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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

Capsule summary

Building on a large scale and heterogenous survey, this paper provides an estimate of the value that the public assigns to future improvements in hurricane forecast accuracy.

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Susan C. van den Heever, Leah D. Grant, Sean W. Freeman, Peter J. Marinescu, Julie Barnum, Jennie Bukowski, Eleanor Casas, Aryeh J. Drager, Brody Fuchs, Gregory R. Herman, Stacey M. Hitchcock, Patrick C. Kennedy, Erik R. Nielsen, J. Minnie Park, Kristen Rasmussen, Muhammad Naufal Razin, Ryan Riesenberg, Emily Riley Dellaripa, Christopher J. Slocum, Benjamin A. Toms, and Adrian van den Heever

Abstract

The intensity of deep convective storms is driven in part by the strength of their updrafts and cold pools. In spite of the importance of these storm features, they can be poorly represented within numerical models. This has been attributed to model parameterizations, grid resolution and the lack of appropriate observations with which to evaluate such simulations. The overarching goal of the Colorado State University Convective CLoud Outflows and UpDrafts Experiment (C3LOUD-Ex) was to enhance our understanding of deep convective storm processes and their representation within numerical models. To address this goal, a field campaign was conducted during July 2016 and May – June 2017 over northeastern Colorado, southeastern Wyoming, and southwestern Nebraska. Pivotal to the experiment was a novel “Flying Curtain” strategy designed around simultaneously employing a fleet of Uncrewed Aerial Systems (UAS; or drones), high frequency radiosonde launches and surface observations to obtain detailed measurements of the spatial and temporal heterogeneities of cold pools. Updraft velocities were observed using targeted radiosondes and radars. Extensive datasets were successfully collected for sixteen cold pool- and seven updraft-focused case studies. The updraft characteristics for all seven supercell updraft cases are compared, and provide a useful database for model evaluation. An overview of the sixteen cold pool characteristics is presented, and an in-depth analysis of one of the cold pool cases suggests that spatial variations in cold pool properties occur on spatial scales of O(100m) through to O(1km). Processes responsible for the cold pool observations are explored and support recent high-resolution modeling results.

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Mark W. Maier, Frank W. Gallagher III, Karen St. Germain, Richard Anthes, Cinzia Zuffada, Robert Menzies, Jeffrey Piepmeier, David Di Pietro, Monica M. Coakley, and Elena Adams

Abstract

Between 2014 and 2018, the NOAA Office of Systems Architecture and Advanced Planning (OSAAP) conducted the NOAA Satellite Observing System Architecture (NSOSA) study to plan the long-term future of the NOAA constellation of operational environmental satellites. This constellation of satellites (which may include space capabilities acquired in lieu of U.S. government satellites) will follow the current GOES-R and JPSS satellite programs, beginning about 2030. This was an opportunity to design a modern architecture with no preconceived notions regarding instruments, platforms, orbits, etc., but driven by user needs, new technology, and exploiting emerging space business models. In this paper we describe how the study was structured, review major results, show how observation priorities and estimated costs drove next-generation choices, and discuss important challenges for implementing the next generation of U.S. civil environmental remote sensing satellites.

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Marina Baldissera Pacchetti, Suraje Dessai, Seamus Bradley, and David A. Stainforth

Abstract

There are now a plethora of data, models, and approaches available to produce regional and local climate information intended to inform adaptation to a changing climate. There is, however, no framework to assess the quality of these data, models, and approaches that takes into account the issues that arise when this information is produced. An evaluation of the quality of regional climate information is a fundamental requirement for its appropriate application in societal decision-making. Here, an analytical framework is constructed for the quality assessment of science-based statements and estimates about future climate. This framework targets statements that project local and regional climate at decadal and longer time scales. After identifying the main issues with evaluating and presenting regional climate information, it is argued that it is helpful to consider the quality of statements about future climate in terms of 1) the type of evidence and 2) the relationship between the evidence and the statement. This distinction not only provides a more targeted framework for quality, but also shows how certain evidential standards can change as a function of the statement under consideration. The key dimensions to assess regional climate information quality are diversity, completeness, theory, adequacy for purpose, and transparency. This framework is exemplified using two research papers that provide regional climate information and the implications of the framework are explored.

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Gretchen L. Mullendore, Mary C. Barth, Petra M. Klein, and James H. Crawford

Abstract

Historically, atmospheric field campaigns typically focused on either meteorology or chemistry with very limited complementary observations from the other discipline. In contrast, a growing number of researchers are working across subdisciplines to include meteorological and chemical measurements when planning field campaigns to increase the value of the collected datasets for subsequent analyses. Including select trace gas measurements should be intrinsic to certain dynamics campaigns, as they can add insights into dynamical processes. This paper highlights the mutual benefits of joint dynamics–chemistry campaigns by reporting on a small sample of examples across a broad range of meteorological scales to demonstrate the value of this strategy, with focus on the Deep Convective Clouds and Chemistry (DC3) campaign as a recent example. General recommendations are presented as well as specific recommendations of chemical species appropriate for a range of meteorological temporal and spatial scales.

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José Vicencio, Roberto Rondanelli, Diego Campos, Raúl Valenzuela, René Garreaud, Alejandra Reyes, Rodrigo Padilla, Ricardo Abarca, Camilo Barahona, Rodrigo Delgado, and Gabriela Nicora

Abstract

In late May 2019, at least seven tornadoes were reported within a 24-h period in southern Chile (western South America, 36°–38°S), including EF1 and EF2 events causing substantial damage to infrastructure, dozens of injuries, and one fatality. Despite anecdotal evidence and chronicles of similar historical events, the threat from tornadoes in Chile was regarded with skepticism until the 2019 outbreak. Herein, we describe the synoptic-scale features instrumental in the development of these tornadic storms, including an extended southwest–northeast trough along the South Pacific, with a large postfrontal instability area. Tornadic storms appear to be embedded in a modestly unstable environment (positive convective available potential energy but less than 1,000 J kg−1) and strong low- and midlevel wind shear, with high near-surface storm-relative helicity values (close to −200 m2 s−2), clearly differing from the Great Plains tornadoes in North America (with highly unstable environments) but resembling cold-season tornadoes previously observed in the midlatitudes of North America, Australia, and Europe. Reanalyzing rainfall and lightning data from the last 10 years, we found that tornadic storms in our region occur associated with locally extreme values of both CAPE and low-level wind shear, where a combination of the two in a low-level vorticity generation parameter appears as a simple first-order discriminant between tornadic and nontornadic environments. Future research should thoroughly examine historical events worldwide to assemble a database of high-shear, low-CAPE midlatitude storms and help improve our understanding of these storms’ underlying physics.

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Jessica Spaccio, Arthur DeGaetano, and Nolan Doesken
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Minghua Zheng, Luca Delle Monache, Xingren Wu, F. Martin Ralph, Bruce Cornuelle, Vijay Tallapragada, Jennifer S. Haase, Anna M. Wilson, Matthew Mazloff, Aneesh Subramanian, and Forest Cannon

Abstract

Conventional observations of atmospheric rivers (ARs) over the northeastern Pacific Ocean are sparse. Satellite radiances are affected by the presence of clouds and heavy precipitation, which impact their distribution in the lower atmosphere and in precipitating areas. The goal of this study is to document a data gap in existing observations of ARs in the northeastern Pacific, and to investigate how a targeted field campaign called AR Reconnaissance (AR Recon) can effectively fill this gap. When reconnaissance data are excluded, there is a gap in AR regions from near the surface to the middle troposphere (below 450 hPa), where most water vapor and its transport are concentrated. All-sky microwave radiances provide data within the AR object, but their quality is degraded near the AR core and its leading edge, due to the existence of thick clouds and precipitation. AR Recon samples ARs and surrounding areas to improve downstream precipitation forecasts over the western United States. This study demonstrates that despite the apparently extensive swaths of modern satellite radiances, which are critical to estimate large-scale flow, the data collected during 15 AR Recon cases in 2016, 2018, and 2019 supply about 99% of humidity, 78% of temperature, and 45% of wind observations in the critical maximum water vapor transport layer from the ocean surface to 700 hPa in ARs. The high-vertical-resolution dropsonde observations in the lower atmosphere over the northeastern Pacific Ocean can significantly improve the sampling of low-level jets transporting water vapor to high-impact precipitation events in the western United States.

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Cenlin He, Olivia Clifton, Emmi Felker-Quinn, S. Ryan Fulgham, Julieta F. Juncosa Calahorrano, Danica Lombardozzi, Gemma Purser, Mj Riches, Rebecca Schwantes, Wenfu Tang, Benjamin Poulter, and Allison L. Steiner

Abstract

Interactions between air pollution and terrestrial ecosystems play an important role in the Earth system. However, process-based knowledge of air pollution–terrestrial ecosystem interactions is limited, hindering accurate quantification of how changes in tropospheric chemistry, biogeochemical cycling, and climate affect air quality and its impact on humans and ecosystems. Here we summarize current challenges and future directions for advancing the understanding of air pollution–ecosystem interactions by synthesizing discussions from a multidisciplinary group of scientists at a recent Integrated Land Ecosystem–Atmosphere Processes Study (iLEAPS) early-career workshop. Specifically, we discuss the important elements of air pollution–terrestrial ecosystem interactions, including vegetation and soil uptake and emissions of air pollutants and precursors, in-canopy chemistry, and the roles of human activities, fires, and meteorology. We highlight the need for a coordinated network of measurements of long-term chemical fluxes and related meteorological and ecological quantities with expanded geographic and ecosystem representation, data standardization and curation to reduce uncertainty and enhance observational syntheses, integrated multiscale observational and modeling capabilities, collaboration across scientific disciplines and geographic regions, and active involvement by stakeholders and policymakers. Such an enhanced network will continue to facilitate the process-level understanding and thus predictive ability of interactions between air pollution and terrestrial ecosystems and impacts on local-to-global climate and human health.

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