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  1. Abstract

    Water vapor supersaturation in clouds is a random variable that drives activation and growth of cloud droplets. The Pi Convection–Cloud Chamber generates a turbulent cloud with a microphysical steady state that can be varied from clean to polluted by adjusting the aerosol injection rate. The supersaturation distribution and its moments, e.g., mean and variance, are investigated for varying cloud microphysical conditions. High-speed and collocated Eulerian measurements of temperature and water vapor concentration are combined to obtain the temporally resolved supersaturation distribution. This allows quantification of the contributions of variances and covariances between water vapor and temperature. Results are consistent with expectations for a convection chamber, with strong correlation between water vapor and temperature; departures from ideal behavior can be explained as resulting from dry regions on the warm boundary, analogous to entrainment. The saturation ratio distribution is measured under conditions that show monotonic increase of liquid water content and decrease of mean droplet diameter with increasing aerosol injection rate. The change in liquid water content is proportional to the change in water vapor concentration between no-cloud and cloudy conditions. Variability in the supersaturation remains even after cloud droplets are formed, and no significant buffering is observed. Results are interpreted in terms of a cloud microphysical Damköhler number (Da), under conditions corresponding to, i.e., the slow-microphysics regime. This implies that clouds with very clean regions, such thatis satisfied, will experience supersaturation fluctuations without them being buffered by cloud droplet growth.

    Significance Statement

    The saturation ratio (humidity) in clouds controls the growth rate and formation of cloud droplets. When air in a turbulent cloud mixes, the humidity varies in space and time throughout the cloud. This is important because it means cloud droplets experience different growth histories, thereby resulting in broader size distributions. It is often assumed that growth and evaporation of cloud droplets buffers out some of the humidity variations. Measuring these variations has been difficult, especially in the field. The purpose of this study is to measure the saturation ratio distribution in clouds with a range of conditions. We measure the in-cloud saturation ratio using a convection cloud chamber with clean to polluted cloud properties. We found in clouds with low concentrations of droplets that the variations in the saturation ratio are not suppressed.

     
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  2. Abstract

    The subgrid-scale (SGS) scalar variance represents the “unmixedness” of the unresolved small scales in large-eddy simulations (LES) of turbulent flows. Supersaturation variance can play an important role in the activation, growth, and evaporation of cloud droplets in a turbulent environment, and therefore efforts are being made to include SGS supersaturation fluctuations in microphysics models. We present results from a priori tests of SGS scalar variance models using data collected in turbulent Rayleigh–Bénard convection in the Michigan Tech Pi chamber for Rayleigh numbers Ra ∼ 108–109. Data from an array of 10 thermistors were spatially filtered and used to calculate the true SGS scalar variance, a scale-similarity model, and a gradient model for dimensionless filter widths ofh/Δ = 25, 14.3, and 10 (wherehis the height of the chamber and Δ is the spatial filter width). The gradient model was found to have fairly low correlations (ρ∼ 0.2), with the most probable values departing significantly from the one-to-one line in joint probability density functions (JPDFs). However, the scale-similarity model was found to have good behavior in JPDFs and was highly correlated (ρ∼ 0.8) with the true SGS variance. Results of the a priori tests were robust across the parameter space considered, with little dependence on Ra andh/Δ. The similarity model, which only requires an additional test filtering operation, is therefore a promising approach for modeling the SGS scalar variance in LES of cloud turbulence and other related flows.

     
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  3. Clinical researchers have identified sensory changes people with age-related cognitive changes, such as dementia and mild cognitive impairment, experience that are different from typical age-related sensory changes. Technology designers and researchers do not yet have an understanding of how these unique sensory changes affect technology use. This work begins to bridge the gap between the clinical knowledge of sensory changes and technology research and design through interviews with people with mild to moderate dementia, mild cognitive impairment, subjective cognitive decline, and healthcare professionals. This extended version of our ASSETS conference paper includes people with a range of age-related cognitive changes describing changes in vision, hearing, speech, dexterity, proprioception, and smell. We discuss each of these sensory changes and ways to leverage optimal modes of sensory interaction for accessible technology use with existing and emerging technologies. Finally, we discuss how accessible sensory stimulation may change across the spectrum of age-related cognitive changes. 
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  4. Background Prior research on health information behaviors of people with dementia has primarily focused on examining the types of information exchanged by people with dementia using various web-based platforms. A previous study investigated the information behaviors of people with dementia within a month of their diagnosis. There is an empirical gap in the literature regarding the evolution of health information needs and behaviors of people with dementia as their condition progresses. Objective Our work primarily investigated the information behaviors of people with dementia who have been living with the condition for several (4 to 26) years. We also aimed to identify their motivations for changing their information behaviors over time. Our primary research questions were as follows: how do people with dementia get informed about their condition, and why do people with dementia seek information about their condition? Methods We adopted an action research approach by including 2 people with dementia as members of our research team. Collaboratively, we conducted 16 remote 1-hour contextual inquiry sessions with people living with mild to moderate dementia. During the study sessions, the first 40 minutes included semistructured interviews with participants concerning their information behaviors, followed by a 20-minute demonstration of their information-seeking strategies. Data from these interviews were analyzed using a constructivist grounded theory approach. Results Participants described their information needs in terms of managing the disrupted physiological, emotional, and social aspects of their lives following a diagnosis of dementia. They used various information behaviors, including active search, ongoing search, monitoring, proxy search, information avoidance, and selective exposure. These information behaviors were not stagnant; however, they were adapted to accommodate the changing circumstances of their dementia and their lives as they worked to re-establish equilibrium to continue to engage in life while living with a degenerative neurological condition. Conclusions Our research revealed the motivations, changing abilities, and chosen strategies of people with dementia in their search for information as their condition evolves. This knowledge can be used to develop and improve person-centered information and support services for people with dementia so that they can more easily re-establish equilibrium and continue to engage in life. 
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  5. Abstract. Microphysical processes are important for the development of clouds and thus Earth's climate. For example, turbulent fluctuations in the water vapor mixing ratio, r, and temperature, T, cause fluctuations in the saturation ratio, S. Because S is the driving factor in the condensational growth of droplets, fluctuations may broaden the cloud droplet size distribution due to individual droplets experiencing different growth rates. The small-scale turbulent fluctuations in the atmosphere that are relevant to cloud droplets are difficult to quantify through field measurements. We investigate these processes in the laboratory using Michigan Tech's Π Chamber. The Π Chamber utilizes Rayleigh–Bénard convection (RBC) to create the turbulent conditions inherent in clouds. In RBC it is common for a large-scale circulation (LSC) to form. As a consequence of the LSC, the temperature field of the chamber is not spatially uniform. In this paper, we characterize the LSC in the Π Chamber and show how it affects the shape of the distributions of r, T, and S. The LSC was found to follow a single roll with an updraft and downdraft along opposing walls of the chamber. Near the updraft (downdraft), the distributions of T and r were positively (negatively) skewed. At each measuring position, S consistently had a negatively skewed distribution, with the downdraft being the most negative. 
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  6. Abstract

    The citizen Continental-America Telescopic Eclipse (CATE) Experiment was a new type of citizen science experiment designed to capture a time sequence of white-light coronal observations during totality from 17:16 to 18:48 UT on 2017 August 21. Using identical instruments the CATE group imaged the inner corona from 1 to 2.1 RSun with 1.″43 pixels at a cadence of 2.1 s. A slow coronal mass ejection (CME) started on the SW limb of the Sun before the total eclipse began. An analysis of CATE data from 17:22 to 17:39 UT maps the spatial distribution of coronal flow velocities from about 1.2 to 2.1 RSun, and shows the CME material accelerates from about 0 to 200 km s−1across this part of the corona. This CME is observed by LASCO C2 at 3.1–13 RSun with a constant speed of 254 km s−1. The CATE and LASCO observations are not fit by either constant acceleration nor spatially uniform velocity change, and so the CME acceleration mechanism must produce variable acceleration in this region of the corona.

     
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