A new method that combines radar reflectivities from individual Next Generation Weather Radars (NEXRAD) into a three-dimensional composite with high horizontal and vertical resolution is used to estimate storm-top altitudes for the continental United States east of the Rocky Mountains. Echo-top altitudes are compared with the altitude of the lapse-rate tropopause calculated from the ERA-Interim reanalysis and radiosondes. To sample the diurnal and annual cycles, tropopause-penetrating convection is analyzed at 3-h intervals throughout 2004. Overshooting convection is most common in the north-central part of the United States (the high plains). There is a pronounced seasonal cycle; the majority of overshooting systems occur during the warm season (March–August). There is also a strong diurnal cycle, with maximum overshooting occurring near 0000 UTC. The overshooting volume decreases rapidly with height above the tropopause. Radiosonde observations are used to evaluate the quality of the reanalysis tropopause altitudes and the dependence of overshooting depth on environmental characteristics. The radar–radiosonde comparison reveals that overshooting is deeper in double-tropopause environments and increases as the stability of the lower stratosphere decreases.

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Purpose Metacognition and critical thinking are essential for academic success. The relationship between these components and medical student learning, as assessed with progress examinations, informs curriculum development and efforts to ensure learning progression of all students. This study assessed learning mechanisms by modeling medical students’ progress test performance longitudinally at Michigan State University College of Human Medicine. Method Medical students’ (n = 184) medical knowledge was assessed 5 times from fall 2017 through spring 2019 using the Comprehensive Basic Science Examination (CBSE). Structural equation modeling was conducted to investigate associations between 3 latent structures—metacognitive awareness, critical thinking, and self-regulation—and their relationship with students’ initial CBSE scores and growth in such scores. The authors measured metacognitive knowledge and regulation by the Metacognitive Awareness Inventory, critical thinking skills by the Watson-Glaser Critical Thinking Appraisal, and self-regulation by the Learning and Study Strategies Inventory. Results Students’ aggregate performance on 5 CBSE scores grew 31.0% the first semester, 16.5% the second semester, 30.1% the third semester, and 22.4% the last semester. Critical thinking had a significant positive relationship with initial performance ( JOURNAL/acmed/04.03/00001888-202102000-00048/inline-graphic1/v/2023-07-18T003513Z/r/image-tiff 1.956, P < .001), self-regulation had a significant positive relationship with growth ( JOURNAL/acmed/04.03/00001888-202102000-00048/inline-graphic2/v/2023-07-18T003513Z/r/image-tiff 3.287, P < .05), and metacognitive awareness had a negative relationship with growth of student performance in the progress test ( JOURNAL/acmed/04.03/00001888-202102000-00048/inline-graphic3/v/2023-07-18T003513Z/r/image-tiff −3.426, P < .01). Conclusions This structural equation framework is useful for examining the relationships among 3 latent structures—critical thinking, metacognition, and self-regulation—and their relationships with students’ progress scores in academic achievement. The initial status of progress examination scores was explained by students’ critical thinking ability, but their learning growth on the progress scores was explained by their self-regulation and metacognitive ability. These findings help explain student performance on standardized progress examinations and can aid in interventions to promote student success.

The growth of the wind industry in recent years has motivated investigation into wind farm interference with the operation of the nationwide Weather Surveillance Radar-1988 Doppler (WSR-88D) network. Observations of a wind farm were taken with a Doppler on Wheels (DOW) during the DOW Radar Observations at Purdue Study (DROPS), a largely studentled field program that took place in the fall of 2009. The DOW sampled clear-air weather and precipitation at locations within 5 km of the Benton County, Indiana, wind farm to determine the wind turbines' effect on Doppler velocity and ref lectivity data. These data were analyzed and compared with data from the Indianapolis WSR-88D (KIND) and a local television station (WLFI) radar. In precipitation, the DOW data show velocity couplets that have the appearance of isolated tornadic vortices. Under clear-air sampling, significant multipath scattering is evident, but no velocity couplets would meet the DOW-equivalent tornado detection algorithm criteria. Broader impacts of these findings are discussed, and suggestions are made for additional studies that would explore how to mitigate these impacts.