3 Big Ways Big Data and Supercomputing Are Making Weather More Predictable

Weather is often the one element that party planners loathe because of the lack of control or even predictability. Controlling weather without superhuman powers is definitely out of the question. Technologists and scientists are however constantly working to get one step closer to accurately predicting the weather.

The supercomputing and big data solution to weather prediction challenges

Improving weather predictability is not an easy task computationally and scientifically. Predictive models for weather have relied heavily on Supercomputing since the 1950s. Today’s climate and weather modeling still follows the same path blazed by Supercomputing.

It is in improving the computational capabilities that results are being churned out faster. Scientists and forecasters work with better computational capabilities to investigate complex phenomenon and produce several products designed specifically for forecasting.

The challenges that weather prediction presents like system and data management and model performance are all unique and high performance challenges. There are three key areas however that big data in collaboration with supercomputing will solve.

1. Making enormous data sets manageable and useful

The diversity and volume of environmental data is exponentially increasing globally. The demand on infrastructure for the management, transportation and storage of this data also increase consequentially.This increased demand can only be met by greater computational power. Thus the need for specialized services is created, to be filled by researchers from public and private institutions.

How it works: An example of this phenomenon is the use and leverage of sensors placed on automobiles. These sensors in large numbers in urban areas will provide real-time information about the weather. This ever-growing giant of data needs newer models that can analyze and then build on simulations used earlier.

2. Creating a higher model resolution

In order to improve weather forecasting and better estimate the long-term state of climate systems, particularly for extreme weather conditions, a higher resolution model is crucial.

Researchers at the University of Illinois and the National Center for Atmospheric Research recently used a new model called the Blue Waters supercomputers and simulated the Hurricane Sandy into a 500 meter resolution.

3. Crossing technology hurdles

With the world of weather forecasting becoming data intensive and computationally demanding, interconnect latencies, bandwidths, memory and I/O are becoming common bottlenecks for researchers.

The world of weather simulation requires thousands of processors to work in tandem and in parallel. This pushes software and hardware to its scalability limits. Apart from these compilers, application libraries and scalable operating systems are essential for sustained performance. Ultimately the software and the hardware are inextricably linked and have to work together.

How businesses benefit from weather forecasting

The IT enterprise stands to benefit the most from weather forecasting. Data centers that could be potentially wiped out by major disasters can now be saved through the forecasts, giving people a chance to prepare.

Channeling sales and work pattern

The early and granular forecasts are creating several business opportunities. If an unusually warm weekend in the mountains is predicted, then the alerts sent out to breweries will help them distribute a greater inventory.

If torrential rains are predicted on days when huge sales are supposed to hit stores, then the store owners can prepare and change their dates or up the infrastructure for patrons waiting outside.

Why we need proper weather forecasting to reduce the cost?

  • Weather impacts 33% of the worldwide GDP: Outside of the data services industry alone, weather has huge safety and economic implications. Just to name a few industries affected directly by weather, tourism, fishing, agriculture, airlines and recreation. The weather impacts a whopping 33% of the worldwide GDP.
  • Extreme weather increases cost: Extreme weather such as cyclones, tsunamis and wild fires can seriously affect public life and safety. Extreme weather in 2013 cost the entire world $125 billion in the year 2013 alone. With the frequency of extreme weather across the world any weather forecasting system can help reduce the cost and the lives lost.
  • Extreme weather leads to the loss of resources: Without data that is accurate and reliable, the government and the private sector have lost innumerable resources in trying to save human lives. When people are evacuated for extreme weather forecasts that are not accurate, the lost revenue and the relocation expenses are staggering. People and institutions like hospitals stock up on reserve fuel in case of an electric shutdown. Numerous resources therefore are stockpiled in anticipation of an inaccurate weather forecast.

While it is impossible for us mortals to control weather, an evolved weather forecasting system will help shape better informed plans. These plans can help plug the financial loses, reduce government spending, save lives and even create new business opportunities.


Advanced research is consistently offering a whole new variety of specialized weather forecast services not only for the public but also for the private sector. When weather prediction was first conceived 64 years ago, the capabilities of the machines that the forecast relies on today couldn’t even be imagined.

Supercomputing and the innovations in that field have hitherto kept up with the demands of the world, and are poised to offer more innovations in the foreseeable future.

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