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1 Teaching a Weather Forecasting Class in the 2020S Lars Van Galen1, Oscar Hartogensis1, Imme Benedict1, Gert-Jan Steeneveld1 1

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1 Teaching a Weather Forecasting Class in the 2020S Lars Van Galen1, Oscar Hartogensis1, Imme Benedict1, Gert-Jan Steeneveld1 1 1 Teaching a Weather Forecasting Class in the 2020s 2 3 Lars van Galen1, Oscar Hartogensis1, Imme Benedict1, Gert-Jan Steeneveld1 4 5 1:Wageningen University, Meteorology and Air Quality Section, PO box 47, 6700 AA Wa- 6 geningen, The Netherlands. 7 8 Corresponding author address: 9 Gert-Jan Steeneveld 10 [email protected] 11 Tel 0031317483839 1 1 Early Online Release: This preliminary version has been accepted for publication in Bulletin of the American Meteorological Society, may be fully cited, and has been assigned DOI 10.1175/BAMS-D-20-0107.1. The final typeset copyedited article will replace the EOR at the above DOI when it is published. © 2021 American Meteorological Society Unauthenticated | Downloaded 09/28/21 11:35 PM UTC 12 Abstract 13 We report on renewing the undergraduate course about synoptic meteorology and weather 14 forecasting at Wageningen University (The Netherlands) to meet the current-day requirements 15 of operational forecasters. Weather strongly affects human activities through its impact on 16 transportation, energy demand planning and personal safety, especially in the case of weather 17 extremes. Numerical weather prediction models (NWP) have developed rapidly in recent dec- 18 ades, with reasonably high scores, even on the regional scale. The amount of available NWP 19 model output has sharply increased. Hence, the role and value of the operational weather fore- 20 caster has evolved into the role of information selector, data quality manager, storyteller, and 21 product developer for specific customers. To support this evolution, we need new academic 22 training methods and tools at the bachelor’s level. Here, we present a renewed education strat- 23 egy for our weather forecasting class, called Atmospheric Practical, including redefined learn- 24 ing outcomes, student activities, and assessments. In addition to teaching the interpretation of st 25 weather maps, we underline the need for 21 century skills like dealing with open data, data 26 handling, and data analysis. These skills are taught using Jupyter Python notebooks as the 27 leading analysis tool. Moreover, we introduce assignments about communication skills and 28 forecast product development as we aim to benefit from the internationalization of the class- 29 room. Finally, we share the teaching material presented in this paper for the benefit of the 30 community. 31 Capsule 32 The role of operational weather forecasters has changed in recent decades, which means that 33 the new academic training in operational synoptic meteorology given at the BSc level must 34 address new topics, skills and infrastructure. 35 Key words: teaching, education, weather forecasting, synoptic meteorology 2 Unauthenticated | Downloaded 09/28/21 11:35 PM UTC Accepted for publication in Bulletin of the American Meteorological Society. DOI 10.1175/BAMS-D-20-0107.1. 36 1. Introduction 37 Weather forecasting is critical not only for social activities for the general public but also for 38 transportation, energy supply, water management, agriculture, and many other crucial infra- 39 structures and business decisions. Weather forecasts have become increasingly more accurate 40 in recent decades due to improved numerical weather prediction (NWP) systems as a result of 41 advances in understanding physical processes, data assimilation techniques and computing ca- 42 pacity (Bauer et al. 2015). 43 With these advances, the role of the operational forecaster has changed. Nowadays, the 44 output of multiple NWP models is freely available at a high temporal frequency, and they 45 cover the continental-scale dynamics for the medium range (3-7 days), and the mesoscale dy- 46 namics for the short range (up to 48 h). Also, observations from satellites, radar systems and 47 routine and crowdsourced near-surface weather stations are readily available. In addition, the 48 userbase of weather forecasts has diversified, requiring tailor-made forecasts for a wide range 49 of applications. As a result, the forecaster’s tasks have increasingly shifted from adapting the 50 NWP results for local conditions, towards data (model and observations) treatment, critical 51 data selection and storytelling for stakeholders. Educating the upcoming generation of 52 weather forecasters should consider the evolution occurring in the field, which motivated us 53 to revise the Atmospheric Practical course at Wageningen University (WU). Also, student 54 mobility and the diversity in the academic education landscape has strengthened, resulting in 55 students with variable prior knowledge. Previously, most of our students were Dutch and all 56 had a uniform prior knowledge from a common study program. Nowadays, the students who 57 enroll in our program have diverse geographical, cultural and educational backgrounds. Alt- 58 hough it may initially pose some challenges, this diversity also offers an opportunity for deep- 59 ening the course (Apple et al., 2014). 60 The Atmospheric Practical course teaches the fundament and practice of operational 3 Unauthenticated | Downloaded 09/28/21 11:35 PM UTC Accepted for publication in Bulletin of the American Meteorological Society. DOI 10.1175/BAMS-D-20-0107.1. 61 weather forecasting and synoptic meteorology, introducing innovations that reflect the devel- 62 opment of the field. We mainly address the introduction of an intake questionnaire, the inter- 63 national classroom, a new student activity to set up a forecast product, the implementation of 64 a modern scientific program language for data analysis, and the deeper attention needed for 65 communicating a weather forecast. 66 67 2. Positioning of the Atmospheric Practical course in the curriculum 68 The Atmospheric Practical is an optional course offered in the 3-year BSc program Soil, Wa- 69 ter, Atmosphere, which combines courses in the three disciplines with special attention to in- 70 terfaces at the land surface and vegetation. Students taking the course need two 6-ECTS at- 71 mospheric introduction courses (each with a workload of 168 hours): “Introduction Atmos- 72 phere” that uses an in-house made course reader and “Meteorology and Climate” based on 73 Wallace and Hobbs (2006). These courses deal with basic atmospheric physics and chemistry 74 covering thermodynamics, radiation, atmospheric dynamics, and boundary layers. Both 75 courses discuss basic weather forecasting, such as interpretation of synoptic observations and 76 radio soundings, and data-assimilation, as well as the concept of deterministic chaos and its 77 consequences. Didactically, the courses combine classroom lectures with pen-and-paper exer- 78 cises and computer-based assignments, mostly addressing the lower cognitive levels of 79 Bloom’s taxonomy (Anderson and Bloom 2001) regarding understanding, recognizing and in- 80 terpreting atmospheric processes. Finally, both courses include a number of weather briefings 81 by a meteorologist from DTN Weather (Data Transmission Network, formerly MeteoGroup). 82 After two years, students specialize in one discipline offered in the BSc program. Typi- 83 cally, 25-40 students follow the Atmospheric Practical for their specialization. The course in- 84 troduces the forecasting cycle, which includes the process of obtaining observed weather data 85 and model outcomes to compile a forecast for different end-users (section 3). 4 Unauthenticated | Downloaded 09/28/21 11:35 PM UTC Accepted for publication in Bulletin of the American Meteorological Society. DOI 10.1175/BAMS-D-20-0107.1. 86 3. Course history, content, structure, learning outcomes and student assessments 87 First, we summarize the course history and then go on to compare the forecasting cycle be- 88 tween the 1980s and the 2020s. Finally, we address the renewed course learning outcomes, 89 structure and student assessment methods. 90 In the previous version of the course, the interpretation of surface and upper air observa- 91 tions and the NWP model output were key. The selected case studies had a national or West- 92 ern European focus, and the exercises involved a lot of manual work (often paper exercises on 93 printed weather maps) or were performed with a variety of outdated software packages. Also, 94 the NWP model datasets were limited to coarse resolutions of >25 km. Some exercises fo- 95 cused on spatiotemporal scales exceeding the characteristic time scales of synoptic meteorol- 96 ogy, e.g., exercises about the physical climatology of the whole globe. For student assess- 97 ments, there was limited discrimination between students, and a number of crucial subjects 98 such as communicating weather forecasts were absent. Nevertheless, the original set up 99 served its purpose for 15 years and was highly appreciated by students who graded the course 100 with a 4.3 out of 5 for the past six years. 101 102 a. Course content: Forecasting cycle 103 The forecasting cycle, which is the backbone of the course, has changed substantially over 104 the years. The forecasting cycle contains the following steps (Inness and Dorling 2013): 105 1. Collecting observations. 106 2. Using collected observations to specify the initial conditions for the forecast. 107 3. Using a model to extrapolate the state of the atmosphere in the future. 108 4. Experienced forecasters assessing the output of the model. 109 5. Producing forecasts for customers. 110 Figure 1a depicts a typical forecast cycle in the 1980s, when the short-term forecast was 5 Unauthenticated | Downloaded 09/28/21 11:35 PM UTC Accepted for publication in Bulletin of
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