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A spatial extension of weather forecasts

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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.

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Correspondence to Thomas J. Fisher.

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Schweitzer, B., Garrett, R.C., Rook, N. et al. A spatial extension of weather forecasts. Comput Stat 38, 1157–1171 (2023). https://doi.org/10.1007/s00180-023-01336-6

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  • DOI: https://doi.org/10.1007/s00180-023-01336-6

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