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NASA NTRSDate not supplied

Fast Radiative Transfer Model and Retrieval Algorithm Development for Satellite Remote Sensing Applications

The radiative transfer model (RTM) has a wide range of applications in satellite remote sensing and atmospheric radiation studies. For example, it can be used as a forward model for an inversion algorithm and a satellite data assimilation system, or as a L1 data simulator for pre-launch end-to-end satellite sensor performance studies. However, millions of line-by-line (LBL) radiative transfer calculations at fine monochromatic frequencies are needed in order to properly calculate spectral contributions of water vapor and trace gases in the atmosphere in infrared and solar spectral regions. Therefore, fast, and accurate radiative transfer models are needed. A Principal Component-based radiative transfer model (PCRTM) was developed at NASA Langley to fulfil this need. The PCRTM can simulate the top-of-atmosphere (TOA) radiance or reflectance spectra from 250 nm to 2000 micrometers with several orders of magnitude faster speed as compared to a LBL RTM. It is also extremely accurate compared to LBL RTM benchmarks. The PCRTM model has been developed for hyperspectral sensors such as AIRS, CrIS, IASI, NAST-I, SHIS, CPF, TEMPO, EMIT, OMI, and SCIAMACHY. By using the PCRTM as forward model for an inversion algorithm, one can reduce the data dimension significantly while maintaining original information content by compressing the TOA radiance spectrum into PC-scores. The PCRTM can directly compute the PC-scores and their derivatives with respect to retrieved parameters. Examples of using various PCRTM inversion algorithms to retrieve atmospheric temperature, water vapor, and trace gas profiles, as well as cloud and surface properties from satellite hyperspectral remote sensors will be given. Some of the algorithms have been transitioned to NASA's Goddard Earth Sciences Data and Information Services Center (GES DISC) for public access of high-quality L2 and L3 data.

Xu Liu↗
NASA NTRS1981

Ultimate limits to error probabilities for ionospheric models based on solar geophysical indices and how these compare with the state of the art

An ideal model based on a given set of geophysical indices is defined as a model that provides a least squares fit to the data set as a function of the indices considered. Satellite measurements of electron content for three stations at different magnetic latitudes were used to provide such data sets which were each fitted to the geophysical indices. The magnitude of the difference between the measured value and the derived equation for the data set was used to estimate the probability of making an error greater than a given magnitude for such an ideal model. Atmospheric Explorer C data is used to examine the causes of the fluctuations and suggestions are made about how real improvements can be made in ionospheric forecasting ability. Joule heating inputs in the auroral electrojets are related to the AL and AU magnetic indices. Magnetic indices based on the time integral of the energy deposited in the electrojets are proposed for modeling processes affected by auroral zone heating.

Nisbet, J. S.↗
NASA NTRS1982

Airfoil deposition model

The methodology to predict deposit evolution (deposition rate and subsequent flow of liquid deposits) as a function of fuel and air impurity content and relevant aerodynamic parameters for turbine airfoils is developed in this research. The spectrum of deposition conditions encountered in gas turbine operations includes the mechanisms of vapor deposition, small particle deposition with thermophoresis, and larger particle deposition with inertial effects. The focus is on using a simplified version of the comprehensive multicomponent vapor diffusion formalism to make deposition predictions for: (1) simple geometry collectors; and (2) gas turbine blade shapes, including both developing laminar and turbulent boundary layers. For the gas turbine blade the insights developed in previous programs are being combined with heat and mass transfer coefficient calculations using the STAN 5 boundary layer code to predict vapor deposition rates and corresponding liquid layer thicknesses on turbine blades. A computer program is being written which utilizes the local values of the calculated deposition rate and skin friction to calculate the increment in liquid condensate layer growth along a collector surface.

Kohl, F. J.↗
NASA NTRSDate not supplied

Performance of Heterogeneous Sulfate Aerosol Formation Mechanisms Against Aircraft and Ground-Based Observations in Seoul, South Korea

Haze events are a common occurrence in East Asia, where local meteorology combines with anthropogenic emissions under certain conditions to create rapid increases in secondary aerosol. Often these events are driven by rapid production of secondary sulfate-nitrate-ammonium (SIA) aerosol. Models have typically included simple parameterizations of the production of sulfate during these events which vary widely in their magnitude. There are a range of different mechanistic descriptions of the chemical processes occurring during these events in large part due to poor constraints on aerosol pH and transition metal content, both of which are important to determining the key pathway(s) driving aerosol production. Here, we use the GEOS-Chem chemical transport model to interpret detailed ground and aircraft observations from May and June 2016 during the Korea-United States Air Quality (KORUS-AQ) field study to evaluate the mechanistic pathways governing sulfate production during a haze event. We apply our model of sulfate production mechanisms to ground-based speciated aerosol measurements in winter, summer, and fall in Seoul.

Katherine R Travis↗
NASA NTRS2022

The Joint Assimilation of Remotely Sensed Leaf Area Index and Surface Soil Moisture into a Land Surface Model

This work tests the hypothesis that jointly assimilating satellite observations of leaf area index and surface soil moisture into a land surface model improves the estimation of land vegetation and water variables. An Ensemble Kalman Filter is used to test such hypothesis across the Contiguous United States during April 2015 – December 2018. The performance of the proposed methodology is assessed for several modeled vegetation and water variables (evapotranspiration, net ecosystem exchange, and soil moisture) in terms of random errors and anomaly correlation coefficients against a set of independent validation datasets (i.e., Global Land Evaporation Amsterdam Model, FLUXCOM, and International Soil Moisture Network). Results show that the assimilation of leaf area index mostly improves the estimation of evapotranspiration and net ecosystem exchange, whereas the assimilation of surface soil moisture alone improves surface soil moisture content, especially in the western US, in terms of both root mean squared error and anomaly correlation coefficient. The joint assimilation of vegetation and soil moisture information combines the results of individual vegetation and soil moisture assimilations and reduces errors (and increases correlations with the reference datasets) in evapotranspiration, net ecosystem exchange, and surface soil moisture simulated by the land surface model. However, because soil moisture satellite observations only provide information on the water content in the top 5 cm of the soil column, the impact of the proposed data assimilation technique on root zone soil moisture is limited. This work moves one step forward in the direction of improving our estimation and understanding of land surface interactions using a multi-variate data assimilation approach, which can be particularly useful in regions of the world where ground observations are sparse or missing altogether.

Data assimilation↗
NASA NTRS2004

Neural network uncertainty assessment using Bayesian statistics: a remote sensing application

Neural network (NN) techniques have proved successful for many regression problems, in particular for remote sensing; however, uncertainty estimates are rarely provided. In this article, a Bayesian technique to evaluate uncertainties of the NN parameters (i.e., synaptic weights) is first presented. In contrast to more traditional approaches based on point estimation of the NN weights, we assess uncertainties on such estimates to monitor the robustness of the NN model. These theoretical developments are illustrated by applying them to the problem of retrieving surface skin temperature, microwave surface emissivities, and integrated water vapor content from a combined analysis of satellite microwave and infrared observations over land. The weight uncertainty estimates are then used to compute analytically the uncertainties in the network outputs (i.e., error bars and correlation structure of these errors). Such quantities are very important for evaluating any application of an NN model. The uncertainties on the NN Jacobians are then considered in the third part of this article. Used for regression fitting, NN models can be used effectively to represent highly nonlinear, multivariate functions. In this situation, most emphasis is put on estimating the output errors, but almost no attention has been given to errors associated with the internal structure of the regression model. The complex structure of dependency inside the NN is the essence of the model, and assessing its quality, coherency, and physical character makes all the difference between a blackbox model with small output errors and a reliable, robust, and physically coherent model. Such dependency structures are described to the first order by the NN Jacobians: they indicate the sensitivity of one output with respect to the inputs of the model for given input data. We use a Monte Carlo integration procedure to estimate the robustness of the NN Jacobians. A regularization strategy based on principal component analysis is proposed to suppress the multicollinearities in order to make these Jacobians robust and physically meaningful.

Neural Networks (Computer)↗
NASA NTRS1974

Descartes Mountains and Cayley Plains - Composition and provenance

Trace element compositions of petrographically characterized 2-4 mm lithic fragments from Apollo 16 soil samples are used to calculate initial REE concentrations in liquids in equilibrium with lunar anorthosites and to discuss the provenance of the Cayley Formation. Lithic fragments may be subdivided into four groups: (1) ANT rocks, (2) K- and SiO2-rich mesostasis-bearing rocks, (3) poikiloblastic rocks, and (4) (spinel) troctolites. Model liquids in equilibrium with essentially monominerallic anorthosites have initial REE concentrations 5-8 times those of chondrites. The REE contents of K- and SiO2-rich mesostasis-bearing rocks and poikiloblastic rocks are dominated by the mesostasis phases. ANT rocks appear to be more abundant in the Descartes Mountains, while poikiloblastic rocks appear to be more abundant in the Cayley Plains. Poikiloblastic rocks have intermediate to high LIL-element concentrations yet the low gamma-ray activity of Mare Orientale implies low LIL-element concentrations. Consequently, it is unlikely that the Cayley Formation is Orientale ejecta. A local origin as ejecta from smaller impacts is a more plausible model for the deposition of the Cayley Formation.

Drake, M. J.↗
NASA NTRS1991

A Variational Formalism for the Radiative Transfer Equation: Prelude to Model 3

The MODEL III variational data assimilation model is the third of four general assimilation models designed to blend weather data measured from space based platforms in the meteorological data mainstream in a way that maximizes the information content of the satellite data. Because there are many different observation locations and there are many instruments with different measurement error characteristics, it is also necessary to require that the blending be done to maximize the information content of the data and simultaneously to retain a dynamically consistent and reasonably accurate description of the state of the atmosphere. This is ideally a variational problem for which the data receive relative weights that are inversely proportional to measurement error and are adjusted to satisfy a set of dynamical equations that govern atmospheric processes. The advantage of MODEL III over the previous two models is that radiance, the atmospheric variable measured by satellite, becomes a dependent variable. In the previous versions, mean layer temperatures that had been retrieved from the radiances by some method, were included in the assimilation by substituting them in place of the rawinsonde temperatures. Now both rawinsonde temperatures and satellite radiances are included independently in the assimilation.

Achtemeier, Gary L.↗
NASA NTRS1972

The global energy budget of the thermosphere.

Experimental neutral atmospheric density and temperature profiles can be used to calculate the energy content variations of a given region as a function of time, season and location for which the data are available. Such calculations may then be compared with estimated energy inputs and losses to determine what other mechanisms may be important. In the present paper a model based on both incoherent scatter data from Arecibo, Nancay, and Jicamarca and satellite density measurements is used to derive the global distributions of thermal energy content and losses in the thermosphere. The energy sources and transport mechanisms required for global thermal balance are then discussed.

Swartz, W. E.↗
NASA NTRS2012

Characterization of Deficiencies in the Frequency Domain Forced Response Analysis Technique for Turbine Bladed Disks

Turbine blades in rocket and jet engine turbomachinery experience enormous harmonic loading conditions. These loads result from the integer number of upstream and downstream stator vanes as well as the other turbine stages. The standard technique for forced response analysis to assess structural integrity is to decompose a CFD generated flow field into its harmonic components, and to then perform a frequency response analysis at the problematic natural frequencies. Recent CFD analysis and water-flow testing at NASA/MSFC, though, indicates that this technique may miss substantial harmonic and non-harmonic excitation sources that become present in complex flows. These complications suggest the question of whether frequency domain analysis is capable of capturing the excitation content sufficiently. Two studies comparing frequency response analysis with transient response analysis, therefore, have been performed. The first is of a bladed disk with each blade modeled by simple beam elements. It was hypothesized that the randomness and other variation from the standard harmonic excitation would reduce the blade structural response, but the results showed little reduction. The second study was of a realistic model of a bladed-disk excited by the same CFD used in the J2X engine program. The results showed that the transient analysis results were up to 10% higher for "clean" nodal diameter excitations and six times larger for "messy" excitations, where substantial Fourier content around the main harmonic exists.

Brown, Andrew M.↗
NASA NTRS1973

Star formation and evolution in spiral galaxies.

Evolutionary models for regions of M31 and M33 and the solar neighborhood are based on a stellar birthrate suggested by the dynamics of spiral structure: we assume that stars are formed very efficiently until the gas content reaches equilibrium at its present value, which takes about 1 b.y.; thereafter, the birthrate just equals the rate at which gas enters the system from stellar mass-loss or infall of intergalactic matter. Each model represents an average around a cylindrical-shell-shaped region, which is homogeneous and closed except for possible infall. The disk and spiral-arm populations only are considered. Each star is followed in the H-R diagram from the main sequence to death as an invisible remnant. Integrated magnitudes, colors, mass-to-light ratio (M/L), gas content, helium and metal abundance (Z), are computed in steps of 1 b.y.

Quirk, W. J.↗
NASA NTRS1995

Subdaily Northern Hemisphere Ionospheric Maps Using an Extensive Network of GPS Receivers

Ionospheric total electron content (TEC) data derived from dual- frequency Global Positioning System (GPS) signals from 30 globally distributed network sites are fit to a simple ionospheric shell model, yielding a map of the ionosphere in the northern hemisphere every 12 hours during the January 1-15, 1993, period.

ionosphere total electron content Global Positioni↗
NASA NTRS2011

Constitutive Soil Properties for Mason Sand and Kennedy Space Center

Accurate soil models are required for numerical simulations of land landings for the Orion Crew Exploration Vehicle (CEV). This report provides constitutive material models for two soil conditions at Kennedy Space Center (KSC) and four conditions of Mason Sand. The Mason Sand is the test sand for LaRC s drop tests and swing tests of the Orion. The soil models are based on mechanical and compressive behavior observed during geotechnical laboratory testing of remolded soil samples. The test specimens were reconstituted to measured in situ density and moisture content. Tests included: triaxial compression, hydrostatic compression, and uniaxial strain. A fit to the triaxial test results defines the strength envelope. Hydrostatic and uniaxial tests define the compressibility. The constitutive properties are presented in the format of LSDYNA Material Model 5: Soil and Foam. However, the laboratory test data provided can be used to construct other material models. The soil models are intended to be specific to the soil conditions they were tested at. The two KSC models represent two conditions at KSC: low density dry sand and high density in-situ moisture sand. The Mason Sand model was tested at four conditions which encompass measured conditions at LaRC s drop test site.

Thomas, Michael A.↗
NASA NTRS1999

SiC and Si3N4 Recession Due to SiO2 Scale Volatility Under Combustor Conditions

Silicon carbide (SiC) and Si3N4 materials were tested in various turbine engine combustion environments chosen to represent either conventional fuel-lean or fuel-rich mixtures proposed for high-speed aircraft. Representative chemical vapor-deposited (CVD), sintered, and composite materials were evaluated by furnace and high-pressure burner rig exposures. Although protective SiO2 scales formed in all cases, the evidence presented supports a model based on paralinear growth kinetics (i.e., parabolic growth moderated simultaneously by linear volatilization). The volatility rate is dependent on temperature, moisture content, system pressure, and gas velocity. The burner tests were thus used to map SiO2 volatility (and SiC recession) over a range of temperatures, pressures, and velocities. The functional dependency of material recession (volatility) that emerged followed the form A[exp(-Q / RT)](P(sup x)v(sup y). These empirical relations were compared with rates predicted from the thermodynamics of volatile SiO and SiOxHy reaction products and a kinetic model of diffusion through a moving boundary layer. For typical combustion conditions, recession of 0.2 to 2 micrometers/hr is predicted at 1200 to 1400 C, far in excess of acceptable long-term limits.

Smialek, James L.↗
NASA NTRS1972

Nonlinear and adaptive estimation techniques in reentry

The development and testing of nonlinear and adaptive estimators for reentry (e.g. space shuttle) navigation and model parameter estimation or identification are reported. Of particular interest is the identifcation of vehicle lift and drag characteristics in real time. Several nonlinear filters were developed and simulated. Adaptive filters for the real time identification of vehicle lift and drag characteristics, and unmodelable acceleration, were also developed and tested by simulation. The simulations feature an uncertain system environment with rather arbitrary model errors, thus providing a definitive test of estimator performance. It was found that nonlinear effects are indeed significant in reentry trajectory estimation and a nonlinear filter is demonstrated which successfully tracks through nonlinearities without degrading the information content of the data. Under the same conditions the usual extended Kalman filter diverges and is useless. The J-adaptive filter is shown to successfully track errors in the modeled vehicle lift and drag characteristics. The same filter concept is also shown to track successfully through rather arbitrary model errors, including lift and drag errors, vehicle mass errors, atmospheric density errors, and wind gust errors.

Jazwinski, A. H.↗
NASA NTRS1986

Estimation of crystallinity in a model thermoplastic composite

Crystallinities as low as 16 percent have been estimated by determination of the interplanar spacing on PET/carbonaceous filament composites with resin content of aobut 25 percent w/w using wide-angle X-ray scattering (WAXS) in the angular range 2 theta = 16-18 deg. The diffraction pattern of the carbonaceous reinforcements masks the major reflections of the resin, and the resin content and the crystallinity are kept low to make the simulation reasonable.

Wakelyn, N. T.↗
NASA NTRS2013

Evaluation of Intercomparisons of Four Different Types of Model Simulating TWP-ICE

Four model intercomparisons were run and evaluated using the TWP-ICE field campaign, each involving different types of atmospheric model. Here we highlight what can be learnt from having single-column model (SCM), cloud-resolving model (CRM), global atmosphere model (GAM) and limited-area model (LAM) intercomparisons all based around the same field campaign. We also make recommendations for anyone planning further large multi-model intercomparisons to ensure they are of maximum value to the model development community. CRMs tended to match observations better than other model types, although there were exceptions such as outgoing long-wave radiation. All SCMs grew large temperature and moisture biases and performed worse than other model types for many diagnostics. The GAMs produced a delayed and significantly reduced peak in domain-average rain rate when compared to the observations. While it was shown that this was in part due to the analysis used to drive these models, the LAMs were also driven by this analysis and did not have the problem to the same extent. Based on differences between the models with parametrized convection (SCMs and GAMs) and those without (CRMs and LAMs), we speculate that that having explicit convection helps to constrain liquid water whereas the ice contents are controlled more by the representation of the microphysics.

convection↗
NASA NTRS1989

Remote sensing of foliar chemistry

Remotely sensed data are being used to estimate foliar chemical content. This paper reviews how stepwise multiple regression and deconvolution have been used to extract chemical information from foliar spectra, and concludes that both methods are useful, but neither is ideal. It is recommended that the focus of research be modeling in the long term and experimentation in the short term. Long-term research should increase our understanding of the interaction between radiation and foliar chemistry so that the focus of research can move from leaf model to canopy model to field experiment. Short-term research should aim to design experiments in which remotely sensed data are used to generate unambiguous and accurate estimates of foliar chemical content.

Curran, Paul J.↗