Search for: All records

Submesoscale fronts with large horizontal buoyancy gradients and$$O(1)$$Rossby numbers are common in the upper ocean. These fronts are associated with large vertical transport and are hotspots for biological activity. Submesoscale fronts are susceptible to symmetric instability (SI) – a form of stratified inertial instability which can occur when the potential vorticity is of the opposite sign to the Coriolis parameter. Here, we use a weakly nonlinear stability analysis to study SI in an idealised frontal zone with a uniform horizontal buoyancy gradient in thermal wind balance. We find that the structure and energetics of SI strongly depend on the front strength, defined as the ratio of the horizontal buoyancy gradient to the square of the Coriolis frequency. Vertically bounded non-hydrostatic SI modes can grow by extracting potential or kinetic energy from the balanced front and the relative importance of these energy reservoirs depends on the front strength and vertical stratification. We describe two limiting behaviours as ‘slantwise convection’ and ‘slantwise inertial instability’ where the largest energy source is the buoyancy flux and geostrophic shear production, respectively. The growing linear SI modes eventually break down through a secondary shear instability, and in the process transport considerable geostrophic momentum. The resulting breakdown of thermal wind balance generates vertically sheared inertial oscillations and we estimate the amplitude of these oscillations from the stability analysis. We finally discuss broader implications of these results in the context of current parameterisations of SI. 

In Part 1 (Wienkers, Thomas & Taylor,J. Fluid Mech., vol. 926, 2021, A6), we described the theory for linear growth and weakly nonlinear saturation of symmetric instability (SI) in the Eady model representing a broad frontal zone. There, we found that both the fraction of the balanced thermal wind mixed down by SI and the primary source of energy are strongly dependent on the front strength, defined as the ratio of the horizontal buoyancy gradient to the square of the Coriolis frequency. Strong fronts with steep isopycnals develop a flavour of SI we call ‘slantwise inertial instability’ by extracting kinetic energy from the background flow and rapidly mixing down the thermal wind profile. In contrast, weak fronts extract more potential energy from the background density profile, which results in ‘slantwise convection.’ Here, we extend the theory from Part 1 using nonlinear numerical simulations to focus on the adjustment of the front following saturation of SI. We find that the details of adjustment and amplitude of the induced inertial oscillations depend on the front strength. While weak fronts develop narrow frontlets and excite small-amplitude vertically sheared inertial oscillations, stronger fronts generate large inertial oscillations and produce bore-like gravity currents that propagate along the top and bottom boundaries. The turbulent dissipation rate in these strong fronts is large, highly intermittent and intensifies during periods of weak stratification. We describe each of these mechanisms and energy pathways as the front evolves towards the final adjusted state, and in particular focus on the effect of varying the dimensionless front strength. 

Abstract. Flow tube reactors are often used to study aerosolkinetics. The goal of this study is to investigate how to best representcomplex growth kinetics of ultrafine particles within a flow tube reactorwhen the chemical processes causing particle growth are unknown. In atypical flow tube experiment, one measures the inlet and outlet particlesize distributions to give a time-averaged measure of growth, which maybe difficult to interpret if the growth kinetics change as particles transitthrough the flow tube. In this work, we simulate particle growth forsecondary organic aerosol (SOA) formation that incorporates both surface-and volume-limited chemical processes to illustrate how complex growthkinetics inside a flow tube can arise. We then develop and assess a methodto account for complex growth kinetics when the chemical processes drivingthe kinetics are not known. Diameter growth of particles is represented by agrowth factor (GF), defined as the fraction of products from oxidation ofthe volatile organic compound (VOC) precursors that grow particles during aspecific time period. Defined in this way, GF is the sum of all non-volatileproducts that condensationally grow particles plus a portion of semi-volatilemolecules that react on or in the particle to give non-volatile products thatremain in the particle over the investigated time frame. With respect toflow tube measurements, GF is independent of wall loss and condensationsink, which influence particle growth kinetics and can vary from experimentto experiment. GF is shown to change as a function of time within the flowtube and is sensitive to factors that affect growth such as gas-phase mixingratios of the precursors and the presence of aerosol liquid water (ALW) onthe surface or in the volume of the particle. A method to calculate GF from theoutlet-minus-inlet particle diameter change in a flow tube experiment ispresented and shown to accurately match GFs from simulations of SOAformation. 

Abstract BackgroundEngineering‐oriented bridge programs and camps are popular strategies for broadening participation. The students who often serve as counselors and mentors in these programs are integral to their success. PurposePredicated on the belief that mentoring contributes to positive outcomes for the mentors themselves, we sought to understand how undergraduate student mentors approached and experienced their work with a 6‐day overnight, NSF‐sponsored youth engineering camp (YEC). This study was guided by the question: How did YEC camp counselors approach and experience their roles as mentors? Design/MethodsWe conducted an exploratory qualitative study of four Black undergraduate engineering students' experiences with and approaches to near‐peer mentorship in the YEC program. Data consisted of transcripts from two post‐program interviews and one written reflection from each participant. We analyzed data through abductive coding and the funds of knowledge framework. ResultsThrough subsequent interpretation of code categories, we found YEC mentors: (1) engaged in altruistic motivations as YEC mentors, (2) leveraged previous experiences to guide their approaches to mentorship, and (3) engaged in self‐directed learning and development. ConclusionsThis study highlights the knowledge and strategies that YEC mentors drew upon in their roles, and how they sought and achieved various personal, academic, and professional benefits. Insights from this study illustrate how near‐peer mentors can support their and others' engineering aspirations. 

Background Cardiovascular disease (CVD) disparities are a particularly devastating manifestation of health inequity. Despite advancements in prevention and treatment, CVD is still the leading cause of death in the United States. Additionally, research indicates that African American (AA) and other ethnic-minority populations are affected by CVD at earlier ages than white Americans. Given that AAs are the fastest-growing population of smartphone owners and users, mobile health (mHealth) technologies offer the unparalleled potential to prevent or improve self-management of chronic disease among this population. Objective To address the unmet need for culturally tailored primordial prevention CVD–focused mHealth interventions, the MOYO app was cocreated with the involvement of young people from this priority community. The overall project aims to develop and evaluate the effectiveness of a novel smartphone app designed to reduce CVD risk factors among urban-AAs, 18-29 years of age. Methods The theoretical underpinning will combine the principles of community-based participatory research and the agile software development framework. The primary outcome goals of the study will be to determine the usability, acceptability, and functionality of the MOYO app, and to build a cloud-based data collection infrastructure suitable for digital epidemiology in a disparity population. Changes in health-related parameters over a 24-week period as determined by both passive (eg, physical activity levels, sleep duration, social networking) and active (eg, use of mood measures, surveys, uploading pictures of meals and blood pressure readings) measures will be the secondary outcome. Participants will be recruited from a majority AA “large city” school district, 2 historically black colleges or universities, and 1 urban undergraduate college. Following baseline screening for inclusion (administered in person), participants will receive the beta version of the MOYO app. Participants will be monitored during a 24-week pilot period. Analyses of varying data including social network dynamics, standard metrics of activity, percentage of time away from a given radius of home, circadian rhythm metrics, and proxies for sleep will be performed. Together with external variables (eg, weather, pollution, and socioeconomic indicators such as food access), these metrics will be used to train machine-learning frameworks to regress them on the self-reported quality of life indicators. Results This 5-year study (2015-2020) is currently in the implementation phase. We believe that MOYO can build upon findings of classical epidemiology and longitudinal studies like the Jackson Heart Study by adding greater granularity to our knowledge of the exposures and behaviors that affect health and disease, and creating a channel for outreach capable of launching interventions, clinical trials, and enhancements of health literacy. Conclusions The results of this pilot will provide valuable information about community cocreation of mHealth programs, efficacious design features, and essential infrastructure for digital epidemiology among young AA adults. International Registered Report Identifier (IRRID) DERR1-10.2196/16699