An exploration of National Weather Service daily forecasts using R Shiny

Dooti Roy (), Gregory Vaughan, Jianan Hui and Junxian Geng
Additional contact information
Dooti Roy: Boehringer Ingelheim Pharmaceuticals Inc.
Gregory Vaughan: Bentley University
Jianan Hui: Boehringer Ingelheim Pharmaceuticals Inc.
Junxian Geng: Boehringer Ingelheim Pharmaceuticals Inc.

Computational Statistics, 2023, vol. 38, issue 3, No 5, 1173-1191

Abstract: Abstract Weather forecasts often affect daily lives of billions of people globally. Accurate forecasts can help combat and effectively mitigate damage caused by extreme weather. Alternatively, faulty forecasts can consequently lead to unnecessary financial investments and a waste of resources. Our work explores what is the extent of variability in errors of the National Weather Service predictions as observed in 113 cities in the United States between July 1, 2014 and September 1, 2017 and attempts to model the distribution of errors. Simultaneously, we deliver an interactive tool for future researchers to explore the actual and forecast weather data as well as expose hidden patterns in the data.

Date: 2023
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DOI: 10.1007/s00180-023-01341-9

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