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Joseph E. Trujillo-Falcón, Orlando Bermúdez, Krizia Negrón-Hernández, John Lipski, Elizabeth Leitman, and Kodi Berry

Abstract

According to recent Census data, the Hispanic or Latino population represents nearly 1 in 5 Americans today, where 71.1% of these individuals speak Spanish at home. Despite increased efforts among the weather enterprise, establishing effective risk communication strategies for Spanish-speaking populations has been an uphill battle. No frameworks exist for translating weather information into the Spanish language, nor are there collective solutions that address this problem within the weather world. The objective of this article is threefold. First, the current translation issue in Spanish is highlighted. Through research conducted at the NOAA/NWS Storm Prediction Center, situations are revealed where regional varieties of Spanish contributed to inconsistent risk messaging across the bilingual weather community. Second, existing resources are featured so that interested readers are aware of ongoing efforts to translate weather information into Spanish. Organizations within the weather service, like the NWS Multimedia Assistance in Spanish Team and the NWS Spanish Outreach Team, are highlighted for their pioneer work on Spanish weather communication. Last, a framework for translation standardization in the atmospheric sciences is introduced, along with future initiatives that are being sought by NWS and AMS to enhance Spanish hazardous weather communication.

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Peyman Abbaszadeh, Hamid Moradkhani, Keyhan Gavahi, Sujay Kumar, Christopher Hain, Xiwu Zhan, Qingyun Duan, Christa Peters-Lidard, and Sepehr Karimiziarani
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Jennifer Collins, Amy Polen, Killian McSweeney, Delián Colón-Burgos, and Isabelle Jernigan

Abstract

The COVID-19 pandemic increases the complexity of planning for hurricanes as social distancing is in direct conflict with human mobility and congregation. COVID-19 presents not only urgent challenges for this hurricane season due to the likeliness of continued or heightened COVID-19 threat, but also challenges with the next hurricane season with additional waves of the pandemic. There is severe urgency to understand the impact of COVID-19 risk perceptions and the extent people are willing to risk their lives by sheltering in place rather than evacuating during severe hurricanes. In June 2020, a survey (in both English and Spanish) of 40 questions was disseminated through regional planning councils, emergency management, and the media to Florida residents. A total of 7,072 people responded from over 50 counties. Most data obtained were ordinal or categorical in nature, encouraging usage of nonparametric analysis and chi-square tests. Almost half the respondents view themselves as vulnerable to COVID-19 due to preexisting health conditions, and 74.3% of individuals viewed the risk of being in a shelter during the COVID-19 pandemic as more dangerous than enduring hurricane hazards. Additionally, there was a significant number of individuals who would choose to not utilize a public shelter during COVID-19 when they would have previously. Officials can use the results of this study regarding how household evacuation plans change with social distancing to better inform strategies of shelter preparedness and COVID-19 risk mitigation to minimize risk to those in harm’s way of storm surge and other hurricane effects during a mandatory evacuation order.

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Dawn Kopacz, Lindsay C. Maudlin, Wendilyn J. Flynn, Zachary J. Handlos, Adam Hirsch, and Swarndeep Gill

Abstract

Increasing participation in education research and encouraging the use of evidence-based practices in the classroom has been identified as a Grand Challenge in the Geosciences. As a first step in addressing this Grand Challenge, a survey was developed and disseminated to a broad range of atmospheric science professionals to collect data about 1) the number of community members involved in atmospheric science education research (ASER); 2) whether ASER is valued within the community, and if so, to what extent; 3) potential barriers to involvement in ASER; and 4) the resources necessary to encourage involvement in ASER. Survey results revealed that while many in the atmospheric science community highly value education research, barriers to greater involvement include a perceived lack of value and a lack of visibility of ASER. Recommendations are made for addressing these barriers.

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Massimo Bonavita, Rossella Arcucci, Alberto Carrassi, Peter Dueben, Alan J. Geer, Bertrand Le Saux, Nicolas Longépé, Pierre-Philippe Mathieu, and Laure Raynaud
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Alexander P. Trishchenko and Calin Ungureanu

Abstract

A novel satellite image processing technique developed at the Canada Centre for Remote Sensing has been utilized to produce annual time series of the minimum snow/ice (MSI) extent over the northern circumpolar landmass area (9,000 km × 9,000 km) for 2000–19. The information has been derived from the Moderate Resolution Imaging Spectroradiometer 10-day clear-sky composites generated at 250-m spatial resolution over the April–September period. Derived interannual variations agree very well with the warm-season average surface air temperatures from the European reanalysis (ERA5). The region-average correlation coefficient is −0.78. The total MSI extent demonstrated a statistically significant declining trend equal to −1,477 km2 yr−1. Results have been compared with data from the Randolph Glacier Inventory (RGI 6.0). The comparison points to a significant contribution of minimum seasonal snow cover relative to RGI glacierized areas. Quantitative estimates obtained for the first time showed that the region-average snow extent that survives the summer melt and resides outside of RGI area can be as high as 15% (or 53 × 103 km2) while in the northern Canadian Arctic it can reach 41% (or 43 × 103 km2). The derived MSI time series data can be recommended to the glacier and land-cover scientific community as a source of validation data and annual updates of snow and ice maps over the northern circumpolar landmass.

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Barbara Brown, Tara Jensen, John Halley Gotway, Randy Bullock, Eric Gilleland, Tressa Fowler, Kathryn Newman, Dan Adriaansen, Lindsay Blank, Tatiana Burek, Michelle Harrold, Tracy Hertneky, Christina Kalb, Paul Kucera, Louisa Nance, John Opatz, Jonathan Vigh, and Jamie Wolff

Abstract

Forecast verification and evaluation is a critical aspect of forecast development and improvement, day-to-day forecasting, and the interpretation and application of forecasts. In recent decades, the verification field has rapidly matured, and many new approaches have been developed. However, until recently, a stable set of modern tools to undertake this important component of forecasting has not been available. The Model Evaluation Tools (MET) was conceived and implemented to fill this gap. MET (https://dtcenter.org/community-code/model-evaluation-tools-met) was developed by the National Center for Atmospheric Research (NCAR), the National Oceanic and Atmospheric Administration (NOAA), and the U.S. Air Force (USAF) and is supported via the Developmental Testbed Center (DTC) and collaborations with operational and research organizations. MET incorporates traditional verification methods, as well as modern verification capabilities developed over the last two decades. MET stands apart from other verification packages due to its inclusion of innovative spatial methods, statistical inference tools, and a wide range of approaches to address the needs of individual users, coupled with strong community engagement and support. In addition, MET is freely available, which ensures that consistent modern verification capabilities can be applied by researchers and operational forecasting practitioners, enabling the use of consistent and scientifically meaningful methods by all users. This article describes MET and the expansion of MET to an umbrella package (METplus) that includes a database and display system and Python wrappers to facilitate the wide use of MET. Examples of MET applications illustrate some of the many ways that the package can be used to evaluate forecasts in a meaningful way.

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Greg M. McFarquhar, Christopher S. Bretherton, Roger Marchand, Alain Protat, Paul J. DeMott, Simon P. Alexander, Greg C. Roberts, Cynthia H. Twohy, Darin Toohey, Steve Siems, Yi Huang, Robert Wood, Robert M. Rauber, Sonia Lasher-Trapp, Jorgen Jensen, Jeffrey L. Stith, Jay Mace, Junshik Um, Emma Järvinen, Martin Schnaiter, Andrew Gettelman, Kevin J. Sanchez, Christina S. McCluskey, Lynn M. Russell, Isabel L. McCoy, Rachel L. Atlas, Charles G. Bardeen, Kathryn A. Moore, Thomas C. J. Hill, Ruhi S. Humphries, Melita D. Keywood, Zoran Ristovski, Luke Cravigan, Robyn Schofield, Chris Fairall, Marc D. Mallet, Sonia M. Kreidenweis, Bryan Rainwater, John D’Alessandro, Yang Wang, Wei Wu, Georges Saliba, Ezra J. T. Levin, Saisai Ding, Francisco Lang, Son C. H. Truong, Cory Wolff, Julie Haggerty, Mike J. Harvey, Andrew R. Klekociuk, and Adrian McDonald

Abstract

Weather and climate models are challenged by uncertainties and biases in simulating Southern Ocean (SO) radiative fluxes that trace to a poor understanding of cloud, aerosol, precipitation, and radiative processes, and their interactions. Projects between 2016 and 2018 used in situ probes, radar, lidar, and other instruments to make comprehensive measurements of thermodynamics, surface radiation, cloud, precipitation, aerosol, cloud condensation nuclei (CCN), and ice nucleating particles over the SO cold waters, and in ubiquitous liquid and mixed-phase clouds common to this pristine environment. Data including soundings were collected from the NSF–NCAR G-V aircraft flying north–south gradients south of Tasmania, at Macquarie Island, and on the R/V Investigator and RSV Aurora Australis. Synergistically these data characterize boundary layer and free troposphere environmental properties, and represent the most comprehensive data of this type available south of the oceanic polar front, in the cold sector of SO cyclones, and across seasons. Results show largely pristine environments with numerous small and few large aerosols above cloud, suggesting new particle formation and limited long-range transport from continents, high variability in CCN and cloud droplet concentrations, and ubiquitous supercooled water in thin, multilayered clouds, often with small-scale generating cells near cloud top. These observations demonstrate how cloud properties depend on aerosols while highlighting the importance of dynamics and turbulence that likely drive heterogeneity of cloud phase. Satellite retrievals confirmed low clouds were responsible for radiation biases. The combination of models and observations is examining how aerosols and meteorology couple to control SO water and energy budgets.

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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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