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Storm-scale interactions with rough terrain are complex. Terrain has been theorized to impact the strength of low-level mesocyclones. Surface roughness and modifications of the surrounding environment also may impact tornadogenesis or tornado intensity. The Mountainburg, Arkansas EF2 tornado on 13 April 2018 traveled along a path with minor variations in intensity and elevation throughout most of the nearly 19-km (11.8 mi) damage path as the storm moved along a river valley. A detailed damage survey showed that the tornado then made an abrupt ascent of more than 200 m (656 ft) in the last 2 km (1.2 mi) before dissipating. By examining model soundings and conducting a detailed terrain analysis, this study examines what role terrain may have had in channeling the momentum surge and enhancing the low-level vorticity to influence tornadogenesis. Other storm-scale factors are investigated to determine their potential impact on the demise of the tornado. The differential reflectivity column is studied to determine if the updraft was weakening. The relative position of the tornado and mesocyclone also are examined as the tornado ascended the terrain and dissipated to determine whether the change in elevation impacted the overall strength of the storm and to evaluate whether the storm was undergoing a traditional occlusion cycle. Finally, a large-eddy simulation model is used to explore physical changes in a tornado encountering terrain similar to the Mountainburg, Arkansas, tornado near its demise. 

ABSTRACT We present the time lag/delay reconstructor (TLDR), an algorithm for reconstructing velocity delay maps in the maximum a posteriori framework for reverberation mapping. Reverberation mapping is a tomographical method for studying the kinematics and geometry of the broad-line region of active galactic nuclei at high spatial resolution. Leveraging modern image reconstruction techniques, including total variation and compressed sensing, TLDR applies multiple regularization schemes to reconstruct velocity delay maps using the alternating direction method of multipliers. Along with the detailed description of the TLDR algorithm we present test reconstructions from TLDR applied to synthetic reverberation mapping spectra as well as a preliminary reconstruction of the Hβ feature of Arp 151 from the 2008 Lick Active Galactic Nuclei Monitoring Project. 

We review comprehensive observations of electromagnetic ion cyclotron (EMIC) wave-driven energetic electron precipitation using data collected by the energetic electron detector on the Electron Losses and Fields InvestigatioN (ELFIN) mission, two polar-orbiting low-altitude spinning CubeSats, measuring 50-5000 keV electrons with good pitch-angle and energy resolution. EMIC wave-driven precipitation exhibits a distinct signature in energy-spectrograms of the precipitating-to-trapped flux ratio: peaks at >0.5 MeV which are abrupt (bursty) (lasting ∼17 s, or$\Delta L\sim 0.56$$\Delta L\sim 0.56$) with significant substructure (occasionally down to sub-second timescale). We attribute the bursty nature of the precipitation to the spatial extent and structuredness of the wave field at the equator. Multiple ELFIN passes over the same MLT sector allow us to study the spatial and temporal evolution of the EMIC wave - electron interaction region. Case studies employing conjugate ground-based or equatorial observations of the EMIC waves reveal that the energy of moderate and strong precipitation at ELFIN approximately agrees with theoretical expectations for cyclotron resonant interactions in a cold plasma. Using multiple years of ELFIN data uniformly distributed in local time, we assemble a statistical database of ∼50 events of strong EMIC wave-driven precipitation. Most reside at$L\sim 5-7$$L\sim 5-7$at dusk, while a smaller subset exists at$L\sim 8-12$$L\sim 8-12$at post-midnight. The energies of the peak-precipitation ratio and of the half-peak precipitation ratio (our proxy for the minimum resonance energy) exhibit an$L$$L$-shell dependence in good agreement with theoretical estimates based on prior statistical observations of EMIC wave power spectra. The precipitation ratio’s spectral shape for the most intense events has an exponential falloff away from the peak (i.e., on either side of$\sim 1.45$$\sim 1.45$MeV). It too agrees well with quasi-linear diffusion theory based on prior statistics of wave spectra. It should be noted though that this diffusive treatment likely includes effects from nonlinear resonant interactions (especially at high energies) and nonresonant effects from sharp wave packet edges (at low energies). Sub-MeV electron precipitation observed concurrently with strong EMIC wave-driven >1 MeV precipitation has a spectral shape that is consistent with efficient pitch-angle scattering down to ∼ 200-300 keV by much less intense higher frequency EMIC waves at dusk (where such waves are most frequent). At ∼100 keV, whistler-mode chorus may be implicated in concurrent precipitation. These results confirm the critical role of EMIC waves in driving relativistic electron losses. Nonlinear effects may abound and require further investigation.

 

Despite many studies confirming that active learning in STEM classrooms improves student outcomes, instructors’ adoption of active learning has been surprisingly slow. This work-in-progress paper describes our broader research study in which we compare the efficacy of a traditional active learning workshop (AL) and an extended version of this workshop that also specifically highlights instructor strategies to reduce resistance (AL+) on instructors’ beliefs about and actual adoption of active learning in undergraduate STEM classrooms. Through a randomized control trial (RCT), we aim to understand the ways in which these workshops influence instructors’ motivation to adopt and the actual use of active learning. This RCT involves instructors and students at a large number of institutions including two-year college, four-year college, and large research institutions in three regions of the country and strategies to reduce student resistance to active learning. We have developed and piloted three instruments, which allow for triangulation of classroom data: an instructor survey, a student survey, and a classroom observation protocol. This work-in-progress paper will cover the current progress of our research study and present our research instruments. 

Despite many studies confirming that active learning in STEM classrooms improves student outcomes, instructors’ adoption of active learning has been surprisingly slow. This work-in-progress paper describes our broader research study in which we compare the efficacy of a traditional active learning workshop (AL) and an extended version of this workshop that also specifically highlights instructor strategies to reduce resistance (AL+) on instructors’ beliefs about and actual adoption of active learning in undergraduate STEM classrooms. Through a randomized control trial (RCT), we aim to understand the ways in which these workshops influence instructors’ motivation to adopt and the actual use of active learning. This RCT involves instructors and students at a large number of institutions including two-year college, four-year college, and large research institutions in three regions of the country and strategies to reduce student resistance to active learning. We have developed and piloted three instruments, which allow for triangulation of classroom data: an instructor survey, a student survey, and a classroom observation protocol. This work-in-progress paper will cover the current progress of our research study and present our research instruments. 

Does engagement in high impact practices such as technical internships and undergraduate research influence engineering students’ career decisions and future plans? And how is learning that comes from these high impact practices related to “school learning”? These high impact educational practices have been shown to increase the rates of student engagement and retention in higher education. While access to and participation in these activities is often unsystematic across various institutions, these practices have been shown to benefit college students with diverse backgrounds and learner qualities. This paper establishes a context for understanding the characteristics and attitudes of students who participate in internships and undergraduate research by drawing from analyses of the first administration of the Engineering Majors Survey (EMS), a longitudinal study designed to examine engineering students’ career objectives related to creativity and innovation, and the experiences and attitudes that might influence those goals. In addition, using interview data from product development interns at a single engineering firm, we add insights into the specific skills that interns identify as learning in their internship and suggest connections between school-and-work learning. The more general picture of the impact of internship and research experiences (from the EMS), complemented with a “deep dive” into the learning that happens in internship experiences (from the interviews) provides a solid starting point for future exploration of how high impact practices such as internships and research experiences might be better integrated into a student’s educational development. 

Continuous, sub‐centennially resolved, paleo terrestrial records are rare from arid environments such as the Pacific south‐west United States. Here, we present a multi‐decadal to centennial resolution sediment core (Lake Elsinore, CA) to reconstruct late Wisconsin pluvials, droughts and vegetation. In general, the late Wisconsin is characterized by a wetter and colder climate than during the Holocene. Specifically, conditions between 32.3 and 24.9k cal a BP are characterized by large‐amplitude hydrologic and ecologic variability. Highlighting this period is a ∼2000‐year glacial mega‐drought (27.6–25.7k cal a BP) during which the lake shallowed (3.2–4.5 m depth). This period is approximately coeval with a Lake Manix regression and an increase in xeric vegetation in the San Bernardino Mountains (Baldwin Lake). The Local Last Glacial Maximum (LLGM) is bracketed between 23.3 and 19.7k cal a BP − a ∼3000‐year interval characterized by reduced run‐off (relative to the glacial), colder conditions and vegetative stability. Maximum sustained wetness follows the LLGM, beginning at 19.7 and peaking by 14.4k cal a BP. A two‐step decrease in runoff characterizes the Lateglacial to Holocene transition; however, the vegetation change is more complex, particularly at the beginning of the Younger Dryas chronozone. By 12.6–12.4k cal a BP, the climate achieved near Holocene conditions.

 

Abstract The Electron Loss and Fields Investigation with a Spatio-Temporal Ambiguity-Resolving option (ELFIN-STAR, or heretoforth simply: ELFIN) mission comprises two identical 3-Unit (3U) CubeSats on a polar (∼93 ∘ inclination), nearly circular, low-Earth (∼450 km altitude) orbit. Launched on September 15, 2018, ELFIN is expected to have a >2.5 year lifetime. Its primary science objective is to resolve the mechanism of storm-time relativistic electron precipitation, for which electromagnetic ion cyclotron (EMIC) waves are a prime candidate. From its ionospheric vantage point, ELFIN uses its unique pitch-angle-resolving capability to determine whether measured relativistic electron pitch-angle and energy spectra within the loss cone bear the characteristic signatures of scattering by EMIC waves or whether such scattering may be due to other processes. Pairing identical ELFIN satellites with slowly-variable along-track separation allows disambiguation of spatial and temporal evolution of the precipitation over minutes-to-tens-of-minutes timescales, faster than the orbit period of a single low-altitude satellite (T orbit ∼ 90 min). Each satellite carries an energetic particle detector for electrons (EPDE) that measures 50 keV to 5 MeV electrons with $\Delta $ Δ E/E < 40% and a fluxgate magnetometer (FGM) on a ∼72 cm boom that measures magnetic field waves (e.g., EMIC waves) in the range from DC to 5 Hz Nyquist (nominally) with <0.3 nT/sqrt(Hz) noise at 1 Hz. The spinning satellites (T spin $\,\sim $ ∼ 3 s) are equipped with magnetorquers (air coils) that permit spin-up or -down and reorientation maneuvers. Using those, the spin axis is placed normal to the orbit plane (nominally), allowing full pitch-angle resolution twice per spin. An energetic particle detector for ions (EPDI) measures 250 keV – 5 MeV ions, addressing secondary science. Funded initially by CalSpace and the University Nanosat Program, ELFIN was selected for flight with joint support from NSF and NASA between 2014 and 2018 and launched by the ELaNa XVIII program on a Delta II rocket (with IceSatII as the primary). Mission operations are currently funded by NASA. Working under experienced UCLA mentors, with advice from The Aerospace Corporation and NASA personnel, more than 250 undergraduates have matured the ELFIN implementation strategy; developed the instruments, satellite, and ground systems and operate the two satellites. ELFIN’s already high potential for cutting-edge science return is compounded by concurrent equatorial Heliophysics missions (THEMIS, Arase, Van Allen Probes, MMS) and ground stations. ELFIN’s integrated data analysis approach, rapid dissemination strategies via the SPace Environment Data Analysis System (SPEDAS), and data coordination with the Heliophysics/Geospace System Observatory (H/GSO) optimize science yield, enabling the widest community benefits. Several storm-time events have already been captured and are presented herein to demonstrate ELFIN’s data analysis methods and potential. These form the basis of on-going studies to resolve the primary mission science objective. Broad energy precipitation events, precipitation bands, and microbursts, clearly seen both at dawn and dusk, extend from tens of keV to >1 MeV. This broad energy range of precipitation indicates that multiple waves are providing scattering concurrently. Many observed events show significant backscattered fluxes, which in the past were hard to resolve by equatorial spacecraft or non-pitch-angle-resolving ionospheric missions. These observations suggest that the ionosphere plays a significant role in modifying magnetospheric electron fluxes and wave-particle interactions. Routine data captures starting in February 2020 and lasting for at least another year, approximately the remainder of the mission lifetime, are expected to provide a very rich dataset to address questions even beyond the primary mission science objective.