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Judicial Selection and Death Penalty Decisions
Most U.S. state supreme court justices face elections or reappointment by elected officials, and research suggests that judicial campaigns have come to resemble those for other offices. We develop predictions on how selection systems should affect judicial decisions and test these predictions on an extensive dataset of death penalty decisions by state courts of last resort. Specifically, the data include over 12,000 decisions on over 2000 capital punishment cases decided between 1980 and 2006 in systems with partisan, nonpartisan, or retention elections or with reappointment. As predicted, the findings suggest that judges face the greatest pressure to uphold capital sentences in systems with nonpartisan ballots. Also as predicted, judges respond similarly to public opinion in systems with partisan elections or reappointment. Finally, the results indicate that the plebiscitary influences on judicial behavior emerge only after interest groups began achieving success at targeting justices for their decisions.
Journal Article
Development of community, capabilities and understanding through unmanned aircraft-based atmospheric research: The LAPSE-RATE campaign
Because unmanned aircraft systems (UAS) offer new perspectives on the atmosphere, their use in atmospheric science is expanding rapidly. In support of this growth, the International Society for Atmospheric Research Using Remotely-Piloted Aircraft (ISARRA) has been developed and has convened annual meetings and “flight weeks.” The 2018 flight week, dubbed the Lower Atmospheric Profiling Studies at Elevation–A Remotely-Piloted Aircraft Team Experiment (LAPSE-RATE), involved a 1-week deployment to Colorado’s San Luis Valley. Between 14 and 20 July 2018 over 100 students, scientists, engineers, pilots, and outreach coordinators conducted an intensive field operation using unmanned aircraft and ground-based assets to develop datasets, community, and capabilities. In addition to a coordinated “Community Day” which offered a chance for groups to share their aircraft and science with the San Luis Valley community, LAPSE-RATE participants conducted nearly 1,300 research flights totaling over 250 flight hours. The measurements collected have been used to advance capabilities (instrumentation, platforms, sampling techniques, and modeling tools), conduct a detailed system intercomparison study, develop new collaborations, and foster community support for the use of UAS in atmospheric science.
Journal Article
Speed, Change of Direction Speed, and Reactive Agility of Rugby League Players
While studies have investigated speed and change of direction speed in rugby league players, no study has investigated the reactive agility of these athletes. In addition, the relationship among speed, change of direction speed, and reactive agility within the specific context of rugby league has not been determined. With this in mind, the purpose of this study was to investigate a wide range of speed, change of direction speed, and reactive agility tests commonly used by rugby league coaches to determine which, if any tests discriminated higher and lesser skilled players, and to investigate the relationship among speed, change of direction speed, and reactive agility in these athletes. Forty-two rugby league players completed tests of speed (5 m, 10 m, and 20 m sprint), change of direction speed (‘L’ run, 505 test, and modified 505 test), and reactive agility. The validity of the tests to discriminate higher and lesser skilled competitors was evaluated by testing first grade (N = 12) and second grade (N = 30) players. First grade players had faster speed, and movement and decision times on the reactive agility test than second grade players. No significant differences were detected between first and second grade players for change of direction speed. While movement times on the reactive agility test were significantly related to 10 m and 20 m sprint times and change of direction speed, no significant relationships were detected among measures of decision time and response accuracy during the reactive agility test and measures of linear speed and change of direction speed. These findings question the validity of preplanned change of direction speed tests for discriminating higher and lesser skilled rugby league players, while also highlighting the contribution of perceptual skill to agility in these athletes.
Journal Article
The new voices of science fiction
\"Your Future Is Bright! After all, your mother is a robot, your father has joined the alien hive mind, and your dinner will be counterfeit 3D-printed steak. Even though your worker bots have staged a mutiny, and your tour guide speaks only in memes, you can always sell your native language if you need some extra cash.\" -- From publisher's description.
Book
A seamless blended multi‐model ensemble approach to probabilistic medium‐range weather pattern forecasts over the UK
This paper describes a new seamless blended multi‐model ensemble configuration of an existing probabilistic medium‐ to extended‐range weather pattern forecasting tool (called Decider) run operationally at the Met Office. In its initial configuration, the tool calculated and presented probabilistic weather pattern forecast information for five individual ensemble forecasting systems, which varied in terms of their number of ensemble members, horizontal resolution, update frequencies and forecast lead time. This resulted in multiple forecasts for the same validity time which varied in terms of forecast skill depending on the lead time in question. This presented challenges for end‐users (e.g., operational meteorologists) in terms of knowing which forecast output is best to use and at which lead time, as well as knowing what to do in situations where forecasts varied between ensembles. To get around these challenges, a new seamless blended multi‐model ensemble configuration has been implemented operationally, comprising of output from five separate ensembles, and provides a single best forecast from day one out to day 45. Objective verification for a set of eight weather pattern groups covering forecasts initialized over a 6‐year period (2017–2022) shows that the seamless blended multi‐model ensemble forecasts are at least as good as, if not better than the best performing individual model. This paper presents a framework for generating probabilistic weather pattern forecasts using a seamless blended multi‐model ensemble approach, to help speed up the decision‐making process for end‐users (e.g., operational meteorologists). Objective verification over a 6‐year period compares probabilistic weather pattern forecasts from separate ensemble systems (MOGREPS‐G, ECMWF medium‐range, GEFS, ECMWF extended‐range and GloSea) with those from a seamless blended multi‐model ensemble. Results show that the multi‐model ensemble forecasts are more skilful on average than the best performing individual model.
Journal Article