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DSC Weekly 31 January 2023 – Data Models for the Weather


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DSC Weekly 31 January 2023 – Data Models for the Weather

Data Models for the Weather

With January coming to an end, we here in the Northeast let out a collective sigh of relief as the month ends without any major snowstorms that tend to happen in the first month of the year. Weather forecasting is a centuries-old practice that has its roots in divination and other less-than-scientific prediction methods, but as we move into the future, our tools allow us to more accurately predict what the future holds.

Our historical approach to weather prediction is based on viewing patterns and creating physics models within the collected data, or Numerical Weather Prediction (NWP). Other methods, such as Deep Learning Weather Prediction (DLWP) that uses historical weather data, are gaining traction as they outperform NWP over longer timeframes. Google’s MetNet-2 uses deep learning algorithms and live satellite inputs to create “nowcasts,” or weather probability predictions in the immediate future.

There has always been jokes at the expense of meteorologists and their inability to accurately predict the weather. This may not be the case for much longer. The models have improved so much that “a modern 5-day forecast is as accurate as a 1-day forecast in 1980.” But even with Google’s foray into meteorology, their predictions are still based on probability. With the increasing popularity and advances in the machine learning field, meteorologists have taken one step closer to becoming the target audience here on DSC.

Scott Thompson
Associate Editor

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DSC Weekly 31 January 2023 – Data Models for the Weather