Weather Service tells Congress radar gaps don’t hurt warning accuracy

Using these radars, forecasters can spot the existence of a tornado by detecting airborne debris lofted by the twister’s circulation. They can track the all-important rain-snow line in winter storms and even spot smoke plumes from severe wildfires. But as capable as the U.S. radar network is, gaps in coverage have drawn consistent complaints from meteorologists and lawmakers frustrated by unwarned-of severe weather.

Now, an overdue report to Congress from the National Oceanic and Atmospheric Administration (NOAA), which operates the National Weather Service, attempts to quantify the impacts of such gaps on warning performance. The results downplay the significance of the gaps, counter to the experience of some public- and private-sector meteorologists.

Several meteorologists said the congressionally mandated report inadequately addresses the true impacts of these gaps, describing its methodology as inadequate and incomplete and its conclusions as “disappointing” and even “offensive.”

The gaps, which the report identifies in some detail, occur in locations so far removed from radar sites that the beams emitted by the radar overshoot the weather they are intended to detect. The greater distance a location is from a radar site, the higher in the sky the radar scans for trouble.

The Charlotte metro area, home to about 2.6 million, is served by a Doppler radar 80 miles away in Greer, S.C., and the radar beam intersects clouds at about 5,000 feet or more above the city, missing some of the most important low-level weather features that can determine whether a storm will spawn a tornado. During the winter, some snow and ice events can take place largely below the height of the beam.

Other cities have far more coverage, including Washington, for which there is a Weather Service Doppler radar in Sterling, Va., as well as less powerful radars situated near the region’s three major airports and Joint Base Andrews. With radar beams reaching clouds at altitudes below 3,000 feet over the city, meteorologists have the ability to see the lower levels of storms, which is where tornadoes tend to form.

Radar gaps have been a contentious issue in the weather community for years, not only in Charlotte, but also in the Pacific Northwest, where spotting dangerous weather moving in from the Pacific is especially important.

Weather Service finally responds to Congress but says there’s no problem here

In a 2017 bill, Congress directed the Weather Service to examine how radar gaps affect warning accuracy and report to Congress within less than a year. Separately, Congress asked for a report on warning performance associated with radar coverage where the beam is 6,000 feet above ground level and higher.

Long past congressional deadlines, the radar gaps report was released in September to address both congressional requests, and it contains some surprising findings.

Instead of concluding that radar gaps make a difference in severe weather detection and warnings, as many meteorologists strongly suspect, the Weather Service told Congress that they make little to no meaningful differences in warning performance.

“Poor radar coverage is never the single contributing

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Cough-scrutinizing AI shows major promise as an early warning system for COVID-19

Asymptomatic spread of COVID-19 is a huge contributor to the pandemic, but of course if there are no symptoms, how can anyone tell they should isolate or get a test? MIT research has found that hidden in the sound of coughs is a pattern that subtly, but reliably, marks a person as likely to be in the early stages of infection. It could make for a much-needed early warning system for the virus.

The sound of one’s cough can be very revealing, as doctors have known for many years. AI models have been built to detect conditions like pneumonia, asthma and even neuromuscular diseases, all of which alter how a person coughs in different ways.

Before the pandemic, researcher Brian Subirana had shown that coughs may even help predict Alzheimer’s — mirroring results from IBM research published just a week ago. More recently, Subirana thought if the AI was capable of telling so much from so little, perhaps COVID-19 might be something it could suss out as well. In fact, he isn’t the first to think so.

He and his team set up a site where people could contribute coughs, and ended up assembling “the largest research cough dataset that we know of.” Thousands of samples were used to train up the AI model, which they document in an open access IEEE journal.

The model seems to have detected subtle patterns in vocal strength, sentiment, lung and respiratory performance, and muscular degradation, to the point where it was able to identify 100% of coughs by asymptomatic COVID-19 carriers and 98.5% of symptomatic ones, with a specificity of 83% and 94% respectively, meaning it doesn’t have large numbers of false positives or negatives.

“We think this shows that the way you produce sound, changes when you have COVID, even if you’re asymptomatic,” said Subirana of the surprising finding. However, he cautioned that although the system was good at detecting non-healthy coughs, it should not be used as a diagnosis tool for people with symptoms but unsure of the underlying cause.

I asked Subirana for a bit more clarity on this point.

“The tool is detecting features that allow it to discriminate the subjects that have COVID from the ones that don’t,” he wrote in an email. “Previous research has shown you can pick up other conditions too. One could design a system that would discriminate between many conditions but our focus was on picking out COVID from the rest.”

For the statistics-minded out there, the incredibly high success rate may raise some red flags. Machine learning models are great at a lot of things, but 100% isn’t a number you see a lot, and when you do you start thinking of other ways it might have been produced by accident. No doubt the findings will need to be proven on other data sets and verified by other researchers, but it’s also possible that there’s simply a reliable tell in COVID-induced coughs that a computer listening system can hear quite

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U.S. Universities Received Billions in Unreported Foreign Funds, Education Department Finds, Warning of ‘National Security Risk’

The Department of Education on Tuesday warned that funding from foreign adversaries at U.S. universities could pose a risk to national security in a report detailing its year-long investigation that found a number of universities had not appropriately reported funding received from entities in China, Qatar, and Russia.



Betsy DeVos wearing a blue shirt: U.S. Education Secretary Betsy Devos speaks in the Rose Garden at the White House in Washington, D.C., July 9, 2020.


© Kevin Lamarque/Reuters
U.S. Education Secretary Betsy Devos speaks in the Rose Garden at the White House in Washington, D.C., July 9, 2020.

The department found that “many large and well-resourced institutions of higher education have aggressively pursued and accepted foreign money,” while failing to properly report the funding.

“The Department’s investigations highlight the fact that foreign adversaries are likely targeting specific institutions for their R&D and technologies. This information highlights the critical national and economic security risks created by institutions’ failure to be fully transparent with respect to foreign gifts and contracts,” the 34-page report warned. 

The agency says foreign state and non-state actors have, for decades, “devoted significant resources to influence or control teaching and research, to the theft of intellectual property or even espionage, and to the use of American campuses as centers for propaganda operations and other projections of soft power.”

The report details the investigation the department began last year into whether U.S. universities are appropriately reporting foreign contracts and gifts that total more than $250,000 in one year. While it isn’t illegal to receive foreign funds, the universities must disclose the funding under Section 117 of the Higher Education Act of 1965 on foreign funding, which the department has worked to enforce with renewed vigor under the leadership of Secretary Betsy DeVos.

The report found that a university, which the Wall Street Journal has identified as Cornell University, had failed to report more than $1.2 billion in foreign funds to U.S. authorities in recent years. The university had not reported $760 million related to its campus in Qatar or roughly $1 million in contracts from Huawei Technologies, the “heavily state-influenced” Chinese technology firm.

Several schools initially failed to report receiving millions of dollars from Huawei, which the report says “became a household name not only because of its products’ international presence but because of these products’ potential enablement of foreign espionage.” The agency detailed how the Chinese Communist Party uses the firm to exert influence, including via a CCP committee baked into its corporate structure and $75 billion in support from the Chinese government. 

Huawei funded a number of initiatives in competitive industries such as robotics, semiconductors and online cloud services, the report said. Though most American universities stopped accepting funds from Huawei in 2018 based on U.S. officials’ concerns that the firm posed a national security risk, several schools were already locked into contracts with the company.

A school, which the Journal identified as MIT, has had roughly $11 million in contracts and agreements with Huawei since 2013, according to the report, funding an array of initiatives from research agreements to donations for specific projects and programs. 

The report said another school, which the

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