PressureNet App Feeds Scientists Atmospheric Data from Thousands of Smartphones | MIT Technology Review

An Android app that measures atmospheric pressure is now feeding that distributed data to scientists working on better ways to predict the weather.

The app, called PressureNet, highlights the potential of distributed sensing using mobile devices and shows how the sophisticated sensors found in modern smartphones could be harnessed for research. It was launched in late 2011 By Jacob Sheehy, a software developer for Flighthub.com, and Phil Jones, an independent Web designer, who became friends while studying at Concordia University in Montreal.

Deep Thunder: Preparing for extreme weather events with modeling technology (by IBMSocialMedia)

IBM’s high resolution weather forecasting and modeling technology - called Deep Thunder - provides a predictive capability to map approaching weather events, and model the anticipated impact. The system applies mathematical algorithms to understand the interaction of the atmosphere with the surface of the earth. Detailed risk assessments are developed using data from soil saturation levels, rates and flow of water run off, the region’s topography, as well as historical rainfall and flood records. Using historical data, sophisticated analytics software and ever more powerful supercomputers, cities can get extremely accurate and detailed weather forecasts for very specific locations — such as a two-block radius — up to 48 hours in advance.

With the predictive information, emergency response teams are able to be deployed close to where problems are likely to occur. This technology can provide longer advance notice of adverse weather conditions, allowing more time for disaster prevention. Rather than monitor a storm, we can stage resources at the right place and time prior to an event to minimize the impact and save lives.

smartercities:

Sheltering A City With Data: The Rio de Janeiro Story (by IBM)

Rio de Janeiro, the most visited city in the southern hemisphere, will soon play host to both the World Cup and the Olympic Games. Unfortunately it is also the location of the biggest natural disaster in Brazil’s history. In 2010, Rio de Janeiro was devastated by severe floods and mudslides, which took hundreds of lives and left thousands homeless.

Out of the need for improved emergency management and better weather prediction, IBM helped the city integrate predictive analytics, real-time data, and weather modeling technology and establish a state-of-the-art operations center. At the heart of the center is PMAR, a high resolution weather prediction system powered by IBM’s Deep Thunder supercomputer. It lets the city predict rains and floods 48 hours in advance, allowing for better management of emergency services and potentially saving lives.

From there the Rio Operations Center grew, and now acts as a nervous system for the entire city: managing traffic congestion, keeping a close eye on crime response and prevention, predicting brownouts in the power grid, and coordinating large-scale events to ensure public safety.

Integrating over 30 agencies and services across the city, the Rio Operations Center empowers the government and its citizens to be prepared for whatever nature may throw their way. IBM is helping make cities smarter. Let’s build a smarter planet -

Made in IBM Labs: New Flood Prediction Technology Simulates Rivers 100x Faster than Real Time (by IBMSmarterWater)

Floods are the most common natural disaster in the United States , but traditionally flood prediction methods are focused only on the main stems of the largest rivers — overlooking extensive tributary networks where flooding actually starts, and where flash floods threaten lives and property.

IBM’s new flood prediction technology can simulate tens of thousands of river branches at a time and could scale further to predict the behavior of millions of branches simultaneously. By coupling analytics software with advanced weather simulation models, such as IBM’s Deep Thunder, municipalities and disaster response teams could make emergency plans and pinpoint potential flood areas on a river.

Advanced Tornado Technology Could Reduce Deaths : NPR
Tornadoes have killed at least 530 people in the U.S. this year, the highest death toll since 1950.
But  researchers say they are working on new detection and forecasting  technologies that could help reduce tornado deaths in the future.
One  of those technologies got put to the test on May 24 when a tornado  touched down near Chickasha, Okla., and began heading northeast at near  freeway speed.
The National Weather Service  was tracking the twister with radar, which uses bursts of radio waves to  gauge the shape, power and direction of a storm. And data from Weather  Service radar showed the tornado would cross the southern part of  Newcastle about 25 miles up Interstate 44. So officials in Newcastle  sent emergency crews to that part of the city.
But by chance, the storm was also being tracked by a separate,  experimental radar system designed to give more precise information. And  as the tornado approached Newcastle, the city’s emergency manager was  studying data from that system."Based on that data, he could  see that the tornado was actually taking a turn to the north," says  Brenda Philips, who works for a group called CASA (Collaborative  Adapting Sensing of the Atmosphere) that developed the new radar system.
So  the emergency manager moved the first responders north, which allowed  them to move into the affected areas more quickly, Philips says.
It  was a big success for CASA, which was founded by several universities  specifically to improve weather radar systems. The group receives  funding from the National Science Foundation.
The  CASA radars did a better job than traditional radars because they were  able to provide a fresh image of the storm every minute, says Michael  Zink, from the electrical and computer engineering department at the  University of Massachusetts Amherst.

Advanced Tornado Technology Could Reduce Deaths : NPR

Tornadoes have killed at least 530 people in the U.S. this year, the highest death toll since 1950.

But researchers say they are working on new detection and forecasting technologies that could help reduce tornado deaths in the future.

One of those technologies got put to the test on May 24 when a tornado touched down near Chickasha, Okla., and began heading northeast at near freeway speed.

The National Weather Service was tracking the twister with radar, which uses bursts of radio waves to gauge the shape, power and direction of a storm. And data from Weather Service radar showed the tornado would cross the southern part of Newcastle about 25 miles up Interstate 44. So officials in Newcastle sent emergency crews to that part of the city.

But by chance, the storm was also being tracked by a separate, experimental radar system designed to give more precise information. And as the tornado approached Newcastle, the city’s emergency manager was studying data from that system.

"Based on that data, he could see that the tornado was actually taking a turn to the north," says Brenda Philips, who works for a group called CASA (Collaborative Adapting Sensing of the Atmosphere) that developed the new radar system.

So the emergency manager moved the first responders north, which allowed them to move into the affected areas more quickly, Philips says.

It was a big success for CASA, which was founded by several universities specifically to improve weather radar systems. The group receives funding from the National Science Foundation.

The CASA radars did a better job than traditional radars because they were able to provide a fresh image of the storm every minute, says Michael Zink, from the electrical and computer engineering department at the University of Massachusetts Amherst.

Mapping Snow Via Mobile Phone
Source: MobileActive
Jim Colgan and the WNYC newsroom wanted to get a sense of what was happening on the streets. Problem was, there was no good or easy way to do this. The station couldn’t rely on the city for real-time information, and reporters couldn’t get to many of the areas. The answer was to have the listeners share their own reports and stories, via mobile phone. WNYC and programs like The Takeaway (which is broadcast from WNYC and distributed byPublic Radio International) are no stranger to mobile technology. “Part of what we are trying to do with the show is be more multi-platform and use interactive tools,” Colgan said. The program has used mobile technology in “sourcing through texting” endeavors and frequently receives SMS reports from subscribers ahead of a given show.  WNYC and The Takeaway also reach out to audiences on Facebook and the internet, but Colgan said the most direct response comes from connecting with people via mobile phone.

Mapping Snow Via Mobile Phone

Source: MobileActive

Jim Colgan and the WNYC newsroom wanted to get a sense of what was happening on the streets. Problem was, there was no good or easy way to do this. The station couldn’t rely on the city for real-time information, and reporters couldn’t get to many of the areas. The answer was to have the listeners share their own reports and stories, via mobile phone. 

WNYC and programs like The Takeaway (which is broadcast from WNYC and distributed byPublic Radio International) are no stranger to mobile technology. “Part of what we are trying to do with the show is be more multi-platform and use interactive tools,” Colgan said. The program has used mobile technology in “sourcing through texting” endeavors and frequently receives SMS reports from subscribers ahead of a given show.  WNYC and The Takeaway also reach out to audiences on Facebook and the internet, but Colgan said the most direct response comes from connecting with people via mobile phone.

Supercomputer  reproduces a cyclone’s birth, may boost forecasting

At the heart of Shen’s work is an advanced computer model that could improve our understanding of the predictability of tropical cyclones. The research team uses the model to run millions of numbers — atmospheric conditions like wind speed, temperature, and moisture — through a series of equations. This results in digital data of the cyclone’s location and atmospheric conditions that are plotted on geographical maps.  

Supercomputer reproduces a cyclone’s birth, may boost forecasting

At the heart of Shen’s work is an advanced computer model that could improve our understanding of the predictability of tropical cyclones. The research team uses the model to run millions of numbers — atmospheric conditions like wind speed, temperature, and moisture — through a series of equations. This results in digital data of the cyclone’s location and atmospheric conditions that are plotted on geographical maps.  

Your phone knows a lot about the world around you. If you take that intelligence and combine it in the cloud with that of every other phone, we have an incredible snapshot of what is going on in the world right now. Weather updates can be based on not hundreds of sensors, but hundreds of millions. Traffic reports can be based not on helicopters and road sensors, but on the density, speed, and direction of the phones (and people) stuck in the traffic jams.

IBM Supercomputers Power Up Weather Forecasts

The National Oceanic and Atmospheric Administration (NOAA) has completed a nine-year, $180 million IBM supercomputer build-out for weather and climate prediction.


The two new systems, dubbed Stratus and Cirrus, will let NOAA run more complex models in an effort tol boost the nation’s watch and warning lead times for tornadoes, floods, hurricanes, tsunamis, and winter storms.

The two supercomputers run as primary and backup in tandem, and are both based on IBM Power 575 Systems. The main Stratus supercomputer will process gigabytes of weather data each day, including temperature, wind, atmospheric pressure, and satellite and oceanographic data.

The computers are capable of making 69.7 trillion calculations per second. NOAA said that’s the equivalent of one person with a calculator working for three million years.

via ibmfan:


Via: http://www.goodcleantech.com/

Reblog this post [with Zemanta]
Precision Forecasting for Weather-Sensitive Business Operations “Deep Thunder” is a service that provides local, high-resolution weather predictions customized to business applications for weather-sensitive operations up to a day ahead of time. In particular, the goal is to provide weather forecasts at a level of precision and fast enough to address specific business problems. Such forecasts can be used for competitive advantage or to improve operational efficiency and safety. (via IBM Deep Thunder)

Precision Forecasting for Weather-Sensitive Business Operations “Deep Thunder” is a service that provides local, high-resolution weather predictions customized to business applications for weather-sensitive operations up to a day ahead of time. In particular, the goal is to provide weather forecasts at a level of precision and fast enough to address specific business problems. Such forecasts can be used for competitive advantage or to improve operational efficiency and safety. (via IBM Deep Thunder)

The West Virginia Division of Highways on Friday opened the first phase of a new Intelligent Transportation System, which uses computer-coordinated data from roadside video cameras, weather stations and pavement sensors to help traffic move more safely and more efficiently.