Teaching a Weather Forecasting Class in the 2020s

Lars van Galen, Oscar Hartogensis, Imme Benedict, Gert Jan Steeneveld*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

We report on redesigning the undergraduate course in synoptic meteorology and weather forecasting at Wageningen University (the Netherlands) to meet the current-day requirements for operational forecasters. Weather strongly affects human activities through its impact on transportation, energy demand planning, and personal safety, especially in the case of weather extremes. Numerical weather prediction (NWP) models have developed rapidly in recent decades, with reasonably high scores, even on the regional scale. The amount of available NWP model output has sharply increased. Hence, the role and value of the operational weather forecaster has evolved into the role of information selector, data quality manager, storyteller, and product developer for specific customers. To support this evolution, we need new academic training methods and tools at the bachelor's level. Here, we present a renewed education strategy for our weather forecasting class, called Atmospheric Practical, including redefined learning outcomes, student activities, and assessments. In addition to teaching the interpretation of weather maps, we underline the need for twenty-first-century skills like dealing with open data, data handling, and data analysis. These skills are taught using Jupyter Python Notebooks as the leading analysis tool. Moreover, we introduce assignments about communication skills and forecast product development as we aim to benefit from the internationalization of the classroom. Finally, we share the teaching material presented in this paper for the benefit of the community.

Original languageEnglish
Pages (from-to)E248-E265
JournalBulletin of the American Meteorological Society
Volume103
Issue number2
DOIs
Publication statusPublished - Feb 2022

Keywords

  • Education
  • Forecasting
  • Forecasting techniques
  • Numerical weather prediction/forecasting
  • Operational forecasting

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