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Enhancing Climate Monitoring & Research with the Right Solutions for Data Analytics



Traditional IT is no longer sufficient to power weather and climate research. Scientists need a combination of HPE solutions and NVIDIA GPUs to handle massive amounts of data and accelerate insights.

Hurricanes have killed approximately 1.9 million people worldwide over the past 200 years. Of these powerful storms, Hurricane Katrina is believed to be the costliest hurricane in history, causing an estimated $100 billion in damages. Data analytics can significantly reduce casualties and damages, and dramatically reduce the anual $12 billion global economic loss by enabling early and precise warning.

Climate monitoring and research is becoming increasingly important as demand rises for more accurate forecasts, scientists strive to understand weather patterns, and try to predict the next natural disaster. Traditional technology is no longer sufficient to accomplish these tasks, leading research organizatons to invest in a powerful, new style of IT capable of handling massive amounts of data anclimateBlog.jpgd driving compute performance.

Deploying a powerful hardware platform is the first step to boosting the speed and quality of operations. High performance computing (HPC) is the cornerstone of a fast, efficient, and reliable IT environment, allowing users to streamline business innovation and scale to fit their evolving needs.  Organizations can harness the power of HPC applications accelerated by NVIDIA GPUs to process a constant stream of weather data - including rainfall, temperature, atmospheric pressure, and sea levels - and compare it to historical data for insights. Additionally, NVIDIA GPU accelerators enhance data stores, like the data center, to optimize analytics and other critical processes. These cutting-edge capabilities enable scientists to tackle their most challenging compute-intensive and data-heavy workloads to enhance climate monitoring and research.


The ability to quickly process data and identify patterns is crucial to improve the accuracy of weather predictions. Researchers can utilize predictive analytics to gain insight into future conditions. For example, the United Nations may resolve to reduce carbon emissions from automobiles, air conditioners, and industrial plants by 2 percent in the next 5 years. However, by analyzing the environmental impact of air pollution, scientists can determine that a 5 percent reduction is necessary to decelerate climate change, reduce respiratory illnesses, and other benefits.

Reserachers can gain highly valuable insight from predictive analytics, and many organizations are investing in artificial intelligence (AI) capabilities to achieve faster, more accurate results. According to a recent survey by PwC, 63 percent of respondents believe AI will help solve complex problems. 67 percent of business leaders feel AI will help humans and machines combine both digital and human intelligences to expand our knowledge, and a majority believe AI will help resolve issues like climate change.

AI adoption is growing rapidly as scientists employ sophisticated learning algorithms to predict how long a storm will last, whether it will product damaging hail, or which communities are at risk. Predictive models are also being used to improve risk analytics - insights gleaned from these models can even project economic losses. Risk Management Solutions (RMS), the world's leading catastrophe risk modeling company, estimated that Hurricane Harvey would cause as much as $70–90 billion in damages from wind, storm surge, and inland flooding. By comparing probable outcomes, scientists were able to identify real-time actions to help mitigate risks.


Today's organizations need next-generation solutions to improve data management across their networks, fuel AI algorithms, and extract real-time insight. NVIDIA GPUs work to accelerate analytics in the data center, allowing scientists to execute increasingly complex workloads - like assessing geospatial data to predict the next hurricane - without compromising on performance. Paired with HPC solutions, users can leverage the massively parallel processing power of NVIDIA GPUs with the scalability, optimized density, and power efficiency of robust HPC solutions to ramp up the speed and accuracy of analytics.

Together, Hewlett Packard Enterprise (HPE) and NVIDIA are helping organizations harness the power of AI to enhance climate research and exploration. To learn more about how predictive analytics and real-time insights are transforming this field, I invite you to follow me on Twitter at @Bill_Mannel. You can also visit @HPE_HPC and @NVIDIADC to learn more about the benefits of HPC and GPU computing, or check out for more information on NVIDIA GPU-accelerated storage solutions.

Bill Mannel
VP & GM - HPC & AI Segment Solutions

twitter.gif @Bill_Mannel
linkedin.gif Bill-Mannel

Bill Mannel
Vice President and GM HPE Servers


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About the Author


As the Vice President and General Manager of HPC and AI Segment Solutions in the Data Center Infrastructure Group, I lead worldwide business and portfolio strategy and execution for the fastest growing market segments in HPE’s Data Center Infrastructure Group which includes the recent SGI acquisition and the HPE Apollo portfolio.

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