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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Soil moisture retrieval in the Oberpfaffenhofen testsite using MAC Europe AIRSAR data

Soil moisture content is an important parameter in many disciplines of science like hydrology, meteorology, agriculture and others. Microwave remote sensing technique has a high potential in measuring the dielectric constant of soils, which is strongly governed by the soil moisture. Much excellent work has been done on investigating the relationship between backscattering coefficient and soil moisture. Most of these studies are measured in a laboratory or are carried out with a multitemporal data set. This means, that the variation in the backscattering coefficient is only related to the soil moisture because all other parameters influencing the backscattering like surface roughness, vegetation cover, plant geometry, phenology of plants and row direction are kept constant. In this study the sensitivity of the backscattering coefficient to soil moisture of corn fields is investigated. In the framework of the MAC-Europe Campaign in June 1991, the NASA/JPL three-frequency polarimetric AIRSAR system collected data over the test site Oberpfaffenhofen. The AIRSAR campaign in Oberpfaffenhofen was complemented with intensive ground truth measurements. The sampled corn fields are nearly in the range of the same incidence angle (approximately 20 deg) and belong to different soil types. The evaluation was carried out at a single data set. The results show that the backscattering, measured at P-band, can be described with only two parameters very well. The main parameter influencing the backscattering is the soil moisture content; the second subordinated parameter is the row direction.

Wever, Tobias↗
NASA NTRS1983

Pacific area data collection stations

The installation of environmental data collection systems at several remotely located sites in islands in the Pacific Ocean is summarized. The effort was designed to enhance the ability to collect hydrological information. The data collection station consists of a data acquisition system for handling data, a transmitter for uplinking information to the GOES-W geostationary satellite, and a variety of environmental sensors for data accumulation. Each system was assembled, tested, and deployed on designated islands. The concept of using microprocessors for handling data at remote sites and relaying it via a satellite link is a cost effective approach. Such systems require high reliability and proven performance in the field.

Rector, R. C.↗
NASA NTRS1993

Sub-Daily Northern Hemisphere Ionospheric Maps Using the IGS GPS Network

Ionospheric total electron content (TEC) data derived from dual-frequency GPS signals from 30 globally distributed IGS network sites are fit to a simple ionospheric shell model, yielding, simultaneously, values for the satellite and receiver biases, and a map of the ionosphere in the northern hemisphere every 12 hours during the period of Jan. 1-15, 1993. RMS residuals of 2-3 TEC units are observed over the 20-80 degree latitude band. Various systematic errors affecting the TEC estimates are discussed. The capability of using these global maps to produce ionosphere calibrations for sites at which no GPS data are available is investigated.

ionospheric total electron content GPS global iono↗
NASA NTRS2018

Enabling Reanalysis Research Using the Collaborative Reanalysis Technical Environment (CREATE)

Modern atmospheric and oceanic reanalysis are valuable assets for atmospheric research and climate monitoring (Kalnay et al. 1996). Now that most reanalysis records are more than 36 years long, the data have become more useful for climate modeling research (Dole et al. 2008). For investigators who need to use multiple reanalysis, a common challenge is that the data are distributed at various sites and often in different formats. The NASA CREATE system provides access to the data in one location in a standard format (one variable per file and standardized metadata in the CMIP5 style; see Table 1 for a list of the key acronyms used in this paper). The collection includes monthly and 6-hourly data from the seven major atmospheric reanalysis: CFSR (Saha et al. 2010), ERA-Interim (Dee et al. 2011), MERRA (Rienecker et al. 2011), MERRA-2 (Gelaro et al. 2017), JRA-25 (Onogi et al. 2007), JRA-55 (Kobayashi et al. 2014), and 20CRv2c (Compo et al. 2011). An ancillary portion of CREATE includes eight ocean reanalysis: NCEP CFSR, CMCC C-GLORSv5 (Storto et al. 2016), ECMWF ORAS4 (Balmaseda et al.2013), ECMWF ORAP5.0 (Zuo et al. 2015), University of Hamburg GECCO2 (Köhl 2015), GFDL ECDA (Zhang et al. 2007), NOAA GODAS (Saha et al. 2010), and MOVE/MRI.COM-G2i (Toyoda et al. 2016). The ocean state variables were similarly reformatted but were then also regridded onto a common horizontal and vertical grid. This approach facilitated the calculation of an ensemble average and spread that is also published alongside the native gridded data. A third reanalysis product is a global hourly 0.5° land surface air temperature dataset constructed by Wang and Zeng (2013). All three datasets are distributed through the ESGF in a format consistent with the CMIP style described by Cinquini et al. (2014).

Potter, Gerald L.↗
NASA NTRS1976

Preliminary design review package for the solar heating and cooling central data processing system

The Central Data Processing System (CDPS) is designed to transform the raw data collected at remote sites into performance evaluation information for assessing the performance of solar heating and cooling systems. Software requirements for the CDPS are described. The programming standards to be used in development, documentation, and maintenance of the software are discussed along with the CDPS operations approach in support of daily data collection and processing.

Source record↗
NASA NTRS2016

Assessment of SNPP VIIRS VIS NIR Radiometric Calibration Stability Using Aqua MODIS and Invariant Surface Targets

The first Visible Infrared Imaging Radiometer Suite (VIIRS) is onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite. As a primary sensor, it collects imagery and radiometric measurements of the land, atmosphere, cryosphere, and oceans in the spectral regions from visible (VIS) to long-wave infrared. NASA's National Polar-orbiting Partnership (NPP) VIIRS Characterization Support Team has been actively involved in the VIIRS radiometric and geometric calibration to support its Science Team Principal Investigators for their independent quality assessment of VIIRS Environmental Data Records. This paper presents the performance assessment of the radiometric calibration stability of the VIIRS VIS and NIR spectral bands using measurements from SNPP VIIRS and Aqua MODIS simultaneous nadir overpasses and over the invariant surface targets at the Libya-4 desert and Antarctic Dome Concordia snow sites. The VIIRS sensor data records (SDRs) used in this paper are reprocessed by the NASA SNPP Land Product Evaluation and Analysis Tool Element. This paper shows that the reprocessed VIIRS SDRs have been consistently calibrated from the beginning of the mission, and the calibration stability is similar to or better than MODIS. Results from different approaches indicate that the calibrations of the VIIRS VIS and NIR spectral bands are maintained to be stable to within 1% over the first three-year mission. The absolute calibration differences between VIIRS and MODIS are within 2%, with an exception for the 0.865-m band, after correction of their spectral response differences.

Wu, Aisheng↗
NASA NTRS1986

A new algorithm for microwave delay estimation from water vapor radiometer data

A new algorithm has been developed for the estimation of tropospheric microwave path delays from water vapor radiometer (WVR) data, which does not require site and weather dependent empirical parameters to produce high accuracy. Instead of taking the conventional linear approach, the new algorithm first uses the observables with an emission model to determine an approximate form of the vertical water vapor distribution which is then explicitly integrated to estimate wet path delays, in a second step. The intrinsic accuracy of this algorithm has been examined for two channel WVR data using path delays and stimulated observables computed from archived radiosonde data. It is found that annual RMS errors for a wide range of sites are in the range from 1.3 mm to 2.3 mm, in the absence of clouds. This is comparable to the best overall accuracy obtainable from conventional linear algorithms, which must be tailored to site and weather conditions using large radiosonde data bases. The new algorithm's accuracy and flexibility are indications that it may be a good candidate for almost all WVR data interpretation.

Robinson, S. E.↗
NASA NTRS2022

NASA’s Lunar Trailblazer Mission: A Pioneering Small Satellite for Lunar Water and Lunar Geology

Selected in 2019 as a NASA SIMPLEx mission, Lunar Trailblazer is in implementation for flight system delivery at the end of 2022. The mission’s goal is to understand the form, abundance, and distribution of water on the Moon and the lunar water cycle. Lunar Trailblazer also collects data of candidate landing sites to inform planning for future human and robotic exploration of the Moon and evaluate the potential for in situ resource utilization. Lunar Trailblazer’s two science instruments, the High-resolution Volatiles and Minerals Moon Mapper (HVM3) and the Lunar Thermal Mapper (LTM) provide simultaneous high-resolution spectral imaging data to map OH/water, crustal composition, and thermophysical properties from a 100±30 km lunar polar orbit. The ~210-kg flight system deploys from an ESPA Grande and utilizes a ~1000 m/s ΔV hydrazine chemical propulsion system, similar to that employed by GRAIL. Trailblazing elements include the novel state-of-the-art dataset collected at substantially reduced price point, fully geographically co-registered data products delivered to the Planetary Data System, planetary mission team demographics, Caltech campus mission operations, and student staffing of select mission ops roles. Lunar Trailblazer’s pioneering development is providing key lessons learned for future planetary small spacecraft.

Zareh, Shannon↗
NASA NTRS2014

How Do Various Maize Crop Models Vary in Their Responses to Climate Change Factors?

Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly -0.5 Mg ha(sup 1) per degC. Doubling [CO2] from 360 to 720 lmol mol 1 increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2] among models. Model responses to temperature and [CO2] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information.

carbon dioxide↗
NASA NTRS1987

Analysis of forest and forest clearings in Amazonia with Landsat and Shuttle Imaging Radar-A data

Landsat and Shuttle Imaging Radar-A L band (23.5 cm wavelength) data from 1981 were used to analyze areas of intact tropical forest and areas recently cleared from forest for agriculture and pasture in Mato Grosso, Brazil. Portions of SIR-A Data Takes #24C and #31 film were digitized using a microdensitometer. Landsat MSS data of July 1981 were also examined. The digital values from SIR-A DT 31 were compared with the normalized difference vegetation index values (NDVI) from the Landsat data for the same sites. Contrary to expectations some cleared areas had brighter radar responses than surrounding forest. The explanation seems to be that a recently cleared forest (cut and burned during the dry season) is texturally very rough as the exposed standing and fallen boles and woody litter may function as effective corner or dihedral reflectors. Combining radar data with NDVI data may help to assess the relative age of forest clearings and determine differences in both woody and green leaf biomass of primary and secondary tropical forests.

Stone, Thomas A.↗
NASA NTRS2002

Measurement Sets and Sites Commonly used for Characterizations

Scientists with NASA's Earth Science Applications Directorate are creating a well-characterized Verification & Validation (V&V) site at the Stennis Space Center (SSC). This site enables the in-flight characterization of remote sensing systems and the data that they require. The data are predominantly acquired by commercial, high-spatial resolution satellite systems, such as IKONOS and QuickBird 2, and airborne systems. The smaller scale of these newer high-resolution remote sensing systems allows scientists to characterize the geometric, spatial, and radiometric data properties using a single V&V site. The targets and techniques used to characterize data from these newer systems can differ significantly from the earlier, coarser spatial resolution systems. Scientists are also using the SSC V&V site to characterize thermal infrared systems and active Light Detection and Ranging (LIDAR) systems. SSC employs geodetic targets, edge targets, radiometric tarps, and thermal calibration ponds to characterize remote sensing data products. This paper presents a proposed set of required measurements for visible-through-longwave infrared remote sensing systems, and a description of the Stennis characterization. Other topics discussed inslude: 1) use of ancillary atmospheric and solar measurements taken at SSC that support various characterizations, 2) other sites used for radiometric, geometric, and spatial characterization in the continental United States,a nd 3) the need for a standardized technique to be adopted by the Committee on Earth Observation Satellites (CEOS) and other organizations.

Pagnutti, Mary↗
NASA NTRS1975

S193 radiometer brightness temperature precision/accuracy for SL2 and SL3

The precision and accuracy with which the S193 radiometer measured the brightness temperature of ground scenes is investigated. Estimates were derived from data collected during Skylab missions. Homogeneous ground sites were selected and S193 radiometer brightness temperature data analyzed. The precision was expressed as the standard deviation of the radiometer acquired brightness temperature. Precision was determined to be 2.40 K or better depending on mode and target temperature.

Pounds, D. J.↗
NASA NTRS2000

BOREAS TGB-10 Oxidant Concentration Data over the SSA

The BOREAS TGB-10 team collected several trace gas data sets in its efforts to determine the role of biogenic hydrocarbon emissions with respect to boreal forest carbon cycles. This data set contains measured peroxide (H2O2 and total organic peroxides (ROOH)) and ozone concentrations as well as H2O2 and ROOH deposition velocities. These data were obtained at the SSA-OJP site from May to September 1994. The data are stored in tabular ASCII files. Some important results were: (1) Ozone concentrations were consistently low, 20-30 ppb, during the summer of 1994. (2) Peroxide concentrations showed a seasonal variation with highest concentrations occurring in July (IFC-2). (3) Midday H2O2 levels averaged around 1.4 ppb during IFC-2 and 0.4 - 0.5 ppb during IFC's 1 and 3. (4) Midday organic peroxide concentrations were lower, averaging 0.8 ppb during IFC-2, and 0.4 - 0.5 ppb during IFC's 1 and 3. (5) The rough pine forest canopy serves as a significant sink for H2O2. (6) Midday H2O2 deposition velocities averaged 4 - 7 cm/s. (7) Organic peroxide deposition velocities (measured as total ROOH) were approximately 40% as large as those of H2O2.

Hall, Forrest G.↗
NASA NTRS2000

BOREAS TGB-10 Volatile Organic Carbon Data over the SSA

The BOREAS TGB-10 team collected several trace gas data sets in its efforts to determine the role of biogenic hydrocarbon emissions with respect to boreal forest carbon cycles. This data set contains measured VOC concentrations. These data were obtained at the SSA-OJP site from May to September 1994. The data are stored in tabular ASCII files.

Westberg, Hal↗
NASA NTRS1991

High resolution lunar radar studies: Preliminary results

High resolution radar data for the lunar surface were acquired over 14 sites in June and November 1990 using the new 10 MHz data taking system at the Arecibo Observatory. The raw data collected for each site covers an area approximately 100 by 400 km and will be processed using delay-Doppler techniques into images of backscatter cross section with three fo four independent looks. All observations transmitted a circularly polarized signal and both senses of circular polarization were received containing the polarized and depolarized component of the backscatter signal. The relative power in these two polarizations provides useful information on properties of the surface, in particular surface roughness. The effort to date focused on the initial data analysis with new software written to perform a full synthetic aperture focusing on the raw radar data. This analysis will involve the use of complementary high resolution optical and topographic data sets to aid interpretation of surface scattering mechanisms.

Stacy, Nicholas J. S.↗
NASA NTRS2021

Advances in the Ocean Color Component of the Aerosol Robotic Network (AERONET-OC)

The Ocean Color Component of the Aerosol Robotic Network(AERONET-OC) supports activities related to ocean color such as validation of satellite data products, assessment of atmospheric correction schemes, and evaluation of bio-optical models through globally distributed standardized measurements of water-leaving radiance and aerosol optical depth. In view of duly assisting the AERONET-OC data user community, this work (i) summarizes the latest investigations on a number of scientific issues related to above-water radiometry, (ii) emphasizes the network expansion that from 2002 until the end of 2020 integrated 31 effective measurement sites, (iii) shows the equivalence of data product accuracy across sites and time for measurements performed with different instrument series, (iv) illustrates the variety of water types represented by the network sites ensuring validation activities across a diversity of observation conditions, and (v) documents the availability of water-leaving radiance data corrected for bidirectional effects by applying a method specifically developed for chlorophyll-a-dominated waters and an alternative one that is likely suitable for any water type.

In situ oceanic observations↗
NASA NTRS1975

Mapping forest vegetation with ERTS-1 MSS data and automatic data processing techniques

This study was undertaken with the intent of elucidating the forest mapping capabilities of ERTS-1 MSS data when analyzed with the aid of LARS' automatic data processing techniques. The site for this investigation was the Great Dismal Swamp, a 210,000 acre wilderness area located on the Middle Atlantic coastal plain. Due to inadequate ground truth information on the distribution of vegetation within the swamp, an unsupervised classification scheme was utilized. Initially pictureprints, resembling low resolution photographs, were generated in each of the four ERTS-1 channels. Data found within rectangular training fields was then clustered into 13 spectral groups and defined statistically. Using a maximum likelihood classification scheme, the unknown data points were subsequently classified into one of the designated training classes. Training field data was classified with a high degree of accuracy (greater than 95 percent), and progress is being made towards identifying the mapped spectral classes.

Messmore, J.↗