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At least 289 records · Page 16

Statistical Prediction of Solar Particle Event Frequency Based on the Measurements of Recent Solar Cycles for Acute Radiation Risk Analysis

Large solar particle events (SPEs) present significant acute radiation risks to the crew members during extra-vehicular activities (EVAs) or in lightly shielded space vehicles for space missions beyond the protection of the Earth's magnetic field. Acute radiation sickness (ARS) can impair performance and result in failure of the mission. Improved forecasting capability and/or early-warning systems and proper shielding solutions are required to stay within NASA's short-term dose limits. Exactly how to make use of observations of SPEs for predicting occurrence and size is a great challenge, because SPE occurrences themselves are random in nature even though the expected frequency of SPEs is strongly influenced by the time position within the solar activity cycle. Therefore, we developed a probabilistic model approach, where a cumulative expected occurrence curve of SPEs for a typical solar cycle was formed from a non-homogeneous Poisson process model fitted to a database of proton fluence measurements of SPEs that occurred during the past 5 solar cycles (19 - 23) and those of large SPEs identified from impulsive nitrate enhancements in polar ice. From the fitted model, the expected frequency of SPEs was estimated at any given proton fluence threshold (Phi(sub E)) with energy (E) >30 MeV during a defined space mission period. Corresponding Phi(sub E) (E=30, 60, and 100 MeV) fluence distributions were simulated with a random draw from a gamma distribution, and applied for SPE ARS risk analysis for a specific mission period. It has been found that the accurate prediction of deep-seated organ doses was more precisely predicted at high energies, Phi(sub 100), than at lower energies such as Phi(sub 30) or Phi(sub 60), because of the high penetration depth of high energy protons. Estimates of ARS are then described for 90th and 95th percentile events for several mission lengths and for several likely organ dose-rates. The ability to accurately measure high energy protons (50-300 MeV) in real-time is shown to be a crucial issue for crew protection.

Myung-Hee, Y. Kim↗

Implications of Wind-Assisted Aerial Navigation for Titan Mission Planning and Science Exploration

The recent Titan Saturn System Mission (TSSM) proposal incorporates a montgolfiere (hot air balloon) as part of its architecture. Standard montgolfiere balloons generate lift through heating of the atmospheric gases inside the envelope, and use a vent valve for altitude control. A Titan aerobot (robotic aerial vehicle) would have to use radioisotope thermoelectric generators (RTGs) for electric power, and the excess heat generated can be used to provide thermal lift for a montgolfiere. A hybrid montgolfiere design could have propellers mounted on the gondola to generate horizontal thrust; in spite of the unfavorable aerodynamic drag caused by the shape of the balloon, a limited amount of lateral controllability could be achieved. In planning an aerial mission at Titan, it is extremely important to assess how the moon-wide wind field can be used to extend the navigation capabilities of an aerobot and thereby enhance the scientific return of the mission. In this paper we explore what guidance, navigation and control capabilities can be achieved by a vehicle that uses the Titan wind field. The control planning approach is based on passive wind field riding. The aerobot would use vertical control to select wind layers that would lead it towards a predefined science target, adding horizontal propulsion if available. The work presented in this paper is based on aerodynamic models that characterize balloon performance at Titan, and on TitanWRF (Weather Research and Forecasting), a model that incorporates heat convection, circulation, radiation, Titan haze properties, Saturn's tidal forcing, and other planetary phenomena. Our results show that a simple unpropelled montgolfiere without horizontal actuation will be able to reach a broad array of science targets within the constraints of the wind field. The study also indicates that even a small amount of horizontal thrust allows the balloon to reach any area of interest on Titan, and to do so in a fraction of the time needed by the unpropelled balloon. The results show that using the Titan wind field allows an aerobot to significantly extend its scientific reach, and that a montgolfiere (unpropelled or propelled) is a highly desirable architecture that can very significantly enhance the scientific return of a future Titan mission.

aerobot↗

WRF-Chem Simulations of Lightning-NOx Production and Transport in Oklahoma and Colorado Thunderstorms Observed During DC3

The focus of this analysis is on lightning-generated nitrogen oxides (LNOx) and their distribution for two thunderstorms observed during the Deep Convective Clouds and Chemistry (DC3) field campaign in May-June 2012. The Weather Research and Forecasting Chemistry (WRF-Chem) model is used to perform cloud-resolved simulations for the May 29-30 Oklahoma severe convection, which contained one supercell, and the June 6-7 Colorado squall line. Aircraft and ground-based observations (e.g., trace gases, lightning and radar) collected during DC3 are used in comparisons against the model-simulated lightning flashes generated by the flash rate parameterization schemes (FRPSs) incorporated into the model, as well as the model-simulated LNOx predicted in the anvil outflow. Newly generated FRPSs based on DC3 radar observations and Lightning Mapping Array data are implemented in the model, along with previously developed schemes from the literature. The results of these analyses will also be compared between storms to investigate which FRPSs were most appropriate for the two types of convection and to examine the variation in the LNOx production. The simulated LNOx results from WRF-Chem will also be compared against other previously studied mid-latitude thunderstorms.

Lightning↗

Application of Strategic Planning Process with Fleet Level Analysis Methods

The goal of this work is to quantify and characterize the potential system-wide reduction of fuel consumption and corresponding CO2 emissions, resulting from the introduction of N+2 aircraft technologies and concepts into the fleet. Although NASA goals for this timeframe are referenced against a large twin aisle aircraft we consider their application across all vehicle classes of the commercial aircraft fleet, from regional jets to very large aircraft. In this work the authors describe and discuss the formulation and implementation of the fleet assessment by addressing the main analytical components: forecasting, operations allocation, fleet retirement, fleet replacement, and environmental performance modeling.

Mavris, Dimitri N.↗

Performance of Trajectory Models with Wind Uncertainty

Typical aircraft trajectory predictors use wind forecasts but do not account for the forecast uncertainty. A method for generating estimates of wind prediction uncertainty is described and its effect on aircraft trajectory prediction uncertainty is investigated. The procedure for estimating the wind prediction uncertainty relies uses a time-lagged ensemble of weather model forecasts from the hourly updated Rapid Update Cycle (RUC) weather prediction system. Forecast uncertainty is estimated using measures of the spread amongst various RUC time-lagged ensemble forecasts. This proof of concept study illustrates the estimated uncertainty and the actual wind errors, and documents the validity of the assumed ensemble-forecast accuracy relationship. Aircraft trajectory predictions are made using RUC winds with provision for the estimated uncertainty. Results for a set of simulated flights indicate this simple approach effectively translates the wind uncertainty estimate into an aircraft trajectory uncertainty. A key strength of the method is the ability to relate uncertainty to specific weather phenomena (contained in the various ensemble members) allowing identification of regional variations in uncertainty.

Lee, Alan G.↗

Technology Alignment and Portfolio Prioritization (TAPP): Advanced Methods in Strategic Analysis, Technology Forecasting and Long Term Planning for Human Exploration and Operations, Advanced Exploration Systems and Advanced Concepts

The Advanced Concepts Office (ACO) at NASA, Marshall Space Flight Center is expanding its current technology assessment methodologies. ACO is developing a framework called TAPP that uses a variety of methods, such as association mining and rule learning from data mining, structure development using a Technological Innovation System (TIS), and social network modeling to measure structural relationships. The role of ACO is to 1) produce a broad spectrum of ideas and alternatives for a variety of NASA's missions, 2) determine mission architecture feasibility and appropriateness to NASA's strategic plans, and 3) define a project in enough detail to establish an initial baseline capable of meeting mission objectives ACO's role supports the decision­-making process associated with the maturation of concepts for traveling through, living in, and understanding space. ACO performs concept studies and technology assessments to determine the degree of alignment between mission objectives and new technologies. The first step in technology assessment is to identify the current technology maturity in terms of a technology readiness level (TRL). The second step is to determine the difficulty associated with advancing a technology from one state to the next state. NASA has used TRLs since 1970 and ACO formalized them in 1995. The DoD, ESA, Oil & Gas, and DoE have adopted TRLs as a means to assess technology maturity. However, "with the emergence of more complex systems and system of systems, it has been increasingly recognized that TRL assessments have limitations, especially when considering [the] integration of complex systems." When performing the second step in a technology assessment, NASA requires that an Advancement Degree of Difficulty (AD2) method be utilized. NASA has used and developed or used a variety of methods to perform this step: Expert Opinion or Delphi Approach, Value Engineering or Value Stream, Analytical Hierarchy Process (AHP), Technique for the Order of Prioritization by Similarity to Ideal Solution (TOPSIS), and other multi­‐criteria decision-making methods. These methods can be labor-intensive, often contain cognitive or parochial bias, and do not consider the competing prioritization between mission architectures. Strategic Decision-Making (SDM) processes cannot be properly understood unless the context of the technology is understood. This makes assessing technological change particularly challenging due to the relationships "between incumbent technology and the incumbent (innovation) system in relation to the emerging technology and the emerging innovation system." The central idea in technology dynamics is to consider all activities that contribute to the development, diffusion, and use of innovations as system functions. Bergek defines system functions within a TIS to address what is actually happening and has a direct influence on the ultimate performance of the system and technology development. ACO uses similar metrics and is expanding these metrics to account for the structure and context of the technology. At NASA technology and strategy is strongly interrelated. NASA's Strategic Space Technology Investment Plan (SSTIP) prioritizes those technologies essential to the pursuit of NASA's missions and national interests. The SSTIP is strongly coupled with NASA's Technology Roadmaps to provide investment guidance during the next four years, within a twenty-year horizon. This paper discusses the methods ACO is currently developing to better perform technology assessments while taking into consideration Strategic Alignment, Technology Forecasting, and Long Term Planning.

Funaro, Gregory V.↗

Rao-Blackwellization for Adaptive Gaussian Sum Nonlinear Model Propagation

When dealing with imperfect data and general models of dynamic systems, the best estimate is always sought in the presence of uncertainty or unknown parameters. In many cases, as the first attempt, the Extended Kalman filter (EKF) provides sufficient solutions to handling issues arising from nonlinear and non-Gaussian estimation problems. But these issues may lead unacceptable performance and even divergence. In order to accurately capture the nonlinearities of most real-world dynamic systems, advanced filtering methods have been created to reduce filter divergence while enhancing performance. Approaches, such as Gaussian sum filtering, grid based Bayesian methods and particle filters are well-known examples of advanced methods used to represent and recursively reproduce an approximation to the state probability density function (pdf). Some of these filtering methods were conceptually developed years before their widespread uses were realized. Advanced nonlinear filtering methods currently benefit from the computing advancements in computational speeds, memory, and parallel processing. Grid based methods, multiple-model approaches and Gaussian sum filtering are numerical solutions that take advantage of different state coordinates or multiple-model methods that reduced the amount of approximations used. Choosing an efficient grid is very difficult for multi-dimensional state spaces, and oftentimes expensive computations must be done at each point. For the original Gaussian sum filter, a weighted sum of Gaussian density functions approximates the pdf but suffers at the update step for the individual component weight selections. In order to improve upon the original Gaussian sum filter, Ref. [2] introduces a weight update approach at the filter propagation stage instead of the measurement update stage. This weight update is performed by minimizing the integral square difference between the true forecast pdf and its Gaussian sum approximation. By adaptively updating each component weight during the nonlinear propagation stage an approximation of the true pdf can be successfully reconstructed. Particle filtering (PF) methods have gained popularity recently for solving nonlinear estimation problems due to their straightforward approach and the processing capabilities mentioned above. The basic concept behind PF is to represent any pdf as a set of random samples. As the number of samples increases, they will theoretically converge to the exact, equivalent representation of the desired pdf. When the estimated qth moment is needed, the samples are used for its construction allowing further analysis of the pdf characteristics. However, filter performance deteriorates as the dimension of the state vector increases. To overcome this problem Ref. [5] applies a marginalization technique for PF methods, decreasing complexity of the system to one linear and another nonlinear state estimation problem. The marginalization theory was originally developed by Rao and Blackwell independently. According to Ref. [6] it improves any given estimator under every convex loss function. The improvement comes from calculating a conditional expected value, often involving integrating out a supportive statistic. In other words, Rao-Blackwellization allows for smaller but separate computations to be carried out while reaching the main objective of the estimator. In the case of improving an estimator's variance, any supporting statistic can be removed and its variance determined. Next, any other information that dependents on the supporting statistic is found along with its respective variance. A new approach is developed here by utilizing the strengths of the adaptive Gaussian sum propagation in Ref. [2] and a marginalization approach used for PF methods found in Ref. [7]. In the following sections a modified filtering approach is presented based on a special state-space model within nonlinear systems to reduce the dimensionality of the optimization problem in Ref. [2]. First, the adaptive Gaussian sum propagation is explained and then the new marginalized adaptive Gaussian sum propagation is derived. Finally, an example simulation is presented.

state estimation↗

Prediction of Seasonal Climate-induced Variations in Global Food Production

Consumers, including the poor in many countries, are increasingly dependent on food imports and are therefore exposed to variations in yields, production, and export prices in the major food-producing regions of the world. National governments and commercial entities are paying increased attention to the cropping forecasts of major food-exporting countries as well as to their own domestic food production. Given the increased volatility of food markets and the rising incidence of climatic extremes affecting food production, food price spikes may increase in prevalence in future years. Here we present a global assessment of the reliability of crop failure hindcasts for major crops at two lead times derived by linking ensemble seasonal climatic forecasts with statistical crop models. We assessed the reliability of hindcasts (i.e., retrospective forecasts for the past) of crop yield loss relative to the previous year for two lead times. Pre-season yield predictions employ climatic forecasts and have lead times of approximately 3 to 5 months for providing information regarding variations in yields for the coming cropping season. Within-season yield predictions use climatic forecasts with lead times of 1 to 3 months. Pre-season predictions can be of value to national governments and commercial concerns, complemented by subsequent updates from within-season predictions. The latter incorporate information on the most recent climatic data for the upcoming period of reproductive growth. In addition to such predictions, hindcasts using observations from satellites were performed to demonstrate the upper limit of the reliability of crop forecasting.

variations↗

Regional scale simulation of atmospheric structure using VAS data

Investigations with both Subsynoptic Scale Model (SSM) and Limited Area Mesoscale Prediction System (LAMPS) are directed at model static initializations using Visible Infrared Spin Scan Radiometer Atmospheric Sounder (VAS) derived temperatures and moistures and also satellite derived winds. The general approach for each day's case study is similar. A 12-hour control forecast (no satellite data) is made 12Z-OZ, using a radiosonde analysis at 12Z as the initial field. For the satellite data experiments, reanalyses are performed at intermediate times, using VAS soundings or VAS soundings in combination with satellite winds. Forecasts are subsequently made from the reanalysis time(s) to the same validation hour (OZ) as the control forecasts. Comparisons are then made between the control forecast and satellite experiments.

Disk, G.↗

Simulating Microwave and Radar Signals in Severe Weather Conditions

The development of radiative transfer simulators for radar and microwave signals, spanning a range of frequencies from 10 to 800 GHz, is paramount for enhancing weather forecasting accuracy, particularly for severe weather events. These tools facilitate the assimilation of microwave and radar observations into numerical weather prediction models, thereby improving accuracy of weather forecasts. Additionally, they directly simulate radar signals crucial for autonomous vehicle operation, with frequencies commonly used in radar systems such as 24, 74, 77, and 79 GHz. However, these frequencies are susceptible to weather phenomena like severe rain and snow, which can significantly impact vehicle safety and performance. These simulation tools, including radiative transfer simulators, serve a dual purpose. Firstly, they enhance forecasts for severe weather events, contributing to autonomous vehicle safety by providing early warnings and risk assessments. Secondly, they enable the direct simulation of radar signals in autonomous vehicle driving systems, allowing researchers and engineers to evaluate radar system performance under various weather conditions. In addition to the radar signal simulator, this abstract discusses the incorporation of advanced scattering properties developed using the discrete dipole approximation (DDA). The DDA technique enhances scattering calculations for frozen hydrometeors at microwave frequencies, thereby improving the accuracy of radar signal simulations and enabling more accurate assessments of radar system performance in adverse weather conditions. In summary, this abstract explores the development and utilization of comprehensive simulation tools, emphasizing their significance in simulating microwave and radar signals and improving weather forecasts. Special attention is given to the simulation of radar signals at critical frequencies for autonomous vehicle sensing and navigation, addressing challenges posed by severe weather phenomena and their effects on signal propagation and detection

Isaac Moradi↗

Near-Surface Meteorology During the Arctic Summer Cloud Ocean Study (ASCOS): Evaluation of Reanalyses and Global Climate Models.

Atmospheric measurements from the Arctic Summer Cloud Ocean Study (ASCOS) are used to evaluate the performance of three atmospheric reanalyses (European Centre for Medium Range Weather Forecasting (ECMWF)- Interim reanalysis, National Center for Environmental Prediction (NCEP)-National Center for Atmospheric Research (NCAR) reanalysis, and NCEP-DOE (Department of Energy) reanalysis) and two global climate models (CAM5 (Community Atmosphere Model 5) and NASA GISS (Goddard Institute for Space Studies) ModelE2) in simulation of the high Arctic environment. Quantities analyzed include near surface meteorological variables such as temperature, pressure, humidity and winds, surface-based estimates of cloud and precipitation properties, the surface energy budget, and lower atmospheric temperature structure. In general, the models perform well in simulating large-scale dynamical quantities such as pressure and winds. Near-surface temperature and lower atmospheric stability, along with surface energy budget terms, are not as well represented due largely to errors in simulation of cloud occurrence, phase and altitude. Additionally, a development version of CAM5, which features improved handling of cloud macro physics, has demonstrated to improve simulation of cloud properties and liquid water amount. The ASCOS period additionally provides an excellent example of the benefits gained by evaluating individual budget terms, rather than simply evaluating the net end product, with large compensating errors between individual surface energy budget terms that result in the best net energy budget.

surface energy↗

AgRISTARS: Foreign commodity production forecasting. The 1980 US/Canada wheat and barley exploratory experiment

The crop identification procedures used performed were for spring small grains and are conducive to automation. The performance of the machine processing techniques shows a significant improvement over previously evaluated technology; however, the crop calendars require additional development and refinements prior to integration into automated area estimation technology. The integrated technology is capable of producing accurate and consistent spring small grains proportion estimates. Barley proportion estimation technology was not satisfactorily evaluated because LANDSAT sample segment data was not available for high density barley of primary importance in foreign regions and the low density segments examined were not judged to give indicative or unequvocal results. Generally, the spring small grains technology is ready for evaluation in a pilot experiment focusing on sensitivity analysis to a variety of agricultural and meteorological conditions representative of the global environment.

Payne, R. W.↗

Applicability of Satellite Freeze Forecasting and Cold Climate Mapping to the Other Parts of the United States

Tasks performed to determine the value of using GOES satellite thermal imagery to enhance fruit crop production in Michigan are described. An overview is presented of the system developed for image processing and thermal image and surface environmental data bases prepared to assess the physical models developed in Florida. These data bases were used to identify correlations between satellite apparent temperatures patterns and Earth surface factors. Significant freeze events in 1981 and the physical models used to provide a perspective on how Florida models can be applied in the context of the Michigan environment are discussed.

Source record↗

An objective method for forecasting tropical cyclone intensity and motion using Nimbus-5 ESMR measurements and non-satellite derived descriptors

An empirical analysis program, based on finding an optimal representation of the data was applied to 120 observations of 29 1973 and 1974 North Pacific tropical cyclones. Each observation consists of a field of Nimbus-5 Electrically Scanning Microwave Radiometer radiation measurements at 267 grid points covering and surrounding the tropical cyclone plus nine other non-satellite derived discriptors. Forecast algorithms to estimate storm intensity and motion at 12, 24, 48, and 72 hours after each observation were developed using an independent eigen screening analysis. These algorithms were based on best track data. Independent testing of these algorithms showed that the performance of most of these algorithms were better than persistence and the algorithms forecasting 24, 48, and 72 hour maximum wind speed were better than those made operationally by the Joint Typhoon Warning Center for 1973 and 1974 that did not use best track data.

Hunter, H. E.↗

The Multi-Dimensional Nature of Wind Shear Investigations

The impact of air carrier accidents has lead to investigations into the wind shear phenomenon. This report includes such topics as wind shear characterization, aircraft pilot performance in shear conditions, terminology and language development, wind shear forecasting, ground and flight wind shear displays, wind shear data collection and dissemination, and pilot factors associated with wind shear encounters. Some areas which show promise for short term solutions to the wind shear hazards includes: (1) improved gust front warning through ground based sensors; (2) greater pilot awareness of wind shear through improved training; and (3) airborne displays based on groundspeed/airspeed comparisons.

Cox, W. J.↗

Simulation Experiments on the Relative Accuracy of Inferred Atmospheric States from Idealized Wind and Temperature Profiling Systems

The First GARP Global Experiment (FGGE) led to the planning, design and implementation of a global observing system. Technologies as coherent CO2 LIDAR systems and highly sensitive IR detectors offer the potential of more accurate global spaceborne observation systems. The advent of super computers allows general circulation modeling and more sophisticated data analysis schemes. The consideration of advanced spaceborne systems better suited to meet the new emerging requirements are suggested. The Global Weather Experiment provides us with a new baseline to assess data accuracy and forecasting capabilities which is used for study of the incremental performance.

Halem, M.↗

Evaluation of a real-time predictive guidance law for landing VTOL aircraft at sea

A piloted simulation evaluation was conducted to assess the merits of a predictive lull/swell guidance law for landing a vertical takeoff and landing aircraft at sea. Two cases were evaluated. The first was performed by the pilot without the aid of the lull/swell guidance indicator, which indicates a landing opportunity. The second was performed in a similar manner with the aid of the guidance indicator. The pilot was instructed to use the guidance indicator only as a landing aid. The results indicated the pilots were able to visually determine ship lulls and swells prior to landing. However, use of the lull/swell guidance resulted in increased pilot confidence in the existence of a landing opportunity, which resulted in significantly shorter hover waiting times prior to landing. The performance of the lull/swell guidance was conservative, in that it forecast the onset of deck lulls and swells later than the pilot could detect them, but with greater reliability and therefore greater pilot confidence. In no instances did the guidance algorithm predict a false ship lull with which the pilot did not agree.

Paulk, C. H., Jr.↗

Use of ground-based wind profiles in mesoscale forecasting

A brief review is presented of recent uses of ground-based wind profile data in mesoscale forecasting. Some of the applications are in real time, and some are after the fact. Not all of the work mentioned here has been published yet, but references are given wherever possible. As Gage and Balsley (1978) point out, sensitive Doppler radars have been used to examine tropospheric wind profiles since the 1970's. It was not until the early 1980's, however, that the potential contribution of these instruments to operational forecasting and numerical weather prediction became apparent. Profiler winds and radiosonde winds compare favorably, usually within a few m/s in speed and 10 degrees in direction (see Hogg et al., 1983), but the obvious advantage of the profiler is its frequent (hourly or more often) sampling of the same volume. The rawinsonde balloon is launched only twice a day and drifts with the wind. In this paper, I will: (1) mention two operational uses of data from a wind profiling system developed jointly by the Wave Propagation and Aeronomy Laboratories of NOAA; (2) describe a number of displays of these same data on a workstation for mesoscale forecasting developed by the Program for Regional Observing and Forecasting Services (PROFS); and (3) explain some interesting diagnostic calculations performed by meteorologists of the Wave Propagation Laboratory.

Schlatter, Thomas W.↗