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At least 217 records · Page 12

Application of engineering codes to the assessment of spacecraft charging induced hazards

One of the major hurdles to developing a better understanding of the environmentally induced interactions in spacecraft systems (spacecraft charging) is the lack of simple tools to analyze the behavior of the spacecraft in a sub-storm environment. The available tool, NASA Charging Analyzer Program (NASCAP), is expensive to use and treats only half of the problem - surface effects only. In response to this need, we have developed, under our IRAD Program, a set of engineering tools that operate on personal computers and addresses both the surface and bulk charging aspects of the interactions. These engineering codes utilize circuit analysis techniques and model simplifications to allow rapid computations. The codes were compared to both NASCAP predictions and to bulk charging data with excellent agreement for both phenomena. The models used in our engineering codes are shown, and in the engineering codes, the models are defined in terms of plates or triangles in an unconfined space. The predictions are based upon current balances to each plate. The code has routines to allow interactions between the plates to simulate 'barrier' effects. The agreement for the predicted differential surface voltages for the model is given. In conducting the comparison of engineering codes to NASCAP predictions, it was found that some inconsistencies existed in the NASCAP code that are not obvious to the user. The use of the grid imposes constraints that voltage gradients exist between the grid points. This allows the existence of voltage gradients in conductors and influences surface resistivity predictions. These points are discussed along with the predictions for treating these inconsistencies properly. The model predictions for a variable intensity substorm is also presented.

Stevens, N. J.↗

The upper bounds of reduced axial and shear moduli in cross-ply laminates with matrix cracks

The present study proposes a mathematical model utilizing the internal state variable concept for predicting the upper bounds of the reduced axial and shear stiffnesses in cross-ply laminates with matrix cracks. The displacement components at the matrix crack surfaces are explicitly expressed in terms of the observable axial and shear strains and the undamaged material properties. The reduced axial and shear stiffnesses are predicted for glass/epoxy and graphite/epoxy laminates. Comparison of the model with other theoretical and experimental studies is also presented to confirm direct applicability of the model to angle-ply laminates with matrix cracks subjected to general in-plane loading.

Lee, Jong-Won↗

Analysis of a general circulation model. II - Distribution of kinetic energy in the South Atlantic and Kuroshio/Oyashio systems

It was found (Garzoli et al., 1992) that the general circulation model of Semtner and Chervin (1992) provides accurate descriptions of the Brazil-Malvinas and the Kuroshio/Oyashio confluence systems, except for the fact that the model prediction shows less variability than that present in observations. This paper investigates the problem of model variability by analyzing the mean and the eddy kinetic energy from the model and comparing the values with the Geosat altimeter observations for the South Atlantic Ocean and for the Kuroshio system. It is found that, while the model shows transient eddy activity in the areas that overlap the Geosat observations, the energy level of the model transient motions is considerably smaller following an arch along the bottom topography. The same was found from the comparisons made with values obtained from FGGE and surface drifters. It is suggested that the model is poorly resolving instabilities in the confluence front, and is not resolving other transients appearing in regions of marked topography.

Garraffo, Zulema↗

An outflow boundary condition for aeroacoustic computations

A formulation of boundary condition for flows with small disturbances is presented. The authors test their methodology in an axisymmetric jet flow calculation, using both the Navier-Stokes and Euler equations. Solutions in the far field are assumed to be oscillatory. If the oscillatory disturbances are small, the growth of the solution variables can be predicted by linear theory. Eigenfunctions of the linear theory are used explicitly in the formulation of the boundary conditions. This guarantees correct solutions at the boundary in the limit where the predictions of linear theory are valid.

Hayder, M. Ehtesham↗

Climate Change and a Global City: An Assessment of the Metropolitan East Coast Region

The objective of the research is to derive an assessment of the potential climate change impacts on a global city - in this case the 31 county region that comprises the New York City metropolitan area. This study comprises one of the regional components that contribute to the ongoing U.S. National Assessment: The Potential Consequences of Climate Variability and Change and is an application of state-of-the-art climate change science to a set of linked sectoral assessment analyses for the Metro East Coast (MEC) region. We illustrate how three interacting elements of global cities react and respond to climate variability and change with a broad conceptual model. These elements include: people (e.g., socio- demographic conditions), place (e.g., physical systems), and pulse (e.g., decision-making and economic activities). The model assumes that a comprehensive assessment of potential climate change can be derived from examining the impacts within each of these elements and at their intersections. Thus, the assessment attempts to determine the within-element and the inter-element effects. Five interacting sector studies representing the three intersecting elements are evaluated. They include the Coastal Zone, Infrastructure, Water Supply, Public Health, and Institutional Decision-making. Each study assesses potential climate change impacts on the sector and on the intersecting elements, through the analysis of the following parts: 1. Current conditions of sector in the region; 2. Lessons and evidence derived from past climate variability; 3. Scenario predictions affecting sector; potential impacts of scenario predictions; 4. Knowledge/information gaps and critical issues including identification of additional research questions, effectiveness of modeling efforts, equity of impacts, potential non-local interactions, and policy recommendations; and 5. Identification of coping strategies - i.e., resilience building, mitigation strategies, new technologies, education that affects decision-making, and better preparedness for contingencies.

Rosenzweig, Cynthia↗

Cycle 2 Nonlinear Design Optimization Analytical Cross Checks

The objectives of the Cycle 2 Nonlinear Design Optimization Anlaytical Cross Checks are to: 1) Understand the variability in the predicted performance levels of the nonlinear designs arising from the use of different inviscid (full potential/Euler) and viscous (Navier-Stokes) analysis methods; and 2) Provide the information required to allow the performance levels of all three designs to be validated using the data from the NCV (nonlinear Cruise Validation) model test.

Bencze, Dan↗

A Start Toward Micronucleus-Based Decompression Models; Altitude Decompression

Do gaseous micronuclei trigger the formation of bubbles in decompression sickness (DCS)? Most previous instructions for DCS prevention have been oriented toward supersaturated gas in tissue. We are developing a mathematical model that is oriented toward the expected behavior of micronuclei. The issue is simplified in altitude decompressions because the aviator or astronaut is exposed only to decompression, whereas in diving there is a compression before the decompression. The model deals with four variables: duration of breathing of 100% oxygen before going to altitude (O2 prebreathing), altitude of the exposure, exposure duration, and rate of ascent. Assumptions: a) there is a population of micronuclei of various sizes having a range of characteristics, b) micronuclei are stable until they grow to a certain critical nucleation radius, c) it takes time for gas to diffuse in or out of micronuclei, and d) all other variables being equal, growth of micronuclei upon decompression is more rapid at high altitude because of the rarified gas in the micronuclei. To estimate parameters, we use a dataset of 4,756 men in altitude chambers exposed to various combinations of the model s variables. The model predicts occurrence of DCS symptoms quite well. It is notable that both the altitude chamber data and the model show little effect of O2 prebreathing until it lasts more than 60 minutes; this is in contrast to a conventional idea that the benefit of prebreathing is directly due to exponential washout of tissue nitrogen. The delay in response to O2 prebreathing can be interpreted as time required for outward diffusion of nitrogen; when the micronuclei become small enough, they are disabled, either by crushing or because they cannot expand to a critical nucleation size when the subject ascends to altitude.

Van Liew, H. D.↗

Drought Predictability and Prediction in a Changing Climate: Assessing Current Predictive Knowledge and Capabilities, User Requirements and Research Priorities

Drought is fundamentally the result of an extended period of reduced precipitation lasting anywhere from a few weeks to decades and even longer. As such, addressing drought predictability and prediction in a changing climate requires foremost that we make progress on the ability to predict precipitation anomalies on subseasonal and longer time scales. From the perspective of the users of drought forecasts and information, drought is however most directly viewed through its impacts (e.g., on soil moisture, streamflow, crop yields). As such, the question of the predictability of drought must extend to those quantities as well. In order to make progress on these issues, the WCRP drought information group (DIG), with the support of WCRP, the Catalan Institute of Climate Sciences, the La Caixa Foundation, the National Aeronautics and Space Administration, the National Oceanic and Atmospheric Administration, and the National Science Foundation, has organized a workshop to focus on: 1. User requirements for drought prediction information on sub-seasonal to centennial time scales 2. Current understanding of the mechanisms and predictability of drought on sub-seasonal to centennial time scales 3. Current drought prediction/projection capabilities on sub-seasonal to centennial time scales 4. Advancing regional drought prediction capabilities for variables and scales most relevant to user needs on sub-seasonal to centennial time scales. This introductory talk provides an overview of these goals, and outlines the occurrence and mechanisms of drought world-wide.

Schubert, Siegfried↗

Seasonal and Non-Seasonal Variations of Jupiter's Atmosphere from Observations of Thermal Emission, 1994-2011

We analyzed mid-infrared images of Jupiter's thermal emission, covering approx.1.5 Jovian years, acquired in discrete filters between 7.8 and 24.5 microns. The behavior of stratospheric (approx.10-mbar) and tropospheric (approx.100-400 mbar) temperatures is generally consistent with predictions of seasonal variability, with differences between 100-mbar temperatures +/-50-60deg from the equator on the order of +/-2. Removing this effect, there appear to be long-term quasi-periodic variability of tropospheric temperatures, whose amplitude, phase and period depend on latitude. The behavior of temperatures in the Equatorial Zone (EZ) suggests a approx.4-6-year period with amplitude of about +/-1-1.5 K in temperature. At mid-latitudes, the periodicity is more distinct with amplitudes around +/-1.5-2.5 K and 4-8 year periods. The 4.2-year variation of stratospheric temperatures known as the quasiquadrennial oscillation or "QQO" (Leovy et al. 1991, Nature 354, 380) continued during this period. There were no variations of zonal mean temperatures associated with any of the "global upheaval" events that have produced dramatic changes of jupiter's visible appearance and cloud cover, although there are colder discrete regions associated with updrafts, e.g. the early stages of the re-darkening ("revival") of the South Equatorial Belt (SEB) in late 2010. On the other hand increases in the visible albedos ("fades") of belts are accompanied by increases in the thickness of a 700-mbar cloud layer (most likely NH3 ice) and clouds at higher pressures, together with the mixing ratio of NH3 gas near 400 mbar (above its condensation level). These quantities decrease during re-darkening ("revival") episodes, during which we note discrete features that are exceptions to the general correlation between dark albedos and minimal cloudiness. In contrast to all these changes, the meridional distribution of the 240-mbar para-H2 fraction appears to be invariant in time.

Orton, G.↗

Assimilation of SMOS Soil Moisture Retrievals in the Land Information System

Soil moisture is a crucial variable for weather prediction because of its influence on evaporation. It is of critical importance for drought and flood monitoring and prediction and for public health applications. The NASA Short-term Prediction Research and Transition Center (SPoRT) has implemented a new module in the NASA Land Information System (LIS) to assimilate observations from the ESA's Soil Moisture and Ocean Salinity (SMOS) satellite. SMOS Level 2 retrievals from the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) instrument are assimilated into the Noah LSM within LIS via an Ensemble Kalman Filter. The retrievals have a target volumetric accuracy of 4% at a resolution of 35-50 km. Parallel runs with and without SMOS assimilation are performed with precipitation forcing from intentionally degraded observations, and then validated against a model run using the best available precipitation data, as well as against selected station observations. The goal is to demonstrate how SMOS data assimilation can improve modeled soil states in the absence of dense rain gauge and radar networks.

Blankenship, Clay↗

Assimilation of SMOS Soil Moisture Retrievals in the Land Information System

Soil moisture is a crucial variable for weather prediction because of its influence on evaporation. It is of critical importance for drought and flood monitoring and prediction and for public health applications. The NASA Short-term Prediction Research and Transition Center (SPoRT) has implemented a new module in the NASA Land Information System (LIS) to assimilate observations from the ESA's Soil Moisture and Ocean Salinity (SMOS) satellite. SMOS Level 2 retrievals from the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) instrument are assimilated into the Noah LSM within LIS via an Ensemble Kalman Filter. The retrievals have a target volumetric accuracy of 4% at a resolution of 35-50 km. Parallel runs with and without SMOS assimilation are performed with precipitation forcing from intentionally degraded observations, and then validated against a model run using the best available precipitation data, as well as against selected station observations. The goal is to demonstrate how SMOS data assimilation can improve modeled soil states in the absence of dense rain gauge and radar networks.

Blakenship, Clay↗

Assimilation of SMOS Retrieved Soil Moisture into the Land Information System

Soil moisture is a crucial variable for weather prediction because of its influence on evaporation and surface heat fluxes. It is also of critical importance for drought and flood monitoring and prediction and for public health applications such as monitoring vector-borne diseases. Land surface modeling benefits greatly from regular updates with soil moisture observations via data assimilation. Satellite remote sensing is the only practical observation type for this purpose in most areas due to its worldwide coverage. The newest operational satellite sensor for soil moisture is the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) instrument aboard the Soil Moisture and Ocean Salinity (SMOS) satellite. The NASA Short-term Prediction Research and Transition Center (SPoRT) has implemented the assimilation of SMOS soil moisture observations into the NASA Land Information System (LIS), an integrated modeling and data assimilation software platform. We present results from assimilating SMOS observations into the Noah 3.2 land surface model within LIS. The SMOS MIRAS is an L-band radiometer launched by the European Space Agency in 2009, from which we assimilate Level 2 retrievals [1] into LIS-Noah. The measurements are sensitive to soil moisture concentration in roughly the top 2.5 cm of soil. The retrievals have a target volumetric accuracy of 4% at a resolution of 35-50 km. Sensitivity is reduced where precipitation, snowcover, frozen soil, or dense vegetation is present. Due to the satellite's polar orbit, the instrument achieves global coverage twice daily at most mid- and low-latitude locations, with only small gaps between swaths.

Blankenship, Clay B.↗

Assessing the Impact of Pre-gpm Microwave Precipitation Observations in the Goddard WRF Ensemble Data Assimilation System

The forthcoming Global Precipitation Measurement (GPM) Mission will provide next generation precipitation observations from a constellation of satellites. Since precipitation by nature has large variability and low predictability at cloud-resolving scales, the impact of precipitation data on the skills of mesoscale numerical weather prediction (NWP) is largely affected by the characterization of background and observation errors and the representation of nonlinear cloud/precipitation physics in an NWP data assimilation system. We present a data impact study on the assimilation of precipitation-affected microwave (MW) radiances from a pre-GPM satellite constellation using the Goddard WRF Ensemble Data Assimilation System (Goddard WRF-EDAS). A series of assimilation experiments are carried out in a Weather Research Forecast (WRF) model domain of 9 km resolution in western Europe. Sensitivities to observation error specifications, background error covariance estimated from ensemble forecasts with different ensemble sizes, and MW channel selections are examined through single-observation assimilation experiments. An empirical bias correction for precipitation-affected MW radiances is developed based on the statistics of radiance innovations in rainy areas. The data impact is assessed by full data assimilation cycling experiments for a storm event that occurred in France in September 2010. Results show that the assimilation of MW precipitation observations from a satellite constellation mimicking GPM has a positive impact on the accumulated rain forecasts verified with surface radar rain estimates. The case-study on a convective storm also reveals that the accuracy of ensemble-based background error covariance is limited by sampling errors and model errors such as precipitation displacement and unresolved convective scale instability.

microwave observations↗

Large-Scale and Global Hydrology

Powered by the sun, water moves continuously between and through Earths oceanic, atmospheric, and terrestrial reservoirs. It enables life, shapes Earths surface, and responds to and influences climate change. Scientists measure various features of the water cycle using a combination of ground, airborne, and space-based observations, and seek to characterize it at multiple scales with the aid of numerical models. Over time our understanding of the water cycle and ability to quantify it have improved, owing to advances in observational capabilities, the extension of the data record, and increases in computing power and storage. Here we present some of the most recent estimates of global and continental ocean basin scale water cycle stocks and fluxes and provide examples of modern numerical modeling systems and reanalyses.Further, we discuss prospects for predicting water cycle variability at seasonal and longer scales, which is complicated by a changing climate and direct human impacts related to water management and agriculture. Changes to the water cycle will be among the most obvious and important facets of climate change, thus it is crucial that we continue to invest in our ability to monitor it.

land hydrology↗

Characterization of Volatiles Loss from Soil Samples at Lunar Environments

Resource Prospector Integrated Thermal Vacuum Test Program A series of ground based dirty thermal vacuum tests are being conducted to better understand the subsurface sampling operations for RP Volatiles loss during sampling operations Hardware performance Sample removal and transfer Concept of operationsInstrumentation5 test campaigns over 5 years have been conducted with RP hardware with advancing hardware designs and additional RP subsystems Volatiles sampling 4 years Using flight-forward regolith sampling hardware, empirically determine volatile retention at lunar-relevant conditions Use data to improve theoretical predictions Determine driving variables for retention Bound water loss potential to define measurement uncertainties. The main goal of this talk is to introduce you to our approach to characterizing volatiles loss for RP. Introduce the facility and its capabilities Overview of the RP hardware used in integrated testing (most recent iteration) Summarize the test variables used thus farReview a sample of the results.

In Situ Resource Utilization↗

Adaptive Antenna Pattern Notching of Interference in Synthetic Aperture Radar Data Using Digital Beamforming

Radio Frequency Interference (RFI) is a growing problem in Synthetic Aperture Radar (SAR)systems as scientific motivations push the radars to lower frequencies and as more wireless services share the frequency spectrum. New, advanced SAR instruments, such as NASA's EcoSAR, DBSAR and DLR's Tandem-L mission, employ a multichannel architecture capable of Digital Beamforming (DBF). Radars with DBF are capable of notching the antenna pattern in specific directions, which can be utilized to suppress RFI on board or in post-processing. A well-researched beamformer for this purpose is the Minimum Variance Distortionless Response (MVDR) Beamformer. However, the number of interferers that can be removed through notching is limited by the number of receive channels. It is therefore essential to adaptively change the antenna pattern notching throughout the image in time and frequency for the best results with a given number of receive channels. In this paper, we present several methods to achieve this notching by making use of the spatial SAR signal distribution in range time, range frequency, azimuth time and azimuth Doppler that is inherent to the SAR imaging geometry. Because this distribution is time-variable and yet predictable, it can be used to improve the angle of arrival estimation of the RFI and the adaptive notching. The presented methods can be applied to a Digital Beamforming (DBF) SAR signal with multiple channels in elevation and/or in azimuth. Simulations show that the proposed methods increase the ability to notch out-of-swath interference from multiple directions and lessen the impact on in-swath interference. The improvement of the interferometric coherence for a single-pass interferogram acquired by NASA's EcoSAR system (capable of DBF in elevation) is demonstrated. The removal of periodic RFI artifacts is achieved.

RFI↗

Scaling Observation Error for Optimal Assimilation of CCI SST Data into a Regional HYCOM EnOI System

South Africa currently possesses no operational ocean forecasting system for the purpose of predicting ocean state variables including temperature,salinity and velocity. Substantial initial efforts towards this goal have been made and resulted in a system using a regional Hybrid Coordinate Ocean Model (HYCOM) along with the Ensemble Optimal Interpolation (EnOI)assimilation scheme. Assimilating only sea surface temperature (SST) observations from the Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) product into the system resulted in a degraded forecast. Aiming to address this, Climate Change Initiative (CCI) SSTs are assimilated into the system in an effort to improve the forecast skill. Observation errors in the assimilated product are used in the EnOI to determine whether more confidence should be placed in the model or observations in producing the analysis, but overconfidence in observations can shock the model and result in failure. To tweak the impact of the assimilation, a scaling factor is applied in the assimilation code. A scaling factor of 25 was found to produce a favourable result with lowest mean root mean square error (RMSE;1.098°C) between the model and observations over time. Postulating the error to be overconfident, a floor value is introduced in order to set a minimum value for the observation error thereby reducing confidence in the observations. These experiments fared less favourably with a floor value of 0.5 and a scaling factor of 15 producing the best mean RMSE (1.118°C).

Luyt, Hermann↗