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At least 1,513 records · Page 84
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Enabling Advanced Wind-Tunnel Research Methods Using the NASA Langley 12-Foot Low Speed Tunnel

Design of Experiment (DOE) testing methods were used to gather wind tunnel data characterizing the aerodynamic and propulsion forces and moments acting on a complex vehicle configuration with 10 motor-driven propellers, 9 control surfaces, a tilt wing, and a tilt tail. This paper describes the potential benefits and practical implications of using DOE methods for wind tunnel testing - with an emphasis on describing how it can affect model hardware, facility hardware, and software for control and data acquisition. With up to 23 independent variables (19 model and 2 tunnel) for some vehicle configurations, this recent test also provides an excellent example of using DOE methods to assess critical coupling effects in a reasonable timeframe for complex vehicle configurations. Results for an exploratory test using conventional angle of attack sweeps to assess aerodynamic hysteresis is summarized, and DOE results are presented for an exploratory test used to set the data sampling time for the overall test. DOE results are also shown for one production test characterizing normal force in the Cruise mode for the vehicle.

Busan, Ronald C.↗
NASA NTRS2017

Inflight Performance of the SDO Fine Pointing Science Mode

The Solar Dynamics Observatory (SDO) was successfully launched and deployed from its Atlas V launch vehicle on February 11, 2010. Three months later, on May 14, 2010, the fully commissioned heliophysics laboratory was handed over to Space Systems Mission Operations to begin its science mission. SDO is an Explorer-class mission now operating in a geosynchronous orbit, sending data 24 hours per day to a dedicated ground station in White Sands, New Mexico. It carries a suite of instruments designed to observe the Sun in multiple wavelengths at unprecedented resolution. The Atmospheric Imaging Assembly (AIA) includes four telescopes with 4096x4096 focal plane CCDs that can image the full solar disk in seven extreme ultraviolet and three ultraviolet-visible wavelengths. The Extreme Ultraviolet Variability Experiment (EVE) collects time-correlated data on the activity of the Sun's corona. The Helioseismic and Magnetic Imager (HMI) enables study of pressure waves moving through the body of the Sun.

Control↗
NASA NTRS1989

The vertical ozone distribution during maximum and minimum solar activity

To study the latitude variation of ozone vertical distribution the complex experiment was carried out in February to July 1985 between 40 deg N to 70 deg S at the Pacific and the Indian Oceans. The great bulk of their data network were taken by the optical rocket ozonometers at the Southern Hemisphere. The results were compared with reference models containing the most extensive set of ozone observations from VS satellites between 1978 and 1982. To analyze latitude-season ozone variability at fixed altitude levels the experimental ozone concentration data were confirmed with model equatorial data. To compare the experimental data with reference model data, analogous model values were calculated. The results of calculation indicated a good agreement between experimental and reference model data of relative latitude-season variations of ozone concentration. Maximum variability is observed at 50 km in the equator and not exceeded 15 percent in the other regions at all altitude levels.

Kokin, G. A.↗
NASA NTRS2015

Statistical Analysis of Large Simulated Yield Datasets for Studying Climate Effects

Many studies have been carried out during the last decade to study the effect of climate change on crop yields and other key crop characteristics. In these studies, one or several crop models were used to simulate crop growth and development for different climate scenarios that correspond to different projections of atmospheric CO2 concentration, temperature, and rainfall changes (Semenov et al., 1996; Tubiello and Ewert, 2002; White et al., 2011). The Agricultural Model Intercomparison and Improvement Project (AgMIP; Rosenzweig et al., 2013) builds on these studies with the goal of using an ensemble of multiple crop models in order to assess effects of climate change scenarios for several crops in contrasting environments. These studies generate large datasets, including thousands of simulated crop yield data. They include series of yield values obtained by combining several crop models with different climate scenarios that are defined by several climatic variables (temperature, CO2, rainfall, etc.). Such datasets potentially provide useful information on the possible effects of different climate change scenarios on crop yields. However, it is sometimes difficult to analyze these datasets and to summarize them in a useful way due to their structural complexity; simulated yield data can differ among contrasting climate scenarios, sites, and crop models. Another issue is that it is not straightforward to extrapolate the results obtained for the scenarios to alternative climate change scenarios not initially included in the simulation protocols. Additional dynamic crop model simulations for new climate change scenarios are an option but this approach is costly, especially when a large number of crop models are used to generate the simulated data, as in AgMIP. Statistical models have been used to analyze responses of measured yield data to climate variables in past studies (Lobell et al., 2011), but the use of a statistical model to analyze yields simulated by complex process-based crop models is a rather new idea. We demonstrate herewith that statistical methods can play an important role in analyzing simulated yield data sets obtained from the ensembles of process-based crop models. Formal statistical analysis is helpful to estimate the effects of different climatic variables on yield, and to describe the between-model variability of these effects.

climate↗
NASA NTRS1983

Turbulent flame propagation and combustion in spark ignition engines

Pressure measurements synchronized with high-speed motion-picture records of flame propagation have been made in a transparent-piston engine. The data show that the initial expansion speed of the flame front is close to that of a laminar flame. As the flame expands, its speed rapidly accelerates to a quasi-steady value comparable with that of the turbulent velocity fluctuations in the unburned gas. During the quasi-steady propagation phase, a significant fraction of the gas behind the visible front is unburned. Final burnout of the charge may be approximated by an exponential decay in time. The data have been analyzed in a model-independent way to obtain a set of empirical equations for calculating mass burning rates in spark-ignition engines. The burning equations contain three parameters: the laminar burning speed, a characteristic speed (uT), and a characteristic length (lT). The laminar burning speed is known from laboratory measurements. Tentative correlations relating uT and lT to engine geometry and operating variables have been derived from the engine data.

Beretta, G. P.↗
NASA NTRS2001

Bio-Optical Measurements at Ocean Boundaries in Support of SIMBIOS

The equatorial Pacific is a major component of global biogeochemical cycles, due to upwelling that occurs from the coast of South America to beyond 180 deg. This upwelling has significant implications for global CO2 fluxes, as well as primary and secondary production. In addition, this region of the world's oceans represents a large oceanic province over which validation data for Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) are necessary. This project consists of a mooring program and supporting cruise-based measurements aimed at quantifying the spectrum of biological and chemical variability in the equatorial Pacific and obtaining validation data for SeaWiFS. The project has the following general objectives: (1) to understand the relationships between physical forcing, primary production, nutrient supply and the exchange of carbon dioxide between ocean and atmosphere in the equatorial Pacific; (2) to describe the biological and chemical responses to climate and ocean variability; (3) to describe the spatial, seasonal and inter-annual variability in near surface plant pigments, primary production, carbon dioxide and nutrient distributions; and (4) to obtain near real-time bio-optical measurements for validation of SeaWiFS and subsequent ocean color sensors.

Chavez, Francisco P.↗
NASA NTRS1992

Variability in the outer planet aurorae

Multiwavelength observations of the aurorae of the outer planets are reviewed emphasizing the findings on physical processes derived from specific wavelengths. The review examines features of the auroral zones such as ionospheric currents, atmospheric heating, and compositional changes in the aurorae of Jupiter, Saturn, Uranus, Neptune, and the earth for comparison. Jupiter's multiwavelength aurora receives special attention since recent observations shed light on the distribution of the UV auroral ovals, the spectroscopy of the UV auroral emissions, auroral dynamics and ion upwelling, and IR emission from auroral latitudes. The observational data on Jupiter facilitate the modeling of variability and detailed thermospheric and magnetospheric processes. Saturn can be studied by extending findings fron Jupiter's aurora, and deficiencies are found in the observational datasets for Neptune and Uranus.

Clarke, John T.↗
NASA NTRS1987

Regional sources and sinks of dust on Mars: Viking observations of Cerberus, Solis Planum and Syrtis Major

A study of seasonal variations of albedo features in the Cerberus, Solis Planum, and Syrtis Major regions was based on Viking Orbiter data obtained over more than one complete Martian year. Contour maps of Lambert albedo and single-point thermal inertia were constructed from the Infrared Thermal Mapper (IRTM) experiment data, and Orbiter images were used to determine the pattern and variability of regional winds (inferred from wind streak orientations). Coupled with ground-based radar data, these data allow the regional sediment transport direction, surface properties (texture, morphology, and roughness), and the implications of the observed seasonal and longer term dust redistribution to be investigated. Results are outlined.

Lee, Steven W.↗
NASA NTRS1988

Arctic Sea ice studies with passive microwave satellite observations

The objectives of this research are: (1) to improve sea ice concentration determinations from passive microwave space observations; (2) to study the role of Arctic polynyas in the production of sea ice and the associated salinization of Arctic shelf water; and (3) to study large scale sea ice variability in the polar oceans. The strategy is to analyze existing data sets and data acquired from both the DMSP SSM/I and recently completed aircraft underflights. Special attention will be given the high resolution 85.5 GHz SSM/I channels for application to thin ice algorithms and processes studies. Analysis of aircraft and satellite data sets is expected to provide a basis for determining the potential of the SSM/I high frequency channels for improving sea ice algorithms and for investigating oceanic processes. Improved sea ice algorithms will aid the study of Arctic coastal polynyas which in turn will provide a better understanding of the role of these polynyas in maintaining the Arctic watermass structure. Analysis of satellite and archived meteorological data sets will provide improved estimates of annual, seasonal and shorter-term sea ice variability.

Cavalieri, D. J.↗
NASA NTRS2023

ENSO and MJO Modulation of U.S. Cloud-to-Ground Lightning Activity

Cloud-to-ground (CG) lightning substantially impacts human health and property. However, the relations between U.S. lightning activity and the Madden-Julian Oscillation (MJO) and El Niño-Southern Oscillation (ENSO), two predictable drivers of global climate variability, remain uncertain, in part because most lightning datasets have short records that cannot robustly reveal MJO- and ENSO-related patterns. To overcome this limitation, we developed an empirical model of 6-hourly lightning flash count over the contiguous U.S. (CONUS) using environmental variables (convective available potential energy and precipitation) andNational Lightning Detection Network data for 2003–2016. This model is shown to reproduce the observed daily and seasonal variability of lightning over most of CONUS. Then, the empirical model was applied to construct a proxy lightning dataset for the period 1979–2021, which was used to investigate the summer MJO-lightning relationship at daily resolution and the winter-spring ENSO-lightning relationship at seasonal resolution. Overall, no robust relationship between MJO phase and lightning patterns was found when seasonality was taken into consideration. El Niño is associated with increased lightning activity over the Coastal Southeast U.S. during early winter, the Southwest during winter through spring, and the Northwest during late spring, whereas La Niña is associated with increased lightning activity over the Tennessee River Valley during winter.

Lightning↗
NASA NTRS2012

Comparative Analysis of Upper Ocean Heat Content Variability from Ensemble Operational Ocean Analyses

Upper ocean heat content (HC) is one of the key indicators of climate variability on many time-scales extending from seasonal to interannual to long-term climate trends. For example, HC in the tropical Pacific provides information on thermocline anomalies that is critical for the longlead forecast skill of ENSO. Since HC variability is also associated with SST variability, a better understanding and monitoring of HC variability can help us understand and forecast SST variability associated with ENSO and other modes such as Indian Ocean Dipole (IOD), Pacific Decadal Oscillation (PDO), Tropical Atlantic Variability (TAV) and Atlantic Multidecadal Oscillation (AMO). An accurate ocean initialization of HC anomalies in coupled climate models could also contribute to skill in decadal climate prediction. Errors, and/or uncertainties, in the estimation of HC variability can be affected by many factors including uncertainties in surface forcings, ocean model biases, and deficiencies in data assimilation schemes. Changes in observing systems can also leave an imprint on the estimated variability. The availability of multiple operational ocean analyses (ORA) that are routinely produced by operational and research centers around the world provides an opportunity to assess uncertainties in HC analyses, to help identify gaps in observing systems as they impact the quality of ORAs and therefore climate model forecasts. A comparison of ORAs also gives an opportunity to identify deficiencies in data assimilation schemes, and can be used as a basis for development of real-time multi-model ensemble HC monitoring products. The OceanObs09 Conference called for an intercomparison of ORAs and use of ORAs for global ocean monitoring. As a follow up, we intercompared HC variations from ten ORAs -- two objective analyses based on in-situ data only and eight model analyses based on ocean data assimilation systems. The mean, annual cycle, interannual variability and longterm trend of HC have been analyzed

Xue, Yan↗
NASA NTRSDate not supplied

The NASA Merra-2 Reanalysis Products: Data and Tools Used for Aerosol and Air Quality Studies

The NASA Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) is atmospheric reanalysis data spanning 1980 to present. It has been produced by the NASA Global Modeling and Assimilation Office (GMAO) and is distributed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). MERRA-2 data includes 100 collections of Earth system variables, mainly from the atmospheric model, such as aerosol fields and meteorological fields, radiation fields, and aerosol fields, guided by the assimilation of as many as six million observations every six hours. MERRA-2 has been one of the most popular datasets from NASA and is widely used in interdisciplinary research and applications, with increasing numbers of new users. For example, at least 7000 users accessed MERRA-2 data at GES DISC in the year 2021, ~1000 more users than in the year 2020. In this presentation, we will introduce the MERRA-2 datasets associated with aerosol and air quality studies and use a wildfire case study to demonstrate the data tools developed at GES DISC to analyze and visualize MERRA-2 data, such as Giovanni and the level 3 and level 4 subsetter, and Jupyter Python notebook. We will also update the status of cloud migration of the MERRA-2 data to Amazon Web Services (AWS).

Xiaohua Pan↗
NASA NTRS1984

Prescription of land-surface boundary conditions in GISS GCM 2: A simple method based on high-resolution vegetation data bases

A simple method was developed for improved prescription of seasonal surface characteristics and parameterization of land-surface processes in climate models. This method, developed for the Goddard Institute for Space Studies General Circulation Model II (GISS GCM II), maintains the spatial variability of fine-resolution land-cover data while restricting to 8 the number of vegetation types handled in the model. This was achieved by: redefining the large number of vegetation classes in the 1 deg x 1 deg resolution Matthews (1983) vegetation data base as percentages of 8 simple types; deriving roughness length, field capacity, masking depth and seasonal, spectral reflectivity for the 8 types; and aggregating these surface features from the 1 deg x 1 deg resolution to coarser model resolutions, e.g., 8 deg latitude x 10 deg longitude or 4 deg latitude x 5 deg longitude.

Matthews, E.↗
NASA NTRS1987

Reexamination of the SAS 2 Cygnus X-3 data

Recent observations of Cygnus X-3 have shown marked variability of the radiation on short time scales. In particular, the bursts lasting on the order of 10 minutes, seen in both the infrared and very high energy (greater than 10 to the 11th eV) gamma-ray regions, and the time-variations on many scales at high energies, have stimulated a reanalysis of the March 6 to 13, 1973 SAS 2 high-energy gamma-ray data. Although a clear periodicity in the E greater 35 MeV gamma radiation is observed at the 4.79 hr period seen in X-rays, there is no evidence for major variations of the radiation from one day to the next, and no statistically significant evidence for bursts on the 10-minute time scale seen in the infrared or very high energy ranges. If the excess observed had been predominantly in the form of ten minute bursts even at a rate as high as two/day, a clearly significant set of bursts would have been seen.

Fichtel, C. E.↗
NASA NTRS2014

Quantification of Inflight Physical Changes: Anthropometry and Neutral Body Posture (Body Measures)

The goal of this study is to gather preliminary data to better understand the magnitude and variability of microgravity changes on the body. To do this, we aim to gather and document microgravity effects on body measurements. Lengths, Breadths, Depths  Circumferences, Joint angles. To determine if/how the Neutral Body Posture (NBP) is influenced by the above factors. This will be the first time these proposed measures are collected in space. It is anticipated that body measurements will change due to microgravity and fluid shifts. This data is important so that the changes that may occur during long-duration space flight can be identified and applied to suit fit, suit sizing, workstation design, etc. for future missions in order to prevent injury and reduce crew time for altering or adjusting suits, workstations, etc.

Rajulu, Sudhakar↗
NASA NTRS2005

The Contribution of CEOP Data to the Understanding and Modeling of Monsoon Systems

CEOP has contributed and will continue to provide integrated data sets from diverse platforms for better understanding of the water and energy cycles, and for validaintg models. In this talk, I will show examples of how CEOP has contributed to the formulation of a strategy for the study of the monsoon as a system. The CEOP data concept has led to the development of the CEOP Inter-Monsoon Studies (CIMS), which focuses on the identification of model bias, and improvement of model physics such as the diurnal and annual cycles. A multi-model validation project focusing on diurnal variability of the East Asian monsoon, and using CEOP reference site data, as well as CEOP integrated satellite data is now ongoing. Preliminary studies show that climate models have difficulties in simulating the diurnal signals of total rainfall, rainfall intensity and frequency of occurrence, which have different peak hours, depending on locations. Further more model diurnal cycle of rainfall in monsoon regions tend to lead the observed by about 2-3 hours. These model bias offer insight into lack of, or poor representation of, key components of the convective and stratiform rainfall. The CEOP data also stimulated studies to compare and contrasts monsoon variability in different parts of the world. It was found that seasonal wind reversal, orographic effects, monsoon depressions, meso-scale convective complexes, SST and land surface land influences are common features in all monsoon regions. Strong intraseasonal variability is present in all monsoon regions. While there is a clear demarcation of onset, breaks and withdrawal in the Asian and Australian monsoon region associated with climatological intraseasonal variabillity, it is less clear in the American and Africa monsoon regions. The examination of satellite and reference site data in monsoon has led to preliminary model experiments to study the impact of aerosol on monsoon variability. I will show examples of how the study of the dynamics of aerosol-water cycle interactions in the monsoon region, can be best achieved using the CEOP data and modeling strategy.

Lau, William K. M.↗
NASA NTRS2011

Use of Remote Sensing/Geographical Information Systems (RS/GIS) to Identify the Distributional Limits of Soil-Transmitted Helminths (STHs) and Their Association to Prevalence of Intestinal Infection in School-Age Children in Four Rural Communities in Boaco, Nicaragua

STHs can infect all members of a population but school-age children living in poverty are at greater risk. Infection can be controlled with drug treatment, health education and sanitation. Helminth control programs often lack resources and reliable information to identify areas of highest risk to guide interventions and to monitor progress. Objectives: To use RS/GIS to identify the environmental variables that correlate with the ecology of STHs and with the prevalence of STH infections. Methods: Geo-referenced in situ prevalence data will be overlaid over an ecological map derived from the RS environmental data using ESRI s ArcGIS 9.3. Prevalence data and RS environmental data matching at the same geographical location will be analyzed for correlation and those RS environmental variables that better correlate with prevalence data will be included in a multivariate regression model. Temperature, vegetation, and distance to bodies of water will be inferred using data from the Moderate-Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites, and Thematic Mapper (TM) and Enhance Thematic Mapper Plus (ETM+) satellite sensors onboard Landsat 5 and Landsat 7 respectively. Elevation will be estimated with data from The Shuttle Radar Topography Mission (SRTM). Prevalence and intensity of infections will be determined by parasitological survey (Kato Katz) of children enrolled in rural schools in Boaco, Nicaragua, in the communities of El Roblar, Cumaica Norte, Malacatoya 1, and Malacatoya 2). Expected Results: Associations between RS environmental data and prevalence in situ data will be determined and their applications to public health will be discussed. Discussion/Conclusions: The use of RS/GIS data to predict the prevalence of STH infections could be useful for helminth control programs, providing improved geographical guidance of interventions while increasing cost-effectiveness. Learning Objectives: (1) To identify the RS environmental variables that can help predict the prevalence of STH infections. (2) To understand potential applications of RS/GIS to national helminth control programs. (3) To asses the applicability of RS/GIS to control STH infections.

Moreno, Max J.↗
NASA NTRS2022

Simulations of Firn Processes Over the Greenland and Antarctic Ice Sheets: 1980-2021

Conversion of altimetry-derived ice-sheet volume change to mass requires an understanding of the evolution of the combined ice and air content within the firn column. In the absence of suitable techniques to observe the changes to the firn column across the entirety of an ice sheet, the firn column processes are typically modeled. Here, we present new simulations of firn processes over the Greenland and Antarctic ice sheets (GrIS and AIS) using the Community Firn Model and atmospheric reanalysis variables for more than four decades. A data set of more than 250 measured depth–density profiles from both ice sheets provides the basis of the calibration of the dry-snow densification scheme. The resulting scheme results in a reduction in the rate of densification, relative to a commonly used semi-empirical model, through a decreased dependence on the accumulation rate, a proxy for overburden stress. The 1980–2020 modeled firn column runoff, when combined with atmospheric variables from MERRA-2, generates realistic mean integrated surface mass balance values for the Greenland (+390 Gt yr(exp −1)) and Antarctic (+2612 Gt yr(exp −1)) ice sheets when compared to published model-ensemble means. We find that seasonal volume changes associated with firn air content are on average approximately 2.5 times larger than those associated with mass fluxes from surface processes for the AIS and 1.5 times larger for the GrIS; however, when averaged over multiple years, ice and air-volume fluctuations within the firn column are of comparable magnitudes. Between 1996 and 2019, the Greenland Ice Sheet lost nearly 5% of its firn air content, indicating a reduction in the total meltwater retention capability. Nearly all (94 %) of the meltwater produced over the Antarctic Ice Sheet is retained within the firn column through infiltration and refreezing.

Greenland↗