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At least 1,549 records · Page 86
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NASA NTRS1976

The impact of stratospheric variability on measurement programs for minor constituents

The scales of temporal and spatial variations in stratospheric minor species concentrations and dynamical quantities are briefly reviewed. Despite the fact that the stratosphere is often considered to be a very quiescent region of the atmosphere, it exhibits transient and generally unpredictable episodes of intense activity. The resultant necessity for some degree of coordination between different observers in their choice of locations and times for measurements of minor constituents is emphasized. A specific suggestion is provided for one or more short 'International Stratospheric Periods' whose duration would depend upon the time of year. During these short periods, as many observers as possible would perform an integrated series of observations designed to optimize the usefulness of their data to atmospheric scientists.

Prinn, R. G.↗
NASA NTRS1980

Evidence for globally coherent variability in solar magnetic flux emergence

We examine the large-scale spatial and temporal variations in the emergence of X-ray bright points on the sun, in order to study the global properties of magnetic flux emergence. Major variations in the rate of flux emergence are observed at all solar latitudes, on a time scale of 3-5 months. The most economical explanation of the observations is that the full sun participated in a single large eruptive event during the available 8 month observing period from Skylab in 1973. The peak of this global event corresponds in time to the eruption of a major complex of activity. Moreover, it appears that the only portion of the solar surface which deviates from the above pattern of behavior is the low latitude region in the vicinity of the AR complex; this area shows a temporary depletion immediately following the AR outburst. The high-latitude regions in both hemispheres show the same variation and appear to lead the low-latitude emergence by approximately 1 month.

Golub, L.↗
NASA NTRS2012

Interannual Variability of OLR as Observed by AIRS and CERES

This paper compares spatial anomaly time series of OLR (Outgoing Longwave Radiation) and OLR(sub CLR) (Clear Sky OLR) as determined using observations from CERES Terra and AIRS over the time period September 2002 through June 2011. Both AIRS and CERES show a significant decrease in global mean and tropical mean OLR over this time period. We find excellent agreement of the anomaly time-series of the two OLR data sets in almost every detail, down to 1 deg X 1 deg spatial grid point level. The extremely close agreement of OLR anomaly time series derived from observations by two different instruments implies that both sets of results must be highly stable. This agreement also validates to some extent the anomaly time series of the AIRS derived products used in the computation of the AIRS OLR product. The paper also examines the correlations of anomaly time series of AIRS and CERES OLR, on different spatial scales, as well as those of other AIRS derived products, with that of the NOAA Sea Surface Temperature (SST) product averaged over the NOAA Nino-4 spatial region. We refer to these SST anomalies as the El Nino Index. Large spatially coherent positive and negative correlations of OLR anomaly time series with that of the El Nino Index are found in different spatial regions. Anomalies of global mean, and especially tropical mean, OLR are highly positively correlated with the El Nino Index. These correlations explain that the recent global and tropical mean decreases in OLR over the period September 2002 through June 2011, as observed by both AIRS and CERES, are primarily the result of a transition from an El Nino condition at the beginning of the data record to La Nina conditions toward the end of the data period. We show that the close correlation of global mean, and especially tropical mean, OLR anomalies with the El Nino Index can be well accounted for by temporal changes of OLR within two spatial regions which lie outside the NOAA Nino-4 region, in which anomalies of cloud cover and mid-tropospheric water vapor are both highly negatively correlated with the El Nino Index. Agreement of the AIRS and CERES OLR(sub CLR) anomaly time series is less good, which may be a result of the large sampling differences in the ensemble of cases included in each OLR(sub CLR) data set.

Susskind, Joel↗
NASA NTRS2012

Interannual Variability of OLR as Observed by AIRS and CERES

The paper examines spatial anomaly time series of Outgoing Longwave Radiation (OLR) and Clear Sky OLR (OLR(sub CLR)) as determined using observations from CERES Terra and AIRS over the time period September 2002 through June 2011. We find excellent agreement of the two OLR data sets in almost every detail down to the x11deg spatial grid point level. The extremely close agreement of OLR anomaly time series derived from observations by two different instruments implies high stability of both sets of results. Anomalies of global mean, and especially tropical mean, OLR are shown to be strongly correlated with an El Nino index. These correlations explain that the recent global and tropical mean decreases in OLR over the time period studied are primarily the result of a transition from an El Nino condition at the beginning of the data record to La Nina conditions toward the end of the data period. We show that the close correlation of mean OLR anomalies with the El Nino Index can be well accounted for by temporal changes of OLR within two spatial regions, one to the east of, and one to the west of, the NOAA Nino-4 region. Anomalies of OLR in these two spatial regions are both strongly correlated with the El Nino Index as a result of the strong anti-correlation of anomalies of cloud cover and mid-tropospheric water vapor in these two regions with the El Nino Index.

Susskind, Joel↗
NASA NTRS1985

Preliminary Evaluation of TM for Soils Information

The capability of the LANDSAT TM for providing information for soil association maps and for detecting soil properties (variability within vegetated fields) was assessed using TM imagery of fields in Mississippi County, Arkansas that were planted with rice, cotton, and soybeans. Results indicate that the TM bands are providing information that is related to the soil properties within the field. Over large areas, these bands also appear to provide information that is related to the soil properties that are important to plant condition. While these results are only an indication of the information that TM can provide, they do indicate the TM data--especially, the mid-TR and thermal bands--show the capability for separating vegetated soil landscapes on a broad basis. The analysis at the field level with a growing crop also indicates that TM, with its additional and narrower bands and improved spatial and radiometric resolution is influenced by within field variability due to soils that has to be accounted for in the analysis of TM data.

Thompson, D. R.↗
DOE OSTI2025

Second-generation downscaled earth system model data using generative machine learning

The second-generation Sup3rCC dataset provides high-resolution meteorological data generated through the downscaling of multiple earth system models (ESMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). This downscaling is performed through application of a generative machine learning approach called Super-Resolution for Renewable Resource Data (sup3r). This dataset builds on the first-generation Sup3rCC data by applying improved bias correction methods and adding downscaled precipitation to the output variables. As with the first Sup3rCC version, the data still include temperature, wind speed and direction at multiple heights, pressure, three components of downwelling solar radiation, and relative humidity—all at 4-kilometer (km) hourly resolution over the contiguous United States. This is a 25x spatial enhancement and 24x temporal enhancement of the source 100-km daily-average ESM data. This extension of the Sup3rCC dataset includes data from six ESMs from two shared socioeconomic pathways (SSPs) totaling 400 years of data with multiple future projections of changing meteorological conditions. The scenario selection was based on a structured evaluation of historical ESM skill and comprehensive representation of possible trajectories of future climate change in temperature, humidity, precipitation, solar irradiance, and near-surface wind speeds. The inclusion of multiple future projections is intended to enable users to assess key drivers of un 36 certainty and variability. All data are double-bias corrected, resulting in a product that can be used out-of-the-box for energy system analysis with minimal historical bias. The potential applications of Sup3rCC data extend to various topics in renewable energy resource assessment, energy systems modeling, and grid resilience studies. High-resolution future meteorological projections are critical for evaluating the effects of changing meteorological conditions on renewable energy generation, energy demand, and for optimizing energy storage and grid infrastructure. The 4-km hourly resolution of the downscaled data enables understanding of spatial and temporal variability at the scales necessary for energy system operational planning. In addition, the dataset can support risk assessments by providing detailed information on possible future extreme weather events and long-term meteorological variability at scales relevant to energy infrastructure. By offering an enhanced representation of possible future meteorological conditions, the second-generation Sup3rCC dataset enables more precise modeling of energy resilience and adaptation strategies in response to changing meteorological conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2015

Tropospheric Emissions: Monitoring of Pollution Overview

TEMPO is now well into its implementation phase, having passed both its Key Decision Point C and the Critical Design Review (CDR) for the instrument. The CDR for the ground systems will occur in March 2016 and the CDR for the Mission component at a later date, after the host spacecraft has been selected. TEMPO is on schedule to measure atmospheric pollution for greater North America from space using ultraviolet and visible spectroscopy. TEMPO measures from Mexico City to the Canadian oil sands, and from the Atlantic to the Pacific, hourly and at high spatial resolution. TEMPO provides a tropospheric measurement suite that includes the key elements of tropospheric air pollution chemistry. Measurements are from geostationary (GEO) orbit, to capture the inherent high variability in the diurnal cycle of emissions and chemistry. The small product spatial footprint resolves pollution sources at sub-urban scale. Together, this temporal and spatial resolution improves emission inventories, monitors population exposure, and enables effective emission-control strategies. TEMPO takes advantage of a GEO host spacecraft to provide a modest cost mission that measures the spectra required to retrieve O3, NO2, SO2, H2CO, C2H2O2, H2O, aerosols, cloud parameters, and UVB radiation. TEMPO thus measures the major elements, directly or by proxy, in the tropospheric O3 chemistry cycle. Multi-spectral observations provide sensitivity to O3 in the lowermost troposphere, substantially reducing uncertainty in air quality predictions by 50 percent. TEMPO quantifies and tracks the evolution of aerosol loading. It provides near-real-time air quality products that will be made widely, publicly available. TEMPO provides much of the atmospheric measurement capability recommended for GEO-CAPE in the 2007 National Research Council Decadal Survey, Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond. Instruments from Europe (Sentinel 4) and Asia (GEMS) will form parts of a global GEO constellation for pollution monitoring later this decade, with a major focus on intercontinental pollution transport. TEMPO will launch at a prime time to be a component of this constellation.

Chance, Kelly↗
NASA NTRS1995

A Comparison between the TOPEX/POSEIDON Data and a Global Ocean General Circulation Model during 1992-1993

The TOPEX/POSEIDON altimetric sea level observation during 1992-1993 was used to validate the simulation made by a global ocean general circulation model (OGCM) forced by the daily wind stress and heat flux derived from the National Meteorological Center operational analysis. The OGCM is a version of the modular ocean model with a horizontal resolution of 2 deg longitude and 1 deg latitude and 22 levels in the vertical. The model simulation is compared to the observation at spatial scales of the order of 500 km and larger. Only the temporal variations are examined. The variability is composed primarily of the annual cycle and intraseasonal fluctuations (periods shorter than 100 days). The basic features of the annual cycle are simulated well by the model. Major discrepancies are found in the eastern tropical Pacific, as well as the eastern North Pacific and most of the interior of the North Atlantic. The culprit is suspected to be the inadequate heat forcing and mixing parameterizations of the model. Significant intraseasonal variability is found in the central North Pacific and the Southern Ocean. The simulation is highly correlated with the observation at periods from 20 to 100 days. The spatial scales are larger than 1000 km in many places. These variabilities are apparently the barotropic response of the ocean to wind forcing. The results of the study provide a basis for future assimilation of the data into the OGCM for improved description of the large-scale ocean variabilities.

Chao, Yi↗
DOE OSTI2025

Genetic Identification of Lamprey Genera and Anadromous Ecotypes in Watersheds of the Northeastern Pacific Ocean

ABSTRACT Nonparasitic, nonmigratory Western Brook Lamprey (WBL; Lampetra ayresii ), and parasitic, anadromous Western River Lamprey (WRL; L. ayresii ) are sympatric lampreys that likely represent different life history variations of a single species. Novel genetic tools are critical for differentiating WBL and WRL, whose larvae preclude morphological identification (ID) and will enable comprehensive assessment of imperiled native lampreys of the Northeastern Pacific (including WBL, WRL, and Pacific Lamprey, Entosphenus tridentatus ). We developed 47 candidate single nucleotide polymorphism (SNP) markers using whole genome resequencing of WBL ( N = 24) and WRL ( N = 15) from Ksi Ts'oohl Ts'ap Creek (Nass River, British Columbia, Canada) which are likely ecotypes distinguished by few divergent SNPs across multiple chromosomes. We used five novel candidate SNPs to perform genetic ID of WBL and WRL ecotypes in collections of mixed native lampreys from lower Columbia River tributaries ( N = 1474), Ksi Ts'oohl Ts'ap Creek ( N = 352), and ocean phase WRL from the Georgia Basin (Salish Sea, British Columbia, Canada; N = 91). Two previously published SNPs were used to ID genera, Entosphenus versus Lampetra . Morphological ID utilized photographs collected from a subset of genotyped lampreys, and high concordance was demonstrated between ID methods for genera (99%) and Lampetra ecotypes (> 98%). We characterized spatial and temporal composition of lamprey genera and ecotypes surveyed across NE Pacific tributaries under the expectation these compositions would be similar across nearby sites and across years at the same site. Proportions of lamprey genera were highly variable within regions and across years; however, Lampetra ecotypic proportions were spatially and temporally stable. WRL were rare in lower Columbia tributaries (~1% average rate among Lampetra ) and common further north (> 40% of Lampetra ). Genetic ID methods are powerful monitoring tools that create the novel ability to ascertain genera and ecotypes regardless of life stage, while increasing the efficiency of surveys by eliminating time‐intensive morphological data collection.

Silver, G. S. [Columbia River Inter‐Tribal Fish Co↗
NASA NTRS2003

Three-Gorge Reservoir: A 'Controlled Experiment' for Calibration/Validation of Time-Variable Gravity Signals Detected from Space

With the advances of measurements, modern space geodesy has become a new type of remote sensing for the Earth dynamics, especially for mass transports in the geophysical fluids on large spatial scales. A case in point is the space gravity mission GRACE (Gravity Recovery And Climate Experiment) which has been in orbit collecting gravity data since early 2002. The data promise to be able to detect changes of water mass equivalent to sub-cm thickness on spatial scale of several hundred km every month or so. China s Three-Gorge Reservoir has already started the process of water impoundment in phases. By 2009,40 km3 of water will be stored behind one of the world s highest dams and spanning a section of middle Yangtze River about 600 km in length. For the GRACE observations, the Three-Gorge Reservoir would represent a geophysical controlled experiment , one that offers a unique opportunity to do detailed geophysical studies. -- Assuming a complete documentation of the water level and history of the water impoundment process and aided with a continual monitoring of the lithospheric loading response (such as in area gravity and deformation), one has at hand basically a classical forwardinverse modeling problem of surface loading, where the input and certain output are known. The invisible portion of the impounded water, i.e. underground storage, poses either added values as an observable or a complication as an unknown to be modeled. Wang (2000) has studied the possible loading effects on a local scale; we here aim for larger spatial scales upwards from several hundred km, with emphasis on the time-variable gravity signals that can be detected by GRACE and follow-on missions. Results using the Green s function approach on the PREM elastic Earth model indicate the geoid height variations reaching several millimeters on wavelengths of about a thousand kilometers. The corresponding vertical deformations have amplitude of a few centimeters. In terms of long-wavelength spherical harmonics, the induced geoid height variations are very close to the accuracy of GRACE- recoverable gravity field, while the low-degree (2 to 5) harmonics should be detectable. With a large regional time-variable gravity signal, the Three-Gorge experiment can serve as a useful calibration/verification for GRACE (including the elastic loading effects), and future gravity missions (especially for visco-elastic yielding as well as underground water variations).

Chao, Benjamin F.↗
NASA NTRS1994

Do Right- and Left-Handed Monkeys Differ on Cognitive Measures?

Twelve left- and 14 right-handed monkeys were compared on 6 measures of cognitive performance (2 maze-solving tasks, matching-to-sample, delayed matching-to-sample, delayed response using spatial cues, and delayed response using form cues). The dependent variable was trials-to-training criterion for each of the 6 tasks. Significant differences were found between left- and right-handed monkeys on the 2 versions of the delayed response task. Right-handed monkeys reached criterion significantly faster on the form cue version of the task, whereas left-handed monkeys reached criterion significantly faster on delayed response for spatial position (p less than .05). The results suggest that sensitive hand preference measures of laterality can reveal differences in cognitive performance, which in turn may reflect underlying laterality in functional organization of the nervous system.

Hopkins, William D.↗
NASA NTRS2001

Large Scale Characteristics and Variability of the Global Sea Ice Cover

More than two decades of satellite passive microwave data are used to study and evaluate the large scale characteristics and the changing state of the sea ice cover in both the Northern and Southern Hemispheres. Satellite data provide day/night almost continuous observation of global sea ice cover thereby enabling quantitative variability studies at various time scales. Despite coarse sensor resolution, spatial detail is provided through the use of sea ice concentrations which are derived using an algorithm that determines the fraction of ice and open water within each satellite footprint. Large seasonal fluctuations in the extent are apparent with those of the Southern Hemisphere having larger amplitudes but less symmetrical seasonal distribution than those of the Northern Hemisphere. The large scale interannual variability of the ice cover has been evaluated globally as well as regionally and in the Northern Hemisphere, the yearly anomaly maps show a predominance of positive values in the 1980s and negative values in the 1990s. Regression analysis show that the ice extent and ice area are on a decline at the rate of -2.0 +/- 0.5% and -3.1 +/- 0.3% per decade, respectively, in the Northern Hemisphere but there are regions like the Bering Sea with positive trends. What is intriguing, however, is that the perennial sea ice cover has been declining at a much faster rate than for the entire hemisphere, i.e., 6.7 +/- 2.4% and 8.3 +/- 2.4 % per decade for ice extent and ice area, respectively. The perennial ice cover consists mainly of thick multiyear ice floes, and its persistent decline would mean a reduction in the average thickness of sea ice and a change in the overall characteristics of the Arctic sea ice cover. Furthermore, the yearly anomaly patterns are coherent with those of surface temperatures derived from 19 years of thermal infrared AVHRR data. The latter also shows that in consolidated ice regions, the average temperature during summer minima has been increasing at about 0.9 +/- 0.6 K per decade.

Comiso, Josefino C.↗
NASA NTRS2003

Production, Outflow Velocity, and Radial Distribution of H2O and OH in the Coma of Comet C/1995 O1 [Hale-Bopp] from Wide Field Imaging of OH

Observations of OH are a useful proxy of the water production rate (Q(sub H2O)) and outflow velocity (V(sub out)) in comets. From wide field images taken on 03/28/1997 and 04/08/1997 that capture the entire scale length of the OH coma of comet C/1995 O1 (Hale-Bopp), we obtain Q(sub H2O) from the model-independent method of aperture summation. With an adaptive ring summation algorithm, we extract the radial brightness distribution of OH 0-0 band emission out to cometocentric distances of up to 10(exp 6) km, both as azimuthal averages and in quadrants covering different position angles relative to the comet-Sun line. These profiles are fit using both fixed and variable velocity 2-component spherical expansion models to estimate V(sub OH) with increasing distance from the nucleus. The OH coma of Hale-Bopp was more spatially extended than previous comets, and this extension is best matched by a variable acceleration of H2O and OH that acted across the entire coma, but was strongest within 1-2 x 10(exp 4) km from the nucleus. Our models indicate that V(sub OH) at the edge of our detectable field of view (10(exp 6) km) was approx. 2-3 times greater in Hale-Bopp than for a 1P/Halley-class comet at 1 AU, which is consistent with the results of more sophisticated gas-kinetic models, extrapolation from previous observations of OH in comets with Q(sub H2O) greater than 10(exp 29)/s , and direct radio measurements of the outer coma Hale-Bopp OH velocity. The most probable source of this acceleration is thermalization of the excess energy of dissociation of H2O and OH over an extended collisional coma. When the coma is broken down by quadrants in position angle, we find an azimuthal asymmetry in the radial distribution that is characterized by an increase in the spatial extent of OH in the region between the orbit-trailing and anti-sunward directions. Model fits specific to this area and comparison with radio OH measurements suggest greater acceleration here, with V(sub OH) approx. 1.5 times greater at a 10(exp 6) km cometocentric distance than elsewhere in the coma. We discuss several mechanisms that may have acted within the coma to produce the observed effect.

Harris, Walter M.↗
DOE OSTI2026

Short-term electricity load forecasting: Application-driven evaluation of machine learning models across spatial and temporal scales

As we transition towards a decarbonized economy, the integration of variable renewable energy resources and new demands (e.g., electric vehicles, heat pumps) into the electricity grid places unprecedented pressure on grid operators to effectively anticipate and manage peak load. In this context, machine learning algorithms are proving to be indispensable for accurate short-term load forecasting, a crucial task to address these challenges. This study benchmarks 6 machine learning algorithms, including three neural networks and three tree-based algorithms, across various levels of spatial aggregation and time horizons (1, 4, 8, 24, and 48 h). The central contribution of this work is the comparison and analysis of load forecasting models not only based on statistical metrics, but also based on a novel error metric, which evaluates the cost implications of forecast errors for power system stakeholders. Results show that tree-based models outperform neural networks, based on statistical metrics, and yield less skewed error distributions for most spatial scales. However, through the lens of the novel error metric, neural networks are the more competitive choice, especially for forecast horizons that exceed 8 h. The study concludes with actionable recommendations to grid operators and highlights the need for the development of error metrics that link forecasting accuracy to operational costs. To promote transparency and open science, the datasets and Python code are open-sourced via a supplementary repository.

Houben, Nikolaus↗
DOE OSTI2022

Understanding the Drivers of Atlantic Multidecadal Variability using a Stochastic Model Hierarchy

The relative importance of ocean and atmospheric dynamics in generating Atlantic Multidecadal Variability (AMV) remains an open question. Comparisons between climate models with SLAB and fully-dynamic (FULL) ocean components are often used to explore this question, but cannot reveal how individual ocean processes generate these differences. We build a hierarchy of physically interpretable stochastic models to investigate the contribution of two upper-ocean processes to AMV: the role of seasonal variation and mixed-layer entrainment. This interpretability arises from the stochastic model’s simplified representation of sea surface temperature (SST), considering only the local upper ocean response to white-noise atmospheric forcing and its impact on surface heat exchange. We focus on understanding differences between SLAB and FULL non-eddy resolving pre-industrial control simulations of the Community Earth System Model 1 (CESM), and estimate the stochastic model parameters from each respective simulation. Despite its simplicity, the stochastic model reproduces temporal characteristics of SST variability in the SPG, including reemergence, seasonal-to-interannual persistence and power spectra. Furthermore, unrealistically persistent SST of the CESM-SLAB ocean simulation is reproduced in the equivalent stochastic model configuration where the mixed-layer depth (MLD) is constant. The stochastic model also reveals that vertical entrainment primarily damps SST variability, thus explaining why SLAB exhibits larger SST variance than FULL. Here, the stochastic model driven by temporally stochastic, spatially coherent forcing patterns reproduces the canonical AMV pattern. However, the amplitude of low-frequency variability remains underestimated, suggesting a role for ocean dynamics beyond entrainment.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

Large Scale Variability of Phytoplankton Blooms in the Arctic and Peripheral Seas: Relationships with Sea Ice, Temperature, Clouds, and Wind

Spatially detailed satellite data of mean color, sea ice concentration, surface temperature, clouds, and wind have been analyzed to quantify and study the large scale regional and temporal variability of phytoplankton blooms in the Arctic and peripheral seas from 1998 to 2002. In the Arctic basin, phytoplankton chlorophyll displays a large symmetry with the Eastern Arctic having about fivefold higher concentrations than those of the Western Arctic. Large monthly and yearly variability is also observed in the peripheral seas with the largest blooms occurring in the Bering Sea, Sea of Okhotsk, and the Barents Sea during spring. There is large interannual and seasonal variability in biomass with average chlorophyll concentrations in 2002 and 2001 being higher than earlier years in spring and summer. The seasonality in the latitudinal distribution of blooms is also very different such that the North Atlantic is usually most expansive in spring while the North Pacific is more extensive in autumn. Environmental factors that influence phytoplankton growth were examined, and results show relatively high negative correlation with sea ice retreat and strong positive correlation with temperature in early spring. Plankton growth, as indicated by biomass accumulation, in the Arctic and subarctic increases up to a threshold surface temperature of about 276-277 degree K (3-4 degree C) beyond which the concentrations start to decrease suggesting an optimal temperature or nutrient depletion. The correlation with clouds is significant in some areas but negligible in other areas, while the correlations with wind speed and its components are generally weak. The effects of clouds and winds are less predictable with weekly climatologies because of unknown effects of averaging variable and intermittent physical forcing (e.g. over storm event scales with mixing and upwelling of nutrients) and the time scales of acclimation by the phytoplankton.

Comiso, Josefino C.↗
NASA NTRS1994

Precision orbit determination of altimetric satellites

The ability to determine accurate global sea level variations is important to both detection and understanding of changes in climate patterns. Sea level variability occurs over a wide spectrum of temporal and spatial scales, and precise global measurements are only recently possible with the advent of spaceborne satellite radar altimetry missions. One of the inherent requirements for accurate determination of absolute sea surface topography is that the altimetric satellite orbits be computed with sub-decimeter accuracy within a well defined terrestrial reference frame. SLR tracking in support of precision orbit determination of altimetric satellites is significant. Recent examples are the use of SLR as the primary tracking systems for TOPEX/Poseidon and for ERS-1 precision orbit determination. The current radial orbit accuracy for TOPEX/Poseidon is estimated to be around 3-4 cm, with geographically correlated orbit errors around 2 cm. The significance of the SLR tracking system is its ability to allow altimetric satellites to obtain absolute sea level measurements and thereby provide a link to other altimetry measurement systems for long-term sea level studies. SLR tracking allows the production of precise orbits which are well centered in an accurate terrestrial reference frame. With proper calibration of the radar altimeter, these precise orbits, along with the altimeter measurements, provide long term absolute sea level measurements. The U.S. Navy's Geosat mission is equipped with only Doppler beacons and lacks laser retroreflectors. However, its orbits, and even the Geosat orbits computed using the available full 40-station Tranet tracking network, yield orbits with significant north-south shifts with respect to the IERS terrestrial reference frame. The resulting Geosat sea surface topography will be tilted accordingly, making interpretation of long-term sea level variability studies difficult.

Shum, C. K.↗
NASA NTRS1993

Buckling response of laminates with spatially varying fiber orientations

The buckling response of a symmetrically laminated composite panel with a spatially varying fiber orientation has been analyzed. Variation of the fiber orientation angle as a function of the position in the panel results in a composite laminate with stiffness properties that are functions of the panel coordinates. The laminates are therefore termed variable stiffness panels. The fiber orientation is assumed to vary only in one spatial direction, although the analysis can be extended to fiber orientations that vary in two spatial directions. The Ritz Method has been used to find the buckling loads and buckling modes for the variable stiffness panels for two different cases. In one of the cases the fiber orientation is assumed to change in the direction of the applied load. The other case is the one in which the fiber orientation varies in a direction perpendicular to the loading direction. Improvements in the buckling load of up to 80 percent over straight fiber configurations were found. Results for three different panel aspect ratios are presented.

Olmedo, Reynaldo↗