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619 records · Page 35

Hypovolemia Induced Orthostatic Hypotension in Presyncopal Astronauts and Normal Subjects Related to Hypoadrenergic Responsiveness

Circulating blood volume is reduced during spaceflight, making astronauts hemodynamically compromised. After landing, astronauts separate into two groups. One group compensates for the hypovolemia with a hyper-sympathetic response during upright tilt testing and can complete a tilt test with few symptoms. The other group is unable to mount a hyper-sympathetic response and experiences orthostatic hypotension and presyncope during upright tilt tests. We tested the hypothesis that hypovolemia alone, in the absence of spaceflight, also would cause subjects to separate into presyncopal and non-presyncopal groups according to their sympathetic responses during tilt. We studied 20 subjects, including 10 veteran astronauts, on three occasions. On Days 1 (normovolemia) and 3 (hypovolemia), plasma volume, tilt tolerance and supine and standing plasma norepinephrine levels were measured. Forty hours prior to Day 3, subjects were given intravenous furosemide, followed by 36 hours of a 10MEq Na diet. Statistical comparisons were made between normovolemia and hypovolemia responses. This protocol reproduced landing day tilt test outcomes with 100% fidelity in the astronauts. Similarly to patterns reported after flight, non-presyncopal subjects had greater norepinephrine responses to tilt during hypovolemia compared to normovolemia (580 plus or minus 79 vs. 298 plus or minus 37 pg/ml, P less than 0.05), but presyncopal subjects had no increase (180 plus or minus 44 vs. 145 plus or minus 32 pg/ml, P=NS). This model can be used to predict astronauts who will become presyncopal on landing day, so that prospective, individualized countermeasures can be developed. Within patient populations, it can be used to study the interaction of volemic state and the sympathetic nervous system.

Meck, Janice V.↗

Orthostatic stress is necessary to maintain the dynamic range of cardiovascular control in space

In the upright position, gravity fills the low-pressure systems of human circulation with blood and interstitial fluid in the sections below the diaphragm. Without gravity one pressure component in the vessels disappears and the relationship between hydrostatic pressure and oncotic pressure, which regulates fluid passage across the capillary endothelium in the terminal vascular bed, shifts constantly. The visible consequences of this are a puffy face and "bird" legs. The plasma volume shrinks in space and the range of cardiovascular control is reduced. When they stand up for the first time after landing, 30-50% of astronauts suffer from orthostatic intolerance. It remains unclear whether microgravity impairs cardiovascular reflexes, or whether it is the altered volume status that causes the cardiovascular instability following space flight. Lower body negative pressure was used in several space missions to stimulate the cardiovascular reflexes before, during and after a space flight. The results show that cardiovascular reflexes are maintained in microgravity. However, the astronauts' volume status changed in space, towards a volume-retracted state, as measurements of fluid-regulating hormones have shown. It can be hypothesized that the control of circulation and body fluid homeostasis in humans is adapted to their upright posture in the Earth's gravitational field. Autonomic control regulates fluid distribution to maintain the blood pressure in that posture, which most of us have to cope with for two-thirds of the day. A determined amount of interstitial volume is necessary to maintain the dynamic range of cardiovascular control in the upright posture; otherwise orthostatic intolerance may occur more often.

manned↗

Using Clustering to Establish Climate Regimes from PCM Output

A multivariate statistical clustering technique--based on the k-means algorithm of Hartigan has been used to extract patterns of climatological significance from 200 years of general circulation model (GCM) output. Originally developed and implemented on a Beowulf-style parallel computer constructed by Hoffman and Hargrove from surplus commodity desktop PCs, the high performance parallel clustering algorithm was previously applied to the derivation of ecoregions from map stacks of 9 and 25 geophysical conditions or variables for the conterminous U.S. at a resolution of 1 sq km. Now applied both across space and through time, the clustering technique yields temporally-varying climate regimes predicted by transient runs of the Parallel Climate Model (PCM). Using a business-as-usual (BAU) scenario and clustering four fields of significance to the global water cycle (surface temperature, precipitation, soil moisture, and snow depth) from 1871 through 2098, the authors' analysis shows an increase in spatial area occupied by the cluster or climate regime which typifies desert regions (i.e., an increase in desertification) and a decrease in the spatial area occupied by the climate regime typifying winter-time high latitude perma-frost regions. The patterns of cluster changes have been analyzed to understand the predicted variability in the water cycle on global and continental scales. In addition, representative climate regimes were determined by taking three 10-year averages of the fields 100 years apart for northern hemisphere winter (December, January, and February) and summer (June, July, and August). The result is global maps of typical seasonal climate regimes for 100 years in the past, for the present, and for 100 years into the future. Using three-dimensional data or phase space representations of these climate regimes (i.e., the cluster centroids), the authors demonstrate the portion of this phase space occupied by the land surface at all points in space and time. Any single spot on the globe will exist in one of these climate regimes at any single point in time. By incrementing time, that same spot will trace out a trajectory or orbit between and among these climate regimes (or atmospheric states) in phase (or state) space. When a geographic region enters a state it never previously visited, a climatic change is said to have occurred. Tracing out the entire trajectory of a single spot on the globe yields a 'manifold' in state space representing the shape of its predicted climate occupancy. This sort of analysis enables a researcher to more easily grasp the multivariate behavior of the climate system.

Oglesby, Robert↗

Climate projections over the Great Lakes Region: using two-way coupling of a regional climate model with a 3-D lake model

Abstract. Warming trends in the Laurentian Great Lakes and surrounding areas have been observed in recent decades, and concerns continue to rise about the pace and pattern of future climate change over the world's largest freshwater system. To date, most regional climate models used for Great Lakes projections either neglected the lake-atmosphere interactions or are only coupled with a 1-D column lake model to represent the lake hydrodynamics. This study presents a Great Lakes climate change projection that has employed the two-way coupling of a regional climate model with a 3-D lake model (GLARM) to resolve 3-D hydrodynamics essential for large lakes. Using the three carefully selected Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCMs), we show that the GLARM ensemble average substantially reduces surface air temperature and precipitation biases of the driving GCM ensemble average in present-day climate simulations. The improvements are not only displayed from an atmospheric perspective but are also evident in the accurate simulations of lake temperature and ice coverage. We further present the GLARM projected climate change for the mid-21st century (2030–2049) and the late 21st century (2080–2099) in the Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 scenarios. Under RCP 8.5, the Great Lakes basin is projected to warm by 1.3–2.1 ∘C by the mid-21st century and 4.1–5.0 ∘C by the end of the century relative to the early century (2000–2019). Moderate mitigation (RCP 4.5) reduces the mid-century warming to 0.8–1.8 ∘C and late-century warming to 1.8–2.7 ∘C. Annual precipitation in GLARM is projected to increase for the entire basin, varying from 0 % to 13 % during the mid-century and from 9 % to 32 % during the late century in different scenarios and simulations. The most significant increases are projected in spring and fall when current precipitation is highest and a minimal increase in winter when it is lowest. Lake surface temperatures (LSTs) are also projected to increase across the five lakes in all of the simulations, but with strong seasonal and spatial variability. The most significant LST increases occur in Lakes Superior and Ontario. The strongest warming is projected in spring that persists into the summer, resulting from earlier and more intense stratification in the future. In addition, diminishing winter stratification in the future suggests the transition from dimictic lakes to monomictic lakes by the end of the century. In contrast, a relatively smaller increase in LSTs during fall and winter is projected with heat transfer to the deep water due to the strong mixing and energy required for ice melting. Correspondingly, the highest monthly mean ice cover is projected to reduce to 3 %–15 % and 10 %–40 % across the lakes by the end of the century in RCP 8.5 and RCP 4.5, respectively. In the coastal regions, ice duration is projected to decrease by up to 60 d.

Xue, Pengfei (ORCID:000000025702421X)↗

The Martian Dust Cycle: Observations and Modeling

The dust cycle is critically important for Mars' current climate system. Suspended atmospheric dust affects the radiative balance of the atmosphere, and thus greatly influences the thermal and dynamical state of the atmosphere. Evidence for the presence of dust in the Martian atmosphere can be traced back to yellow clouds telescopically observed as early as the early 19th century. The Mariner 9 orbiter arrived at Mars in November of 1971 to find a planet completely enshrouded in airborne dust. Since that time, the exchange of dust between the planet's surface and atmosphere and the role of airborne dust on Mars' weather and climate has been studied using observations and numerical models. The goal of this talk is to give an overview of the observations and to discuss the successes and challenges associated with modeling the dust cycle. Dust raising events on Mars range in size from meters to hundreds of kilometers. During some years, regional storms merge to produce hemispheric or planet encircling dust clouds that obscure the surface and raise atmospheric temperatures by tens of kelvin. The interannual variability of planet encircling dust storms is poorly understood. Although the occurrence and season of large regional and global dust storms are highly variable from one year to the next, there are many features of the dust cycle that occur year after year. A low-level dust haze is maintained during northern spring and summer, while elevated levels of atmospheric dust occur during northern autumn and winter. During years without global-scale dust storms, two peaks in total dust loading are generally observed: one peak occurs before northern winter solstice and one peak occurs after northern winter solstice. Numerical modeling studies attempting to interactively simulate the Martian dust cycle with general circulation models (GCMs) include the lifting, transport, and sedimentation of radiatively active dust. Two dust lifting processes are commonly represented in these models: wind-stress lifting (i.e., saltation) and dust devil lifting. Although the predicted patterns of dust lifting and atmospheric dust loading from these simulations capture some aspects of the observed dust cycle, there are many notable differences between the simulated and observed dust cycles. For example, it is common for models to predict one peak in global dust loading near northern winter solstice due to excessive dust lifting in the Hellas basin at this season. Additionally, it is difficult for models to realistically capture the observed interannual variability in global dust storms. New avenues of dust cycle modeling research include exploring the effects of finite surface dust reservoirs and the effects of coupling the dust and water cycles on the predicted dust cycle.

Kahre, Melinda A.↗

Utilizing Advanced Statistics to Determine Anomalistic Conditions in Pebble-Bed Reactors

Pebble-bed reactors (PBRs) utilize hundreds of thousands of fuel pebbles, which continuously circulate through the core, in lieu of traditional fuel assemblies to generate fissions and produce power. The use of unmarked fuel pebbles presents a challenge for international safeguards verification that nuclear material is not being diverted. To ensure pebble diversion is not taking place, new methods for accounting for and monitoring the pebbles should be examined to determine an appropriate methodology for performing bulk accountancy with pebbles. Here, this work examines the use of statistical methods for determining if the reactor is within a declared range of operation by examining the statistical distribution of pebble burnup as they are discharged from the core. Using this methodology, we created a model that detects diversion over 95% of the time, over multiple diversion pathways, if the reactor core maintains a constant power density during the diversion process and only falsely labels a diversion case nominal 2% of the time. For a diversion scenario where the reactor is maintained at a constant power, the statistical analysis can correctly identify if diversion is occurring over 80% of the time; however, nearly 20% of specific diversion pathways are mislabeled nominal. These results provide a basis and framework for exploring the further use of statistical methods to determine where these methods could be most useful and where additional methods, such as machine learning, could be used to capture if diversion is occurring in pebble-bed reactors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Characterization of oceanic post-cold frontal clouds and their model representation. Final report

Low-level clouds are ubiquitous over the oceans, and their impact on the Earth’ radiative budget is important. However, general circulation models (GCMs) that are used to represent our climate and its evolution still experience problems to represent their correct amount and radiative impact. In the extratropical latitudes (~30-60 N/S), cloud properties are strongly modulated by the occurrence of anti-cyclones (high pressure systems) and cyclones (low pressure systems). While deep clouds dominate in cyclones near the center and along the cold and warm fronts, low-level clouds populate the colder regions of the cyclones, and more specifically the region in the wake of the cold fronts, the post-cold frontal region (PCF). The GCMs mentioned above were found to underestimate the amount of these PCF clouds, and this caused errors in their representation of the amount of solar radiation at the surface of the southern hemisphere oceans, causing an excess in absorption and errors in long-term predictions. To better understand which processes are ill-represented in the GCMs to cause such issues, we used ground-based observations from the Eastern North Atlantic (ENA) ARM site and a high resolution regional model (called WRF) to examine the properties of PCF clouds. With the WRF model, we simulated the passage of a cold front at the ENA site using theoretically distinct representations of convection and the physics of the boundary layer. While these physical representations had little impact on the timing, structure and circulation of the cold front, we found a high sensitivity to how the large scale information was fed into the model. Errors rapidly developed if the incoming flow information was injected too far from the site, but 1000 km was found to be an optimal distance between the outer boundary and the ENA site for a realistic cold front passage. With this model, we then conducted a series of experiment where convection and boundary layer schemes were changed, and revealed that 1) the clouds were more sensitive to the convection than boundary layer schemes and 2) the interaction between the two has a large impact. Furthermore, changing the representation of the physics in the model had greater impacts on PCF clouds than changing the initial conditions. As large-scale models increase their spatial resolution, convection will eventually be resolved but it remains that their representation of the physics of the boundary layer will matter for the correct representation of shallow (low-level) clouds. Observations were used to find which large-scale information had a clear relationship with PCF cloud and precipitation properties, in view of helping with GCM parameterizations and evaluation. Both lower troposphere stability and surface forcing were found to be important for PCF clouds that experience more vigorous dynamics than their tropical or subtropical counterparts. For cloud base and top heights, a simple measure of the change in potential temperature between the surface and the 800 hPa was found to be a good predictor. This relationship was found to hold as well when using data from campaigns recently conducted in the southern ocean south of Tasmania. A recent GCM was found to succeed in representing similar relations. For cloud depth, water content, and different characteristics of precipitation both the temperature contrast between the surface and near-air and the near-surface wind speed had a strong relationship. To summarize, through observational constraints and regional model experiments, the project has provided guidance to evaluate GCMs and tools to improve their representation of low-level clouds in the extratropics. It has also highlighted differences in behavior between these clouds and those typically found in the subtropics, thus opening new avenues of research for shallow clouds in general.

54 ENVIRONMENTAL SCIENCES↗