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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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NASA NTRS1985

A comparative study of spherical and flat-Earth geopotential modeling at satellite elevations

Flat-Earth and spherical-Earth geopotential modeling of crustal anomaly sources at satellite elevations are compared by computing gravity and scalar magnetic anomalies perpendicular to the strike of variably dimensioned rectangular prisms at altitudes of 150, 300, and 450 km. Results indicate that the error caused by the flat-Earth approximation is less than 10% in most geometric conditions. Generally, error increase with larger and wider anomaly sources at higher altitudes. For most crustal source modeling applications at conventional satellite altitudes, flat-Earth modeling can be justified and is numerically efficient.

Parrott, M. H.↗
NASA NTRS2007

Satellite-Based Model Parameterization of Diabatic Heating

Future meteorological satellites are expected to provide much needed fine-scale information that can improve the accuracy of weather and climate models. As one application of this improved capability, we introduce the concept of a generalized parameterization framework using satellite datasets that will increase the accuracy and the computational efficiency of weather and climate modeling. In an atmospheric model, several different parameterizations usually are used to reproduce the various physical processes. However, it is generally unrealistic to separate the processes in this artificial way since the observations and physics make no such artificial separation. Thus, we propose a new unified parameterization framework to remove the unrealistic separation between parameterizations.

Pielke, Roger, Sr.↗
NASA NTRS2019

NASA Global Satellite and Model Data Products and Services for Tropical Cyclone Research

The lack of observations over vast tropical oceans is a major challenge for tropical cyclone research. Satellite observations and model reanalysis data play an important role in filling these- gaps. Established in the mid-1980's, the Goddard Earth Sciences Data and Information Services Center (GES DISC), as one of the 12 NASA data centers, archives and distributes data from several Earth science disciplines such as precipitation, atmospheric dynamics, atmospheric composition, hydrology, including well-known NASA satellite missions (e.g. TRMM, GPM) and model assimilation projects (MERRA-2). Acquiring datasets suitable for tropical cyclone research in a large data archive is a challenge for many, especially for those who are not familiar with satellite or model data. Over the years, the GES DISC has developed user-friendly data services. For example, Giovanni is an online visualization and analysis tool, allowing users to visualize and analyze over 2000 satellite- and model-based variables with a Web browser, without downloading data and software. In this chapter, we will describe data and services at the GES DISC with emphasis on tropical cyclone research. We will also present two case studies and discuss future plans.

Liu, Zhong↗
NASA NTRS1991

A Pacific Ocean general circulation model for satellite data assimilation

A tropical Pacific Ocean General Circulation Model (OGCM) to be used in satellite data assimilation studies is described. The transfer of the OGCM from a CYBER-205 at NOAA's Geophysical Fluid Dynamics Laboratory to a CRAY-2 at NASA's Ames Research Center is documented. Two 3-year model integrations from identical initial conditions but performed on those two computers are compared. The model simulations are very similar to each other, as expected, but the simulations performed with the higher-precision CRAY-2 is smoother than that with the lower-precision CYBER-205. The CYBER-205 and CRAY-2 use 32 and 64-bit mantissa arithmetic, respectively. The major features of the oceanic circulation in the tropical Pacific, namely the North Equatorial Current, the North Equatorial Countercurrent, the South Equatorial Current, and the Equatorial Undercurrent, are realistically produced and their seasonal cycles are described. The OGCM provides a powerful tool for study of tropical oceans and for the assimilation of satellite altimetry data.

Chao, Y.↗
NASA NTRS2021

Precipitable water vapor over oceans from the Maritime Aerosol Network: Evaluation of global models and satellite products under clear sky conditions

We present results from an evaluation of precipitable water vapor (W) over remote oceanic areas as derived from global reanalysis models and from satellites against observations from the Maritime Aerosol Network (MAN) for cloudless skies during the period of 2004–2017. They cover polar, mid latitude and tropical oceanic regions and represent a first effort to use MAN observations for such evaluation. The global reanalysis model products evaluated in this study are from the Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2), the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Reanalysis (ERA I), and the Climate Forecast System Reanalysis (CFSR) model. The satellite products evaluated are from the Moderate Resolution Imaging Spectroradiometer (MODIS), the Polarization and Directionality of the Earth's Reflectances (POLDER), the Global Ozone Monitoring Experiment (GOME-2), the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY), and the Atmospheric Infra-red Sounder (AIRS). Satellite retrievals of W are based on the attenuation of solar reflected light by water vapor absorption bands, except those from AIRS that rely on brightness temperature measurements. A very good agreement is observed between the model estimates and MAN, with mean differences of ~5% and standard deviations of ~15%. These results are within the uncertainties associated with the models and the measurements, indicating the skill of the reanalysis models to estimate W over oceans under clear sky conditions. Mean differences of W between the satellite and MAN products are ~11, 6.7, 12, −7, and 3% for MODIS, POLDER, GOME-2, SCIAMACHY and AIRS respectively, while their standard deviations are 31, 29, 28, 20 and 17%. These differences reveal the need to address inconsistencies among different satellite sensors and ground-based measurements to reduce the uncertainties associated with the retrievals.

Daniel Pérez-Ramírez↗
NASA NTRS2007

Global Distortion of GPS Networks Associated with Satellite Antenna Model Errors

Recent studies of the GPS satellite phase center offsets (PCOs) suggest that these have been in error by approx.1 m. Previous studies had shown that PCO errors are absorbed mainly by parameters representing satellite clock and the radial components of site position. On the basis of the assumption that the radial errors are equal, PCO errors will therefore introduce an error in network scale. However, PCO errors also introduce distortions, or apparent deformations, within the network, primarily in the radial (vertical) component of site position that cannot be corrected via a Helmert transformation. Using numerical simulations to quantify the effects of PC0 errors, we found that these PCO errors lead to a vertical network distortion of 6-12 mm per meter of PCO error. The network distortion depends on the minimum elevation angle used in the analysis of the GPS phase observables, becoming larger as the minimum elevation angle increases. The steady evolution of the GPS constellation as new satellites are launched, age, and are decommissioned, leads to the effects of PCO errors varying with time that introduce an apparent global-scale rate change. We demonstrate here that current estimates for PCO errors result in a geographically variable error in the vertical rate at the 1-2 mm/yr level, which will impact high-precision crustal deformation studies.

Cardellach, E.↗
NASA NTRS2018

Comparison of Magnetic Fields from a New Satellite Magnetic Model of the Lithosphere with Magnetic Fields Predicted from Crust 1.0

Both magnetic and seismic techniques can provide information about the Moho (Mohorovicic discontinuity). We develop a new technique that provides a better estimate of the magnetic thickness of the crust, as compared with previous approaches. It uses prior knowledge from seismology (Crust 1.0), a new high-degree model from CHAMP (CHAllenging Mini-satellite Payload) and Swarm (LCS-1 - a model of Earth's lithospheric field) and a newly developed technique. The technique is appropriate for regions where induced magnetization dominates over remanent magnetization. We compare the predictions from LCS-1 with those from Crust 1.0, with some simple assumptions, and find that the correlations increase until about spherical harmonic degree 30, and then decrease globally. Spatially, the correlations between the seismic and magnetic techniques are strongest over North America and Australia, and weakest over South America and northern Africa. Strong correlations also exist between the two approaches over the Antarctic, northern Europe, and Greenland. While we might expect the seismic and magnetic approaches to correlate over well-characterized regions (i.e. North America), and show weaker correlations over poorly-characterized regions (i.e. South America and north Africa), the strong correlation in the Antarctic and Greenland is puzzling, because both of these regions are poorly-characterized. We discuss some possible explanations, and implications, of this attempt to correlate seismic and magnetic approaches to characterizing the lithosphere.

Seismic↗
NASA NTRS1988

Antarctic ozone decrease: Possible impact on the seasonal and latitudinal distribution of total ozone as simulated by a 2-D model

Satellite borne instruments, the Total Ozone Mapping Spectrometer (TOMS) and the Solar Backscatter Ultraviolet spectrometer (SBUV), show that total column ozone has decreased by more than 5 percent in the neighborhood of 60 S at all seasons since 1979. This is considerably larger than the decrease calculated by 2-D models which take into account solar flux variation and increases of trace gas concentrations over the same period. The meteorological conditions (warmer temperature and the apparent lack of polar stratospheric clouds) at these latitudes do not seem to favor heterogeneous chemistry as the direct cause for the observed ozone reduction. A mechanism involving the seasonal transport of ozone-poor air mass from within the polar vortex to lower latitudes (the so-called dilution effect) is proposed as a possible explanation for the observed year-round ozone reduction in regions away from the vortex.

Ko, Malcolm K. W.↗
NASA NTRS1995

Narrowband land mobile satellite channel modeling

The subject of this paper is the development of a generalized analog model for the narrowband Land Mobile Satellite Channel (LMSC). It is based on the model proposed by Lutz, the 3-dimensional scattering model of Aulin and the multipath interference simulation method proposed by Jakes. Statistical tests of the simulated data show excellent agreement with the expected distributions whereas the power spectrum predicted by Aulin is duplicated in a discrete manner.

Kanatas, A. G.↗
NASA NTRS1988

Comparison of simulation modeling and satellite techniques for monitoring ecological processes

In 1985 improvements were made in the world climatic data base for modeling and predictive mapping; in individual process models and the overall carbon-balance models; and in the interface software for mapping the simulation results. Statistical analysis of the data base was begun. In 1986 mapping was shifted to NASA-Goddard. The initial approach involving pattern comparisons was modified to a more statistical approach. A major accomplishment was the expansion and improvement of a global data base of measurements of biomass and primary production, to complement the simulation data. The main accomplishments during 1987 included: production of a master tape with all environmental and satellite data and model results for the 1600 sites; development of a complete mapping system used for the initial color maps comparing annual and monthly patterns of Normalized Difference Vegetation Index (NDVI), actual evapotranspiration, net primary productivity, gross primary productivity, and net ecosystem production; collection of more biosphere measurements for eventual improvement of the biological models; and development of some initial monthly models for primary productivity, based on satellite data.

Box, Elgene O.↗
NASA NTRS2020

Evaluating impacts of snow, surface water, soil and vegetation on empirical vegetation and snow indices for the Utqiaġvik tundra ecosystem in Alaska with the LVS3 model

Satellite observations for the Arctic and boreal region may contain information of vegetation, soil, snow, snowmelt, and/or other surface water bodies. We investigated the impacts of vegetation, soil, snow and surface water on empirical vegetation/snow indices on a tundra ecosystem area located around Utqiaġvik (formerly Barrow) of Alaska with the Moderate Resolution Imaging Spectrometer (MODIS) images in 2001–2014. Empirical vegetation indices, such as normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), the index of near infrared of vegetation (NIRv), and modified EVI (EVI2), have been used to monitor vegetation. Normalized difference snow index (NDSI) has been widely applied to monitor snow. The vegetation cover fraction (VGCF), the soil cover fraction (SOILCF), the snow cover fraction (SNOWCF), the surface water body cover fraction (WaterBodyCF), the fractional absorption of photosynthetically active radiation (PAR) by vegetation chlorophyll (fAPARchl), the fractional absorption of PAR by non-chlorophyll components of the vegetation (fAPARnon-chl), and the fractional absorption of PAR by the entire canopy (fAPARcanopy) are retrieved with the MODIS images and a coupled Leaf-Vegetation-Soil-Snow-Surface water body radiative transfer model, LVS3. The vegetation indices (NDVI, EVI, EVI2 and NIRv) differ from VGCF, fAPARchl, fAPARnon-chl, and fAPARcanopy. In addition to vegetation, we find that soil, snow and surface water also have impacts on vegetation indices NDVI, EVI (EVI2), and NIRv. Presence of snow makes lower the observed values of NDVI, EVI2 and NIRv. After snowmelt is gone, the vegetation indices (NDVI, EVI, EVI2 and NIRv) linearly decrease with SOILCF and WaterBodyCF, and WaterBodyCF has stronger impacts on these vegetation indices than SOILCF. The relationship between EVI and snow is complicated. NDSI non-linearly increases with SNOWCF, but linearly increases with sum of SNOWCF and WaterBodyCF (sum = 0.5893 × NDSI +0.4342, R2 = 0.976). NDSI linearly decreases with VGCF, and the relationship between NDSI and SOILCF is complex. Retrievals of VGCF, fAPARchl, fAPARnon-chl and fAPARcanopy with the LVS3 model provide alternatives for vegetation monitoring and ecological modeling.

Qingyuan Zhang↗
NASA NTRS1992

Space debris characterization in support of a satellite breakup model

The Space Kinetic Impact and Debris Branch began an ambitious program to construct a fully analytical model of the breakup of a satellite under hypervelocity impact. In order to provide empirical data with which to substantiate the model, debris from hypervelocity experiments conducted in a controlled laboratory environment were characterized to provide information of its mass, velocity, and ballistic coefficient distributions. Data on the debris were collected in one master data file, and a simple FORTRAN program allows users to describe the debris from any subset of these experiments that may be of interest to them. A statistical analysis was performed, allowing users to determine the precision of the velocity measurements for the data. Attempts are being made to include and correlate other laboratory data, as well as those data obtained from the explosion or collision of spacecraft in low earth orbit.

Fortson, Bryan H.↗
NASA NTRS1994

A geopotential model from satellite tracking, altimeter, and surface gravity data: GEM-T3

An improved model of Earth's gravitational field, Goddard Earth Model T-3 (GEM-T3), has been developed from a combination of satellite tracking, satellite altimeter, and surface gravimetric data. GEM-T3 provides a significant improvement in the modeling of the gravity field at half wavelengths of 400 km and longer. This model, complete to degree and order 50, yields more accurate satellite orbits and an improved geoid representation than previous Goddard Earth Models. GEM-T3 uses altimeter data from GEOS 3 (1975-1976), Seasat (1978) and Geosat (1986-1987). Tracking information used in the solution includes more than 1300 arcs of data encompassing 31 different satellites. The recovery of the long-wavelength components of the solution relies mostly on highly precise satellite laser ranging (SLR) data, but also includes Tracking Network (TRANET) Doppler, optical, and satellite-to-satellite tracking acquired between the ATS 6 and GEOS 3 satellites. The main advances over GEM-T2 (beyond the inclusion of altimeter and surface gravity information which is essential for the resolution of the shorter wavelength geoid) are some improved tracking data analysis approaches and additional SLR data. Although the use of altimeter data has greatly enhanced the modeling of the ocean geoid between 65 deg N and 60 deg S latitudes in GEM-T3, the lack of accurate detailed surface gravimetry leaves poor geoid resolution over many continental regions of great tectonic interest (e.g., Himalayas, Andes). Estimates of polar motion, tracking station coordinates, and long-wavelength ocean tidal terms were also made (accounting for 6330 parameters). GEM-T3 has undergone error calibration using a technique based on subset solutions to produce reliable error estimates. The calibration is based on the condition that the expected mean square deviation of a subset gravity solution from the full set values is predicted by the solutions' error covariances. Data weights are iteratively adjusted until this condition for the error calibration is satisfied. In addition, gravity field tests were performed on strong satellite data sets withheld from the solution (thereby ensuring their independence). In these tests, the performance of the subset models on the withheld observations is compared to error projections based on their calibrated error covariances. These results demonstrate that orbit accuracy projections are reliable for new satellites which were not included in GEM-T3.

Lerch, F. J.↗
NASA NTRS1982

The effect of model resolution and satellite sounding data on GLAS model forecasts

The effect of horizontal model resolution on satellite data impact has been studied for two versions of the GLAS second-order general circulation model: the C-model with a 4-deg latitude by 5-deg longitude resolution and the F-model with a 2.5-deg latitude and 3-deg longitude resolution. It is found that the 48-72 h forecast skill of the GLAS model was significantly improved by the increased resolution. Initial state differences between the SAT and NOSAT cycles using the F-model were on the average smaller than the corresponding differences with the C-model. However, the F-model cycle differences exhibited a smaller scale structure and, in some cases, larger gradients.

Atlas, R.↗
NASA NTRS1994

Evaluation of water vapor distribution in general circulation models using satellite observations

This paper presents a comparison of the water vapor distribution obtained from two general circulation models, the European Centre for Medium-Range Weather Forecasts (ECMWF) model and the National Center for Atmospheric Research (NCAR) Community Climate Model (CCM), with satellite observations of total precipitable water (TPW) from Special Sensor Microwave/Imager (SSM/I) and upper tropospheric relative humidity (UTH) from GOES. Overall, both models are successful in capturing the primary features of the observed water vapor distribution and its seasonal variation. For the ECMWF model, however, a systematic moist bias in TPW is noted over well-known stratocumulus regions in the eastern subtropical oceans. Comparison with radiosonde profiles suggests that this problem is attributable to difficulties in modeling the shallowness of the boundary layer and large vertical water vapor gradients which characterize these regions. In comparison, the CCM is more successful in capturing the low values of TPW in the stratocumulus regions, although it tends to exhibit a dry bias over the eastern half of the subtropical oceans and a corresponding moist bias in the western half. The CCM also significantly overestimates the daily variability of the moisture fields in convective regions, suggesting a problem in simulating the temporal nature of moisture transport by deep convection. Comparison of the monthly mean UTH distribution indicates generally larger discrepancies than were noted for TPW owing to the greater influence of large-scale dynamical processes in determining the distribution of UTH. In particular, the ECMWF model exhibits a distinct dry bias along the Intertropical Convergence Zone (ITCZ) and a moist bias over the subtropical descending branches of the Hadley cell, suggesting an underprediction in the strength of the Hadley circulation. The CCM, on the other hand, demonstrates greater discrepancies in UTH than are observed for the ECMWF model, but none that are as clearly correlated with well-known features of the large-scale circulation.

Soden, Brian J.↗
NASA NTRS1981

Internal structures of the Galilean satellites

Models for the interior structures of Io, Ganymede and Callisto are proposed based on recent discoveries of volcanism and high heat flow on Io, a primordial, heavily cratered surface on Callisto, and a surface modified by endogenic processes on Ganymede. The model for Io consists of a thin, high-rigidity outer shell overlying a thin, partially molten or molten layer maintained by tidal dissipation in the outer shell, which in turn surrounds a solid interior. Ganymede is modeled as an ice outer layer surrounding a shell of undifferentiated, primordial ice-silicate mixture and a rock core, with accretional heating responsible for melting the ice in an originally homogeneous ice-silicate interior. Finally, the old, heavily cratered surface of Callisto is interpreted as suggesting a primordial ice-silicate mixture with little, if any, ice-rock differentiation in the interior.

Schubert, G.↗
NASA NTRS1997

Comparison of the Seasonal Change in Cloud-Radiative Forcing from Atmospheric General Circulation Models and Satellite Observations

We compare seasonal changes in cloud-radiative forcing (CRF) at the top of the atmosphere from 18 atmospheric general circulation models, and observations from the Earth Radiation Budget Experiment (ERBE). To enhance the CRF signal and suppress interannual variability, we consider only zonal mean quantities for which the extreme months (January and July), as well as the northern and southern hemispheres, have been differenced. Since seasonal variations of the shortwave component of CRF are caused by seasonal changes in both cloudiness and solar irradiance, the latter was removed. In the ERBE data, seasonal changes in CRF are driven primarily by changes in cloud amount. The same conclusion applies to the models. The shortwave component of seasonal CRF is a measure of changes in cloud amount at all altitudes, while the longwave component is more a measure of upper level clouds. Thus important insights into seasonal cloud amount variations of the models have been obtained by comparing both components, as generated by the models, with the satellite data. For example, in 10 of the 18 models the seasonal oscillations of zonal cloud patterns extend too far poleward by one latitudinal grid.

Cess, R. D.↗
NASA NTRS2020

Toward a Consistent Definition between Satellite and Model Clear-Sky Radiative Fluxes

A new method of determining clear-sky radiative fluxes from satellite observations for climate model evaluation is presented. The method consists of applying adjustment factors to existing satellite clear-sky broadband radiative fluxes that make the observed and simulated clear-sky flux definitions more consistent. The adjustment factors are determined from the difference between observation-based radiative transfer model calculations of monthly mean clear-sky fluxes obtained by ignoring clouds in the atmospheric column and by weighting hourly mean clear-sky fluxes with imager-based clear-area fractions. The global mean longwave (LW) adjustment factor is −2.2 W m−2 at the top of the atmosphere and 2.7 W m−2 at the surface. The LW adjustment factors are pronounced at high latitudes during winter and in regions with high upper-tropospheric humidity and cirrus cloud cover, such as over the west tropical Pacific, and the South Pacific and intertropical convergence zones. In the shortwave (SW), global mean adjustment is 0.5 W m−2 at TOA and −1.9 W m−2 at the surface. It is most pronounced over sea ice off of Antarctica and over heavy aerosol regions, such as eastern China. However, interannual variations in the regional SW and LW adjustment factors are small compared to those in cloud radiative effect. After applying the LW adjustment factors, differences in zonal mean cloud radiative effect between observations and climate models decrease markedly between 60°S and 60°N and poleward of 65°N. The largest regional improvements occur over the west tropical Pacific and Indian Oceans. In contrast, the impact of the SW adjustment factors is much smaller.

Norman G Loeb↗