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Abstract
Strong winds crossing elevated terrain and descending to its lee occur over mountainous areas worldwide. Winds fulfilling these two criteria are called foehn in this paper although different names exist depending on the region, the sign of the temperature change at onset, and the depth of the overflowing layer. These winds affect the local weather and climate and impact society. Classification is difficult because other wind systems might be superimposed on them or share some characteristics. Additionally, no unanimously agreed-upon name, definition, nor indications for such winds exist. The most trusted classifications have been performed by human experts. A classification experiment for different foehn locations in the Alps and different classifier groups addressed hitherto unanswered questions about the uncertainty of these classifications, their reproducibility, and dependence on the level of expertise. One group consisted of mountain meteorology experts, the other two of master’s degree students who had taken mountain meteorology courses, and a further two of objective algorithms. Sixty periods of 48 h were classified for foehn–no foehn conditions at five Alpine foehn locations. The intra-human-classifier detection varies by about 10 percentage points (interquartile range). Experts and students are nearly indistinguishable. The algorithms are in the range of human classifications. One difficult case appeared twice in order to examine the reproducibility of classified foehn duration, which turned out to be 50% or less. The classification dataset can now serve as a test bed for automatic classification algorithms, which—if successful—eliminate the drawbacks of manual classifications: lack of scalability and reproducibility.
Abstract
Strong winds crossing elevated terrain and descending to its lee occur over mountainous areas worldwide. Winds fulfilling these two criteria are called foehn in this paper although different names exist depending on the region, the sign of the temperature change at onset, and the depth of the overflowing layer. These winds affect the local weather and climate and impact society. Classification is difficult because other wind systems might be superimposed on them or share some characteristics. Additionally, no unanimously agreed-upon name, definition, nor indications for such winds exist. The most trusted classifications have been performed by human experts. A classification experiment for different foehn locations in the Alps and different classifier groups addressed hitherto unanswered questions about the uncertainty of these classifications, their reproducibility, and dependence on the level of expertise. One group consisted of mountain meteorology experts, the other two of master’s degree students who had taken mountain meteorology courses, and a further two of objective algorithms. Sixty periods of 48 h were classified for foehn–no foehn conditions at five Alpine foehn locations. The intra-human-classifier detection varies by about 10 percentage points (interquartile range). Experts and students are nearly indistinguishable. The algorithms are in the range of human classifications. One difficult case appeared twice in order to examine the reproducibility of classified foehn duration, which turned out to be 50% or less. The classification dataset can now serve as a test bed for automatic classification algorithms, which—if successful—eliminate the drawbacks of manual classifications: lack of scalability and reproducibility.
Abstract
Over much of the globe, the temporal extent of meteorological records is limited, yet a wealth of data remains in paper or image form in numerous archives. To date, little attention has been given to the role that students might play in efforts to rescue these data. Here we summarize an ambitious research-led, accredited teaching experiment in which undergraduate students successfully transcribed more than 1,300 station years of daily precipitation data and associated metadata across Ireland over the period 1860–1939. We explore i) the potential for integrating data rescue activities into the classroom, ii) the ability of students to produce reliable transcriptions and, iii) the learning outcomes for students. Data previously transcribed by Met Éireann (Ireland’s National Meteorological Service) were used as a benchmark against which it was ascertained that students were as accurate as the professionals. Details on the assignment, its planning and execution, and student-aids used are provided. The experience highlights the benefits that can accrue for data rescue through innovative collaboration between national meteorological services and academic institutions. At the same time, students have gained valuable learning outcomes and firsthand understanding of the processes that underpin data rescue and analysis. The success of the project demonstrates the potential to extend data rescue in the classroom to other universities, thus providing both an enriched learning experience for the students and a lasting legacy to the scientific community.
Abstract
Over much of the globe, the temporal extent of meteorological records is limited, yet a wealth of data remains in paper or image form in numerous archives. To date, little attention has been given to the role that students might play in efforts to rescue these data. Here we summarize an ambitious research-led, accredited teaching experiment in which undergraduate students successfully transcribed more than 1,300 station years of daily precipitation data and associated metadata across Ireland over the period 1860–1939. We explore i) the potential for integrating data rescue activities into the classroom, ii) the ability of students to produce reliable transcriptions and, iii) the learning outcomes for students. Data previously transcribed by Met Éireann (Ireland’s National Meteorological Service) were used as a benchmark against which it was ascertained that students were as accurate as the professionals. Details on the assignment, its planning and execution, and student-aids used are provided. The experience highlights the benefits that can accrue for data rescue through innovative collaboration between national meteorological services and academic institutions. At the same time, students have gained valuable learning outcomes and firsthand understanding of the processes that underpin data rescue and analysis. The success of the project demonstrates the potential to extend data rescue in the classroom to other universities, thus providing both an enriched learning experience for the students and a lasting legacy to the scientific community.
Abstract
Recent studies have indicated the importance of fall climate forcings and teleconnections in influencing the climate of the northern mid- to high latitudes. Here, we present some exploratory analyses using observational data and seasonal hindcasts, with the aim of highlighting the potential of the El Niño–Southern Oscillation (ENSO) as a driver of climate variability during boreal late fall and early winter (November and December) in the North Atlantic–European sector, and motivating further research on this relatively unexplored topic. The atmospheric ENSO teleconnection in November and December is reminiscent of the east Atlantic pattern and distinct from the well-known arching extratropical Rossby wave train found from January to March. Temperature and precipitation over Europe in November are positively correlated with the Niño-3.4 index, which suggests a potentially important ENSO climate impact during late fall. In particular, the ENSO-related temperature anomaly extends over a much larger area than during the subsequent winter months. We discuss the implications of these results and pose some research questions.
Abstract
Recent studies have indicated the importance of fall climate forcings and teleconnections in influencing the climate of the northern mid- to high latitudes. Here, we present some exploratory analyses using observational data and seasonal hindcasts, with the aim of highlighting the potential of the El Niño–Southern Oscillation (ENSO) as a driver of climate variability during boreal late fall and early winter (November and December) in the North Atlantic–European sector, and motivating further research on this relatively unexplored topic. The atmospheric ENSO teleconnection in November and December is reminiscent of the east Atlantic pattern and distinct from the well-known arching extratropical Rossby wave train found from January to March. Temperature and precipitation over Europe in November are positively correlated with the Niño-3.4 index, which suggests a potentially important ENSO climate impact during late fall. In particular, the ENSO-related temperature anomaly extends over a much larger area than during the subsequent winter months. We discuss the implications of these results and pose some research questions.
Abstract
During the 2014–15 academic year, the National Oceanic and Atmospheric Administration (NOAA) National Weather Service Storm Prediction Center (SPC) and the University of Oklahoma (OU) School of Meteorology jointly created the first SPC-led course at OU focused on connecting traditional theory taught in the academic curriculum with operational meteorology. This class, “Applications of Meteorological Theory to Severe-Thunderstorm Forecasting,” began in 2015. From 2015 through 2017, this spring–semester course has engaged 56 students in theoretical skills and related hands-on weather analysis and forecasting applications, taught by over a dozen meteorologists from the SPC, the NOAA National Severe Storms Laboratory, and the NOAA National Weather Service Forecast Offices. Following introductory material, which addresses many theoretical principles relevant to operational meteorology, numerous presentations and hands-on activities focused on instructors’ areas of expertise are provided to students. Topics include the following: storm-induced perturbation pressure gradients and their enhancement to supercells, tornadogenesis, tropical cyclone tornadoes, severe wind forecasting, surface and upper-air analyses and their interpretation, and forecast decision-making. This collaborative approach has strengthened bonds between meteorologists in operations, research, and academia, while introducing OU meteorology students to the vast array of severe thunderstorm forecast challenges, state-of-the-art operational and research tools, communication of high-impact weather information, and teamwork skills. The methods of collaborative instruction and experiential education have been found to strengthen both operational–academic relationships and students’ appreciation of the intricacies of severe thunderstorm forecasting, as detailed in this article.
Abstract
During the 2014–15 academic year, the National Oceanic and Atmospheric Administration (NOAA) National Weather Service Storm Prediction Center (SPC) and the University of Oklahoma (OU) School of Meteorology jointly created the first SPC-led course at OU focused on connecting traditional theory taught in the academic curriculum with operational meteorology. This class, “Applications of Meteorological Theory to Severe-Thunderstorm Forecasting,” began in 2015. From 2015 through 2017, this spring–semester course has engaged 56 students in theoretical skills and related hands-on weather analysis and forecasting applications, taught by over a dozen meteorologists from the SPC, the NOAA National Severe Storms Laboratory, and the NOAA National Weather Service Forecast Offices. Following introductory material, which addresses many theoretical principles relevant to operational meteorology, numerous presentations and hands-on activities focused on instructors’ areas of expertise are provided to students. Topics include the following: storm-induced perturbation pressure gradients and their enhancement to supercells, tornadogenesis, tropical cyclone tornadoes, severe wind forecasting, surface and upper-air analyses and their interpretation, and forecast decision-making. This collaborative approach has strengthened bonds between meteorologists in operations, research, and academia, while introducing OU meteorology students to the vast array of severe thunderstorm forecast challenges, state-of-the-art operational and research tools, communication of high-impact weather information, and teamwork skills. The methods of collaborative instruction and experiential education have been found to strengthen both operational–academic relationships and students’ appreciation of the intricacies of severe thunderstorm forecasting, as detailed in this article.
Abstract
Over the past two decades, the National Science Foundation’s Division of Atmospheric and Geospace Sciences (AGS) has funded nearly 200 atmospheric science–related field campaigns that have included deployment of AGS-sponsored observing facilities. These projects have spanned the range from modest, single-investigator experiments to massive, multi-investigator, multiagency campaigns. They have occurred both domestically and abroad, on every continent and over most oceans. In this article, we present an analysis of some of the details about these campaigns, including such elements as deployment location and cost of the campaign, and of statistics related to the principal investigators (e.g., type and location of institution, gender, years since degree). In addition, we assess trends in field campaign cost. These results provide a retrospective view of atmospheric science field work that has been supported since 1992.
Abstract
Over the past two decades, the National Science Foundation’s Division of Atmospheric and Geospace Sciences (AGS) has funded nearly 200 atmospheric science–related field campaigns that have included deployment of AGS-sponsored observing facilities. These projects have spanned the range from modest, single-investigator experiments to massive, multi-investigator, multiagency campaigns. They have occurred both domestically and abroad, on every continent and over most oceans. In this article, we present an analysis of some of the details about these campaigns, including such elements as deployment location and cost of the campaign, and of statistics related to the principal investigators (e.g., type and location of institution, gender, years since degree). In addition, we assess trends in field campaign cost. These results provide a retrospective view of atmospheric science field work that has been supported since 1992.
Abstract
The emergence of 3D scanning technologies has provided a new opportunity to explore the shape characteristics of hailstones in great detail. The ability to effectively map the shape of hailstones will improve assessments of hailstone aerodynamic properties, how their density relates to their strength, and how radar energy is scattered. Ultimately, 3D scanning of hailstones will contribute toward research in hail detection, forecasting, and damage mitigation of severe hail, which accounts for well over $1 billion in annual insured losses.
The use of a handheld 3D laser scanner in a field setting was explored during field campaigns in 2015 and 2016. Hailstones were collected following thunderstorm passages and were measured, weighed, and scanned. The system was successful in capturing 3D models of more than 40 hailstones. A full scan takes approximately 3 minutes to complete, and data can be captured at a resolution of 0.008 cm. It is believed this is the first time such a system has been used to produce 3D digital hailstone models. Analysis of the model data has shown that hailstones depart from spherical shapes as they increase in diameter, and that bulk density and strength show little correlation. While the dataset presented here is small, the use of 3D scanners in the field is a practical method to obtain detailed datasets on hailstone characteristics. In addition, these data could be used to 3D-print hailstones to explore their aerodynamics, to produce cavity molds for ice impact tests, and for modeling radar scattering properties of natural hailstone shapes.
Abstract
The emergence of 3D scanning technologies has provided a new opportunity to explore the shape characteristics of hailstones in great detail. The ability to effectively map the shape of hailstones will improve assessments of hailstone aerodynamic properties, how their density relates to their strength, and how radar energy is scattered. Ultimately, 3D scanning of hailstones will contribute toward research in hail detection, forecasting, and damage mitigation of severe hail, which accounts for well over $1 billion in annual insured losses.
The use of a handheld 3D laser scanner in a field setting was explored during field campaigns in 2015 and 2016. Hailstones were collected following thunderstorm passages and were measured, weighed, and scanned. The system was successful in capturing 3D models of more than 40 hailstones. A full scan takes approximately 3 minutes to complete, and data can be captured at a resolution of 0.008 cm. It is believed this is the first time such a system has been used to produce 3D digital hailstone models. Analysis of the model data has shown that hailstones depart from spherical shapes as they increase in diameter, and that bulk density and strength show little correlation. While the dataset presented here is small, the use of 3D scanners in the field is a practical method to obtain detailed datasets on hailstone characteristics. In addition, these data could be used to 3D-print hailstones to explore their aerodynamics, to produce cavity molds for ice impact tests, and for modeling radar scattering properties of natural hailstone shapes.
Abstract
This article analyzes open-ended survey responses to understand how members of the American Meteorological Society (AMS) perceive conflict within the AMS over global warming. Of all survey respondents, 53% agreed that there was conflict within the AMS; of these individuals who perceived conflict, 62% saw it as having at least some productive aspects, and 53% saw at least some unproductive aspects. Among members who saw a productive side to the conflict, most agreed as to why it was productive: debate and diverse perspectives enhance science. However, among members who saw an unproductive side, there was considerable disagreement as to why. Members who are convinced of largely human-caused climate change expressed that debate over global warming sends an unclear message to the public. Conversely, members who are unconvinced of human-caused climate change often felt that their peers were closed-minded and suppressing unpopular views. These two groups converged, however, on one point: politics was seen as an overwhelmingly negative influence on the debate. This suggests that scientific organizations faced with similar conflict should understand that there may be a contradiction between legitimizing all members’ views and sending a clear message to the public about the weight of the evidence. The findings also reinforce the conclusion that attempts by scientific societies to directly address differences in political views may be met with strong resistance by many scientists.
Abstract
This article analyzes open-ended survey responses to understand how members of the American Meteorological Society (AMS) perceive conflict within the AMS over global warming. Of all survey respondents, 53% agreed that there was conflict within the AMS; of these individuals who perceived conflict, 62% saw it as having at least some productive aspects, and 53% saw at least some unproductive aspects. Among members who saw a productive side to the conflict, most agreed as to why it was productive: debate and diverse perspectives enhance science. However, among members who saw an unproductive side, there was considerable disagreement as to why. Members who are convinced of largely human-caused climate change expressed that debate over global warming sends an unclear message to the public. Conversely, members who are unconvinced of human-caused climate change often felt that their peers were closed-minded and suppressing unpopular views. These two groups converged, however, on one point: politics was seen as an overwhelmingly negative influence on the debate. This suggests that scientific organizations faced with similar conflict should understand that there may be a contradiction between legitimizing all members’ views and sending a clear message to the public about the weight of the evidence. The findings also reinforce the conclusion that attempts by scientific societies to directly address differences in political views may be met with strong resistance by many scientists.
