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Adam J. Clark, Israel L. Jirak, Burkely T. Gallo, Brett Roberts, Andrew R. Dean, Kent H. Knopfmeier, Louis J. Wicker, Makenzie Krocak, Patrick S. Skinner, Pamela L. Heinselman, Katie A. Wilson, Jake Vancil, Kimberly A. Hoogewind, Nathan A. Dahl, Gerald J. Creager, Thomas A. Jones, Jidong Gao, Yunheng Wang, Eric D. Loken, Montgomery Flora, Christopher A. Kerr, Nusrat Yussouf, Scott R. Dembek, William Miller, Joshua Martin, Jorge Guerra, Brian Matilla, David Jahn, David Harrison, David Imy, and Michael C. Coniglio
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Dylan R. Card, Heather S. Sussman, and Ajay Raghavendra
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Daniel B. Wright, Constantine Samaras, and Tania Lopez-Cantu

Abstract

Intensification of extreme rainfall due to climate change means that federally published rainfall metrics such as the “100-yr storm” are outdated throughout much of the United States. Given their central role in a wide range of infrastructure designs and risk management decisions, updating these metrics to reflect recent and future changes is essential to protect communities. There have been considerable advances in recent years in data collection, statistical methods, and climate modeling that can now be brought to bear on the problem. Scientists must take a lead in this updating process, which should be open, inclusive, and leverage recent scientific advances.

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Weihong Qian, Jun Du, and Yang Ai

Abstract

Comparisons between anomaly and full-field methods have been carried out in weather analysis and forecasting over the last decade. Evidence from these studies has demonstrated the superiority of anomaly to full field in the following four aspects: depiction of weather systems, anomaly forecasts, diagnostic parameters, and model prediction. To promote the use and further discussion of the anomaly approach, this article summarizes those findings. After examining many types of weather events, anomaly weather maps show at least five advantages in weather system depiction: 1) less vagueness in visually connecting the location of an event with its associated meteorological conditions, 2) clearer and more complete depictions of vertical structures of a disturbance, 3) easier observation of time and spatial evolution of an event and its interaction or connection with other weather systems, 4) simplification of conceptual models by unifying different weather systems into one pattern, and 5) extension of model forecast length due to earlier detection of predictors. Anomaly verification is also mentioned. The anomaly forecast is useful for raising one’s awareness of potential societal impact. Combining the anomaly forecast with an ensemble is emphasized, where a societal impact index is discussed. For diagnostic parameters, two examples are given: an anomalous convective instability index for convection, and seven vorticity and divergence related parameters for heavy rain. Both showed positive contributions from the anomalous fields. For model prediction, the anomaly version of the beta-advection model consistently outperformed its full-field version in predicting typhoon tracks with clearer physical explanation. Application of anomaly global models to seasonal forecasts is also reviewed.

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Markus Rapp, Bernd Kaifler, Andreas Dörnbrack, Sonja Gisinger, Tyler Mixa, Robert Reichert, Natalie Kaifler, Stefanie Knobloch, Ramona Eckert, Norman Wildmann, Andreas Giez, Lukas Krasauskas, Peter Preusse, Markus Geldenhuys, Martin Riese, Wolfgang Woiwode, Felix Friedl-Vallon, Björn-Martin Sinnhuber, Alejandro de la Torre, Peter Alexander, Jose Luis Hormaechea, Diego Janches, Markus Garhammer, Jorge L. Chau, J. Federico Conte, Peter Hoor, and Andreas Engel

Abstract

The southern part of South America and the Antarctic peninsula are known as the world’s strongest hotspot region of stratospheric gravity wave (GW) activity. Large tropospheric winds are deflected by the Andes and the Antarctic Peninsula and excite GWs that might propagate into the upper mesosphere. Satellite observations show large stratospheric GW activity above the mountains, the Drake Passage, and in a belt centered along 60°S. This scientifically highly interesting region for studying GW dynamics was the focus of the Southern Hemisphere Transport, Dynamics, and Chemistry–Gravity Waves (SOUTHTRAC-GW) mission. The German High Altitude and Long Range Research Aircraft (HALO) was deployed to Rio Grande at the southern tip of Argentina in September 2019. Seven dedicated research flights with a typical length of 7,000 km were conducted to collect GW observations with the novel Airborne Lidar for Middle Atmosphere research (ALIMA) instrument and the Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA) limb sounder. While ALIMA measures temperatures in the altitude range from 20 to 90 km, GLORIA observations allow characterization of temperatures and trace gas mixing ratios from 5 to 15 km. Wave perturbations are derived by subtracting suitable mean profiles. This paper summarizes the motivations and objectives of the SOUTHTRAC-GW mission. The evolution of the atmospheric conditions is documented including the effect of the extraordinary Southern Hemisphere sudden stratospheric warming (SSW) that occurred in early September 2019. Moreover, outstanding initial results of the GW observation and plans for future work are presented.

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Cheng Liu, Meng Gao, Qihou Hu, Guy P. Brasseur, and Gregory R. Carmichael

Abstract

Monitoring and modeling/predicting air pollution are crucial to understanding the links between emissions and air pollution levels, to supporting air quality management, and to reducing human exposure. Yet, current monitoring networks and modeling capabilities are unfortunately inadequate to understand the physical and chemical processes above ground and to support attribution of sources. We highlight the need for the development of an international stereoscopic monitoring strategy that can depict three-dimensional (3D) distribution of atmospheric composition to reduce the uncertainties and to advance diagnostic understanding and prediction of air pollution. There are three reasons for the implementation of stereoscopic monitoring: 1) current observation networks provide only partial view of air pollution, and this can lead to misleading air quality management actions; 2) satellite retrievals of air pollutants are widely used in air pollution studies, but too often users do not acknowledge that they have large uncertainties, which can be reduced with measurements of vertical profiles; and 3) air quality modeling and forecasting require 3D observational constraints. We call on researchers and policymakers to establish stereoscopic monitoring networks and share monitoring data to better characterize the formation of air pollution, optimize air quality management, and protect human health. Future directions for advancing monitoring and modeling/predicting air pollution are also discussed.

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Paulina Ćwik, Renee A. McPherson, and Harold E. Brooks

Abstract

The term “tornado outbreak” appeared in the meteorological literature in the 1950s and was used to highlight severe weather events with multiple tornadoes. The exact meaning of “tornado outbreak,” however, evolved over the years. Depending on the availability of scientific data, technological advancements, and the intended purpose of these definitions, authors offered a diverse set of approaches to shape the perception and applications of the term “tornado outbreak.” This paper reviews over 200 peer-reviewed publications—by decade—to outline the evolving nature of the “tornado outbreak” definition and to examine the changes in the “tornado outbreak” definition or its perception. A final discussion highlights the importance, limitations, and potential future evolution of what defines a “tornado outbreak.”

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Steven Caluwaerts, Sara Top, Thomas Vergauwen, Guy Wauters, Koen De Ridder, Rafiq Hamdi, Bart Mesuere, Bert Van Schaeybroeck, Hendrik Wouters, and Piet Termonia

Abstract

Today, the vast majority of meteorological data are collected in open, rural environments to comply with the standards set by the World Meteorological Organization. However, these traditional networks lack local information that would be of immense value, for example, for studying urban microclimate, evaluating climate adaptation measures, or improving high-resolution numerical weather predictions. Therefore an urgent need exists for reliable meteorological data in other environments (e.g. cities, lakes, forests) to complement these conventional networks. At present, however, high-accuracy initiatives tend to be limited in space and/or time as a result of the substantial budgetary requirements faced by research teams and operational services. We present a novel approach for addressing the existing observational gaps based on an intense collaboration with high schools. This methodology resulted in the establishment of a region-wide climate monitoring network of 59 accurate weather stations in a wide variety of locations across northern Belgium. The project is also of large societal relevance as it bridges the gap between the youth and atmospheric science. To guarantee a sustainable and mutually valuable collaboration, the schools and their students are involved at all stages, ranging from proposing measurement locations, building the weather stations, and even data analysis. We illustrate how the approach received an overwhelming enthusiasm from high schools and students and resulted in a high-accuracy monitoring network with unique locations offering novel insights.

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Brian A. Colle, Rosemary Auld, Kenneth Johnson, Christine O’Connell, Temis G. Taylor, and Joshua Rice

Abstract

It is challenging to communicate uncertainty for high-impact weather events to the public and decision makers. As a result, there is an increased emphasis and training within the National Weather Service (NWS) for “impact-based decision support.” A Collaborative Science, Technology, And Research (CSTAR) project led by Stony Brook University (SBU) in collaboration with the Alan Alda Center for Communicating Science, several NWS forecast offices, and NWS operational centers held two workshops at SBU on effective forecast communication of probabilistic information for high-impact weather. Trainers in two 1.5-day workshops helped 15-20 forecasters learn to distill their messages, engage audiences, and more effectively communicate risk and uncertainty to decision makers, media, and the general public. The novel aspect of the first workshop focused on using improvisational techniques to connect with audiences along with exercises to improve communication skills using short, clear, conversational statements. The same forecasters participated in the second workshop, which focused on matching messages to intended audiences and stakeholder interaction. Using a recent high-impact weather event, representatives in emergency management, TV media, departments of transportation, and emergency services provided feedback on the forecaster oral presentations (2-3 minute) and a visual slide. This article describes our innovative workshop approach, illustrates some of the techniques used, and highlights participant feedback.

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Renato Molina, David Letson, Brian McNoldy, Pallab Mozumder, and Matthew Varkony

Abstract

Hurricanes are the costliest type of natural disaster in the United States. Every year, these natural phenomena destroy billions of dollars in physical capital, displace thousands, and greatly disrupt local economies. While this damage will never be eliminated, the number of fatalities and the cost of preparing and evacuating can be reduced through improved forecasts. This paper seeks to establish the public’s willingness to pay for further improvement of hurricane forecasts by integrating atmospheric modeling and a double-bounded dichotomous choice method in a large-scale contingent valuation experiment. Using an interactive survey, we focus on areas affected by hurricanes in 2018 to elicit residents’ willingness to pay for improvements along storm track, wind speed and precipitation forecasts. Our results indicate improvements in wind speed forecast are valued the most, followed by storm track and precipitation, and that maintaining a rate of improvement of 5% error reduction for another decade is worth between US$90.25 to US$121.86 per person in vulnerable areas. Our study focuses on areas recently hit by hurricanes in the United States, but the implications of our results can be extended to areas vulnerable to tropical cyclones globally. In a world where the intensity of hurricanes is expected to increase and research funds are limited, these results can inform relevant agencies regarding the effectiveness of different private and public adaptive actions, as well as the value of publicly funded hurricane research programs.

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