyons that dissect the lower continental slope.
Spanning almost 4.5 km of ocean depths, the Perth Canyon has a significant influence on the local ecosystem across the food chain.
The size and location of the canyon is such that it promotes upwelling from the deep ocean, leading to plankton blooms that attract seasonal aggregations of larger pelagic fish, including whales.
Over geological time, the canyon has evolved to provide extensive areas of potential seabed habitat suitable for deep-sea corals and sponges.
The Perth Canyon has been the focus of a study undertaken by the Marine Biodiversity Hub as part of the National Environmental Science Program.

Flythrough movie of Bremer Commonwealth Marine Reserve, southwest Western Australia showing bathymetry of Bremer Canyon, Hood Canyon, Henry Canyon and Knob Canyon.
These canyons are part of the Albany Group of 81 canyons that extend along the continental margin of southwest Australia reaching to water depths of 4000 m.
The Bremer Canyon is one of the few canyons in the group that have incised into the continental shelf, providing a pathway for upwelling of nutrient rich waters to the shelf.
This upwelling is thought to form the basis for aggregations of marine life around the Bremer and adjacent canyons, including orca whales and giant squid.
The Bremer offshore region has been the focus of a study undertaken in 2017 by the Marine Biodiversity Hub as part of the National Environmental Science Program.

Friday, December 7, 2018

The new American weather model shone during Hurricane Lane

Satellite view of Hurricane Lane on Aug. 21.
(Cooperative Institute for Meteorological Satellite Studies)

From WashingtonPost by Jason Samenow

It’s well established that the European weather model, on average, produces the most accurate weather forecasts in the world.
For years, the American model, run by the National Weather Service, has ranked third-best.

The also-ran status of the American model, known as the Global Forecast System (GFS), has caught the attention of Congress, which has appropriated money to the Weather Service to improve our nation’s weather modeling on multiple occasions.
In addition, the Trump administration has stated that building the best prediction model in the world is a “top priority.”
[Trump administration official says it’s a ‘top priority’ to improve U.S. weather forecasting model]

A new analysis of model performance during Hurricane Lane, which unloaded historic amounts of rain on Hawaii’s Big Island, shows that the Weather Service may be making progress.

The Weather Service has developed a new version of the GFS, known as the FV3 (which stands for Finite Volume Cubed-Sphere dynamical core), which it touts as “its next-generation global prediction system.”
While still considered experimental, the FV3 produced the most consistently accurate forecasts of Lane’s track.

 Second only to Katrina in damage cost, Harvey hit the Texas coast as expected.
It stalled for four days, dumped over 60 inches of rain and caused severe flooding

Despite warnings that Maria would hit Puerto Rico, emergency responders were not prepared.
The entire island lost power, clean water and cell service
Five days before hitting Florida, models showed Irma going east.
As it veered west, so too did evacuation orders.
All told, a third of Floridians were mandated to leave 

We obtained a Weather Service chart displaying the track errors for each of the models at different points in time.
Track errors tend to be large for forecasts of the storm’s position several days into the future but grow smaller with time.

(National Weather Service)

NOAA's Geophysical Fluid Dynamics Laboratory (GFDL) Research Team leader, Shian-Jiann Lin, Ph.D, is behind the new FV3-powered GFDL model.
The GFDL model is designed to improve the global weather forecast model by enhancing short-term forecasts and long-term climate prediction.
For more information about the GFDL model and how it will improve the Global Forecast System

The FV3 produced the most accurate forecasts (or smallest track errors) made four (96 hours) and five (120 hours) days into the future, and was neck and neck with the European model and National Hurricane Center forecasts within 72 hours.

The European model, which is run by the European Center for Medium-Range Weather Forecasts in Reading, United Kingdom, had large errors in its forecasts four and five days out but exhibited the skill it is known for within 72 hours as the top performer.

The U.K. Met model, which is the second-most-accurate model in the world and is run by the U.K. Met Office in Exeter, trailed the performance of the European, Hurricane Center and FV3 model forecasts at all times.

 National Weather Service

The current, operational version of the American GFS model had just about the worst forecast performance at every step.
The related American HWRF model, which is a specialized model for hurricanes, also performed poorly, ranking second to last.
Some of its input data come from the GFS, which explains why both models performed comparably poor.

Although the FV3’s results were very promising for Hurricane Lane, they reflect just one very limited case.
To be convinced that this new modeling system might close the gap with the European model, we will need to see such performance repeated storm after storm and in everyday weather situations, from the tropics to the poles.

The target date for the FV3 to become operational is late 2019.

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Thursday, December 6, 2018

The final frontier: who owns the oceans and their hidden treasures?

From Reuters by Zoe Tabary and Claudio Accheri (see Place)

Ransom-hungry pirates, polar explorers, offshore oil giants - the race for the riches of the world’s final frontier is on.

From Thailand to Alaska, the battle to tap ever-dwindling resources from minerals to fish is spurring new conflicts over who has the right to the treasures of the deep seas.
As India, China and Brazil seek new sources of cobalt, copper and nickel to build the gadgets demanded by their booming populations, they are preparing to mine a new realm - the dark depths of the ocean.
Over the next decade India will spend more than $1 billion to develop and test deep-sea technologies - including human-piloted exploration submarines - in the Indian Ocean that could give access to once inaccessible mineral riches up to 6.8 miles (11 km) under water.
“We have to depend on ocean resources sooner or later ... there is no other way,” said Gidugu Ananda Ramadass, head of India’s deep-sea mining project at the National Institute of Ocean Technology in the southern city of Chennai.
But mining the seas - home to the vast majority of life on Earth - carries huge risks and could cause irreversible damage to the environment, campaigners warn.

Oceans - which scientists say are less understood than the moon or Mars - cover more than 70 percent of the Earth’s surface, yet less than 20 percent of their seafloor has been mapped or observed, according to the U.S. National Oceanic and Atmospheric Administration (NOAA).
And what lies below the waves is worth trillions of dollars.
The so-called “blue economy” of marine resources is expected to contribute $3 trillion to the world’s GDP by 2030 - equivalent to the size of the UK economy - up from $1.5 trillion in 2010, according to the Organisation for Economic Co-operation and Development (OECD).

But from overfishing, to a rush to mine deep seas, to slavery on fishing boats, the world’s oceans are a source of growing dispute, not least over who should get access to them.

Experts say oceans are a neglected area of global governance despite the United Nations’ 1982 Convention on the Law of the Sea (UNCLOS) and the 193 member states agreeing in 2015 to a global goal to sustainably manage and protect marine resources.
“Oceans’ governance is the classic public good challenge,” said Dominic Waughray, head of the World Economic Forum’s Centre for Global Public Goods.

Smart rules are essential to keep oceans healthy - but because nobody owns them, “we have a real problem”, he said.
Liz Karan, senior manager for the high seas at Pew Charitable Trusts, a non-profit organization, said existing regulations were patchy and had struggled to protect ecosystems in international waters.
But a proposed U.N. treaty to protect ocean biodiversity - and prevent over-exploitation - could change that.
Negotiations on a legally binding treaty – which would cover the high seas, or ocean areas that extend beyond national boundaries capped at 200 nautical miles from coasts – began in September and aim to reach an agreement by 2020.
But government and U.N. action are only part of the answer, experts caution.
“Governments are good at setting targets, but to really get things done you’re going to need more than hoping U.N. agencies alone can fix this,” said Waughray.
He said technology and monitoring tools to enforce the would-be treaty would be crucial.

So who are the main players controlling Earth’s final frontier?
And how will the global hunt for resources affect the communities who now depend on the seas to survive?

How can Senegal combat illegal fishing?

Fishing under threat

From fast-expanding tourist resorts to disputes over maritime borders, fishing communities are finding their main source of income increasingly under threat.

In southern Thailand, a tourism boom is pitting the Chao Lay, or people of the sea, against land developers, while marine conservation efforts also limit their traditional fishing grounds.
“Our lives have changed. We have to go further and dive deeper to catch fish, and that is affecting our health,” said Ri Fongsaithan, an Urak Lawoi community elder.
Some Chao Lay have taken their plight to the courts, fighting eviction from their homes.
According to Brad Adams of Human Rights Watch, an advocacy group, the Chao Lay “generally do not assert ownership rights because they believe that land and water should not be owned or controlled by one person, but rather shared by many”.

Maritime borders between Nicaragua and Colombia until 2012

The legal fight over the sea is also playing out at national levels.
The Latin American nations of Colombia and Nicaragua, for instance, have for decades fought over a cluster of islands in the western Caribbean - and the fishing rights around them.
In 2012, a ruling by the International Court of Justice redrew the maritime borders around the archipelago of San Andres, Providencia and Santa Catalina in favor of Nicaragua, reducing the expanse of sea belonging to Colombia.
The loss of waters – and of income – has hit the islands’ artisanal fishermen hard, with some saying the money they make from fishing cannot even pay for the fuel to power their boats.
“Our territory at the end of the day is the ocean,” said Erlid Arroyo, secretary of agriculture and fishing at the governor’s office in San Andres. He estimated lost income from the court ruling at “millions and millions of dollars”.
But the crisis has spurred a rethink of the island’s fishing industry, he said, with the government training fishermen to catch fish in other areas and make more of their catch.
These islands’ underwater riches might not last, however.
In the last few decades, the oceans have undergone unprecedented warming while currents have shifted.

From the waters off the east coast of the United States to the coasts of West Africa, the changes are causing fish and other sea life to seek out new waters - leaving the communities that depend on them facing disruption as a result.

For other communities, fishing regulations present the most potent threat.
For decades the Inupiaq, a Native Alaskan group living north of the Arctic Circle, have argued that international limits on subsistence whaling were not big enough to meet their food needs.
“They controlled what we could hunt and what we could eat,” said Roy Nageak, a retired whaling captain, referring to when the International Whaling Commission (IWC) set quotas on catching bowhead whales in 1977 to protect existing stocks.
The Inupiaq hired scientists to convince the IWC that whale stocks were still healthy and to increase the quota, said Crawford Patkotak, an Inupiaq whaling captain.
Then ensued a constant struggle to negotiate and renew whaling quotas with the IWC - which expired every five-six years - the indigenous group said.
Inupiaq leaders welcomed the International Whaling Commission’s decision in September to reaffirm their shared quota of 56 whales per year, increase the number of unused strikes permitted to carry over into the next year, and to renew aboriginal quotas automatically.
“We’ll now be able to hunt in peace without the anxiety of worrying about an expiring quota,” said Patkotak.

 Main marine mineral deposits.
Source: Hein et al.
Digging deep

Much of the quest for ocean resources, however, lies not near its surface but in its depths.
Technological advances and growing demand for minerals used in consumer electronics have fueled a rush to mine the deep seas.

When Oscar-winning director James Cameron ventured in 2012 on a record-breaking solo dive to the deepest-known place on Earth in the Pacific Ocean, he described a flat, desolate landscape, 50 times larger than the Grand Canyon.

UK Seabed Resources, a wholly owned subsidiary of Lockheed Martin UK, in partnership with the Department for Business Innovation and Skills, has received a licence and contract to explore a 58,000 sq kilometre area of the Pacific for mineral-rich polymetallic nodules.

But new technology like autonomous robots and deep-diving submarines could allow scientists to unearth treasures like copper, nickel and cobalt.
Resource-hungry countries are racing ahead in the hunt for minerals, with India planning to explore a 75,000-square-km (29,000-square miles) area of the Indian Ocean - equal to about 2 percent of the country’s size.
“We are exploring Mars, we are exploring the moon. Why don’t we explore our own oceans?” asked Ramadass, of India’s National Institute of Ocean Technology.

China, the world’s second-largest economy, is seeking minerals in the eastern Pacific Ocean.
And Brazil has won rights to explore the Rio Grande Rise off its southeastern coast, in the southern Atlantic Ocean.
“The more (natural) resources are exhausted on the continent, the more interesting marine mining will become,” said Lauro Julio Calliari, an oceanographer at Brazil’s Federal University of Rio Grande do Sul.

But, with little of the deep ocean mapped or explored, environmentalists worry about the potential loss of species not yet well understood - or even recorded.
Sediment plumes and disturbance caused by mining could wipe out habitats, including for slow-growing corals and fish, said Richard Mahapatra, managing editor of the New Delhi-based science and environment magazine Down To Earth.

In the longer run, disturbing oceans, which absorb carbon dioxide and heat, could affect how they regulate the world’s climate, he added.
“We should not rush (deep sea mining). Otherwise we will head towards another disaster,” he said.

The hunt for yet another ocean resource - offshore oil - could have disastrous consequences for marine wildlife, campaigners warn.

Last December, Italian oil producer Eni began drilling a new well in U.S. waters off the north coast of Alaska – the first company to drill in the area since 2015, and a move warily eyed by indigenous communities.
Arnold Brower Jr., executive director of the Alaska Eskimo Whaling Commission (AEWC), worries that potentially devastating oil spills could affect whale food sources, including krill.
“Of course we’re concerned because we’ve seen the mess down in the Gulf of Mexico - BP’s blowout,” he said, referring to the Deepwater Horizon oil drilling rig that exploded in 2010, causing the worst spill in history.

The Coast Guard and other Law Enforcement Agencies of Bangladesh deserve respect and reverence to bring such trafficking incidents into concern.
To intercept and detect such incident is not an easy task.
Small human trafficking vessels enter into the territorial water of Bangladesh at night.
These vessels then take people and cross the territorial water boundary at night. 
o, it is very difficult to detect such vessels at sea.
Photo Source: The Wall Street Journal

Slavery at sea

Determining who owns or has the right to the ocean’s resources raises another question: Who should police them?

The multi-billion-dollar seafood industry has come under scrutiny – particularly in Thailand – after investigations showed widespread slavery, human trafficking and violence on fishing boats and in onshore processing facilities.
Experts said slavery was also rife on fishing vessels in Cape Town’s luxurious waterfront in South Africa.

Part of the problem stems from a lack of oversight on fishermen’s working conditions on the high seas, said Brandt Wagner, head of the transport and maritime unit at the International Labour Organization, a U.N. agency.

The main international convention regulating crew safety and conditions on fishing vessels - called the Cape Town Agreement - was adopted in 2012 by the International Maritime Organization (IMO), a U.N. agency.
But only 10 countries have signed it, according to the Pew Charitable Trusts, a non-profit.
NASA flies Osiris-Rex within 12 miles of asteroid
“So the international law which is most needed to make sure the fishing vessels are safe is not yet in force,” said Wagner.

Dane du Plessis, with South African charity Biblia, has tried to identify and help exploited fishermen when their boats dock in the port of Cape Town.
“People ignore what’s going on because these fishermen, they’re poor, they’re uneducated,” he said,
Migrant fishermen told the Thomson Reuters Foundation they were routinely abused by employers, including being punched, forced to drink dirty water and subjected to racist slurs.

Experts hope that could change with stricter enforcement of fishing regulation.
In May a Taiwanese trawler was detained – and later released – in Cape Town after crew complaints about working conditions.
The detention was the first under the International Labour Organization’s Fishing Convention , which seeks to improve fishermen’s working conditions.
Du Plessis worries, however, that efforts to identify victims of slavery aboard fishing vessels are “only scratching the surface”.
“I believe there’s worse things happening,” he said.
“The ocean is so vast - and what happens there, none of us will know.”

Authorities are trying to police another kind of criminal wreaking havoc on the seas - pirates.
While piracy has decreased worldwide in the past decade, the Gulf of Guinea off the coast of West Africa has become an increasing target for pirates who steal cargo and demand ransoms, according to the International Maritime Bureau (IMB).
Ships in or around Nigerian waters were the target of a series of piracy-related incidents last year, with 10 kidnappings involving 65 crew members, the IMB said in a report in January.

We’ve mapped other planets to more detail than we have our own oceans.
How close are we to a complete ocean map?

Mapping the unknown

Crucial to protecting oceans as pressure mounts is understanding what lies at the bottom, experts say.
A U.N.-backed initiative, called Seabed 2030, is trying to do that by pooling data from around the world to produce a publicly available map of the entire ocean seafloor by 2030.
“Can you imagine operating on the land without a map, or doing anything without a map?” asked Larry Mayer, director of the U.S.-based Center for Coastal and Ocean Mapping, a research body that develops tools for underwater mapping.
“We depend on having that knowledge of what’s around us - and the same is true for the ocean,” he said.

The project initiated by the Nippon Foundation, a Japanese philanthropic organization, and GEBCO, a non-profit association of ocean experts, aims to improve knowledge of marine biodiversity, predict disasters and protect deep-sea resources.

From underwater drones to crowdsourced data from fishing boats, new technology could drastically speed up the mapping process, researchers said.
“With advanced sonar technology it really is like seeing. I think we’ve come out of the era of being the blind man with the stick,” said Robert Larter, a marine geophysicist at the British Antarctic Survey.

Advances in technology could also help in the fight against illegal, unreported and unregulated fishing, with theft estimated to be worth $23.5 billion a year, experts said.
A range of platforms are tracking fishing on the high seas and in marine reserves, aided by radio and satellite data that transmits vessel locations and movements, allowing authorities to identify illegal behaviour.

But political infighting is a roadblock in the way of data and knowledge-sharing, said Julian Barbiere of UNESCO’s Intergovernmental Oceanographic Commission, which is supporting the Seabed 2030 initiative.
Some countries are reluctant to share what they consider strategic data with the project, he said, largely due to national security concerns or because it comes from areas with sensitive geopolitical tensions, such as the disputed South China Sea.
But too much is at stake for countries to hoard data, he said.
“(It) goes back to this principle: the ocean is an international space by definition ... part of the common heritage of mankind,” said Barbiere.

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Wednesday, December 5, 2018

New satellites will use radio waves to spy on ships and planes

A HawkEye 360 data visualization that shows every instance over a month in which a boat turned off its automatic identification system (AIS) for more than 8 hours.
HawkEye 360 claims it's unique not only for its radio-signal-detecting technology, but also artificial-intelligence-powered software the startup has developed to process data. 

From Wired by Sarah Scoles

When a company called HawkEye 360 wanted to test its wares, it gave an employee a strange, deceptive task.
While the worker stood in Virginia, he held the kind of transceiver that ships carry to broadcast their GPS locations.
Usually such a signal would reveal his true position to a radio receiver, but he’d altered the broadcast to spoof his GPS position, making it seem like he was in fact off the coast of Maine.

But his company’s instruments, which in this test were carried by Cessnas flying routes over East Coast waters, picked up on the chicanery.
Now HawkEye 360, the satellite startup that made the detectors, plans to send its first three instruments into space later this month.
Called Pathfinder, the cluster of satellites will work together to locate and make sense of radio emissions beamed up from the ground.
With it, HawkEye 360 gains access to communications information that has mostly been controlled by governments.

The SEAker product provides new Maritime Domain Awareness capabilities.
HawkEye 360 RF-based analytics can help resolve challenges such as dark ship tracking and monitoring of illegal fishing or smuggling.

Lots of companies have launched, or hope to launch, satellites that snap pictures of Earth.
But HawkEye 360 wanted to do something different: scan the planet for its radio-frequency signals instead.
That kind of intelligence has mostly been the domain of militaries and intelligence agencies.
But with ever-cheaper and simpler radio technology, and the relative ease of building small satellites, the time seemed right for private industry to give it a shot.

The company began after Chris DeMay, an expert in radio frequencies who’d spent 14 years working in the intelligence community, attended a conference called SmallSat a few years ago.
He saw all of those picture-taking satellite companies, and realized that the invisible part of the electromagnetic spectrum could also be used to monitor the Earth.

 courtesy of Sumitomo

Radio waves come from ships, planes, battlefields, search-and-rescue operations, cell towers, and basically anything that needs to communicate with another thing.
These waves reveal the things’ locations and their character.
Ever more crowded, this spectrum is full of interference and crosstalk.
Maybe a new fleet of satellites could help clear the air, DeMay thought, and understand what was whipping through it unseen, and from where.

 HawkEye 360's three microsatellites that will form its Pathfinder constellation.

HawkEye 360’s first three satellites will fly in formation around 350 miles above Earth, using tiny thrusters to keep their position relative to one another stable.
On board, they will each carry a receiver that collects radio waves coming from Earth—any transmission more powerful than a watt—and then sends information about those waves down to a station on the ground.

Some customers, of which HawkEye 360 currently has 10 in the government sector, are just interested in that data, straight up.
Others, though, want a little more hand-holding.
For them, HawkEye 360 plans to offer more specialized support, answering such questions as, “Whose communications are messing with mine?”

“Our strategy is focused primarily on the US government today,” says John Serafini, HawkEye’s CEO.
With its advisers having done time in the CIA, the NSA, and various defense-related agencies, the company’s initial strategy seems likely to tilt toward spycraft.
It also has a deal with Raytheon, a large defense contractor and one of its main investors, to feed HawkEye data and analysis into Raytheon’s own systems.

 Data from HawkEye 360's airplane-based test of its core technology.
Blue dots show reported locations, based on automatic identification system (AIS) data, while orange dots show radio-frequency-based locations.
Red circles indicate a zone of 95% certainty.

At first, HawkEye 360 will focus on the high seas: illegal fishing, drug trafficking, human trafficking, weapons trafficking.
“That takes place in the open ocean where people think they’re unseen,” says DeMay.
If a ship spoofs its location or identity, HawkEye 360 believes its birds will be able to detect that.
A 2013 report estimated that such spoofing had increased by 59 percent in the two years before.
More recently, ships in the Black Sea were subject to spoofing from the outside; someone else had scrambled their locations.
On top of spotting such spoofs, HawkEye 360’s analytics could identify a target’s rendezvous with relay ships—even if both are “dark.” "We can detect signals it didn’t realize it was transmitting," says DeMay.

After the company picks up different signals from a ship (or a plane), it’s got its fingerprint.
"We can...track it into perpetuity,” says Serafini.

The satellites should also be able to pinpoint distress signals, and, in a disaster, figure out which wireless communications are still working.
HawkEye 360 also plans to thrust itself into "spectrum allocation," or watching who's using which frequencies, almost in real-time.
That kind of monitoring could eventually make spectrum use more on-the-fly (the topic of an ongoing Darpa program): People could pop into bands when they’re silent, not just stare longingly at them.

HawkEye 360 Satellite Concept – each spacecraft is a small approximately 10 kg microsatellite, with roughly 40 x 30 x 20 cm dimensions.

HawkEye 360’s three small satellites are booked to ship out for space on a bigger launch that’s been dubbed the SmallSat Express.
The mere existence of the launch speaks to the space industry's hawkishness on small satellites.
While little satellites normally have to nestle in, as second-class citizens, among bigger orbiters (or book specialized space on a small rocket), a company called Spaceflight Industries bought out the entire payload of one of SpaceX’s Falcon 9 rockets and gathered 60-some satellite passengers for a clown-car rideshare.
Currently slated to launch on November 19, these dozens of satellites will take the ride of their lives together, shaking and pulling big Gs until they get to space.
Then they will cut loose, disperse to their desired orbits, to see if they can do the big jobs for which they were built.

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