Tuesday, November 23, 2021

Seabed features named after eminent American and Russian scientists

Agapova Seamount
 
Munk moment

From IHO
 
The work of two outstanding scientists has been recognized this year by the IHO-IOC GEBCO Sub-Committee of Undersea Feature Names (SCUFN) through the approval of the naming of two major undersea features.
  • the “Agapova Seamount” was proposed by the Geological Institute of the Russian Academy of Science (GINRAS);
  • the “Walter Munk Guyot” by the Scripps Institution of Oceanography at the University of California San Diego, USA.
“Their reputation transcends all borders and there is not a single oceanographer or geophysicist who ignores their work” Yves Guillam, IHO Assistant Director and Secretary of SCUFN

The name “Agapova Seamount” was given in memory of Galina Vladimirovna Agapova (1930-2018), marine geomorphologist and cartographer, who started working at the Russian Academy of Sciences in 1955.
She participated in many expeditions in the Black, Caspian, and Mediterranean Seas, as well as in the Pacific and Atlantic Oceans.
She contributed to the discovery of numerous seamounts, ridges and other features of the seafloor topography.
She was the author of more than 100 scientific papers and bathymetric, geological and tectonic maps, including the 5th edition of GEBCO, International Geological and Geophysical Atlases of the Indian, Atlantic and Pacific Oceans, the International Tectonic Map of the World etc.

 
Galina Vladimirovna Agapova participated in many expeditions and contributed to the discovery of numerous seamounts, ridges and other features of the seafloor.
In some places, the Agapova Seamount has inclines 30° steep.



G.V Agapova participated in the GEBCO Subcommittee on the nomenclature and terminology of the underwater relief forms (GEBCO-SCGN, now SCUFN) between1974 and 2007 and participated in the creation of the Guidelines on Standardization and the GEBCO Gazetteer.

The “Walter Munk Guyot” was named in memory of the legendary oceanographer/geophysicist whose body of work had profound implications for science and society as a whole.
Dr.
Munk’s contributions to science throughout the latter half of the 20th century and into the present century were measured not only in terms of the new knowledge his research yielded, but in the quality and diversity of the questions he considered.
His early research on waves for example, enabled him to work out a scheme to create reliable predictions, which was subsequently used during world War II to correctly predict that the waves troops would face taking the beach in Normandy would be high but manageable.
Research on the stability in water of bodies such as buoys is still used, for example in hydrodynamic analyses when evaluating the “Munk moment”.

More about Dr Munk here.

This guyot is located in the eastern Mid-Pacific Mountains.
Its deepest point is at 5200m and it is 3803m high.

 
The deepest point of the Walter Munk Guyot is at 5200m and it is 3803m high.




But what is a GUYOT ?
The official international definition says:
“A GUYOT is a SEAMOUNT with a comparatively smooth flat top”.
 
Examples of seamounts

Well… so what is a SEAMOUNT?
For the 12 Members of SCUFN (6 represent the IHO, and 6 the Intergovernmental Oceanographic Commission of UNESCO), who are responsible for developing and maintaining the Publication B-6, the standard and guidelines for Undersea Feature Naming: “A SEAMOUNT is a distinct generally equidimensional elevation greater than 1000m above the surrounding relief as measured from the deepest isobath that surrounds most of the feature.” 
 
Seafloor bathymetry (STRM) showing seamounts  in the GeoGarage platform

Recognized scientists in marine geosciences, hydrographers, oceanographers etc may have their name in the hall of fame of the GEBCO Gazetteer, however in accordance with a resolution of the United Nations Conference on the Standardization of Geographical Names, this can only be once they are deceased (as explained in B6).

The IHO-IOC GEBCO Gazetteer is the official international record of Undersea Feature Names across the globe.
It includes an interactive 3D map of the Earth to navigate and view undersea features, as well as Polar projections and 2D maps.
It records more than 4500 undersea features and allows visitors to search, view, and download information such as geographical location, feature type (seamount, ridge...) and dimensions, the person who discovered it, and the origin of the name.

Links :

Monday, November 22, 2021

Report: new data law cuts off access to Chinese AIS tracking

Inland traffic on Shanghai's Huangpu River (file image)

From Maritime Executive

Two new Chinese laws appear to be shutting down international access to ship AIS data picked up by shoreside stations in China, according to a new report.

According to Reuters, multiple Western users of AIS data have reported plummeting volumes of received signals - and it isn't because ships have turned off their AIS transcievers.
Instead, it appears that Chinese AIS data providers are responding to the restrictions in China's new Data Security Law (DSL) and Personal Information Protection Law (PIPL), which both took effect this fall.

These two laws restrict foreign access to any "important" data with bearing on Chinese national security or key infrastructure.
The fines for companies that fail to comply with the DSL are steep, up to $1.5 million, and PIPL's penalties are even larger.

The laws are new, and much will depend on how they are interpreted by China's regulators, but they appear to have created an immediate fall-off in the availability of Chinese terrestrial AIS receiver data for foreign users.
 
 MSA Maritime Safety Administration of the People's Republic of China AIS website :
 
One Chinese AIS data vendor confirmed to Reuters that it has stopped selling to foreign parties.

UK-based consultancy VesselsValue, which uses terrestrial AIS to track shipping patterns, told Reuters that it has seen a fall-off in AIS data availability of about 90 percent across all Chinese waters.
Two other sources said that the drop was smaller, about 45 percent, but still quite significant. 

Terrestrial AIS fills an important role in ship-tracking, according to Dana Goward, the former director of the U.S. Coast Guard's Maritime Domain Awareness Program.
 

Ships' AIS signals can be received by satellites, and this may fill in part of the gap left by China's new laws, but the loss of access to terrestrial AIS will mean a steep fall-off in tracking fidelity in Chinese littoral waters.
In China's busy harbors and waterways, hundreds of ships may be broadcasting in the same small area, and it can be hard for satellite receivers to pick those tightly-packed signals apart.

The change doesn't mean that ships have stopped broadcasting AIS, so it should have little impact on safety of navigation.
However, it will make it significantly harder for foreign observers to track ship movements in and around China - including movements potentially associated with illicit or clandestine activity.
"This is an unfortunate step backward for transparency in shipping," Goward said.
 

Saturday, November 20, 2021

NVIDIA to build Earth-2 supercomputer to see our future

Climate change is arguably the greatest threat facing humanity today.
Accurately predicting climate change is critical to plan for its disastrous impacts well in advance and to adapt to sea level rise, ecosystem shifts, and food and water security needs.
The Fourier Neural Operator (FNO) -- a novel AI model -- learns complex physical systems accurately and efficiently.
Here we see the FNO emulate a high-resolution Earth dataset, ERA5, and predict the behavior of extreme weather events across the globe days in advance in just 0.25 seconds on NVIDIA GPUs.
At 100,000 times faster than traditional numerical weather models, this is a significant step towards building digital twin Earth.
other video

 
The earth is warming.
The past seven years are on track to be the seven warmest on record.
The emissions of greenhouse gases from human activities are responsible for approximately 1.1°C of average warming since the period 1850-1900.
What we’re experiencing is very different from the global average.
We experience extreme weather — historic droughts, unprecedented heatwaves, intense hurricanes, violent storms and catastrophic floods.
Climate disasters are the new norm.
We need to confront climate change now.
Yet, we won’t feel the impact of our efforts for decades.
It’s hard to mobilize action for something so far in the future. But we must know our future today — see it and feel it — so we can act with urgency.
To make our future a reality today, simulation is the answer.
 
"The hardware needed to “see” just how bad it’s gonna be." @AnthonyDiMare
see large video
 
To develop the best strategies for mitigation and adaptation, we need climate models that can predict the climate in different regions of the globe over decades.
Unlike predicting the weather, which primarily models atmospheric physics, climate models are multidecade simulations that model the physics, chemistry and biology of the atmosphere, waters, ice, land and human activities.
Climate simulations are configured today at 10- to 100-kilometer resolutions.
But greater resolution is needed to model changes in the global water cycle — water movement from the ocean, sea ice, land surface and groundwater through the atmosphere and clouds.
Changes in this system lead to intensifying storms and droughts.
Meter-scale resolution is needed to simulate clouds that reflect sunlight back to space.
Scientists estimate that these resolutions will demand millions to billions of times more computing power than what’s currently available.
It would take decades to achieve that through the ordinary course of computing advances, which accelerate 10x every five years.
For the first time, we have the technology to do ultra-high-resolution climate modeling, to jump to lightspeed and predict changes in regional extreme weather decades out.
We can achieve million-x speedups by combining three technologies: GPU-accelerated computing; deep learning and breakthroughs in physics-informed neural networks; and AI supercomputers, along with vast quantities of observed and model data to learn from.
And with super-resolution techniques, we may have within our grasp the billion-x leap needed to do ultra-high-resolution climate modeling.
Countries, cities and towns can get early warnings to adapt and make infrastructures more resilient.
And with more accurate predictions, people and nations will act with more urgency.
So, we will dedicate ourselves and our significant resources to direct NVIDIA’s scale and expertise in computational sciences, to join with the world’s climate science community.
NVIDIA this week revealed plans to build the world’s most powerful AI supercomputer dedicated to predicting climate change.
Named Earth-2, or E-2, the system would create a digital twin of Earth in Omniverse.
All the technologies we’ve invented up to this moment are needed to make Earth-2 possible.
I can’t imagine a greater or more important use.