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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Spectral Cloud-Filtering of AIRS Data: Non-Polar Ocean

The Atmospheric Infrared Sounder (AIRS) is a grating array spectrometer which covers the thermal infrared spectral range between 640 and 1700/cm. In order to retain the maximum radiometric accuracy of the AIRS data, the effects of cloud contamination have to be minimized. We discuss cloud filtering which uses the high spectral resolution of AIRS to identify about 100,000 of 500,000 non-polar ocean spectra per day as relatively "cloud-free". Based on the comparison of surface channels with the NCEP provided global real time sst (rtg.sst), AIRS surface sensitive channels have a cold bias ranging from O.5K during the day to 0.8K during the night. Day and night spatial coherence tests show that the cold bias is due to cloud contamination. During the day the cloud contamination is due to a 2-3% broken cloud cover at the 1-2 km altitude, characteristic of low stratus clouds. The cloud-contamination effects surface sensitive channels only. Cloud contamination can be reduced to 0.2K by combining the spectral filter with a spatial coherence threshold, but the yield drops to 16,000 spectra per day. AIRS was launched in May 2002 on the Earth Observing System (EOS) Aqua satellite. Since September 2002 it has returned 4 million spectra of the globe each day.

infrared↗
NASA NTRS1996

Spatial Transformation of the Vestibulo-Ocular Reflex during Spaceflight

It was hypothesized that the absence of the gravitational reference cues may be responsible for adaptive changes in the vestibulo-ocular reflex (VOR). These changes result in the alteration of the direction of the compensatory slow phase (SP) eye movements in microgravity. In order to test this hypothesis, the direction of the VOR SP relative to head motion was investigated in three astronauts during and after an eight-day orbital flight by passive sinusoidal pitch or yaw angular motion at two frequencies. The results of the inflight and postflight testing are considered. The observed deviation between VOR SP and head motion suggests that spatial transformation in the VOR occurred during adaptation to microgravity. It is considered that, although this spatial transformation might be due to a sensory bias, it may reflect central changes in the reference system used for spatial orientation in microgravity.

Clement, Gilles↗
NASA NTRS1989

Separate visual representations for perception and for visually guided behavior

Converging evidence from several sources indicates that two distinct representations of visual space mediate perception and visually guided behavior, respectively. The two maps of visual space follow different rules; spatial values in either one can be biased without affecting the other. Ordinarily the two maps give equivalent responses because both are veridically in register with the world; special techniques are required to pull them apart. One such technique is saccadic suppression: small target displacements during saccadic eye movements are not preceived, though the displacements can change eye movements or pointing to the target. A second way to separate cognitive and motor-oriented maps is with induced motion: a slowly moving frame will make a fixed target appear to drift in the opposite direction, while motor behavior toward the target is unchanged. The same result occurs with stroboscopic induced motion, where the frame jump abruptly and the target seems to jump in the opposite direction. A third method of separating cognitive and motor maps, requiring no motion of target, background or eye, is the Roelofs effect: a target surrounded by an off-center rectangular frame will appear to be off-center in the direction opposite the frame. Again the effect influences perception, but in half of the subjects it does not influence pointing to the target. This experience also reveals more characteristics of the maps and their interactions with one another, the motor map apparently has little or no memory, and must be fed from the biased cognitive map if an enforced delay occurs between stimulus presentation and motor response. In designing spatial displays, the results mean that what you see isn't necessarily what you get. Displays must be designed with either perception or visually guided behavior in mind.

Bridgeman, Bruce↗
NASA NTRS1995

Space and time aliasing structure is monthly mean polar-orbiting satellite data

Monthly mean wind fields from the European Remote Sensing Satellite (ERS1) scatterometer are presented. A banded structure which resembles the satellite subtrack is clearly and consistently apparent in the isotachs as well as the u and v components of the routinely produced fields. The structure also appears in the means of data from other polar-orbiting satellites and instruments. An experiment is designed to trace the cause of the banded structure. The European Centre for Medium-Range Weather Forecast (ECMWF) gridded surface wind analyses are used as a control set. These analyses are also sampled with the ERS1 temporal-spatial samplig pattern to form a simulated scatterometer wind set. Both sets are used to create monthly averages. The banded structures appear in the monthly mean simulated data but do not appear in the control set. It is concluded that the source of the banded structure lies in the spatial and temporal sampling of the polar-orbiting satellite which results in undersampling. The problem involves multiple timescales and space scales, oversampling and under-sampling in space, aliasing in the time and space domains, and preferentially sampled variability. It is shown that commonly used spatial smoothers (or filters), while producing visually pleasing results, also significantly bias the true mean. A three-dimensional spatial-temporal interpolator is designed and used to determine the mean field. It is found to produce satisfactory monthly means from both simulated and real ERS1 data. The implications to climate studies involving polar-orbiting satellite data are discussed.

Zeng, Lixin↗
NASA NTRS1982

Dynamic environments for space shuttle payloads

Payload bay dynamic data from the first two space shuttle flights are summarized and evaluated. Development of dynamic environment design and test criteria for shuttle payloads from measured flight data is discussed. Factors that must be considered are flight to flight variations, spatial variations, temporal variations, measurement bias errors and the degree of confidence desired that a predicted environment will not be exceeded in flight. Summary and conclusion reports will be published after STS-4 and at appropriate intervals thereafter. The nature of these future reports and their impact on the user community is discussed.

Kern, D. L.↗
NASA NTRS1985

Retrieval of sea surface temperatures from HIRS2/MSU

The methods used at the Goddard Laboratory for Atmospheres (GLA) to retrieve sea surface temperatures from HIRS2/MSU data for the last 2 months of the NASA sea surface temperature intercomparison workshop are described. Results are shown that compare anomaly fields produced by using data from ships, AVHRR, and HIRS2/MSU for these months. Monthly mean fields derived from AVHRR and HIRS2 data show roughly comparable statistical accuracy compared to ship fields. Errors in the HIRS2 fields appear more random, while AVHRR data have larger regionally dependent biases and show large area spatially coherent errors. The random errors in the HIRS2 fields should be further reduced by performing the retrievals at a higher spatial resolution.

Susskind, J.↗
NASA NTRS2010

High-Resolution Subtropical Summer Precipitation Derived from Dynamical Downscaling of the NCEP-DOE Reanalysis: How Much Small-Scale Information Is Added by a Regional Model?

This study assesses the regional-scale summer precipitation produced by the dynamical downscaling of analyzed large-scale fields. The main goal of this study is to investigate how much the regional model adds smaller scale precipitation information that the large-scale fields do not resolve. The modeling region for this study covers the southeastern United States (Florida, Georgia, Alabama, South Carolina, and North Carolina) where the summer climate is subtropical in nature, with a heavy influence of regional-scale convection. The coarse resolution (2.5deg latitude/longitude) large-scale atmospheric variables from the National Center for Environmental Prediction (NCEP)/DOE reanalysis (R2) are downscaled using the NCEP Environmental Climate Prediction Center regional spectral model (RSM) to produce precipitation at 20 km resolution for 16 summer seasons (19902005). The RSM produces realistic details in the regional summer precipitation at 20 km resolution. Compared to R2, the RSM-produced monthly precipitation shows better agreement with observations. There is a reduced wet bias and a more realistic spatial pattern of the precipitation climatology compared with the interpolated R2 values. The root mean square errors of the monthly R2 precipitation are reduced over 93 (1,697) of all the grid points in the five states (1,821). The temporal correlation also improves over 92 (1,675) of all grid points such that the domain-averaged correlation increases from 0.38 (R2) to 0.55 (RSM). The RSM accurately reproduces the first two observed eigenmodes, compared with the R2 product for which the second mode is not properly reproduced. The spatial patterns for wet versus dry summer years are also successfully simulated in RSM. For shorter time scales, the RSM resolves heavy rainfall events and their frequency better than R2. Correlation and categorical classification (above/near/below average) for the monthly frequency of heavy precipitation days is also significantly improved by the RSM.

NARR↗
NASA NTRS1990

Analysis of spatial pseudodepolarizers in imaging systems

The objective of a number of optical instruments is to measure the intensity accurately without bias as to the incident polarization state. One method to overcome polarization bias in optical systems is the insertion of a spatial pseudodepolarizer. Both the degree of depolarization and image degradation (from the polarization aberrations of the pseudodepolarizer) are analyzed for two depolarizer designs: (1) the Cornu pseudodepolarizer, effective for linearly polarized light, and (2) the dual Babinet compensator pseudodepolarizer, effective for all incident polarization states. The image analysis uses a matrix formalism to describe the polarization dependence of the diffraction patterns and optical transfer function.

Mcguire, James P., Jr.↗
NASA NTRS2018

Spatial Representativeness Error in the Ground-Level Observation Networks for Black Carbon Radiation Absorption

There is high uncertainty in the direct radiative forcing of black carbon (BC), an aerosol that strongly absorbs solar radiation. The observation-constrained estimate, which is several times larger than the bottom-up estimate, is influenced by the spatial representativeness error due to the mesoscale inhomogeneity of the aerosol fields and the relatively low resolution of global chemistry-transport models. Here we evaluated the spatial representativeness error for two widely used observational networks (AErosol RObotic NETwork and Global Atmosphere Watch) by downscaling the geospatial grid in a global model of BC aerosol absorption optical depth to 0.1° × 0.1°. Comparing the models at a spatial resolution of 2° × 2° with BC aerosol absorption at AErosol RObotic NETwork sites (which are commonly located near emission hot spots) tends to cause a global spatial representativeness error of 30%, as a positive bias for the current top-down estimate of global BC direct radiative forcing. By contrast, the global spatial representativeness error will be 7% for the Global Atmosphere Watch network, because the sites are located in such a way that there are almost an equal number of sites with positive or negative representativeness error.

Wang, Rong↗
NASA NTRS2023

Identification of Sea Surface Temperature and Sea Surface Salinity Fronts along the California Coast: Application Using Saildrone and Satellite Derived Products

Coastal upwelling regions are one of the most dynamic areas of the world’s oceans. The California and Baja California Coasts are impacted by both coastal upwelling and the California Current, leading to frontal activity that is captured by gradients in both Sea Surface Temperature (SST) and Sea Surface Salinity (SSS). Satellite data are a great source of spatial data to study fronts. However, biases near coastal areas and coarse resolutions can impair its usefulness in upwelling areas. In this work gradients in SST from NASA Multi-Scale Ultra-High Resolution (MUR) and in two SSS products derived from the Soil Moisture Active Passive (SMAP) NASA mission are compared directly with gradients derived from the Saildrone uncrewed vehicles to validate the gradients as well as to assess their ability to detect known frontal features. The three remotely sensed data sets (MURSST/JPL, SMAP SSS/RSS, SMAP SSS) were co-located with the Saildrone data prior to the calculation of the gradients. Wavelet analysis is used to determine how well the satellite derived SST and SSS products are reproducing the Saildrone derived gradients. Overall results indicate the remote sensing products are reproducing features of known areas of coastal upwelling. Differences between the SST and SSS gradients are mainly associated with the limitations of the microwave derived SSS coverage near land and its reduced spatial resolution. The results are promising for using remote sensing data sets to monitor frontal structure along the California Coast and the application to long term changes in coastal upwelling and dynamics.

Sea Surface Salinity↗
NASA NTRS2019

Improvements in the Uncertainty Model in the Goddard Institute for Space Studies Surface Temperature (GISTEMP) Analysis

We outline a new and improved uncertainty analysis for the Goddard Institute of Space Studies (GISS) Surface Temperature product version 4 (GISTEMP v4). Historical spatial variations in surface temperature anomalies are derived from historical weather station data and ocean data from ships, buoys and other sensors. Uncertainties arise from measurement uncertainty, changes in spatial coverage of the station record, and systematic biases due to technology shifts and land cover changes. Previously published uncertainty estimates for GISTEMP included only the effect of incomplete station coverage. Here, we update this term using currently available spatial distributions of source data, state‐of‐the‐art reanalyses and incorporate independently derived estimates for ocean data processing, station homogenization and other structural biases. The resulting 95% uncertainties are near 0.05° C in the global annual mean for the last 50 years, and increase going back further in time reaching 0.15° C in 1880. In addition, we quantify the benefits and inherent uncertainty due to the GISTEMP interpolation and averaging method. We use the total uncertainties to estimate the probability for each record year in the GISTEMP to actually be the true record year (to that date), and conclude with 86% likelihood that 2016 was indeed the hottest year of the instrumental period (so far).

Nathan J L Lenssen↗
NASA NTRS1985

Effects of upstream-biased third-order space correction terms on multidimensional Crowley advection schemes

The impact of upstream-biased corrections for third-order spatial truncation error on the stability and phase error of the two-dimensional Crowley combined advective scheme with the cross-space term included is analyzed, putting primary emphasis on phase error reduction. The various versions of the Crowley scheme are formally defined, and their stability and phase error characteristics are intercompared using a linear Fourier component analysis patterned after Fromm (1968, 1969). The performances of the schemes under prototype simulation conditions are tested using time-dependent numerical experiments which advect an initially cone-shaped passive scalar distribution in each of three steady nondivergent flows. One such flow is solid rotation, while the other two are diagonal uniform flow and a strongly deformational vortex.

Schlesinger, R. E.↗
NASA NTRS1990

A comparison of the climate simulated by the NCAR Community Climate Model (CCM1:R15) with ECMWF analyses

The Community Climate Model (CCM) is a comprehensive three-dimensional global atmospheric model assembled at the National Center for Atmospheric Research. Detailed comparisons are made between the climate simulated by a seasonal version of CCM, namely CCM1, at 12 level, R15 spectral resolution, and that revealed by ECMWF operational analyses over 1980-86 truncated to a similar resolution. A variety of circulation statistics are presented in order to reveal the spatial character and seasonality of CCM1 biases in temperature, winds, and wave flux quantities. The biases revealed for CCM1 are similar in many respects to those found in other climate models run at similar resolution. Results of this study are then presented, discussing temperature biases and thermodynamic balances, wind fields, zonal mean wave diagnostics, stationary waves, and local eddy statistics. The major findings are then summarized.

Randel, William J.↗
NASA NTRS1993

Steady induction effects in geomagnetism. Part 1B: Geomagnetic estimation of steady surficial core motions: A non-linear inverse problem

The problem of estimating a steady fluid velocity field near the top of Earth's core which induces the secular variation (SV) indicated by models of the observed geomagnetic field is examined in the source-free mantle/frozen-flux core (SFI/VFFC) approximation. This inverse problem is non-linear because solutions of the forward problem are deterministically chaotic. The SFM/FFC approximation is inexact, and neither the models nor the observations they represent are either complete or perfect. A method is developed for solving the non-linear inverse motional induction problem posed by the hypothesis of (piecewise, statistically) steady core surface flow and the supposition of a complete initial geomagnetic condition. The method features iterative solution of the weighted, linearized least-squares problem and admits optional biases favoring surficially geostrophic flow and/or spatially simple flow. Two types of weights are advanced radial field weights for fitting the evolution of the broad-scale portion of the radial field component near Earth's surface implied by the models, and generalized weights for fitting the evolution of the broad-scale portion of the scalar potential specified by the models.

Voorhies, Coerte V.↗
NASA NTRS2021

Chapter 13: Errors and Uncertainties Associated with Quasi-Global Satellite Precipitation Products

Measuring precipitation on a global scale is only possible from satellite platforms. Satellite precipitation estimates are based on geosynchronous infrared sensors on geostationary satellites, characterized by high sampling frequency, and polar-orbiting microwave sensors on low-Earth-orbiting satellites with less-frequent sampling. Assessing satellite product performance is fundamental to infer the reliability of such estimates and effectively use them in water resources management, extreme event characterization, disease control, or weather forecasting. Nevertheless, errors and uncertainties associated with satellite precipitation products are often masked due to temporal and spatial sampling, as well as bias-corrections against a reference dataset. Moreover, the verification of satellite precipitation products is easier over land areas, where rain gauges and ground radars are available as benchmark, but extremely limited over the oceans. Substantial work still remains to better quantify relative and absolute errors and uncertainties within satellite-based precipitation products over land and oceans.

Viviana Maggioni↗
NASA NTRSDate not supplied

Coronal FIP Bias: From Full-Sun X-Ray Spectroscopy to Imaging Spectroscopy

The First Ionization Potential (FIP) bias, whereby the abundances of the low FIP elements in different coronal structures vary from their photospheric values and may also vary with time, has been known for a long time, but still poorly understood. X-ray spectroscopic observations of the Sun are very crucial to study the spatio-temporal variation, and to understand the physical mechanisms giving rise to the FIP bias. Recent X-ray spectroscopic observations of the Sun in disk-integrated mode by Solar X-ray Monitor (XSM) onboard Chandrayaan-2 enhanced our knowledge of the temporal variation of FIP bias during solar flares and in hot AR cores. Here we will summarize the results from these recent studies. Also we will discuss the importance of spatially resolved spectroscopic observation to understand the FIP bias. In this context we will explore the role of upcoming X-ray imaging spectrographs.

solar corona↗
NASA NTRS1998

Characterization of Clouds and the Anisotropy of Emitted and Reflected Radiances for the Purpose of Obtaining the Radiative Heating of the Atmosphere

The goal of the work supported through this grant was to assess the validity of the assumptions underlying the CERES Strategy for determining radiative fluxes. Specifically, the work focused on the determination of scene type and the use of anisotropic factors to derive radiative fluxes from observed broadband radiances. The work revealed a dependence of the anisotropy of reflected and emitted broadband radiances on the spatial resolution of the observations that had been overlooked in the formulation of the CERES strategy. This dependence on spatial resolution coupled with errors in scene identification led to view zenith angle dependent biases in the ERBE derived radiative fluxes. Scene identification will be greatly improved in CERES thereby alleviating somewhat the biases arising from the dependence of the anisotropy of the radiances on spatial resolution. Attention was then focused on the validity of plane-parallel radiative transfer theory which is relied on to characterize the scene types viewed by the CERES scanner. Again, viewing geometry dependent biases were found even for single-layered, overcast cloud systems. Such systems are taken to be the closest examples of plane-parallel clouds. At least some of the departures from plane-parallel behavior were evidently due to relatively small bumps on the tops of extensive stratus layers. The bumps cannot be resolved in the imagery that will be used to characterize the scenes viewed by the CERES scanner. As part of this investigation, the ice sheets of Greenland and Antarctica were shown to provide radiometrically stable targets for determining the visible and near infrared calibrations of radiometers. These targets were used to calibrate the reflected sunlight at visible wavelengths used in this study. Finally, the limitations of plane-parallel theory notwithstanding, the common practice of ignoring fractional cloud cover within the fields of view of imaging radiometers was shown to lead to biases in the retrieved cloud properties. The development of retrievals for pixel-scale cloud cover fraction is an attempt to reduce such bases. Work on these retrievals continues.

Coakley, James A., Jr.↗
NASA NTRS1997

Report to TRMM

The effort involved three elements all related to the measurement of rain and clouds using microwaves: (1) Examine recently proposed techniques for measuring rainfall rate and rain water content using data from ground-based radars and the TRMM microwave link in order to develop improved ground validation and radar calibration techniques; (2) Develop dual-polarization, multiple frequency radar techniques for estimating rain water content and cloud water content to interpret the vertical profiles of radar reflectivity factors (Z) measured by the TRMM Precipitation Radar; and (3) Investigate theoretically and experimentally the potential biases in TRMM Z measurements due to spatial inhomogeneities in precipitation. The research succeeded in addressing all of these topics, resulting in several referred publications. addition, the research indicated that the effects of non-Rayleigh statistics resulting from the nature of the precipitation inhomogeneities will probably not result in serious errors for the TRMM radar Measurements, but the TRMM radiometers may be subject to significant bias due to the inhomogeneities.

Jameson, Arthur R.↗