Daily Activity Patterns Among Apex Predators in the Northwest United States

The gray wolf [Canis lupus], brown bear [Ursus arctos], and American black bear [Ursus americanus], are all ecologically interesting because they are all apex predators that exist in the same spaces in the United States. However, little research has been done after wolf reintroduction in many parts of the western U.S. to see if these three predators will change their daily activity patterns around each other. The goal of this research project was to see whether the daily activity patterns of the gray wolf, brown bear, and American black bear differ, and it was hypothesized that he American black bear and brown bear will be more active during the day while the gray wolf will be more active at night. Bar graphs of the daily activity pattern of each species was created using occurrences in camera trap images from Snapshot USA. Overall, the observed daily activity patterns show that the American black bear and brown bear followed a crepuscular activity pattern and the gray wolf followed a nocturnal activity pattern. Knowing these daily activity patterns can help mitigate human-wildlife conflict in spaces where they interact, which is especially important for the gray wolf since it is endangered, and future research could look into the cause of the activity patterns of the gray wolf, brown bear, and American black bear, whether it be due to competition among each other, with other species, or with humans

Overshooting Convection in Tropical Cyclones

Using infrared satellite imagery, best-track data, and reanalysis data, tropical cyclones are shown to contain a disproportionate amount of the deepest convection in the tropics. Although tropical cyclones account for only 7% of the deep convection in the tropics, they account for about 15% of the deep convection with cloud-top temperatures below the monthly averaged tropopause temperature and 29% of the clouds that attain a cloud-top temperature 15 K below the temperature of the tropopause. This suggests that tropical cyclones could play an important role in setting the humidity of the stratosphere.Earth and Planetary Science

A Numerical Study of Methods for Moist Atmospheric Flows: Compressible Equations

We investigate two common numerical techniques for integrating reversible moist processes in atmospheric flows in the context of solving the fully compressible Euler equations. The first is a one-step, coupled technique based on using appropriate invariant variables such that terms resulting from phase change are eliminated in the governing equations. In the second approach, which is a two-step scheme, separate transport equations for liquid water and vapor water are used, and no conversion between water vapor and liquid water is allowed in the first step, while in the second step a saturation adjustment procedure is performed that correctly allocates the water into its two phases based on the Clausius-Clapeyron formula. The numerical techniques we describe are first validated by comparing to a well-established benchmark problem. Particular attention is then paid to the effect of changing the time scale at which the moist variables are adjusted to the saturation requirements in two different variations of the two-step scheme. This study is motivated by the fact that when acoustic modes are integrated separately in time (neglecting phase change related phenomena), or when sound-proof equations are integrated, the time scale for imposing saturation adjustment is typically much larger than the numerical one related to the acoustics

Developing a Quality Control Protocol for Evaluation of Recorded Interviews

This presentation will describe the process used at the University of Michigan Survey Research Center for evaluating interviewer performance in survey administration. Within the Survey Research Operations unit, we use an online system for evaluating the interviewer-respondent interaction using recorded interviews. We will present our framework for measuring how well interviewers adhere to General Interviewing Techniques (GIT) - the guidelines in which they were trained. The presentation will describe the question-level and session-level measurement criteria employed, in addition to the selection protocols and the integration of paradata into the selection process. The presentation will include analysis of some evaluation data, with a discussion of how the data were used to inform further development of the evaluation protocol. Although some aggregate data will be shared, the presentation will largely focus on the operational considerations related to the development and implementation of the quality control protocol across projects

Developing a Quality Control Protocol for Evaluation of Recorded Interviews

This presentation will describe the process used at the University of Michigan Survey Research Center for evaluating interviewer performance in survey administration. Within the Survey Research Operations unit, we use an online system for evaluating the interviewer-respondent interaction using recorded interviews. We will present our framework for measuring how well interviewers adhere to General Interviewing Techniques (GIT) - the guidelines in which they were trained. The presentation will describe the question-level and session-level measurement criteria employed, in addition to the selection protocols and the integration of paradata into the selection process. The presentation will include analysis of some evaluation data, with a discussion of how the data were used to inform further development of the evaluation protocol. Although some aggregate data will be shared, the presentation will largely focus on the operational considerations related to the development and implementation of the quality control protocol across projects

Remember, remember the fifth of November: was that thunder I heard or not?

‘Thunder days’ are simple records of thunderstorm activity, logging whether a human observer heard thunder on a particular day or not. Despite their low dynamic range and inherent subjectivity, thunder days are invaluable as the only long-term observations of thunderstorm occurrence, with some records stretching back into the nineteenth century. Thunder days, however, are potentially susceptible to false positives, particularly from explosions. Thus one might expect UK thunder days to show anomalously high counts on New Year's Eve and the days around 5 November, Bonfire Night, both of which are celebrated with large firework displays across the country. It is demonstrated that UK Met Office records of thunder days between 1980 and 2010 do not show any significant increase in thunder reporting around 5 November or 31 December. In fact, the days around 5 November exhibit the largest reduction in the amount of reported thunder relative to annual climatology. While meteorological variability cannot be completely ruled out, this result is suggestive of observer bias; it is speculated that human observers, armed with a priori knowledge of the likelihood of false positives, ‘second guess’ themselves to a greater degree around 5 November than the rest of the year. In fact, the data suggest they should trust in their ability to correctly discriminate between thunder and fireworks

Increases in moist-convective updraught velocities with warming in radiative-convective equilibrium

The scaling of updraught velocities over a wide range of surface temperatures is investigated in simulations of radiative-convective equilibrium with a cloud-system resolving model. The updraught velocities increase with warming, with the largest fractional increases occurring in the upper troposphere and for the highest percentile updraughts. A plume model approximately reproduces the increases in updraught velocities if the plume environment is prescribed as the mean profile in each simulation while holding the entrainment and microphysical assumptions fixed. Convective available potential energy (CAPE) also increases with warming in the simulations but at a much faster fractional rate when compared with the square of the updraught velocities. This discrepancy is investigated with a two-plume model in which a weakly entraining plume represents the most intense updraughts, and the environment is assumed to adjust so that a more strongly entraining plume has negligible buoyancy. The two-plume model suggests that updraught velocities increase with warming at a lower fractional rate than implied by the CAPE because of the influence of entrainment on both the mean stratification and the updraughts themselves.National Science Foundation (U.S.) (grant AGS-1148594)United States. National Aeronautics and Space Administration. Research Opportunities in Earth and Space Science (grant 09-IDS09-0049

CAPE Times P Explains Lightning Over Land But Not the Land-Ocean Contrast

The contemporaneous pointwise product of convective available potential energy (CAPE) and precipitation is shown to be a good proxy for lightning. In particular, the CAPE × P proxy for lightning faithfully replicates seasonal maps of lightning over the contiguous United States, as well as the shape, amplitude, and timing of the diurnal cycle in lightning. Globally, CAPE × P correctly predicts the distribution of flash rate densities over land, but it does not predict the pronounced land-ocean contrast in flash rate density; some factor other than CAPE or P is responsible for that land-ocean contrast

Predicting suicides after outpatient mental health visits in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS).

The 2013 US Veterans Administration/Department of Defense Clinical Practice Guidelines (VA/DoD CPG) require comprehensive suicide risk assessments for VA/DoD patients with mental disorders but provide minimal guidance on how to carry out these assessments. Given that clinician-based assessments are not known to be strong predictors of suicide, we investigated whether a precision medicine model using administrative data after outpatient mental health specialty visits could be developed to predict suicides among outpatients. We focused on male nondeployed Regular US Army soldiers because they account for the vast majority of such suicides. Four machine learning classifiers (naive Bayes, random forests, support vector regression and elastic net penalized regression) were explored. Of the Army suicides in 2004-2009, 41.5% occurred among 12.0% of soldiers seen as outpatient by mental health specialists, with risk especially high within 26 weeks of visits. An elastic net classifier with 10-14 predictors optimized sensitivity (45.6% of suicide deaths occurring after the 15% of visits with highest predicted risk). Good model stability was found for a model using 2004-2007 data to predict 2008-2009 suicides, although stability decreased in a model using 2008-2009 data to predict 2010-2012 suicides. The 5% of visits with highest risk included only 0.1% of soldiers (1047.1 suicides/100 000 person-years in the 5 weeks after the visit). This is a high enough concentration of risk to have implications for targeting preventive interventions. An even better model might be developed in the future by including the enriched information on clinician-evaluated suicide risk mandated by the VA/DoD CPG to be recorded