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Fuqing Zhang
,
Masashi Minamide
,
Robert G. Nystrom
,
Xingchao Chen
,
Shian-Jian Lin
, and
Lucas M. Harris

Abstract

Hurricane Harvey brought catastrophic destruction and historical flooding to the Gulf Coast region in late August 2017. Guided by numerical weather prediction models, operational forecasters at NOAA provided outstanding forecasts of Harvey’s future path and potential for record flooding days in advance. These forecasts were valuable to the public and emergency managers in protecting lives and property. The current study shows the potential for further improving Harvey’s analysis and prediction through advanced ensemble assimilation of high-spatiotemporal all-sky infrared radiances from the newly launched, next-generation geostationary weather satellite, GOES-16. Although findings from this single-event study should be further evaluated, the results highlight the potential improvement in hurricane prediction that is possible via sustained investment in advanced observing systems, such as those from weather satellites, comprehensive data assimilation methodologies that can more effectively ingest existing and future observations, higher-resolution weather prediction models with more accurate numerics and physics, and high-performance computing facilities that can perform advanced analysis and forecasting in a timely manner.

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Ed Hawkins
,
Taran Fæhn
, and
Jan Fuglestvedt

Abstract

Graphical visualizations have the potential to engage diverse audiences in understanding the changes to our climate, especially when spread worldwide using both traditional and social media. The animated global temperature spiral was one of the first climate graphics to “go viral,” being viewed by millions of people online and by more than a billion people when it was used in the opening ceremony of the 2016 Rio Olympics. The idea, design, and communication aspects that led to the successes of this animated graphic are discussed, highlighting the benefits to scientists of engaging actively online and openly sharing their creative ideas.

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K. M. Lambrecht
,
B. J. Hatchett
,
L. C. Walsh
,
M. Collins
, and
Z. Tolby

Abstract

Communicating weather-related hazards to the public can be a challenge for meteorologists, particularly given the nature of confidence levels in forecasting science. Despite these challenges, communicating high-impact weather remains extremely important because it has implications for the safety, health, and resilience of impacted communities. Because the dynamics of this issue are complex, solutions to weather hazard communication benefit from interdisciplinary solutions and multiple types of expertise. Our work demonstrates how rhetoric, a foundational communication discipline, can be applied to improving weather forecast communication. Applying a rhetorical framework allows the identification of communication strategies that not only invite public involvement but encourage users to act as conduits for weather information distribution. As a result, trust can be developed between the National Weather Service (NWS) and public audiences. The initial results support the hypothesis that effective public communication from NWS messaging can be improved by incorporating the concept of “commonplaces,” which are the expressions of beliefs, values, and norms that construct community attitudes toward weather or natural hazard forecasts, into visual communication techniques such as NWS Weather Stories.

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Abhay S. D. Rajput

Abstract

While writing is integral to science, it gets little attention in formal science education/academics. Such neglect has serious implications for nonnative English-speaking (NNES) scientists. An inability to write effective and efficient manuscripts can considerably delay the publication of new results while reflecting badly on the performance of individual scientists and on institutional productivity. In the multiethnic and multilingual Indian society, NNES scientists may face more linguistic complexities that inhibit clear and precise scientific writing. This article tries to address the predicament of scientific writing among NNES scientists in weather and climate sciences in India. Results from an informal e-mail survey with 80 respondents, mostly drawn from academic and research institutions in India, bolster anecdotal evidence of the difficulties NNES scientists have in writing about their science in research and popular publications. The responses also reflect high levels of interest these scientists have in addressing their communication difficulties. The survey results address the scientists’ perceptions and dilemmas in clear scientific writing as well as their perceived skills and training needs. The article also suggests possible solutions.

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Julie Haggerty
,
Eric Defer
,
Adrianus De Laat
,
Kristopher Bedka
,
Jean-Marc Moisselin
,
Rodney Potts
,
Julien Delanoë
,
Frédéric Parol
,
Alice Grandin
, and
Stephanie Divito

Abstract

In the past two decades, more than 150 jet engine power-loss and damage events have been attributed to a phenomenon known as ice crystal icing (ICI). Ingestion of large numbers of ice particles into the engine core are thought to be responsible for these events, which typically occur at high altitudes near large convective systems in tropical air masses. In recent years, scientists, engineers, aviation regulators, and airlines from around the world have collaborated to better understand the relevant meteorological processes associated with ICI events, solve critical engineering problems, develop new certification standards, and devise mitigation strategies for the aviation industry. One area of research is the development of nowcasting techniques based on available remote sensing technology and numerical weather prediction (NWP) models to identify areas of high ice water content (IWC) and enable the provision of alerts to the aviation industry. Multiple techniques have been developed using geostationary and polar-orbiting satellite products, NWP model fields, and ground-based radar data as the basis for high-IWC products. Targeted field experiments in tropical regions with high incidence of ICI events have provided data for product validation and refinement of these methods. Beginning in 2015, research teams have assembled at a series of annual workshops to exchange ideas and standardize methods for evaluating performance of high-IWC detection products. This paper provides an overview of the approaches used and the current skill for identifying high-IWC conditions. Recommendations for future work in this area are also presented.

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Michael C. Kruk
,
Russell Vose
,
Richard Heim
,
Anthony Arguez
,
Jesse Enloe
,
Xungang Yin
, and
Trevor Wallis
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Georg j. Mayr
,
David Plavcan
,
Laurence Armi
,
Andrew Elvidge
,
Branko Grisogono
,
Kristian Horvath
,
Peter Jackson
,
Alfred Neururer
,
Petra Seibert
,
James W. Steenburgh
,
Ivana Stiperski
,
Andrew Sturman
,
Željko Večenaj
,
Johannes Vergeiner
,
Simon Vosper
, and
Günther Zängl

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.

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Chris D. Hewitt
and
Jason A. Lowe
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Ciara Ryan
,
Catriona Duffy
,
Ciaran Broderick
,
Peter W. Thorne
,
Mary Curley
,
Séamus Walsh
,
Conor Daly
,
Mairéad Treanor
, and
Conor Murphy

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.

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