Teaching a Weather Forecasting Class in the 2020s

Abstract

We report on renewing the undergraduate course about synoptic meteorology and weather forecasting at Wageningen University (The Netherlands) to meet the current-day requirements of 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 models (NWP) 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 21st 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.

Harnessing the Power of Stacked GRU for Accurate Weather Predictions

“…For the energy sector, accurate weather prediction is crucial for optimizing the generation and distribution of renewable energy sources like solar and wind power, enabling efficient operations and planning [10]. In transportation, weather forecasts aid in route planning, scheduling, and safety measures, reducing the risk of accidents and improving efficiency [11]. Additionally, accurate weather prediction is vital in disaster management, allowing for timely evacuation and preparation for extreme weather events [12].…”