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The Atmospheric Variability Experiment - Severe Environmental Storms and Mesascale Experiment 6 period is described. Data collected, synoptic conditions and severe and unusual weather are discussed.
The present investigation is concerned with the role of remote sensing in the analysis of biochemical cycling. A general review is provided of the interest of NASA in biochemical cycling, taking into account an assessment of the state and dynamics of the pools and fluxes of four major elements (carbon, nitrogen, phosphorus, sulfur), an understanding of the coupling and interaction of the biosphere and the atmosphere, and an understanding of the biosphere and the oceans. Attention is given to biogeochemical cycling science issues, the potential remote sensing role, the vegetation type, aspects of vegetation structure, the leaf area index, the canopy height, functional relationships, environmental and soil variables, questions of experimental design, sampling sites and ground data, and radiometric data and analysis.
In the present probabilistic methodology for the strength of aerospace propulsion system structural components subjected to such environmentally-induced primitive variables as loading stresses, high temperature, chemical corrosion, and radiation, time is encompassed as an interacting element, allowing the projection of creep and fatigue effects. A probabilistic constitutive equation is postulated to account for the degradation of strength due to these primitive variables which may be calibrated by an appropriately curve-fitted least-squares multiple regression of experimental data. The resulting probabilistic constitutive equation is embodied in the PROMISS code for aerospace propulsion component random strength determination.
NASA technical memorandum reviews state of art of use of ion-assisted treatments to coat and otherwise modify surfaces of materials to reduce friction and increase resistance to wear. Focuses upon treatment of materials destined for use in sliding, rolling, rotating, and/or oscillating contact under such severe environmental conditions as variable temperature, ionizing radiation, vacuum, and oxidizing or corrosive atmospheres at high temperatures.
This paper presents the integrated approach toward failure detection, isolation, and recovery/reconfiguration to be used for the Space Station Freedom External Active Thermal Control System (EATCS). The on-board and on-ground diagnostic capabilities of the EATCS are discussed. Time and safety critical features, as well as noncritical failures, and the detection coverage for each provided by existing capabilities are reviewed. The allocation of responsibility between on-board software and ground-based systems, to be shown during ground testing at the Johnson Space Center, is described. Failure isolation capabilities allocated to the ground include some functionality originally found on orbit but moved to the ground to reduce on-board resource requirements. Complex failures requiring the analysis of multiple external variables, such as environmental conditions, heat loads, or station attitude, are also allocated to ground personnel.
This paper adds data to help with the development of possible go-around criteria for transport category aircraft. Presently, airline procedures state that pilots make a go-around decision using multiple criteria at 1000 or 500 ft above the ground, or so-called gates. An experiment conducted on three level-D full-flight simulators investigated the conditions from which pilots cannot successfully recover from an unstable approach and make a normal landing. In addition, pilots' perceptions of risk under these various unstable approach conditions and resulting landings were assessed. Six crews, comprised of a captain and a first officer from the same airline, participated in each simulator. Both the captain and the first officer flew approaches and landings from 55 different initial conditions with varying gate heights, localizer deviations, glideslope deviations, reference-speed deviations, and rate of descents. The initial condition at the starting gate mainly affected longitudinal touchdown deviation and rate of descent at touchdown, with reference-speed deviation having the most significant effect. Results show little difference in touchdown performance for conditions from the 300-ft and 500-ft gates. Conditions at the 100-ft gate introduced significant differences in touchdown performance. Reference-speed and localizer deviation at the starting gate had the strongest influences on perceived risk and go-around decision. In line with other studies, these findings suggest that a 300-ft go-around gate might be acceptable. More research is required to investigate the effects of environmental and runway variables before possible go-around criteria for transport category aircraft can be defined.
This paper discusses a method for delineating and testing hypotheses about the relationship between the retinal images and the three-dimensional visual space they serve. The method may be used under the conditions of changing eye position, occlusion by structures that are part of or are mounted on the observer, occlusions by environmental objects, defects of the visual field, and variables that alter the focus of environmental imagery on the retinas.
A method for performing a probabilistic thermal analysis during aerobraking has been developed. The analysis is performed on the Mars Reconnaissance Orbiter solar array during aerobraking. The methodology makes use of a response surface model derived from a more complex finite element thermal model of the solar array. The response surface is a quadratic equation which calculates the peak temperature for a given orbit drag pass at a specific location on the solar panel. Five different response surface equations are used, one of which predicts the overall maximum solar panel temperature, and the remaining four predict the temperatures of the solar panel thermal sensors. The variables used to define the response surface can be characterized as either environmental, material property, or modeling variables. Response surface variables are statistically varied in a Monte Carlo simulation. The Monte Carlo simulation produces mean temperatures and 3 sigma bounds as well as the probability of exceeding the designated flight allowable temperature for a given orbit. Response surface temperature predictions are compared with the Mars Reconnaissance Orbiter flight temperature data.
Seven atmospheric variability experiments (AVE), two atmospheric variability and severe storms experiments (AVSSE), and six atmospheric variability experiment-severe environmental storm and mesoscale experiments (AVE-SESAME) conducted by NASA are discussed. The dates, observation times, and data reports for each of the experiments for which data was processed are listed. The AVE experiments were conducted primarily to study atmospheric variability with emphasis on spatial and temporal in atmospheric structure that can be detected from soundings taken at 3 hr intervals but not seen in soundings taken at 12 hr intervals. The AVSSE experiments were conducted to study atmospheric structure and variability associated with severe storms combining both rawinsonde and aircraft data to provide information on near storm environments. The method of processing is discussed, estimates of the rms errors in the data are presented, an example of contact data is given, and soundings are listed which exhibited abnormal characteristics.
Ozone (O3) is a greenhouse gas and toxic pollutant which plays a major role in air quality and atmospheric chemistry. The understanding and ability to model the horizontal and vertical structure of O3 mixing ratios is difficult due to the complex formation/destruction processes and transport pathways that cause large variability of O3. The Environmental Protection Agency has National Ambient Air Quality Standards for O3 set at 75 ppb with future standards proposed to be as low as 65 ppb. These lower values emphasize the need to better understand/simulate the transport processes, emission sources, and chemical processes controlling precursor species (e.g., NOx, VOCs, and CO) which influence O3 mixing ratios. The uncertainty of these controlling variables is particularly large in the southeast United States (US) which is a region impacted by multiple different emission sources of precursor species (anthropogenic and biogenic) and transport processes resulting in complex spatio-temporal O3 patterns. During this work we will evaluate O3 and precursor species in the southeast US applying models, ground-based and airborne in situ data, and lidar observations. In the summer of 2013, the UAH O3 Differential Absorption Lidar (DIAL) (part of the Tropospheric Ozone Lidar Network (TOLNet)) measured vertical O3 profiles from the surface up to approximately 12 km. During this period, the lidar observed numerous periods of dynamic temporal and vertical O3 structures. In order to determine the sources/processes impacting these O3 mixing ratios we will apply the CTM GEOS-Chem (v9-02) at a 0.25 deg x 0.3125 deg resolution. Using in situ ground-based (e.g., SEARCH Network, CASTNET), airborne (e.g., NOAA WP-3D - SENEX 2013, DC-8 - SEAC4RS), and TOLNet lidar data we will first evaluate the model to determine the capability of GEOS-Chem to simulate the spatio-temporal variability of O3 in the southeast US. Secondly, we will perform model sensitivity studies in order to quantify which emission sources (e.g., anthropogenic, biogenic, lighting, wildfire) and transport processes (e.g., stratospheric, long-range, local scale) are contributing to these TOLNet-observed dynamic O3 patterns. Results from the evaluation of the model and the study of sources/processes impacting observed O3 mixing ratios will be presented.
The author has identified the following significant results. Least squares techniques were applied for parameter estimation of functions to predict winter wheat phenological stage with daily maximum temperature, minimum temperature, daylength, and precipitation as independent variables. After parameter estimation, tests were conducted using independent data. It may generally be concluded that exponential functions have little advantage over polynomials. Precipitation was not found to significantly affect the fits. The Robertson triquadratic form, in general use for spring wheat, yielded good results, but special techniques and care are required. In most instances, equations with nonlinear effects were found to yield erratic results when utilized with averaged daily environmental values as independent variables.
To better understand the distribution of soil microbial communities at multiple spatial scales, a survey was conducted to examine the spatial organization of community structure in a wheat field in eastern Virginia (USA). Nearly 200 soil samples were collected at a variety of separation distances ranging from 2.5 cm to 11 m. Whole-community DNA was extracted from each sample, and community structure was compared using amplified fragment length polymorphism (AFLP) DNA fingerprinting. Relative similarity was calculated between each pair of samples and compared using geostatistical variogram analysis to study autocorrelation as a function of separation distance. Spatial autocorrelation was found at scales ranging from 30 cm to more than 6 m, depending on the sampling extent considered. In some locations, up to four different correlation length scales were detected. The presence of nested scales of variability suggests that the environmental factors regulating the development of the communities in this soil may operate at different scales. Kriging was used to generate maps of the spatial organization of communities across the plot, and the results demonstrated that bacterial distributions can be highly structured, even within a habitat that appears relatively homogeneous at the plot and field scale. Different subsets of the microbial community were distributed differently across the plot, and this is thought to be due to the variable response of individual populations to spatial heterogeneity associated with soil properties. c2003 Federation of European Microbiological Societies. Published by Elsevier Science B.V. All rights reserved.
This paper discusses the diverse climate forcings that impact agricultural systems, and contrasts the current paradigm of using global models downscaled to agricultural areas (a top-down approach) with a new paradigm that first assesses the vulnerability of agricultural activities to the spectrum of environmental risk including climate (a bottom-up approach). To illustrate the wide spectrum of climate forcings, regional climate forcings are presented including land-use/land-cover change and the influence of aerosols on radiative and biogeochemical fluxes and cloud/precipitation processes, as well as how these effects can be teleconnected globally. Examples are presented of the vulnerability perspective, along with a small survey of the perceived drought impacts in a local area, in which a wide range of impacts for the same precipitation deficits are found. This example illustrates why agricultural assessments of risk to climate change and variability and of other environmental risks should start with a bottom-up perspective.
The essence of environmental modeling is presented as suited for radiation analysis purposes. The variables of fundamental importance for radiation environmental assessment are discussed. The characterization is performed by dividing modeling into three areas, namely the interplanetary medium, the circumplanetary environment, and the planetary or satellite surface. In the first area, the galactic cosmic rays (GCR) and their modulation by the heliospheric magnetic field as well as and solar particle events (SPE) are considered, in the second area the magnetospheres are taken into account, and in the third area the effect of the planetary environment is also considered. Planetary surfaces and atmospheres are modeled based on results from the most recent targeted spacecraft. The results are coupled with suited visualization techniques and radiation transport models in support of trade studies of health risks for future exploration missions.
Ways to determine the turbulence intensity and the horizontal variability in cirrus clouds have been investigated using FIRE-II aircraft, radiosonde and radar data. Higher turbulence intensities were found within some, but not all, of the neutrally stratified layers. It was also demonstrated that the stability of cirrus layers with high extinction values decrease in time, possibly as a result of radiative destabilization. However, these features could not be directly related to each other in any simple manner. A simple linear relationship was observed between the amount of horizontal variability in the ice water content and its average value. This was also true for the extinction and ice crystal number concentrations. A relationship was also suggested between the variability in cloud depth and the environmental stability across the depth of the cloud layer, which requires further investigation.
The application of remote sensing measurement techniques to scientific questions involving forests is a necessity because of the extent of forests, their variability, and the need to measure their interaction with environmental processes. The synoptic view given by remote sensing data of the extent, variability, and relation to environmental processes involving energy balances, disposition of water, and tree growth in relation to elemental storage of carbon, nitrogen and other essential elements is essential to understanding the forest in a scientific way. The ability to make comparisons in these properties at various intervals allows the determination of process functions and rates where the forest affects environmental properties. The ultimate objective in using these data is to define the extent of the forest and wildland resource, to determine the changes that are occurring in the resource due to utilization by man under conditions of changing market and population demands, and to evaluate the correlated changes occurring in various environmental properties influenced by forest vegetation on a local as well as global scale.
The author has identified the following significant results. After parameter estimation, tests were conducted with variances from the fits, and on independent data. From these tests, it was generally concluded that exponential functions have little advantage over polynomials. Precipitation was not found to significantly affect the fits. The Robertson's triquadratic form, in general use for spring wheat, was found to show promise for winter wheat, but special techniques and care were required for its use. In most instances, equations with nonlinear effects were found to yield erratic results when utilized with daily environmental values as independent variables.
NASA's Marshall Space Flight Center participated with its AVE (Atmospheric Variability Experiment) in a large interagency mesoscale and severe storms experiment identified herein as AVE-SESAME '79 (Atmospheric Variability Experiment-Severe Environmental Storms and Mesoscale Experiment 1979). A primary objective of NASA was to support an effort to acquire carefully edited sets of rawinsonde data during selected severe weather events for use in correlative and diagnostic studies with satellite and radar data obtained at approximately the same times. Data were acquired during six individual 24-h experiments on both the regional and storm scales over a network in the central United States that utilized approximately 20 supplemental rawinsonde sites meshed among 23 standard National Weather Service sites. Included among the six experiments are data obtained between 1200 GMT on April 10 and 1200 GMT on April 11, encompassing the formation and development period for the tornado-producing systems that devastated Wichita Falls, Texas, and other sections of Oklahoma and Texas. The other dates for which data sets are available are April 19-20 and 25-26, May 9-10 and 20-21, and June 7-8, 1979.