Many people know about Moore’s Law, which predicts how quickly computing capability increases over time. But did you know that a similar, if little known, axiom applies to the science of meteorology? It holds that the accuracy of the weather forecast improves by one day every ten years. Call it the Meteorologist’s Maxim.
Empirical evidence bears it out. The five-day forecast today is about as accurate as a one-day forecast was 40 years ago. People of a certain age remember just how dicey forecasts were back then, with unexpected snowstorms, heat waves and cold snaps a common occurrence. Today, individuals can confidently plan their daily lives around the meteorologist’s pronouncements. Businesses also factor weather forecasts into their strategies for operations, supply chains, product mix, transportation schedules and a host of other operations.
But while past advances in forecasting have delivered undeniable benefits to society, many challenges must be surmounted for the Meteorologist’s Maxim to be sustained in the future. Organizations that help advance weather science, and those that use the science to make better forecasts, recognize that we can improve only if we make substantial investments.
In particular, a new generation of computing technologies must be developed that can deliver hundreds of times more computing power. That’s why IBM invests heavily in next-generation supercomputing architectures and quantum computing.
But advancing weather science is also critical. That requires focus and creativity as well as openness and collaboration across the business, government and academic organizations that make up the weather enterprise. It’s an extraordinarily complex undertaking, and no one entity can be successful in isolation. At IBM, we remain committed to an open approach, which includes working with the broader community to improve both our own capabilities and those of the entire weather enterprise.
The Proven Benefits of Collaboration
For example, our partnership with the National Center for Atmospheric Research (NCAR) resulted in a state-of-the-science forecasting model for the world, called IBM GRAF, which stands for Global High-Resolution Atmospheric Forecasting System.
GRAF is based on NCAR’s latest-generation, open source global model—the Model for Prediction Across Scales (MPAS). The first global model that is updated hourly, GRAF can predict high-impact weather events at a level of detail not previously available for much of the world.
We also share many of our scientific advancements. This includes contributing new source code to open-source modeling projects such as MPAS and the Weather Research and Forecasting model developed by the weather enterprise community. We also keep the scientific community up to date on our forecasting technology and architecture.
IBM is also an enthusiastic supporter of the National Oceanic and Atmospheric Administration’s Earth Prediction Innovation Center. The center is designed to help the public, private and academic sectors work together to improve the nation’s forecasts, allowing consumers and businesses alike to better anticipate—or avoid—potential weather disruptions.
These twin commitments—to technological innovation and community collaboration—are essential in meteorology. That’s why businesses looking to engage private-sector weather forecasters should ask them about their commitment to those principles.
The Way Forward
State-of-the-art forecast services require deep and sustaining partnerships. So the first thing to ask of a private-sector forecast is whether it works with a community of partners, or is flying solo.
Businesses should also demand accountability from their forecast provider. That means asking questions about accuracy and dependability, including which methodologies are used to create the forecast, what is the relative quality of the delivered content to standard benchmarks, and how is that quality determined? Are independent assessments available to back that up?
Equally important: Does the provider have the expertise to transform weather data into actionable insights and decisions—or at least suggest best practices for integrating weather data into a company’s business practices?
Meteorology has come a long way in recent decades. It has never been more powerful or more integrated into our economy and our lives. To continue innovating and advancing the science, we must ensure that collaboration and two-way communication between the business and scientific communities remain alive and well.
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