But utilizing weather data that is coming from an increasingly diverse array of sources is not so easy.
Weather researchers are now pushing for good metadata along with the sensor data. The metadata, or data about the data, will help researchers know which instruments were used to gather the data and their accuracy, so the people who run forecasting models "can pick and choose data sets that are going to be of value," said Mahoney.
The sensor data that is now collected from vehicles is being used for research. The quality of this vehicle data can vary depending on where sensors are located, such as their proximity to the engine. Even the color of the car -- light or dark -- influences the accuracy of the sensor data. There are no standards yet for optimizing sensor placement.
There are potential life-saving benefits to using vehicle sensor data to improve weather information and alert systems for drivers. There are over 5.76 million car crashes a year, and approximately 22% of those crashes -- or 1.3 million -- are weather related, according to the Federal Highway Administration (FHA).
"On average, nearly 6,000 people are killed and over 445,000 people are injured in weather-related crashes each year," reported the FHA.
There are plenty of challenges ahead. Increasing amounts of sensor data also means "trying to capture the physics correctly" at those finer resolutions, said Mahoney. The feedback from urban environments, lakes, rivers, streams and many other conditions all influence micro-climates. "Those physical interrelationships matter," he said.
For now, weather forecasters aren't routinely using cellphone or vehicle data "but that's coming," said Mahoney, who said that over the next few years, research will result in methods and techniques to take advantage of those data sources.
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