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Gilbert Brunet, David B. Parsons, Dimitar Ivanov, Boram Lee, Peter Bauer, Natacha B. Bernier, Veronique Bouchet, Andy Brown, Antonio Busalacchi, Georgina Campbell Flatter, Rei Goffer, Paul Davies, Beth Ebert, Karl Gutbrod, Songyou Hong, P.K. Kenabatho, Hans-Joachim Koppert, David Lesolle, Amanda Lynch, Jean-François Mahfouf, Laban Ogallo, Tim Palmer, Netatua Pelesikoti, Kevin Petty, Dennis Schulze, Theodore G. Shepherd, Thomas F. Stocker, Alan Thorpe, and Rucong Yu

Abstract

Our world is rapidly changing. Societies are facing an increase in the frequency and intensity of high impact and extreme weather and climate events. These extremes together with exponential population growth and demographic shifts (e.g., urbanization, increase in coastal populations) are increasing the detrimental societal and economic impact of hazardous weather and climate events. Urbanization and our changing global economy have also increased the need for accurate projections of climate change and improved predictions of disruptive and potentially beneficial weather events on km-scales. Technological innovations are also leading to an evolving and growing role of the private sector in the weather and climate enterprise.

This article discusses the challenges faced in accelerating advances in weather and climate forecasting and proposes a vision for key actions needed across the private, public, and academic sectors. Actions span: i) Utilizing the new observational and computing ecosystems; ii) Strategies to advance earth system models; iii) Ways to benefit from the growing role of artificial intelligence; iv) Practices to improve the communication of forecast information and decision support in our age of internet and social media; and v) Addressing the need to reduce the relatively large, detrimental impacts of weather and climate on all nations and especially on low income nations. These actions will be based on a model of improved cooperation between the public, private, and academic sectors.

This article represents a concise summary of the White Paper on the Future of Weather and Climate Forecasting (2021) put together by the World Meteorological Organizations’s Open Consultative Platform.

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Il-Ju Moon, Thomas R. Knutson, Hye-Ji Kim, Alexander V. Babanin, and Jin-Yong Jeong

Abstract

Tropical cyclones operate as heat engines, deriving energy from the thermodynamic disequilibrium between ocean surfaces and atmosphere. Available energy for the cyclones comes primarily from upper-ocean heat content. Here, we show that eastern North Pacific hurricanes reach a given intensity 15% faster on average than western North Pacific typhoons despite having half the available ocean heat content. Eastern North Pacific hurricanes also intensify on average 16% more with a given ocean energy (i.e., air-sea enthalpy flux) than western North Pacific typhoons. As efficient intensifiers, eastern Pacific hurricanes remain small during their intensification period, tend to stay at lower latitudes, and are affected by relatively lower vertical wind shear, colder troposphere, and drier boundary layer. Despite a shallower warm upper-ocean layer in the eastern North Pacific, average hurricane-induced sea surface cooling there is only slightly larger than in the western North Pacific due to the opposing influences of stronger density stratification, smaller size, and related wave-interaction effects. In contrast, western North Pacific typhoons encounter a more favorable oceanic environment for development, but several factors cause typhoons to greatly increase their size during intensification, resulting in a slow and inefficient intensification process. These findings on tropical cyclones’ basin-dependent characteristics contribute toward a better understanding of TC intensification.

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Scotney D. Evans, Kenneth Broad, Alberto Cairo, Sharanya J. Majumdar, Brian D. McNoldy, Barbara Millet, and Leigh Rauk

Abstract

The accurate interpretation of hurricane risk graphics is expected to benefit public decision-making. To investigate public interpretation and suggest improvements to graphical designs, an interdisciplinary, mixed-methods approach is being undertaken. Drawing on a series of focus groups with Miami residents that focused on understanding interpretations of the National Hurricane Center’s track forecast cone or “Cone of Uncertainty”, we developed an online survey targeting a much larger sample of Florida residents (n=2,847). The findings from this survey are the primary focus of this short article. We attempt to answer three questions: 1) What are the most frequent and trusted sources of information that Florida residents use when they learn that a hurricane is coming their way? 2) How accurately are Florida residents able to interpret risk based on the NHC Cone of Uncertainty graphic? 3) What is the relationship, if any, between the number of correct interpretations and income, age, education, housing location, housing type, or “most trusted” sources of information? Unlike previous public surveys that focused more on evacuation decisions, forecast usage, and perception of hurricane risk, our approach specifically pays attention to the details of design elements of the forecast graphics with the long-term goal of minimizing misinterpretation of future graphics. Our analysis suggests that many residents have difficulty interpreting several aspects, suggesting a rethink on how to graphically communicate aspects such as uncertainty; the size of the storm; areas of likely damage; watches and warnings; and wind intensity categories. Graphical communication strategies need to be revised to better support the different ways in which people understand forecast products, and these strategies should be tested for validity in real world settings.

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Margaret E. Mooney, Cathy Middlecamp, Jonathan Martin, and Steve A. Ackerman

Abstract

Advances in science literacy documented in an undergraduate course on Climate and Climate Change at the University of Wisconsin-Madison (UW) in 2020 begged the question: does the new climate knowledge translate into behavior change? Traditionally a “knowledge-action gap” has undermined educators’ efforts to galvanize actions towards mitigating climate change. Through a survey focused on carbon footprint and civic engagement and testimonials gleaned from students’ capstone elevator speeches, this study presents an encouraging update on young adults’ response to the climate crisis. By comparing responses to a similar survey distributed to UW students in another undergraduate course in 2021, we show that the course focused on Climate and Climate Change motivated behavior modifications that lighten carbon footprint to a greater degree than a traditional introductory meteorology course.

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Yi-Jie Zhu, Jennifer M. Collins, Philip J. Klotzbach, and Carl J. Schreck III

Abstract

Hurricane Ida recently became one of the strongest hurricanes to hit Louisiana on record, with an estimated landfalling maximum sustained wind of 130 kt. Although Hurricane Ida made landfall at a similar time of year and landfall location as Hurricane Katrina (2005), Ida’s postlandfall decay rate was much weaker than Hurricane Katrina. This manuscript includes a comparative analysis of pre- and post-landfall synoptic conditions for Hurricane Ida and other historical major landfalling hurricanes (Category 3+ on the Saffir-Simpson Hurricane Wind Scale) along the Gulf Coast since 1983, with a particular focus on Hurricane Katrina.

Abundant precipitation in southeastern Louisiana prior to Ida’s landfall increased soil moisture. This increased soil moisture along with extremely weak overland steering flow likely slowed the storm’s weakening rate post-landfall. Offshore environmental factors also played an important role, particularly anomalously high nearshore sea surface temperatures and weak vertical wind shear that fueled the rapid intensification of Ida just before landfall. Strong nearshore vertical wind shear weakened Hurricane Katrina before landfall, and moderate northward steering flow caused Katrina to move inland relatively quickly, aiding in its relatively fast weakening rate following landfall.

The results of this study improve our understanding of critical factors influencing the evolution of the nearshore intensity of major landfalling hurricanes in the Gulf of Mexico. This study can help facilitate forecasting and preparation for inland hazards resulting from landfalling hurricanes with nearshore intensification and weak post-landfall decay.

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Pablo Ortega, Edward W. Blockley, Morten Køltzow, François Massonnet, Irina Sandu, Gunilla Svensson, Juan C. Acosta Navarro, Gabriele Arduini, Lauriane Batté, Eric Bazile, Matthieu Chevallier, Rubén Cruz-García, Jonathan J. Day, Thierry Fichefet, Daniela Flocco, Mukesh Gupta, Kerstin Hartung, Ed Hawkins, Claudia Hinrichs, Linus Magnusson, Eduardo Moreno-Chamarro, Sergio Pérez-Montero, Leandro Ponsoni, Tido Semmler, Doug Smith, Jean Sterlin, Michael Tjernström, Ilona Välisuo, and Thomas Jung

Abstract

The Arctic environment is changing, increasing the vulnerability of local communities and ecosystems, and impacting its socio-economic landscape. In this context, weather and climate prediction systems can be powerful tools to support strategic planning and decision-making at different time horizons. This article presents several success stories from the H2020 project APPLICATE on how to advance Arctic weather and seasonal climate prediction, synthesizing the key lessons learned throughout the project and providing recommendations for future model and forecast system development.

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Natalie J. Harvey, Luke M. Western, Helen F. Dacre, and Antonio Capponi

Abstract

Making decisions about the appropriate action to take when presented with uncertain information is difficult, particularly in an emergency response situation. Decision makers can be influenced by factors such as how information is framed, their risk sensitivity and the impact of false alarms. Uncertainty arising from limited knowledge of the current state or future outcome of an event is unavoidable when making decisions. However, there is no universally agreed method on the design and presentation of uncertainty information. The aim of this article is to demonstrate that decision theory can be applied to an ensemble of plausible realisations of a situation to build a transparent framework which can then be used to determine the optimal action by assigning losses to different decision outcomes. The optimal action is then visualized, enabling the uncertainty information to be presented in a condensed manner suitable for decision makers. The losses are adaptable depending on the hazard and the individual operational model of the decision maker. To illustrate this approach, decision theory will be applied to an ensemble of volcanic ash simulations used for the purpose of airline flight planning, focussing on the 2019 eruption of Russian volcano Raikoke. Three idealised scenarios are constructed to show the impact of different loss models on the optimal action. In all cases, applying decision theory can significantly alter the regions, and therefore potential flight tracks, identified as potentially hazardous. Thus we show that different end users would and should make different decisions when presented with the same probabilistic information based on their individual user requirements.

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Christiane Voigt, Jos Lelieveld, Hans Schlager, Johannes Schneider, Joachim Curtius, Ralf Meerkötter, Daniel Sauer, Luca Bugliaro, Birger Bohn, John N. Crowley, Thilo Erbertseder, Silke Groß, Valerian Hahn, Qiang Li, Mariano Mertens, Mira L. Pöhlker, Andrea Pozzer, Ulrich Schumann, Laura Tomsche, Jonathan Williams, Andreas Zahn, Meinrat Andreae, Stephan Borrmann, Tiziana Bräuer, Raphael Dörich, Andreas Dörnbrack, Achim Edtbauer, Lisa Ernle, Horst Fischer, Andreas Giez, Manuel Granzin, Volker Grewe, Hartwig Harder, Martin Heinritzi, Bruna A. Holanda, Patrick Jöckel, Katharina Kaiser, Ovid O. Krüger, Johannes Lucke, Andreas Marsing, Anna Martin, Sigrun Matthes, Christopher Pöhlker, Ulrich Pöschl, Simon Reifenberg, Akima Ringsdorf, Monika Scheibe, Ivan Tadic, Marcel Zauner-Wieczorek, Rolf Henke, and Markus Rapp

Abstract

During spring 2020, the COVID-19 pandemic caused massive reductions in emissions from industry and ground and airborne transportation. To explore the resulting atmospheric composition changes, we conducted the BLUESKY campaign with two research aircraft and measured trace gases, aerosols, and cloud properties from the boundary layer to the lower stratosphere. From 16 May to 9 June 2020, we performed 20 flights in the early COVID-19 lockdown phase over Europe and the Atlantic Ocean. We found up to 50% reductions in boundary layer nitrogen dioxide concentrations in urban areas from GOME-2B satellite data, along with carbon monoxide reductions in the pollution hot spots. We measured 20%–70% reductions in total reactive nitrogen, carbon monoxide, and fine mode aerosol concentration in profiles over German cities compared to a 10-yr dataset from passenger aircraft. The total aerosol mass was significantly reduced below 5 km altitude, and the organic aerosol fraction also aloft, indicative of decreased organic precursor gas emissions. The reduced aerosol optical thickness caused a perceptible shift in sky color toward the blue part of the spectrum (hence BLUESKY) and increased shortwave radiation at the surface. We find that the 80% decline in air traffic led to substantial reductions in nitrogen oxides at cruise altitudes, in contrail cover, and in resulting radiative forcing. The light extinction and depolarization by cirrus were also reduced in regions with substantially decreased air traffic. General circulation–chemistry model simulations indicate good agreement with the measurements when applying a reduced emission scenario. The comprehensive BLUESKY dataset documents the major impact of anthropogenic emissions on the atmospheric composition.

Open access
Neil A. Stuart, Gail Hartfield, David M. Schultz, Katie Wilson, Gregory West, Robert Hoffman, Gary Lackmann, Harold Brooks, Paul Roebber, Teresa Bals-Elsholz, Holly Obermeier, Falko Judt, Patrick Market, Daniel Nietfeld, Bruce Telfeyan, Dan DePodwin, Jeffrey Fries, Elliot Abrams, and Jerry Shields

Abstract

A series of webinars and panel discussions were conducted on the topic of the evolving role of humans in weather prediction and communication, in recognition of the 100th anniversary of the founding of the AMS. One main theme that arose was the inevitability that new tools using artificial intelligence will improve data analysis, forecasting, and communication. We discussed what tools are being created, how they are being created, and how the tools will potentially affect various duties for operational meteorologists in multiple sectors of the profession. Even as artificial intelligence increases automation, humans will remain a vital part of the forecast process as that process changes over time. Additionally, both university training and professional development must be revised to accommodate the evolving forecasting process, including addressing the need for computing and data skills (including artificial intelligence and visualization), probabilistic and ensemble forecasting, decision support, and communication skills. These changing skill sets necessitate that both the U.S. Government’s Meteorologist General Schedule 1340 requirements and the AMS standards for a bachelor’s degree need to be revised. Seven recommendations are presented for student and forecaster preparation and career planning, highlighting the need for students and operational meteorologists to be flexible lifelong learners, acquire new skills, and be engaged in the changes to forecast technology in order to best serve the user community throughout their careers. The article closes with our vision for the ways that humans can maintain an essential role in weather prediction and communication, highlighting the interdependent relationship between computers and humans.

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Steven J. Cooper, Tristan S. L’Ecuyer, Mareile Astrid Wolff, Thomas Kuhn, Claire Pettersen, Norman B. Wood, Salomon Eliasson, Claire E. Schirle, Julia Shates, Franziska Hellmuth, Bjørg Jenny Kokkvoll Engdahl, Sandra Vásquez-Martín, Trond Ilmo, and Knut Nygård

Abstract

The High-Latitude Measurement of Snowfall (HiLaMS) campaign explored variability in snowfall properties and processes at meteorologically distinct field sites located in Haukeliseter, Norway, and Kiruna, Sweden, during the winters of 2016/17 and 2017/18, respectively. Campaign activities were founded upon the sensitivities of a low-cost, core instrumentation suite consisting of Micro Rain Radar, Precipitation Imaging Package, and Multi-Angle Snow Camera. These instruments are highly portable to remote field sites and, considered together, provide a unique and complementary set of snowfall observations including snowflake habit, particle size distributions, fall speeds, surface snowfall accumulations, and vertical profiles of radar moments and snow water content. These snow-specific parameters, used in combination with existing observations from the field sites such as snow gauge accumulations and ambient weather conditions, allow for advanced studies of snowfall processes. HiLaMS observations were used to 1) successfully develop a combined radar and in situ microphysical property retrieval scheme to estimate both surface snowfall accumulation and the vertical profile of snow water content, 2) identify the predominant snowfall regimes at Haukeliseter and Kiruna and characterize associated macrophysical and microphysical properties, snowfall production, and meteorological conditions, and 3) identify biases in the HARMONIE-AROME numerical weather prediction model for forecasts of snowfall accumulations and vertical profiles of snow water content for the distinct snowfall regimes observed at the mountainous Haukeliseter site. HiLaMS activities and results suggest value in the deployment of this enhanced snow observing instrumentation suite to new and diverse high-latitude locations that may be underrepresented in climate and weather process studies.

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