Category Archives: Complex Systems Concepts

EarthRisk crunches data to predict extreme weather

EarthRisk crunches data to predict extreme weather | Green Tech – CNET News.

The HeatRisk application gives trained meteorologists tools to analyze the weather patterns that lead to extreme heat weeks before these events occur.

(Credit: EarthRisk Technologies)

EarthRisk Technologies is mining years of weather data for profit.

The San Diego-based start-up today launched HeatRisk, a Web-based application designed to predict extreme heat events 30 to 40 days out. The target audience is meteorologists who work for energy companies or other organizations which need a long-range forecast to hedge their risk from extreme temperatures.

Over time, EarthRisk Technologies intends to design a product aimed at less technical users and investigate whether its research method can be applied to predicting extreme storms, according to President and Chief Science Officer Stephen Bennett. Its first product, released last year, is for analyzing the factors that lead to extreme cold events.

More researchers are tapping powerful computers and software able to present big sets of data to address environmental problems, such as air and water quality or extreme weather. EarthRisk Technologies originally began as a research project at the Scripps Institute of Oceanography in San Diego, but company founders saw there was a business opportunity buried in its research.

“We realized if we could write a software application around our research, it would increase the value of the underlying research tremendously,” said Bennett. “The (corporate sponsors) said if you can put together a good application and continue to do cutting-edge research, we will be the first to sign up.”

Three years ago, Scripps was approached by energy companies and hedge funds which deal in energy futures to see if there was a way to identify major weather events beyond the National Weather Service forecast. In addition to causing safety hazards, extreme weather throws energy markets out of whack by creating an imbalance between supply and demand.

A power generator, for example, could use HeatRisk to prepare for a coming heat wave by purchasing fuel for auxiliary generators to meet higher demand. Having a longer lead time than traditional forecasts gives energy buyers and traders an advantage, explained Bennett.

Right now, the people who use the software need to be skilled in meteorology and be comfortable analyzing atmospheric conditions directly. Eventually, the company hopes its software could be used by retailers, farmers, or municipalities which can use long-range forecasts to prepare for extreme temperatures, Bennett said.

Dominoes lining up
The accuracy of weather forecasting has improved over the past decade from supercomputers and simulation software, but the focus tends to be on shorter-term windows than what EarthRisk is doing, Bennett said. And rather than trying to forecast average temperatures, EarthRisk is seeking the factors that lead to specific extreme temperature events.

The company’s TempRisk platform uses historical weather data to isolate the factors that lead to extreme temperatures.

(Credit: EarthRisk Technologies)

To build the application, researchers analyzed weather data going back to 1948 to identify the patterns that led up to extreme cold or heat. Each pattern is sort of like a domino and when enough of them line up, the software can help identify the probability of an extreme weather event, Bennett explained.

In a recent example, a combination of a large high-pressure system over Scandinavia and a low-pressure system in the Atlantic, followed by another system over the Solomon Islands pointed to a heat spike in the U.S.

People can use the analytical application through a Web browser and pay a fee for using it during a season and specific regions. A forecasting application could be ready in about six months, Bennett said.

Using software to dodge weather risk is new so it’s still not clear there is a strong demand for it. But EarthRisk isn’t the only company to use cloud computing and large amounts of data to hedge against extreme weather. Earlier this year, WeatherBill launched a service that gives farmers insurance against the effects of extreme weather by continuously analyzing weather data.

 

High-speed trading algorithms place markets at risk

One Per Cent: High-speed trading algorithms place markets at risk.

Jacob Aron, technology reporter

Computers that buy and sell shares in a fraction of a second are in danger of destabilising stock markets around the world says Andrew Haldane, executive director for financial stability at the Bank of England. Speaking last night at the International Economic Association in Beijing, China, Haldane said that High Frequency Trading (HFT) firms were in a “race to zero” that could increase market volatility.

HFT algorithms can execute an order in just a few hundred microseconds, rapidly trading shares back and forth in order to quickly eke out profits from minor differences on the various exchanges. These trades are so fast that the physical location of the computers executing them becomes vital – even being a few hundred kilometres away from the exchange could mean missing out. It’s commerce far removed from any ordinary experience, as Haldane illustrated with an every day example: “If supermarkets ran HFT programmes, the average household could complete its shopping for a lifetime in under a second.”

Now it seems this lightning-fast trading could come at a cost. Haldane blamed HFT for causing the “Flash Crash” which occurred on US markets last year, with the Dow Jones losing $1 trillion in just half an hour. The event was marked by trading oddities such as management consulting firm Accenture shares falling from $40 to $0.01, while auction house Sotheby’s rose from $34 to $99,999.99 – the lowest and highest values permitted by HFT algorithms.

Haldane said that the latest research shows that while HFT increases liquidity when markets are functioning normally, it has the opposite effect during more troubled times. He also built on work by Benoit Mandelbrot, the mathematician famous for inventing the word “fractal” for patterns with self-similarity. Mandelbrot showed that stock trading can also display fractal behaviour, and Haldane last night said that HFT algorithms cramming more and more trades into this fractal structure could lead to the kind of pricing abnormalities seen during the Flash Crash.

The solution? Introduce new rules to limit the speed of HFT. “Flash Crashes, like car crashes, may be more severe the greater the velocity,” said Haldane. “Grit in the wheels, like grit on the roads, could help forestall the next crash.”

World's oceans move into 'extinction phase'

World’s oceans move into ‘extinction phase’ – Telegraph.

Maybe a dupe of something V posted….

A preliminary report from an international panel of marine experts said that the condition of the world’s seas was worsening more quickly than had been predicted.

The scientists, gathered for a workshop at Oxford University, warned that entire ecosystems, such as coral reefs, could be lost in a generation.

Already fish stocks are collapsing, leading to a risk of rising food prices and even starvation in some parts of the world.

The experts blamed the increased amount of carbon dioxide in the atmosphere for pushing up ocean temperatures, boosting algae so there is less oxygen and increasing acidity of the water.

The conditions are similar to every previous mass extinction event in the Earth’s history.

Dr Alex Rogers, scientific director of the International Programme on the State of the Ocean (IPSO) which convened the panel with the International Union for Conservation of Nature (IUCN), said the next generation would suffer if species are allowed to go extinct.

“As we considered the cumulative effect of what humankind does to the ocean the implications became far worse than we had individually realised,” he said.

“This is a very serious situation demanding unequivocal action at every level.

“We are looking at consequences for humankind that will impact in our lifetime and, worse, our children’s and generations beyond that.”

The marine scientists called for a range of urgent measures to cut carbon emissions, reduce over-fishing, shut unsustainable fisheries, create protected areas in the seas and cut pollution.

Earthquake? Terrorist bomb? Call in the AI

Earthquake? Terrorist bomb? Call in the AI – tech – 23 May 2011 – New Scientist.

In the chaos of large-scale emergencies, artificially intelligent software could help direct first responders

9.47 am, Tavistock Square, London, 7 July 2005. Almost an hour has passed since the suicide bombs on board three underground trains exploded. Thirty-nine commuters are now dead or dying, and many more are badly injured.

Hassib Hussain, aged 18, now detonates his own device on the number 30 bus – murdering a further 13 and leaving behind one of the most striking images of the day: a bus ripped open like a tin of sardines.

In the aftermath of the bus bomb, questions were raised about how emergency services had reacted to the blast. Citizens and police called emergency services within 5 minutes, but ambulance teams did not arrive on the scene for nearly an hour.

As the events of that day show, the anatomy of a disaster – whether a terrorist attack or an earthquake – can change in a flash, and lives often depend on how police, paramedics and firefighters respond to the changing conditions. To help train for and navigate such chaos, new research is employing computer-simulation techniques to help first responders adapt to emergencies as they unfold.

Most emergency services prepare for the worst with a limited number of incident plans – sometimes fewer than 10 – that tell them how to react in specific scenarios, says Graham Coates of Durham University, UK. It is not enough, he says. “They need something that is flexible, that actually presents them with a dynamic, tailor-made response.”

A government inquest, concluded last month, found that no additional lives were lost because of the delay in responding to the Tavistock Square bomb, but that “communication difficulties” on the day were worrying.

So Coates and colleagues are developing a training simulation that will help emergency services adapt more readily. The “Rescue” system comprises up to 4000 individual software agents that represent the public and members of emergency services. Each is equipped with a rudimentary level of programmed behaviours, such as “help an injured person”.

In the simulation, agents are given a set of orders that adhere to standard operating procedure for emergency services – such as “resuscitate injured victims before moving them”. When the situation changes – a fire in a building threatens the victims, for example – agents can deviate from their orders if it helps them achieve a better outcome.

Meanwhile, a decision-support system takes a big-picture view of the unfolding situation. By analysing information fed back by the agents on the ground, it can issue updated orders to help make sure resources like paramedics, ambulances and firefighters are distributed optimally.

Humans that train with the system can accept, reject or modify its recommendations, and unfolding event scenarios are recorded and replayed to see how different approaches yield different results. Coates presented his team’s work at the International Conference on Information Systems for Crisis Response and Management in Lisbon, Portugal, last week.

That still leaves the problem of predicting how a panicked public might react to a crisis – will fleeing crowds hamper a rescue effort, or will bystanders comply with any instructions they receive?

To explore this, researchers at the University of Notre Dame in South Bend, Indiana, have built a detailed simulation of how crowds respond to disaster. The Dynamic Adaptive Disaster Simulation (DADS) also uses basic software agents representing humans, only here they are programmed to simply flee from danger and move towards safety.

When used in a real emergency situation, DADS will utilise location data from thousands of cellphones, triangulated and streamed from masts in the region of the emergency. It can make predictions of how crowds will move by advancing the simulation faster than real-time events. This would give emergency services a valuable head start, says Greg Madey, who is overseeing the project.

A similar study led by Mehdi Moussaïd of Paul Sabatier University in Toulouse, France, sought to address what happens when such crowds are packed into tight spaces.

In his simulation, he presumed that pedestrians choose the most direct route to their destination if there is nothing in their way, and always try to keep their distance from those around them. Running a simulation based on these two rules, Moussaïd and his colleagues found that as they increased the crowd’s density, the model produced crushes and waves of people just like those seen in real-life events such as stampedes or crushes at football stadiums (Proceedings of the National Academy of Sciences, DOI: 10.1073/pnas.1016507108). The team hope to use their model to help plan emergency evacuations.

Jenny Cole, head of emergency services at London-based independent think tank The Royal United Services Institute, wrote a report on how the different emergency services worked together in the wake of the London bombings. She remains “sceptical” about these kinds of simulations. “No matter how practical or useful they would be, there’s usually no money left in the end to implement them,” she says.

For his part, Coates says he plans to release his system to local authorities for free as soon as it is ready.

A cacophony of tweets

In the chaotic moments after disaster strikes, people often turn to Twitter for information. But making sense of a flurry of Twitter posts can be difficult.

Now Jacob Rogstadius at the University of Madeira in Portugal and his team have developed a system that sorts updates from Twitter by keyword – for example “Japan” or “earthquake” – and places them into an event timeline, without the need for hashtags.

In the next phase of development, people will look at tweets clustered in this way to judge the pertinence and reliability of different sources of information, or request more – pictures of the area, for example – to create a virtual “incident room” as the crisis unfolds.

Scientists Decide on Top 5 Issues for Sustainability: Scientific American Podcast

Scientists Decide on Top 5 Issues for Sustainability: Scientific American Podcast.

It’s the environmental question of our time: what sustainable practices can keep our planet optimally habitable? Now a group of international scientists has published a report outlining five key areas of concentration necessary to protect the environment, as well as human societies and economies. The report was published by the International Council for Science (ICSU) and the International Social Science Council.

And the winners are…

Forecasting —we need to have pertinent & accurate forecasts of future environmental conditions and their consequences for people.

The second is observing. We need to develop better observation systems to record global and regional environmental change.

Three is something they call confining—anticipating and recognizing disruptive environmental change to quickly manage it.

Four: Responding—Determine those institutional, economic and behavioral responses that will make global sustainability possible.

Lastly, five is a big one: encourage innovation in technology and policy to achieve sustainability.

Clearly, these bullet points represent an overarching, general strategy. The next step, already underway, is to create an organized and focused international structure that can make these five recommendations a reality—and soon: the ICSU hopes for significant progress in all five areas within the next decade.

—Christie Nicholson