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Neil A. Jacobs

Abstract

Despite having the largest associated research community and a rapidly growing private sector, the lack of a well-coordinated national research and development effort for U.S. numerical weather prediction continues to impede our ability to utilize more of the scientific and technical capacity of the Nation more efficiently. Over the last few years, considerable progress has been made towards developing a community-friendly Unified Forecast System (UFS) by embracing an open innovation approach that is mutually beneficial to the public, private, and academic sectors. Once fully implemented, the UFS has the potential to catalyze a significant increase in the efficacy of our Nation’s weather, water, and climate science and prediction.

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Maude Dinan, Emile Elias, Nicholas P. Webb, Greg Zwicke, Timothy S. Dye, Skye Aney, Michael Brady, Joel R. Brown, Robert R. Dobos, Dave DuBois, Brandon L. Edwards, Sierra Heimel, Nicholas Luke, Caitlin M. Rottler, and Caitriana Steele
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A. Marshak, A. Ackerman, A. Da Silva, T. Eck, B. Holben, R. Kahn, R. Kleidman, K. Knobelspiesse, R. Levy, A. Lyapustin, L. Oreopoulos, L. Remer, O. Torres, T. Varnai, G. Wen, and J. Yorks

Abstract

Aerosol properties are fundamentally different near clouds than distant from clouds. This paper reviews the current state of knowledge of aerosol properties in the near low cloud environment and quantitatively compares them with aerosols far from clouds, limited in scope to remote sensing observations. It interprets observations of aerosol properties from different sensors using satellite, aircraft and ground-based observations. The correlation (and anticorrelation) between proximity to cloud and aerosol properties is discussed. Retrieval artifacts in the near-cloud environment are demonstrated and quantified for different sensor attributes and environmental conditions. Finally, the paper describes the possible corrections for near-cloud enhancement in remote-sensing retrievals. This study is timely in view of science definition studies for NASA’s Aerosols-Clouds, Convection and Precipitation (ACCP) mission, which will also seek to directly links aerosol properties to nearby clouds.

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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 16 cold pool–focused 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 16 cold pools’ 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 from O(100) m through to O(1) km. Processes responsible for the cold pool observations are explored and support recent high-resolution modeling results.

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Cara L. Cuite, Rebecca E. Morss, Julie L. Demuth, and William K. Hallman

Abstract

Both hurricanes and nor’easters can be destructive and deadly. The current study investigates whether, when all other features of a storm warning message are held constant, people perceive the risks posed by nor’easters and hurricanes differently and whether these differences affect their attitudes and decisions about taking protective action. We conducted an online experiment involving 1,700 Americans residing in northeastern coastal ZIP codes to test the effects of storm type (hurricane vs nor’easter). Participants were told that their area was under an evacuation order due to either a predicted hurricane or nor’easter. Reported message comprehension and perceived relevance were similar across storm type; however, storm type had small but significant effects on other dependent measures. Those in the hurricane condition were more likely to believe the storm would be severe (p = 0.007). They were also more likely to say that it is important to evacuate, that they would evacuate their homes, and that they would recommend to their neighbors that they evacuate (p < 0.001). Additional analysis demonstrated that the effect of storm type on evacuation likelihood is mediated, at least in part, by perceived severity. These findings provide evidence that people perceive hurricanes as more severe and more likely to require taking protective action than nor’easters, even when other attributes of the storms remain the same. Forecasters, broadcast meteorologists, and emergency management professionals should consider these small but important differences in perceptions when communicating about these types of storms.

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Bradley Wade Bishop, Ashley Marie Orehek, and Hannah R. Collier

Abstract

This study’s purpose is to capture the skills of Earth science data managers and librarians through interviews with current job holders. Job analysis interviews were conducted of 14 participants—six librarians and eight data managers—to assess the types and frequencies of job tasks. Participants identified tasks related to communication, including collaboration, teaching, and project management activities. Data-specific tasks included data discovery, processing, and curation, which require an understanding of the data, technology, and information infrastructures to support data use, reuse, and preservation. Most respondents had formal science education and six had a master’s degree in Library and Information Sciences. Most of the knowledge, skills, and abilities for these workers were acquired through on-the-job experience, but future professionals in these careers may benefit from tailored education informed through job analyses.

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Robert Palmer, David Whelan, David Bodine, Pierre Kirstetter, Matthew Kumjian, Justin Metcalf, Mark Yeary, Tian-You Yu, Ramesh Rao, John Cho, David Draper, Stephen Durden, Stephen English, Pavlos Kollias, Karen Kosiba, Masakazu Wada, Joshua Wurman, William Blackwell, Howard Bluestein, Scott Collis, Jordan Gerth, Aaron Tuttle, Xuguang Wang, and Dusan Zrnić
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Bing Pu and Qinjian Jin

Abstract

High concentrations of dust can affect climate and human health, yet our understanding of extreme dust events is still limited. A record-breaking trans-Atlantic African dust plume occurred during 14–28 June 2020, greatly degrading air quality over large areas of the Caribbean Basin and the United States. Daily PM2.5 concentrations exceeded 50 µg m−3 in several Gulf States, while the air quality index reached unhealthy levels for sensitive groups in more than 11 states. The magnitude and duration of aerosol optical depth over the tropical North Atlantic Ocean were the greatest ever observed during summer over the past 18 years based on satellite retrievals. This extreme trans-Atlantic dust event is associated with both enhanced dust emissions over western North Africa and atmospheric circulation extremes that favor long-range dust transport. An exceptionally strong African easterly jet and associated wave activities export African dust across the Atlantic toward the Caribbean in the middle to lower troposphere, while a westward extension of the North Atlantic subtropical high and a greatly intensified Caribbean low-level jet further transport the descended, shallower dust plume from the Caribbean Basin into the United States. Over western North Africa, increased dust emissions are associated with strongly enhanced surface winds over dust source regions and reduced vegetation coverage in the western Sahel. While there are large uncertainties associated with assessing future trends in African dust emissions, model-projected atmospheric circulation changes in a warmer future generally favor increased long-range transport of African dust to the Caribbean Basin and the United States.

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Mark S. Kulie, Claire Pettersen, Aronne J. Merrelli, Timothy J. Wagner, Norman B. Wood, Michael Dutter, David Beachler, Todd Kluber, Robin Turner, Marian Mateling, John Lenters, Peter Blanken, Maximilian Maahn, Christopher Spence, Stefan Kneifel, Paul A. Kucera, Ali Tokay, Larry F. Bliven, David B. Wolff, and Walter A. Petersen

Abstract

A multisensor snowfall observational suite has been deployed at the Marquette, Michigan, National Weather Service Weather Forecast Office (KMQT) since 2014. Micro Rain Radar (MRR; profiling radar), Precipitation Imaging Package (PIP; snow particle imager), and ancillary ground-based meteorological observations illustrate the unique capabilities of these combined instruments to document radar and concomitant microphysical properties associated with northern Great Lakes snowfall regimes. Lake-effect, lake-orographic, and transition event case studies are presented that illustrate the variety of snowfall events that occur at KMQT. Case studies and multiyear analyses reveal the ubiquity of snowfall produced by shallow events. These shallow snowfall features and their distinctive microphysical fingerprints are often difficult to discern with conventional remote sensing instruments, thus highlighting the scientific and potential operational value of MRR and PIP observations. The importance of near-surface lake-orographic snowfall enhancement processes in extreme snowfall events and regime-dependent snow particle microphysical variability controlled by regime and environmental factors are also highlighted.

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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 the current annual rate of error reduction for another decade is worth between $90.25 and $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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