This post was written by Alis Wang

The rise of Big Data is helping experts better predict severe storms as well as increase their understanding of climate change. All of this has important ramifications for how we respond to emergency weather events, mitigate global warming, and even verify insurance claims. Advanced technology has improved the ability of forecasters to predict a storm’s path by providing a more efficient way to process the mounds of weather data that satellites bring in. Recent advances in Big Data and cloud computing also allow researchers a way to make sense of massive weather-related data sets.

The Climate Corporation—a company founded by two former Google employees to provide weather insurance to the agriculture industry—for example, uses Big Data analysis, agronomics, and climatology to build their products and analyze the 2.5 million weather measurements and 10 trillion scenario data points that are collected daily; their goal is to reduce the effects of severe weather events (which cause 90% of crop loss) on U.S. farmers. IBM research scientists are also bringing the latest Big Data tech to weather forecasting. They are working on a long-term weather forecasting project called Deep Thunder, which uses complex mathematical algorithms and computing power to forecast weather changes more accurately, potentially saving lives and protecting property from costly damage. Another company, EarthRisk Technologies, has worked with the University of California, San Diego’s Institution of Oceanography to produce a new model for predicting adverse weather events. The model uses 82 billion calculations and 60 years of data to identify weather patterns and compare them to current conditions with the goal of predicting the weather up to 40 days in advance.

Some groups also see business opportunities in these new technological advances. The Weather Channel, for example, provides services to a wide variety of industries from aviation to energy by helping their clients make sense of weather data so that they can adjust their behavior accordingly. Multi-million dollar decisions are often made by transportation companies, retailers, and pharmaceutical giants based on this wealth of weather data. For example, DHL Express uses The Weather Channel’s data to make important daily decisions that affect 3000 flights per day worldwide. EMC Industries also uses this weather data to verify hail-damage claims.

Finally, various organizations are crunching giant data sets to better understand and combat global warming. The NASA Center for Climate Simulation, for example, utilizes several powerful computers to integrate the millions of observations gathered daily and to produce simulations and visualizations to help them understand the natural and man-made changes in the environment at various points in time in the earth’s history. Australia’s Information and Communications Technology Research Centre of Excellence is also leading a new effort that will utilize Big Data and machine learning to advance knowledge of the natural sciences and climate change. The project will use publicly available geological data and data analytic to produce these insights.