A spatial extension of weather forecasts

Benjamin Schweitzer (), Robert C. Garrett (), Nichole Rook () and Thomas J. Fisher ()
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Benjamin Schweitzer: Miami University
Robert C. Garrett: Miami University
Nichole Rook: Miami University
Thomas J. Fisher: Miami University

Computational Statistics, 2023, vol. 38, issue 3, No 4, 1157-1171

Abstract: Abstract One of the more popular usages of predictive modeling is in the forecasting of weather. We use machine learning techniques to spatially extend provided forecasts to sites across the continental United States. The forecasts and observed weather for 113 sites across the United States (2014–2017) were used, along with supplementary data on observed weather from the National Oceanic and Atmospheric Administration National Climatic Data Center. Based on the spatially extended forecasts, visual displays are created to analyze the prediction accuracy of the forecasts. Our results allow for an in-depth exploration into the accuracy of our new weather forecasts across the nation.

Keywords: Data visualization; Machine learning; Weather forecasts (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s00180-023-01336-6

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