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Disaster Management

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Revealing the inner workings of a tornado

Supercomputers and high-speed data connections play a crucial role when researchers re-create tornadoes and thunderstorms to better understand the dynamics of these powerful natural phenomena. Leigh Orf from CIMSS, the Cooperative Institute for Meteorological Satellite Studies at the University of Wisconsin-Madison, leads a group of researchers specialised in re-creating meteorological events leading up to the forming of tornadoes. Built on real-world observational data, the computer simulations unveil the inner workings of these monstrous events in unprecedented detail.

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Protecting the Earth from hazardous asteroids

On 19 April 2017 the ‘Rock’ asteroid made an uncomfortably close pass to Earth – the closest in 400 years. The first step to protecting against such hazards is to monitor them to calculate their precise orbits; this requires fast, reliable internet connections so that the huge volumes of observation data involved can be sent speedily and reliably to researchers around the world for analysis.

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Weather forecasting to keep the population safe

As weather forecasts are becoming increasingly detailed, data volumes are increasing as well, demanding high-speed connectivity and supercomputing power.

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DUMBO to the rescue – deploying ICT for emergency medical care in post earthquake Nepal

On the 12th of April 2015, a devastating earthquake hit Nepal, including its capital Kathmandu, demolishing half a million buildings, killing 8.800 and injuring over 16.000 people. The research and education network of Nepal, NREN, participated in the relief work by setting up emergency wireless networks at a number of hospitals treating earthquake victims.

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Grid computing helps India manage floods, monsoons and climate change

The Indian summer monsoon is a manifestation of complex interactions between land, ocean and atmosphere and the simulation of its mean pattern and its variability on inter-annual scales is one of the challenging problems in climate studies. The correct prediction of this complex phenomenon is vital to national planning and economic policy making.

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Helping to win the race against severe weather

With extreme weather events increasingly hitting news headlines around the world, accurate and timely forecasts are essential for effective disaster warning and mitigation systems. This, in turn, calls for joint research efforts within the global meteorological community to improve models and tools for predicting severe weather, such as hurricanes, tornadoes, cyclones, floods, heat waves etc.

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Monitoring and forecasting extreme environmental events to save lives

When the Latin American Observatory of Extraordinary Events announced in October 2011 that rainfall was expected to be above average for the South American Northwest and above average for the Southeast of the same region, an early alert for floods was issued for Panama, Colombia and Venezuela, and one of a drought for North-western Argentina, Uruguay and Paraguay. This is an example of how the information gathered and disseminated by the Observatory, a collaboration involving a number of institutions, helps Latin American nations with risk management for extreme environmental events.

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Sensor networks helping predict and respond to natural disasters

Ocean Networks Canada (an initiative of the University of Victoria) is developing a software system to co-ordinate readings from underwater sensors in order to detect and report natural hazards, such as earthquakes and tsunamis. This system has the potential to help save lives and limit the impacts of natural disasters.

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Saving lives and livelihoods

Central Asia is under constant threat from its vulnerability to earthquakes. The region sits on the junction of two tectonic plates that have been colliding for millions of years, building mountains and causing earthquakes. CAREN – the Central Asia Research and Education Network – underpins international scientific efforts in the region to protect lives and to safeguard economic growth from the consequences.