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At least 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

New Interstellar Dust Models Consistent with Interstellar Extinction, Emission and Abundances Constraints

We present new interstellar dust models that are consistent with both, the FUV to near-IR extinction and infrared (IR) emission measurements from the diffuse interstellar medium. The models are characterized by different dust compositions and abundances. The problem we solve consists of determining the size distribution of the various dust components of the model. This problem is a typical ill-posed inversion problem which we solve using the regularization approach. We reproduce the Li Draine (2001, ApJ, 554, 778) results, however their model requires an excessive amount of interstellar silicon (48 ppM of hydrogen compared to the 36 ppM available for an ISM of solar composition) to be locked up in dust. We found that dust models consisting of PAHs, amorphous silicate, graphite, and composite grains made up from silicates, organic refractory, and water ice, provide an improved fit to the extinction and IR emission measurements, while still requiring a subsolar amount of silicon to be in the dust. This research was supported by NASA Astrophysical Theory Program NRA 99-OSS-01.

Zubko, V.↗
NASA NTRS1988

Radiative transfer in planetary atmospheres

Rheoretical techniques and observations at millimeter wavelengths are combined to study the atmosphere of planets and comets, planetary and satellite regoliths, and planetary rings. Analysis of the very high quality data on the 18 cm OH line observed in recent comets continued. The high spectral resolution and high signal-to-noise make these lines ideal for study of the kinematics in cometary comae. A model of the collisional quenching of the inversion of the lambda doublet responsible for the OH radio emission has been developed by P. Schloerb. For conditions appropriate to Halley's Comet, collisional quenching should lead radio observers to systematically underestimate the OH parent production rate by a factor of approximately 3 relative to its actual value, which is very consistent with differences observed between radio and ultraviolet-derived production rates. Modeling is likewise continuing for the profiles observed in the lowest rotational transition of HCN in Comet Halley in order to better estimate the excitation and hence the abundance of HCN, as well as the kinematics of parent molecules in the coma. A collaborative program to combine data from the 14 m antenna with interferometric data abtained at the Hat Creek Radio Observatory is allowing aperture synthesis mapping of Venus in the CO J=1-0 line.

Irvine, William M.↗
NASA NTRS1984

Models of auroral-zone conductances

The magnetosphere-ionosphere system is strongly coupled, with magnetospheric Birkeland currents feeding ionospheric Pedersen and Hall currents. Central to any computer simulation of this system is a detailed, valid conductivity model. An accurate conductivity model is also vital in order to infer Birkeland currents and electric field patterns from inversions of magnetometer chain data. Several recent attempts at constructing conductivity models are presented and their strengths and weaknesses discussed. Incoherent scatter radar measurements can determine height profiles of electron content, from which Pedersen and Hall conductances may be calculated. These yield excellent spatial and good temporal resolution; however, they are limited in field of view. A global pattern requires either 24 hours of data or a chain of stations. Synoptic empirical models (quantized by indices such as Kp or AE) typically are limited by their large bin size (1 deg invariant latitude x 1 hour MLT), and cannot reproduce arcs. Estimating conductivity globally from Dynamics Explorer auroral images is promising, and can yield reasonable time scales (of about 10 minutes); however, this procedure is still only now being tested.

Reiff, P. H.↗
NASA NTRS1987

On determining important aspects of mathematical models: Application to problems in physics and chemistry

The use of parametric and functional gradient sensitivity analysis techniques is considered for models described by partial differential equations. By interchanging appropriate dependent and independent variables, questions of inverse sensitivity may be addressed to gain insight into the inversion of observational data for parameter and function identification in mathematical models. It may be argued that the presence of a subset of dominantly strong coupled dependent variables will result in the overall system sensitivity behavior collapsing into a simple set of scaling and self similarity relations amongst elements of the entire matrix of sensitivity coefficients. These general tools are generic in nature, but herein their application to problems arising in selected areas of physics and chemistry is presented.

Rabitz, Herschel↗
NASA NTRS1991

Estimation of optimal Kalman filter gain from non-optimal filter residuals

This paper presents a novel method of estimating the optimal steady state Kalman filter gain of a linear discrete time-invariant system from a non-optimal Kalman filter residual sequence. The relation between the optimal residual sequence and a signal derived from the non-optimal residual sequence is described by a Moving Average (MA) model whose coefficients are expressed in terms of the state space parameters and the optimal steady state Kalman filter gain. In order to identify the MA model, a whitening filter of the derived signal, which corresponds to an AutoRegressive (AR) model of the signal, is first identified using the least-squares method. Then the inverse filter of the whitening filter, which corresponds to the MA model, is calculated. From the coefficients of the identified MA model, the optimal steady state Kalman filter gain can be obtained. Numerical example is provided to illustrate the feasibility of this approach.

Chen, Chung-Wen↗
NASA NTRS1976

The development of a model to infer precipitation from microwave measurements

To permit the inference of precipitation amounts from radiometric measurements, a radiative interaction model was developed. This model uses a simple computational scheme to determine the effects of rain upon brightness temperatures and can be used with a statistical inversion procedure to invert for rain rate. Precipitating cloud models was also developed and used with the microwave model for frequencies of 19.35 and 37 GHz to determine the variability of the microwave-rain rate relationship on a global and seasonal basis.

Fowler, M. G.↗
NASA NTRS1987

Compression of oceanic lithosphere - An analysis of intraplate deformation in the Central Indian Basin

The development of intraplate structure in the Central Indian Basin is examined using models in which deformation is due to flexural buckling and the hydrodynamic growth of instabilities. Comparison of the models reveal that in a strong viscous lithosphere, deformation of the layer occurs by flexural folding at a wavelength which corresponds to the flexural buckling theory; in a lithosphere of intermediate strength, the layer deforms by folding characterized by thickening which localizes beneath topographic heights; and in a relatively weak lithosphere, the layer incurs an even greater amount of localized thickening and deforms in the symmetric or pinch-and-swell mode by inverse boudinage. It is noted that the models in which the layer folds either flexurally or with periodic thickening correspond with observed depth distribution of seismicity in the Central Indian Basin and with experimental rock rheological data.

Zuber, Maria T.↗
NASA NTRS1994

The Teton fault, Wyoming: Topographic signature, neotectonics, and mechanisms of deformation

We integrated geophysical and geological methods to evalute the structural evolution of the active Teton normal fault, Wyoming, and its role in the development of the dramatic topography of Teton Range and Jackson Hole. Comparison of variations in surface offsets with the topographic expression of the Teton range crest and drainage divide, and the overall structure of the range, suggests that the effects ofpostglacial faulting cannot be discriminated from the influence of pre-extensional structures and differential; erosion on the footwall topography. In contrast, the effects of multiple scarp-forming normal faulting earthquakes are expressed by the anomalous drainage pattern and westward tilt of the hanging wall, Jackson Hole, toward the Teton fault. Kinematic boundary element fault models suggest that the westward tilt of the valley floor is the product of 110-125 m of displacement on a 45 deg-75 deg E dipping Teton fault in the past 25,000-75,000 years. Comparisons with historic normal faulting earthquake displacements imply that this range of displacement corresponds to 10-50, M greater than 7 scarp-forming earthquakes. A total throw of 2.5 to 3.5 km across the Teton fault is suggested by inverse ray-tracing and forward gravity models. These models also suggest that Laramide age structures have been offset across the Teton fault and obscure its geophysical signature but also continue to influence the structural and topographic expression of the footwall and hanging wall blocks. Paleomagnetic analyses of the approximately 2.0 Ma Huckelberry Ridge Tuff suggest that the overall westward tilt of the Teton Range is a result ofabout 10 deg of west side down tilt across the Teton fault since tuff emplacement. This suggests that much if not all of the throw across the Teton fault has accumulated in the past 2 m.y. Complex demagnetization and rock magnetic behavior and local emplacement of the Huckleberry Ridge Tuff on preexisting topogrpahy preclude determination of the amount or variations in throw along strike of the Teton fault from the paleomagnetic data.

Byrd, John O. D.↗
NASA NTRS1976

The prediction of zenith range refraction from surface measurements of meteorological parameters

In the last two decades, increasingly sophisticated deep space missions have placed correspondingly stringent requirements on navigational accuracy. As part of the effort to increase navigational accuracy, and hence the quality of radiometric data, much effort has been expended in an attempt to understand and compute the tropospheric effect on range (and hence range rate) data. The general approach adopted has been that of computing a zenith range refraction, and then mapping this refraction to any arbitrary elevation angle via an empirically derived function of elevation. The prediction of zenith range refraction derived from surface measurements of meteorological parameters is presented. Refractivity is separated into wet (water vapor pressure) and dry (atmospheric pressure) components. The integration of dry refractivity is shown to be exact. Attempts to integrate wet refractivity directly prove ineffective; however, several empirical models developed by the author and other researchers at JPL are discussed. The best current wet refraction model is here considered to be a separate day/night model, which is proportional to surface water vapor pressure and inversely proportional to surface temperature. Methods are suggested that might improve the accuracy of the wet range refraction model.

Berman, A. L.↗
NASA NTRS2019

Bayesian Inference and the Effects of Varying Uncertainty Models in Charring Ablator Calibration and Uncertainty Quantification Problems

The Mars Science Laboratory (MSL) vehicle utilized a heat shield constructed from NASA’s Phenolic-Impregnated Carbon Ablator (PICA) material to protect the main structure from the high enthalpy environment encountered during hypersonic atmospheric entry. During the vehicle’s descent through Martian atmosphere, multiple thermocouples embedded within the heat shield captured in-depth material temperature data that allow for studies to be conducted on current material response reconstruction tools. In the present work, material temperature data obtained from thermocouples within the MISP-4 plug (MEDLI (Mars Science Laboratory Entry, Descent, and Landing Instrument) Integrated Sensor Plug) are utilized in the calibration of Theoretical Ablative Composite for Open Testing (TACOT) model parameters in conjunction with NASA’s Porous material Analysis Toolbox (PATO) through Bayesian inference where uncertainty due to parametric, modeling, and experimental sources is simultaneously quantified. Prior to the study, a sensitivity analysis is performed through computation of the robust Sobol indices in an effort to study the relationship between input space and model response and to reduce the dimensionality of the statistical inverse problem. The Bayesian inference methodology necessitates an a-priori choice to be made for the uncertainty model for which numerous possibilities are available. Across most works, however, only basic additive or multiplicative models are utilized with pre-defined magnitudes of uncertainty based on a-priori knowledge or to-be-calibrated multipliers of static covariance matrix structures. The present effort explores the effects of informed uncertainty models, ones with temporal dependence that are simultaneously calibrated through Bayesian inference, on calibrated results for parameters that make up the uncertain input space.

Sensitivity Analysis↗
NASA NTRS1978

The impact of chlorofluoromethane and NO/x/ injections on stratospheric ozone

The chlorofluoromethane problem and the SST problem have been subject to continuing evaluation by the use of one-dimensional stratospheric photochemistry models. The problems to some extent appear to be inversely related to one another through hydroxyl radical reactions; in other words, processes which tend to increase the amount of OH in a model tend to increase the sensitivity of the ozone column to ClX perturbations, while at the same time decreasing the sensitivity to NO(x) perturbations. Evaluations of sensitivity to ClX and NO(x) have varied as new input information has become available and modeling techniques have improved. It is clear that either NO(x) or ClX, or both, will affect the distribution of ozone with altitude.

Stolarski, R. S.↗
NASA NTRS1992

A simple analytical function for bidirectional reflectance

A simple bidirectional reflectance model based on physical scattering laws is developed to calculate the bidirectional reflectance of a wide variety of surfaces. Chandrasekhar's radiative transfer solution, obtained for the anisotropically scattering semi-infinite medium, is used to compute the multiple-scattered radiances. However, since the radiative transfer solution does not take architectural effects into consideration, we adopt Hapke's (1986) approach and add an empirical term to explain the hot-spot phenomenon and use Cox and Munk's (1954) formulation to take into account the specular reflection. The physical parameters of the model are retrieved from bidirectional reflectance measurements. For each surface, only one set of model parameters is needed for application to all illumination and viewing geometries. The validity of the model is established by comparing the computed and measured reflectances for sets of viewing and illumination angles that were not included in the inversion algorithm. Good agreement is shown between the model-computed and the observed reflectances for dense prairie vegetation canopies, a sparse desert scrub community, a plowed agricultural field, and an alkali flat.

Ahmad, Suraiya P.↗
NASA NTRS1980

Investigation of multiple scattering effects in aerosols

The results are presented of investigations on the various aspects of multiple scattering effects on visible and infrared laser beams transversing dense fog oil aerosols contained in a chamber (4' x 4' x 9'). The report briefly describes: (1) the experimental details and measurements; (2) analytical representation of the aerosol size distribution data by two analytical models (the regularized power law distribution and the inverse modified gamma distribution); (3) retrieval of aerosol size distributions from multispectral optical depth measurements by two methods (the two and three parameter fast table search methods and the nonlinear least squares method); (4) modeling of the effects of aerosol microphysical (coagulation and evaporation) and dynamical processes (gravitational settling) on the temporal behavior of aerosol size distribution, and hence on the extinction of four laser beams with wavelengths 0.44, 0.6328, 1.15, and 3.39 micrometers; and (5) the exact and approximate formulations for four methods for computing the effects of multiple scattering on the transmittance of laser beams in dense aerosols, all of which are based on the solution of the radiative transfer equation under the small angle approximation.

Deepak, A.↗
NASA NTRSDate not supplied

Variance Decomposition of MEDLI2 Reconstructed Heating Using Neural Networks

The Mars Entry, Descent, and Landing Instrumentation (MEDLI2) sensor suite collected data during entry of the Mars 2020 Perseverance rover into Mars’ atmosphere. An inverse estimation of the backshell and heatshield surface aeroheating was performed, using the data from the MEDLI2 Instrumented Sensor Plugs, a network of thermocouples embedded within the thermal protection system across the aeroshell. Monte Carlo analysis was conducted to assess the sensitivity of the surface heat rate, temperature, and heat load to uncertainties in thermocouple depth and material properties. In this paper, a variance decomposition method using Sobol indices was employed to understand the relative contributions of each uncertainty parameter. Performing this analysis using results from the inverse analysis tool FIAT_Opt was found to require incredibly high computation time, and thus machine learning models were trained and evaluated as a surrogate model for FIAT_Opt. This paper demonstrates that machine learning models can be an efficient, accurate alternative to state-of-the-art inverse analysis tools like FIAT_Opt, especially for computationally-expensive processes. Using these models, the sensitivity analysis showed that uncertainties in heat capacity and thermal conductivity were the main drivers for the overall uncertainty in peak reconstructed heating and heat load.

H S Alpert↗
NASA NTRS2019

Evaluation of Matthews-WLR-CH4: A New Wetland, Lake, and Reservoir Methane Emissions Data Set

Methane (CH4) is emitted from a variety of sources, both natural and anthropogenic, and is the second most important greenhouse gas contributing to climate change. Natural wetlands are the largest single contributor to annual global CH4 emissions and other inland water sources, such as lakes and reservoirs, produce CH4 but have received less attention. These emission sources are among the most uncertain components of the global CH4 cycle. These uncertainties stem from numerous issues, including the vast variability in these ecosystems and the sensitivity of CH4 emissions to interannual climate variations. Existing CH4 emission models display large differences in wetland spatial extent and include simplified, or lack all together, wetland-type classifications. Furthermore, CH4 emissions from lakes and reservoirs are typically combined with wetlands, or ignored, on a regional and global scale. Our NASA Interdisciplinary Research in Earth Science (IDS) study is focused on developing a suite of data sets on wetlands, lakes, and reservoirs (WLR) including global distributions of types, CH4-centric classifications, and daily CH4 emission rates (hereafter Matthews-WLR-CH4). This project is unique in that it comprises source-independent emission data for WLR, the first spatially-explicit data set of lake and reservoir CH4 emissions, and wetland emissions comprising numerous different wetland-type classifications.The focus of this study is to perform the initial evaluation of the wetland and lake CH4 emissions data from Matthews-WLR-CH4. This evaluation will focus on the domain of North America and include: 1) estimates of the contribution of wetland and lake sources to total CH4 emissions and atmospheric mixing ratios, 2) comparisons of wetland fraction and CH4 emissions to a suite of existing models (e.g., Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP), Global Carbon Project (GCP)), and 3) an accuracy assessment with in situ airborne and tower-based atmospheric CH4 observations when the Matthews-WLR-CH4 emissions are implemented in forward and inverse CarbonTracker-Lagrange (CT-L) CH4 model simulations. Here we will present the new Matthews-WLR-CH4 wetland and lake CH4 emissions data, the initial evaluation of these products, and the path forward for our project.

Reservoir↗
NASA NTRS2012

Water Vapor on Titan: The Stratospheric Vertical Profile from Cassini/CIRS Infrared Spectra

Water vapor in Titan's middle atmosphere has previously been detected only by disk-average observations from the Infrared Space Observatory (Coustenis et al., 1998). We report here the successful detection of stratospheric water vapor using the Cassini Composite Infrared Spectrometer (CIRS, Flasar et al., 2004) following an earlier null result (de Kok et al., 2007a). CIRS senses water emissions in the far-infrared spectral region near 50 microns, which we have modeled using two independent radiative transfer and inversion codes (NEMESIS, Irwin et al 2008 and ART, Coustenis et al., 2010). From the analysis of nadir spectra we have derived a mixing ratio of (0.14 plus or minus 0.05) ppb at 100 km, corresponding to a column abundance of approximately (3.7 plus or minus 1.3) x 10(exp 14) moles per square centimeter. Using limb observations, we obtained mixing ratios of (0.13 plus or minus 0.04) ppb at 125 km and (0.45 plus or minus 0.15) ppb at 225 km of altitude, confirming that the water abundance has a positive vertical gradient as predicted by photochemical models. In the latitude range (80 deg. S - 30 deg. N) we see no evidence for latitudinal variations in these abundances within the error bars.

Cottini, V.↗
NASA NTRS2017

Retrievals of Aerosol Microphysics from Simulations of Spaceborne Multiwavelength Lidar Measurements

In support of the Aerosol, Clouds, Ecosystems mission, simulations of a spaceborne multiwavelength lidar are performed based on global model simulations of the atmosphere along a satellite orbit track. The yield for aerosol microphysical inversions is quantified and comparisons are made between the aerosol microphysics inherent in the global model and those inverted from both the model's optical data and the simulated three backscatter and two extinction lidar measurements, which are based on the model's optical data. We find that yield can be significantly increased if inversions based on a reduced optical dataset of three backscatter and one extinction are acceptable. In general, retrieval performance is better for cases where the aerosol fine mode dominates although a lack of sensitivity to particles with sizes less than 0.1 microns is found. Lack of sensitivity to coarse mode cases is also found, in agreement with earlier studies. Surface area is generally the most robustly retrieved quantity. The work here points toward the need for ancillary data to aid in the constraints of the lidar inversions and also for joint inversions involving lidar and polarimeter measurements.

aerosols↗
NASA NTRS2020

Robust Algorithm for Estimating Total Suspended Solids (TSS) in Inland and Nearshore Coastal Waters

One of the challenging tasks in modern aquatic remote sensing is the retrieval of near-surface concentrations of Total Suspended Solids (TSS). This study aims to present a Statistical, inherent Optical property (IOP) -based, and muLti-conditional Inversion proceDure (SOLID) for enhanced retrievals of satellite-derived TSS under a wide range of in-water bio-optical conditions in rivers, lakes, estuaries, and coastal waters. In this study, using a large in situ database (N > 3500), the SOLID model is devised using a three-step procedure: (a) water-type classification of the input remote sensing reflectance (R(sub rs)), (b) retrieval of particulate backscattering (b(sub bp)) in the red or near-infrared (NIR) regions using semi-analytical, machine-learning, and empirical models, and (c) estimation of TSS from b(sub bp) via water-type-specific empirical models. Using an independent subset of our in situ data (N = 2729) with TSS ranging from 0.1 to 2626.8 [g/m (exp 3)], the SOLID model is thoroughly examined and compared against several state-of-the-art algorithms (Miller and McKee, 2004; Nechad et al., 2010; Novoa et al., 2017; Ondrusek et al., 2012; Petus et al., 2010). We show that SOLID outperforms all the other models to varying degrees, i.e., from 10 to > 100%, depending on the statistical attributes (e.g., global versus water-type-specific metrics). For demonstration purposes, the model is implemented for images acquired by the MultiSpectral Imager aboard Sentinel-2A/B over the Chesapeake Bay, San-Francisco-Bay-Delta Estuary, Lake Okeechobee, and Lake Taihu. To enable generating consistent, multimission TSS products, its performance is further extended to, and evaluated for, other missions, such as the Ocean and Land Color Instrument (OLCI), Moderate Resolution Imaging Spectroradiometer (MODIS), Visible Infrared Imaging Radiometer Suite (VIIRS), and Operational Land Imager (OLI). Sensitivity analyses on uncertainties induced by the atmospheric correction indicate that 10% uncertainty in Rrs leads to < 20% uncertainty in TSS retrievals from SOLID. While this study suggests that SOLID has a potential for producing TSS products in global coastal and inland waters, our statistical analysis certainly verifies that there is still a need for improving retrievals across a wide spectrum of particle loads.

Total suspended solids↗