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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Applications of the GPCP Satellite-Gauge Merged Precipitation Data Set to the Goals of PACS and GCIP

Recently, under the direction of GEWEX/GCIP there has been an attempt to link North American monsoon rainfall to precipitation in the Great Plains for the purposes of predictability on the seasonal time scale. Rain gauge analyses have been used to show continental-scale relationships. However, the interannual variability of warm season precipitation over the United States is linked to the east Pacific climate system. The Global Precipitation Climatology Project (GPCP) satellite estimates of precipitation over oceans add a vital piece of information towards the goals of PACS and GCIP. This preliminary study will begin by focusing on the East Pacific sector. El-Nino-Southern Ossilation (ENSO) modulates the position and strength of the Inter-Tropical Convergence Zone (ITCZ), which affects the precipitation source for the Mexican monsoon. For example, the five driest summers in coastal Mexico occurred during the five strongest El Ninos (as determined by positive values of Nino 3.4) since 1979. Previous work has investigated lag-lead relationships between the North American monsoon and continental rainfall. GPCP has the potential to extend these relationships to a global scale. Finally data sets with a finer time and space scale, including Tropical Rainfall Measurement Mission (TRMM) products, will be used to examine wave dynamics. Kelvin waves, in particular, may be trigger mechanisms for the onset of the North American monsoon.

Curtis, Scott↗
NASA NTRS2003

Aeronomy of Ice in the Mesosphere (AIM)

The overall goal of the Aeronomy of Ice in the Mesosphere (AIM) experiment is to resolve why Polar Mesospheric Clouds form and why they vary. By measuring PMCs and the thermal, chemical and dynamical environment in which they form, we will quanti@ the connection between these clouds and the meteorology of the polar mesosphere. In the end, this will provide the basis for study of long-term variability in the mesospheric climate and its relationship to global change. The results of AIM will be a rigorous validation of predictive models that can reliably use past PMC changes and present trends as indicators of global change. The AIM goal will be achieved by measuring PMC extinction, brightness, spatial distribution, particle size distributions, gravity wave activity, dust influx to the atmosphere and precise, vertical profile measurements of temperature, H20, C&, 0 3 , C02, NO. and aerosols. These data can only be obtained by a complement of instruments on an orbiting spacecraft (S/C).

Source record↗
NASA NTRS2008

Using an Informative Missing Data Model to Predict the Ability to Assess Recovery of Balance Control after Spaceflight

Astronauts show degraded balance control immediately after spaceflight. To assess this change, astronauts' ability to maintain a fixed stance under several challenging stimuli on a movable platform is quantified by "equilibrium" scores (EQs) on a scale of 0 to 100, where 100 represents perfect control (sway angle of 0) and 0 represents data loss where no sway angle is observed because the subject has to be restrained from falling. By comparing post- to pre-flight EQs for actual astronauts vs. controls, we built a classifier for deciding when an astronaut has recovered. Future diagnostic performance depends both on the sampling distribution of the classifier as well as the distribution of its input data. Taking this into consideration, we constructed a predictive ROC by simulation after modeling P(EQ = 0) in terms of a latent EQ-like beta-distributed random variable with random effects.

Feiveson, Alan H.↗
NASA NTRS2006

The Orbiting Carbon Observatory (OCO) Mission

Science objectives include: Collect the first space-based measurements of atmospheric CO2 with the precision, resolution, and coverage needed to characterize its sources and sinks on regional scales and quantify their variability over the seasonal cycle. Use independent data validation approaches to ensure high accuracy (1-2 ppm, 0.3% - 0.5%). Reliable climate predictions require an improved understanding of CO2 sinks. What human and natural processes are controlling atmospheric CO2? What are the relative roles of the oceans and land ecosystems in absorbing CO2?

carbon dioxide↗
NASA NTRS2010

Soil Moisture Controls on Rainfall and Temperature Variability: A Modeler Searches Through Observational Data

The degree to which atmospheric processes respond to variations in soil moisture - a potentially important but largely untapped element of subseasonal to seasonal prediction - can be determined easily and directly for an atmospheric model but cannot be determined directly for nature through an analysis of observations. In atmospheric models) directions of causality can be artificially manipulated; we can avoid difficulties associated with the fact that atmospheric variations have a much larger impact on land state variations than vice-versa. In nature) on the other hand) the dominant direction of causality (the atmosphere forcing the ground) cannot be artificially "turned off") and the statistics associated with this dominant direction overwhelm those of the feedback signal. Observational data) however) do allow a number of indirect measures of landatmosphere feedback. This seminar reports on a series of joint analyses of observational and model data designed to illuminate the degree of land-atmosphere feedback present in the real world. The indirect measures do in fact suggest that feedback in nature, though small) is significant - enough to warrant the development of realistic land initialization strategies for subseasonal and seasonal forecasts.

Koster, Randal↗
NASA NTRS2009

Synthesis and Assimilation Systems - Essential Adjuncts to the Global Ocean Observing System

Ocean assimilation systems synthesize diverse in situ and satellite data streams into four-dimensional state estimates by combining the various observations with the model. Assimilation is particularly important for the ocean where subsurface observations, even today, are sparse and intermittent compared with the scales needed to represent ocean variability and where satellites only sense the surface. Developments in assimilation and in the observing system have advanced our understanding and prediction of ocean variations at mesoscale and climate scales. Use of these systems for assessing the observing system helps identify the strengths of each observation type. Results indicate that the ocean remains under-sampled and that further improvements in the observing system are needed. Prospects for future advances lie in improved models and better estimates of error statistics for both models and observations. Future developments will be increasingly towards consistent analyses across components of the Earth system. However, even today ocean synthesis and assimilation systems are providing products that are useful for many applications and should be considered an integral part of the global ocean observing and information system.

Rienecker, Michele M.↗
NASA NTRS2011

Development and Testing of Operational Dual-Polarimetric Radar Based Lightning Initiation Forecast Techniques

Lightning is one of Earth s natural dangers, destructive not only to life but also physical property. According to the National Weather Service, there are on average 58 lightning fatalities each year, with over 300 related injuries (NWS 2010). The ability to forecast lightning is critical to a host of activities ranging from space vehicle launch operations to recreational sporting events. For example a single lightning strike to a Space Shuttle could cause billions of dollars of damage and possible loss of life. While forecasting that provides longer lead times could provide sporting officials with more time to respond to possible threatening weather events, thus saving the lives of player and bystanders. Many researchers have developed and tested different methods and tools of first flash forecasting, however few have done so using dual-polarimetric radar variables and products on an operational basis. The purpose of this study is to improve algorithms for the short-term prediction of lightning initiation through development and testing of operational techniques that rely on parameters observed and diagnosed using C-band dual-polarimetric radar.

Woodard, Crystal↗
NASA NTRS2011

A Comparison of Methods for a Priori Bias Correction in Soil Moisture Data Assimilation

Data assimilation is being increasingly used to merge remotely sensed land surface variables such as soil moisture, snow and skin temperature with estimates from land models. Its success, however, depends on unbiased model predictions and unbiased observations. Here, a suite of continental-scale, synthetic soil moisture assimilation experiments is used to compare two approaches that address typical biases in soil moisture prior to data assimilation: (i) parameter estimation to calibrate the land model to the climatology of the soil moisture observations, and (ii) scaling of the observations to the model s soil moisture climatology. To enable this research, an optimization infrastructure was added to the NASA Land Information System (LIS) that includes gradient-based optimization methods and global, heuristic search algorithms. The land model calibration eliminates the bias but does not necessarily result in more realistic model parameters. Nevertheless, the experiments confirm that model calibration yields assimilation estimates of surface and root zone soil moisture that are as skillful as those obtained through scaling of the observations to the model s climatology. Analysis of innovation diagnostics underlines the importance of addressing bias in soil moisture assimilation and confirms that both approaches adequately address the issue.

Kumar, Sujay V.↗
NASA NTRS2015

Fluid Shifts

INTRODUCTION: Mechanisms responsible for the ocular structural and functional changes that characterize the visual impairment and intracranial pressure (ICP) syndrome (VIIP) are unclear, but hypothesized to be secondary to the cephalad fluid shift experienced in spaceflight. This study will relate the fluid distribution and compartmentalization associated with long-duration spaceflight with VIIP symptoms. We also seek to determine whether the magnitude of fluid shifts during spaceflight, as well as the VIIP-related effects of those shifts, can be predicted preflight with acute hemodynamic manipulations, and also if lower body negative pressure (LBNP) can reverse the VIIP effects. METHODS: Physiologic variables will be examined pre-, in- and post-flight in 10 International Space Station crewmembers including: fluid compartmentalization (D2O and NaBr dilution); interstitial tissue thickness (ultrasound); vascular dimensions and dynamics (ultrasound and MRI (including cerebrospinal fluid pulsatility)); ocular measures (optical coherence tomography, intraocular pressure, ultrasound); and ICP measures (tympanic membrane displacement, otoacoustic emissions). Pre- and post-flight measures will be assessed while upright, supine and during 15 deg head-down tilt (HDT). In-flight measures will occur early and late during 6 or 12 month missions. LBNP will be evaluated as a countermeasure during HDT and during spaceflight. RESULTS: The first two crewmembers are in the preflight testing phase. Preliminary results characterize the acute fluid shifts experienced from upright, to supine and HDT postures (increased stroke volume, jugular dimensions and measures of ICP) which are reversed with 25 millimeters Hg LBNP. DISCUSSION: Initial results indicate that acute cephalad fluid shifts may be related to VIIP symptoms, but also may be reversible by LBNP. The effect of a chronic fluid shift has yet to be evaluated. Learning Objectives: Current spaceflight VIIP research is described, including novel hardware and countermeasures.

Stenger, M. B.↗
NASA NTRS2017

Modeling Oxygen Prebreathe Protocols for Exploration Extravehicular Activities Using Variable Pressure Suits

Exploration missions are expected to use variable pressure extravehicular activity (EVA) spacesuits as well as a spacecraft "exploration atmosphere" of 56.5 kPa (8.2 psia), 34% O2, both of which provide the possibility of reducing the oxygen prebreathe times necessary to reduce decompression sickness (DCS) risk. Previous modeling work predicted 8.4% DCS risk for an EVA beginning at the exploration atmosphere, followed by 15 minutes of in-suit O2 prebreathe, and 6 hours of EVA at 29.6 kPa (4.3 psia). In this study we model notional prebreathe protocols for a variable pressure suit where the exploration atmosphere is unavailable.

Abercromby, Andrew F. J.↗
NASA NTRS2020

The Effect of Europa and Enceladus Analog Seawater Composition on Isotopic Measurements of Volatile CO2

Science goals for icy ocean worlds missions include characterizing the chemical compositionof the surface and interior using remote sensing and in situ techniques. The next class of flightmass spectrometers for these missions will obtain compositional identifications and isotope ratiomeasurements of volatiles evolved from the ice surface (exosphere) and plumes. These massspectra will be combined with data from other flight instruments to infer the composition of theinterior from volatiles. To ensure accurate interpretation of these measurements, it is critical toverify whether the fundamental assumption that volatiles observed in icy ocean world exospheresor plumes will be a direct reflection of the sub-ice ocean. The present study evaluates whether isotopologues from an initial CO2 gas fractionate by interacting with seawater (brine) of varyingsalt composition and concentration. δ13CCO2 are affected by the pH of the brine and subsequentspeciation of {CO2}, where {CO2} represents the combination of CO2, H2CO3, HCO3-, and CO32-.{CO2} for low pH brines hypothesized for Europa will preferentially speciate as CO2. Analyzedδ13CCO2 for low pH brines are within error of the original δ13CCO2, demonstrating that volatile CO2in a low pH system will be a direct reflection of the original CO2. However, Europa’s radiativeenvironment and rapid depressurization due to plume ejection may impose fractionation effects.In contrast, high pH systems relevant to Enceladus or a more alkaline Europa are expected toform all carbonate species, while favoring speciation as HCO3-. High pH brines in theseexperiments include both an original CO2 gas and an isotopically distinct HCO3- (from NaHCO3salt). These alkaline experiments demonstrate that δ13CCO2 values are highly variable, and dependon the concentration of the dominant carbonate species, (Na)HCO3-. Mass balance estimatesindicate that measured δ13CCO2 is a thermodynamically predictable mixture of both carbonsources, suggesting that measurements of δ13C at Enceladus would directly reflect of the sourcesof CO2 and carbonate buffering in the ocean. δ18O measurements for CO2 interacting with KCland MgCl2 follow established models for δ18O-ionic strength. CO2 interacting with MgSO4,Na2SO4, and NaCl demonstrate an offset from established δ18O-ionic strength models dependingon the concentration of initial CO2. These results suggest that current predictive models for δ18Oin brines need to be resolved for changing concentrations of CO2

Ocean Worlds↗
NASA NTRS2002

Advances in Data Assimilation and Weather Prediction Using TRMM Observations

Understanding the Earth's climate and how it responds to climate perturbations requires knowledge of how atmospheric moisture, clouds, latent heating, the large-scale circulation and energy fluxes vary with changing climatic conditions. The physical process linking these climate elements is precipitation. Accurate knowledge of how precipitation varies in space and time and how it couples with other atmospheric variables is essential for understanding the global water and energy cycle. In recent years, TRMM data products have played a key role in advancing the field of data assimilation to provide better global analyses for climate research and numerical weather prediction. TRMM research has demonstrated the effectiveness of microwave-based rainfall and total precipitable water (TPW) observations in improving the quality of assimilated datasets and upgrading forecast skills. TRMM latent heating products have also stimulated experimentation with innovative techniques to use this type of information to improve global analyses. We discuss strategies of assimilating TRMM observations at NASA s Data Assimilation Office and present results on the impact assimilating TRMM data on the Goddard Earth Observing System (GEOS) analyses and forecast capabilities.

Atlas, Robert↗
NASA NTRS2005

Trends from the Long-term Data Record and Models: What Do They Tell Us About our Ability to Predict Ozone Recovery?

Our industrial society has performed an experiment on the stratospheric ozone layer over the last several decades. The initial part of this experiment was the rapidly increasing release of halogen-containing compounds that carry chlorine and bromine to the stratosphere where they can cause a loss of ozone. The present part of this experiment is the implementation of the Montreal Protocol, which has led to a leveling off of these halogen compounds and the beginning of their slow removal from the atmosphere. The observation and attribution of ozone response to the halogens has been a particularly important and difficult task because of the impact of solar cycle uv variation, two major volcanic eruptions (El Chichon and Pinatubo), and interannual dynamic variability of the stratosphere. We have run 3 different simulations of the chemistry and transport of ozone and the minor constituents that affect ozone to help evaluate our understanding of the causes of ozone change and to assess our ability to predict ozone recovery with the removal of halogens from the stratosphere. One simulation, using the Goddard chemical transport model (CTM), had interannual variability in the dynamics for the entire 50 years of simulation, which included the past 3 decades (1974-2004) and the next 2 decades to 2022. The other two simulations used the Global Modeling Initiative (GMI) CTM with no dynamical variability: one used a the winds and temperatures from a repeating warm Arctic winter and the other used a repeating cold Arctic winter. All simulations included the effects of aerosol surfaces from volcanic eruptions on chemical reactions as well as the variation in UV over the 11-year solar cycle.

Strahan, Susan↗
NASA NTRS2016

Consistent Evaluation of ACOS-GOSAT, BESD-SCIAMACHY, CarbonTracker, and MACC Through Comparisons to TCCON

Consistent validation of satellite CO2 estimates is a prerequisite for using multiple satellite CO2 measurements for joint flux inversion, and for establishing an accurate long-term atmospheric CO2 data record. Harmonizing satellite CO2 measurements is particularly important since the differences in instruments, observing geometries, sampling strategies, etc. imbue different measurement characteristics in the various satellite CO2 data products. We focus on validating model and satellite observation attributes that impact flux estimates and CO2 assimilation, including accurate error estimates, correlated and random errors, overall biases, biases by season and latitude, the impact of coincidence criteria, validation of seasonal cycle phase and amplitude, yearly growth, and daily variability. We evaluate dry-air mole fraction (X(sub CO2)) for Greenhouse gases Observing SATellite (GOSAT) (Atmospheric CO2 Observations from Space, ACOS b3.5) and SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) (Bremen Optimal Estimation DOAS, BESD v2.00.08) as well as the CarbonTracker (CT2013b) simulated CO2 mole fraction fields and the Monitoring Atmospheric Composition and Climate (MACC) CO2 inversion system (v13.1) and compare these to Total Carbon Column Observing Network (TCCON) observations (GGG2012/2014). We find standard deviations of 0.9, 0.9, 1.7, and 2.1 parts per million vs. TCCON for CT2013b, MACC, GOSAT, and SCIAMACHY, respectively, with the single observation errors 1.9 and 0.9 times the predicted errors for GOSAT and SCIAMACHY, respectively. We quantify how satellite error drops with data averaging by interpreting according to (error(sup 2) equals a(sup 2) plus b(sup 2) divided by n (with n being the number of observations averaged, a the systematic (correlated) errors, and b the random (uncorrelated) errors). a and b are estimated by satellites, coincidence criteria, and hemisphere. Biases at individual stations have year-to-year variability of 0.3 parts per million, with biases larger than the TCCON predicted bias uncertainty of 0.4 parts per million at many stations. We find that GOSAT and CT2013b under-predict the seasonal cycle amplitude in the Northern Hemisphere (NH) between 46 and 53 degrees North latitude, MACC over-predicts between 26 and 37 degrees North latitude, and CT2013b under-predicts the seasonal cycle amplitude in the Southern Hemisphere (SH). The seasonal cycle phase indicates whether a data set or model lags another data set in time. We find that the GOSAT measurements improve the seasonal cycle phase substantially over the prior while SCIAMACHY measurements improve the phase significantly for just two of seven sites. The models reproduce the measured seasonal cycle phase well except for at Lauder_125HR (CT2013b) and Darwin (MACC). We compare the variability within 1 day between TCCON and models in June-July-August; there is correlation between 0.2 and 0.8 in the NH, with models showing 10-50 percent the variability of TCCON at different stations and CT2013b showing more variability than MACC. This paper highlights findings that provide inputs to estimate flux errors in model assimilations, and places where models and satellites need further investigation, e.g., the SH for models and 45-67 degrees North latitude for GOSAT and CT2013b.

ACOS-GOSAT↗
NASA NTRS1992

Chapman Conference on the Hydrologic Aspects of Global Climate Change, Lake Chelan, WA, June 12-14, 1990, Selected Papers

The present conference on the hydrological aspects of global climate change discusses land-surface schemes for future climate models, modeling of the land-surface boundary in climate models as a composite of independent vegetation, a land-surface hydrology parameterizaton with subgrid variability for general circulation models, and conceptual aspects of a statistical-dynamical approach to represent landscape subgrid-scale heterogeneities in atmospheric models. Attention is given to the impact of global warming on river runoff, the influence of atmospheric moisture transport on the fresh water balance of the Atlantic drainage basin, a comparison of observations and model simulations of tropospheric water vapor, and the use of weather types to disaggregate the prediction of general circulation models. Topics addressed include the potential response of an Arctic watershed during a period of global warming and the sensitivity of groundwater recharge estimates to climate variability and change.

Lettenmaier, Dennis P.↗
NASA NTRS2007

Neural Network Burst Pressure Prediction in Composite Overwrapped Pressure Vessels

Acoustic emission data were collected during the hydroburst testing of eleven 15 inch diameter filament wound composite overwrapped pressure vessels. A neural network burst pressure prediction was generated from the resulting AE amplitude data. The bottles shared commonality of graphite fiber, epoxy resin, and cure time. Individual bottles varied by cure mode (rotisserie versus static oven curing), types of inflicted damage, temperature of the pressurant, and pressurization scheme. Three categorical variables were selected to represent undamaged bottles, impact damaged bottles, and bottles with lacerated hoop fibers. This categorization along with the removal of the AE data from the disbonding noise between the aluminum liner and the composite overwrap allowed the prediction of burst pressures in all three sets of bottles using a single backpropagation neural network. Here the worst case error was 3.38 percent.

Hill, Eric v. K.↗
NASA NTRS2013

Estimating Ground-Level PM(sub 2.5) Concentrations in the Southeastern United States Using MAIAC AOD Retrievals and a Two-Stage Model

Previous studies showed that fine particulate matter (PM(sub 2.5), particles smaller than 2.5 micrometers in aerodynamic diameter) is associated with various health outcomes. Ground in situ measurements of PM(sub 2.5) concentrations are considered to be the gold standard, but are time-consuming and costly. Satellite-retrieved aerosol optical depth (AOD) products have the potential to supplement the ground monitoring networks to provide spatiotemporally-resolved PM(sub 2.5) exposure estimates. However, the coarse resolutions (e.g., 10 km) of the satellite AOD products used in previous studies make it very difficult to estimate urban-scale PM(sub 2.5) characteristics that are crucial to population-based PM(sub 2.5) health effects research. In this paper, a new aerosol product with 1 km spatial resolution derived by the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was examined using a two-stage spatial statistical model with meteorological fields (e.g., wind speed) and land use parameters (e.g., forest cover, road length, elevation, and point emissions) as ancillary variables to estimate daily mean PM(sub 2.5) concentrations. The study area is the southeastern U.S., and data for 2003 were collected from various sources. A cross validation approach was implemented for model validation. We obtained R(sup 2) of 0.83, mean prediction error (MPE) of 1.89 micrograms/cu m, and square root of the mean squared prediction errors (RMSPE) of 2.73 micrograms/cu m in model fitting, and R(sup 2) of 0.67, MPE of 2.54 micrograms/cu m, and RMSPE of 3.88 micrograms/cu m in cross validation. Both model fitting and cross validation indicate a good fit between the dependent variable and predictor variables. The results showed that 1 km spatial resolution MAIAC AOD can be used to estimate PM(sub 2.5) concentrations.

aerosol optical depth↗
NASA NTRS1992

LDEF microenvironments, observed and predicted

Complex protrusions and surface indentations on spacecraft equipment alter exposure environments by casting shadows, producing reflections and scattering incident atomic oxygen flux and UV radiation. A computer model is being developed to predict these effects. The model accounts for any arbitrary shape, size, orientation, or curvature of exposed objects. LDEF offers a unique opportunity to compare model prediction with observations. For this purpose, a study is underway on twelve of LDEF's copper grounding straps. These straps were exposed at various angles from the ram vector during the LDEF flight. Microenvironment variables include shadowing and reflections from clamps and fasteners, and varying exposure caused by bending of the straps. Strap measurements include optical properties, surface film composition by ESCA, and film thickness measurements by optical interference techniques. The features of the microenvironment model and the analytical methods used to examine the straps are discussed. Data are presented showing predicted microenvironmental variations. These variations are compared with observed point to point differences in surface properties of the straps.

Bourassa, R. J.↗