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NASA NTRS1991

Single board system for fuzzy inference

The very large scale integration (VLSI) implementation of a fuzzy logic inference mechanism allows the use of rule-based control and decision making in demanding real-time applications. Researchers designed a full custom VLSI inference engine. The chip was fabricated using CMOS technology. The chip consists of 688,000 transistors of which 476,000 are used for RAM memory. The fuzzy logic inference engine board system incorporates the custom designed integrated circuit into a standard VMEbus environment. The Fuzzy Logic system uses Transistor-Transistor Logic (TTL) parts to provide the interface between the Fuzzy chip and a standard, double height VMEbus backplane, allowing the chip to perform application process control through the VMEbus host. High level C language functions hide details of the hardware system interface from the applications level programmer. The first version of the board was installed on a robot at Oak Ridge National Laboratory in January of 1990.

Symon, James R.↗
NASA NTRS1992

An expert system shell for inferring vegetation characteristics: Implementation of additional techniques (task E)

The NASA VEGetation Workbench (VEG) is a knowledge based system that infers vegetation characteristics from reflectance data. The VEG subgoal PROPORTION.GROUND.COVER has been completed and a number of additional techniques that infer the proportion ground cover of a sample have been implemented. Some techniques operate on sample data at a single wavelength. The techniques previously incorporated in VEG for other subgoals operated on data at a single wavelength so implementing the additional single wavelength techniques required no changes to the structure of VEG. Two techniques which use data at multiple wavelengths to infer proportion ground cover were also implemented. This work involved modifying the structure of VEG so that multiple wavelength techniques could be incorporated. All the new techniques were tested using both the VEG 'Research Mode' and the 'Automatic Mode.'

Harrison, P. Ann↗
NASA NTRS1993

Truth-Valued-Flow Inference (TVFI) and its applications in approximate reasoning

The framework of the theory of Truth-valued-flow Inference (TVFI) is introduced. Even though there are dozens of papers presented on fuzzy reasoning, we think it is still needed to explore a rather unified fuzzy reasoning theory which has the following two features: (1) it is simplified enough to be executed feasibly and easily; and (2) it is well structural and well consistent enough that it can be built into a strict mathematical theory and is consistent with the theory proposed by L.A. Zadeh. TVFI is one of the fuzzy reasoning theories that satisfies the above two features. It presents inference by the form of networks, and naturally views inference as a process of truth values flowing among propositions.

Wang, Pei-Zhuang↗
NASA NTRS1993

Mountain-wave drag in the stratosphere and mesosphere inferred from observed winds and a simple mountain-wave parameterization scheme

A daily analysis of mountain-wave propagation through observed, global wind, and temperature fields in January and August is presented. Winds and temperatures are obtained from the daily 18-level NMC Climate Analysis Center. Mountain-wave properties are deduced from a simple, gravity wave parameterization scheme in which the effects of topographic anisotropy (ridge orientation) are explicitly included. Planetary waves in the northern winter stratosphere are found to play an important role in modulating the magnitude and distribution of inferred mountain-wave drag in the middle atmosphere. The Aleutian anticyclone is found to effectively block mountain waves generated over western North America from reaching the mesosphere by inducing local mountain-wave-critical levels in the stratosphere. Stratospheric sudden warmings have a similar effect at all longitudes so that during months with sudden warmings the average inferred drag in the mesosphere is reduced by a factor of 4 to 5 from its normal value. Partly as a consequence of larger planetary-wave filtering in the Northern Hemisphere, inferred mountain-wave drag in the southern winter mesosphere is found to be comparable to that in the northern winter mesosphere. Almost all of the mountain wave drag exerted on the southern middle atmosphere is found to originate over the southern Andes and Antarctic Peninsula.

Bacmeister, Julio T.↗
NASA NTRS1994

How well was total ozone abundance inferred with Mariner 9?

Ozone is a key to understanding atmospheric chemistry on Mars. Over 20 photochemical models of the martian atmosphere have been published, and O3 is often used as a benchmark for these models. O3 abundance has been inferred from instrumentation on several spacecraft, with the most complete coverage provided by Mariner 9. The Mariner 9 UV spectrometer scanned from 2100 to 3500 Angstroms with a spectral resolution of 15 Angstroms and an effective field-of-view of approximately 300 sq km. The only atmospheric absorption in the 2000 to 3000 A wavelength region was previously assumed to come from the Hartley band system of ozone, which has an opacity of order unity at winter polar latitudes. Therefore, the amount of ozone was inferred by fitting this absorption feature with laboratory data of ozone absorption. Mars O3 shows strong seasonal and latitudinal variation, with column abundances ranging from 0.2 micron-atm at equatorial latitudes to 60 micron-atm over northern winter polar latitudes (1 micron-atm is a column abundance of 2.689 x 10 exp 15 molecules cm(exp -2)). However, the O3 abundance is never great enough to significantly affect atmospheric temperatures or surface temperatures and frost amounts. Some of the previously-inferred O3 abundances are shown. A radiative transfer computer model is used to re-examine the Mariner 9 UV spectra. Assuming a constant mixing ratio for O3 and no chemical or radiative interaction between O3 and clouds/dust, it is shown that when typical amounts of dust and cloud are present that significant underestimation of O3 abundance occurs. A factor of 3 times as much O3 is needed to generate the same spectrum the spacecraft would measure for a cloudy, dusty atmosphere as for a clear atmosphere. If the scattering properties of martian clouds and dust were well known, then their appearance would not be a problem, as a model would be capable of retrieving the O3 abundance. However, these properties are not well known, which raises doubts about the effectiveness of the UV reflectance spectroscopy technique for measuring O3 abundance on Mars.

Lindner, Bernhard Lee↗
NASA NTRS1998

Central Plasma Sheet Ion Properties as Inferred from Ionospheric Observations

A method of inferring central plasma sheet (CPS) temperature, density, and pressure from ionospheric observations is developed. The advantage of this method over in situ measurements is that the CPS can be studied in its entirely, rather than only in fragments. As a result, for the first time, comprehensive two-dimensional equatorial maps of CPS pressure, density, and temperature within the isotropic plasma sheet are produced. These particle properties are calculated from data taken by the Special Sensor for Precipitating Particles, version 4 (SSJ4) particle instruments onboard DMSP F8, F9, F10, and F11 satellites during the entire year of 1992. Ion spectra occurring in conjunction with electron acceleration events are specifically excluded. Because of the variability of magnetotail stretching, the mapping to the plasma sheet is done using a modified Tsyganenko [1989] magnetic field model (T89) adjusted to agree with the actual magnetotail stretch at observation time. The latter is inferred with a high degree of accuracy (correlation coefficient -0.9) from the latitude of the DMSP b2i boundary (equivalent to the ion isotropy boundary). The results show that temperature, pressure, and density all exhibit dawn-dusk asymmetries unresolved with previous measurements. The ion temperature peaks near the midnight meridian. This peak, which has been associated with bursty bulk flow events, widens in the Y direction with increased activity. The temperature is higher at dusk than at dawn, and this asymmetry increases with decreasing distance from the Earth. In contrast, the density is higher at dawn than at dusk, and there appears to be a density enhancement in the low-latitude boundary layer regions which increases with decreasing magnetic activity. In the near-Earth regions, the pressure is higher at dusk than at dawn, but this asymmetry weakens with increasing distance from the Earth and may even reverse so that at distances X less than approx. 10 to -12 R(sub E), depending on magnetic activity, the dawn sector has slightly higher pressure. The temperature and density asymmetries in the near-Earth region are consistent with the ion westward gradient/curvature drift as the ions ExB convect earthward. When the solar wind dynamic pressure increases, CPS density and pressure appear to increase, but the temperature remains relatively constant. Comparison with previously published work indicates good agreement between the inferred pressure, temperature, and density and those obtained from in situ data. This new method should provide a continuous mechanism to monitor the pressure, temperature, and density in the magnetotail with unprecedented comprehensiveness.

Wing, Simon↗
NASA NTRS1998

Comment on the Predicted Size of Cycle 23 Based on the Inferred Three-Cycle Quasi-Periodicity of the Planetary Index Ap

Recently, Ahluwalia [1998] reviewed the solar and geomagnetic data for the last 6 decades and remarked that these data "indicate the existence of a three-solar-activity-cycle quasi-periodicity in them." Futhermore, on the basis of this inferred quasi-periodicity, he asserted that cycle 23 represents the initial cycle in a new 3-cycle string, implying that it "will be more modest (a la cycle 17) with an annual mean sunspot number count of 119.3 +/- 30 at the maximum," a prediction that is considerably below the consensus prediction of 160 +/- 30 by Joselyn et al. [1997] and of similar predictions by others based on a variety of predictive techniques. Several major sticking points of Ahluwalia's presentation, however, must be redressed, and these issues form the basis of this comment. In particular, it is shown that Ahluwalia used inappropriate values of the Ap index in his analysis, that the inferred 3-cycle relationship which Ahluwalia claims for both Ap and SSN does not exist for the previous 6-cycle interval (prior to cycle 17) for SSN, that his inferred fit is only of marginal statistical significance (having r = 0.81), and that two alternative precursor fits (both with r = 0.96 or greater) exist which strongly suggest that R max for cycle 23 will be much larger than forecast by Ahluwalia (namely, about 168-187). Thus, caution must be exercised in accepting Ahluwalia's findings.

Hathaway, David H.↗
NASA NTRS1998

Reveal, A General Reverse Engineering Algorithm for Inference of Genetic Network Architectures

Given the immanent gene expression mapping covering whole genomes during development, health and disease, we seek computational methods to maximize functional inference from such large data sets. Is it possible, in principle, to completely infer a complex regulatory network architecture from input/output patterns of its variables? We investigated this possibility using binary models of genetic networks. Trajectories, or state transition tables of Boolean nets, resemble time series of gene expression. By systematically analyzing the mutual information between input states and output states, one is able to infer the sets of input elements controlling each element or gene in the network. This process is unequivocal and exact for complete state transition tables. We implemented this REVerse Engineering ALgorithm (REVEAL) in a C program, and found the problem to be tractable within the conditions tested so far. For n = 50 (elements) and k = 3 (inputs per element), the analysis of incomplete state transition tables (100 state transition pairs out of a possible 10(exp 15)) reliably produced the original rule and wiring sets. While this study is limited to synchronous Boolean networks, the algorithm is generalizable to include multi-state models, essentially allowing direct application to realistic biological data sets. The ability to adequately solve the inverse problem may enable in-depth analysis of complex dynamic systems in biology and other fields.

Liang, Shoudan↗
NASA NTRS2003

Inferring the palaeoenvironment of ancient bacteria on the basis of resurrected proteins

Features of the physical environment surrounding an ancestral organism can be inferred by reconstructing sequences of ancient proteins made by those organisms, resurrecting these proteins in the laboratory, and measuring their properties. Here, we resurrect candidate sequences for elongation factors of the Tu family (EF-Tu) found at ancient nodes in the bacterial evolutionary tree, and measure their activities as a function of temperature. The ancient EF-Tu proteins have temperature optima of 55-65 degrees C. This value seems to be robust with respect to uncertainties in the ancestral reconstruction. This suggests that the ancient bacteria that hosted these particular genes were thermophiles, and neither hyperthermophiles nor mesophiles. This conclusion can be compared and contrasted with inferences drawn from an analysis of the lengths of branches in trees joining proteins from contemporary bacteria, the distribution of thermophily in derived bacterial lineages, the inferred G + C content of ancient ribosomal RNA, and the geological record combined with assumptions concerning molecular clocks. The study illustrates the use of experimental palaeobiochemistry and assumptions about deep phylogenetic relationships between bacteria to explore the character of ancient life.

Bacteria/classification/metabolism↗
NASA NTRS2006

Intra-seasonal Oscillations Inferred from SABER (TIMED) and MLS (UARS) Temperature Measurements

In the zonal mean meridional winds of the upper mesosphere, intra-seasonal oscillations with periods between 1 and 4 months have been inferred from UARS measurements and independently predicted with the Numerical Spectral Model WSM). The wind oscillations tend to be confined to low latitudes and appear to be driven, at least in part, by small-scale gravity waves propagating in the meridional direction. Winds across the equator should generate, due to dynamical heating and cooling, temperature oscillations with opposite phase in the two hemispheres. Investigating this phenomenon, we have analyzed SABER temperatures from TIMED in the altitude range between 55 and 95 km to delineate with an empirical model, the year-long variability of the migrating tides and zonal mean components. The inferred seasonal variations of the diurnal tide, characterized by amplitude maxima near equinox, are in substantial agreement with UARS observations and results from the NSM. For the zonal mean, the dominant seasonal variations in the SABER temperatures, with annual (12 months) and semiannual (6 months) periodicities, agree well with those derived from UARS measurements. The intra-seasonal variations with periods between 2 and 4 months have amplitudes close to 2 K, almost half as large as those for the dominant seasonal variations. Their amplitudes are in qualitative agreement with the corresponding values inferred from UARS during different years. The SABER and UARS temperature variations reveal pronounced hemispherical asymmetries, consistent with meridional wind oscillations across the equator. The phase of the semi-annual temperature oscillations from the NSM agrees with the observations from UARS and SABER. But the amplitudes are systematically smaller, which may indicate that planetary waves are more important than is allowed for in the model. For the shorter-period intra-seasonal variations, which can be generated by gravity wave drag, the model results are generally in better agreement with the observations.

Huang, F. T.↗
NASA NTRS2012

Inferred Lunar Boulder Distributions at Decimeter Scales

Block size distributions of impact deposits on the Moon are diagnostic of the impact process and environmental effects, such as target lithology and weathering. Block size distributions are also important factors in trafficability, habitability, and possibly the identification of indigenous resources. Lunar block sizes have been investigated for many years for many purposes [e.g., 1-3]. An unresolved issue is the extent to which lunar block size distributions can be extrapolated to scales smaller than limits of resolution of direct measurement. This would seem to be a straightforward statistical application, but it is complicated by two issues. First, the cumulative size frequency distribution of observable boulders rolls over due to resolution limitations at the small end. Second, statistical regression provides the best fit only around the centroid of the data [4]. Confidence and prediction limits splay away from the best fit at the endpoints resulting in inferences in the boulder density at the CPR scale that can differ by many orders of magnitude [4]. These issues were originally investigated by Cintala and McBride [2] using Surveyor data. The objective of this study was to determine whether the measured block size distributions from Lunar Reconnaissance Orbiter Camera - Narrow Angle Camera (LROC-NAC) images (m-scale resolution) can be used to infer the block size distribution at length scales comparable to Mini-RF Circular Polarization Ratio (CPR) scales, nominally taken as 10 cm. This would set the stage for assessing correlations of inferred block size distributions with CPR returns [6].

Baloga, S. M.↗
NASA NTRS2014

Inferred Variable FeO Content in Medium-sized Lunar Pyroclastic Deposits from LRO Diviner Data

Lunar pyroclastic deposits (LPDs) are low albedo features that mantle underlying terrain (Gaddis et al. 1985). They are high priority targets for science and exploration as they are believed to originate from and therefore reflect the composition of the deep lunar interior (NRC, 2011). They are also the best potential resource of oxygen out of any Apollo samples (Allen et al. 1996). Historically, LPDs have been divided into regional versus local categories (Gaddis et al. 2003). The large (>1000 km2 area) regional deposits are deeply sourced (>400 km deep) and result from fire fountaining. Small (<1000 km2) local deposits are thought to result from Vulcanian eruptions in which magma is slowly emplaced beneath the surface until enough volatiles exsolve and the high pressure causes an explosion. Bennett et al. (2013) identified a local deposit (674 km2 area) that may have resulted from both Vulcanian activity and fire fountaining. This deposit potentially represents a new intermediate class of LPDs that straddles the interface between the two formation mechanisms. The deposit also exhibits the highest inferred FeO wt.% of any known lunar glass. In this work we investigate the inferred FeO abundances of other medium-sized deposits to characterize this potential new class of deposits and understand the magnitude of variations in inferred FeO among pyroclastic deposits. We use the method of Greenhagen et al. (2010) to calculate the wavelength of the Christiansen Feature (CF) from Lunar Reconnaissance Orbiter Diviner Lunar Radiometer instrument thermal-infrared observations for four medium-sized deposits. From the CF values, we estimate each deposit's FeO abundance using the method of Allen et al. (2012). The four LPDs that we examined (Oppenheimer South, Beer, Cleomedes, and J. Herschel) all have average CF values from 8.22-8.28 microns, corresponding to FeO abundances of approx. 10-15 wt.%. All of these values are within the range and uncertainties of FeO abundances measured in Apollo samples. As previously identified, the Oppenheimer South deposit exhibits an area of enhanced CF values (8.49 microns) that, if the methods of Allen et al. (2012) can be extrapolated, correspond to a highest observed approx. 30 wt.% FeO. Moon Mineralogy Mapper near-infrared spectra indicate that this area is glass-rich as opposed to olivine-rich. While we are still investigating the nature of the high CF wavelength in Oppenheimer South, spatially-resolved observations there and (to a smaller degree) in our other study sites, shows that FeO wt.% can vary within LPDs. Thus, obtaining only the average FeO abundance over a large area may not be adequate to understand global variation. The magnitude of Oppenheimer South's CF variability, if due to actual surface variations rather than calibration artifacts or spectral mixing, could indicate that it is a unique deposit and not part of a new mid-sized class of deposits. The higher value could be a result of its location within the South Pole Aitken Basin and exsolution of more deeply sourced magma due to the thin crust there.

Bennett, K. A.↗
NASA NTRS2014

A Corrected Formulation of the Multilayer Model (MLM) for Inferring Gaseous Dry Deposition to Vegetated Surfaces

The Multilayer Model (MLM) has been used for many years to infer dry deposition fluxes from measured trace species concentrations and standard meteorological measurements for national networks in the U.S., including the U.S. Environmental Protection Agency's Clean Air Status and Trends Network (CASTNet). MLM utilizes a resistance analogy to calculate deposition velocities appropriate for whole vegetative canopies, while employing a multilayer integration to account for vertically varying meteorology, canopy morphology and radiative transfer within the canopy. However, the MLM formulation, as it was originally presented and as it has been subsequently employed, contains a non-physical representation related to the leaf-level quasi-laminar boundary layer resistance that affects the calculation of the total canopy resistance. In this note, the non-physical representation of the canopy resistance as originally formulated in MLM is discussed and a revised, physically consistent, formulation is suggested as a replacement. The revised canopy resistance formulation reduces estimates of HNO3 deposition velocities by as much as 38% during mid-day as compared to values generated by the original formulation. Inferred deposition velocities for SO2 and O3 are not significantly altered by the change in formulation (less than 3%). Inferred deposition loadings of oxidized and total nitrogen from CASTNet data may be reduced by 10-20% and 5-10%, respectively, for the Eastern U. S. when employing the revised formulation of MLM as compared to the original formulation.

vegetated surfaces↗
NASA NTRS2016

Uncertainty Reduction using Bayesian Inference and Sensitivity Analysis: A Sequential Approach to the NASA Langley Uncertainty Quantification Challenge

This paper presents a computational framework for uncertainty characterization and propagation, and sensitivity analysis under the presence of aleatory and epistemic un- certainty, and develops a rigorous methodology for efficient refinement of epistemic un- certainty by identifying important epistemic variables that significantly affect the overall performance of an engineering system. The proposed methodology is illustrated using the NASA Langley Uncertainty Quantification Challenge (NASA-LUQC) problem that deals with uncertainty analysis of a generic transport model (GTM). First, Bayesian inference is used to infer subsystem-level epistemic quantities using the subsystem-level model and corresponding data. Second, tools of variance-based global sensitivity analysis are used to identify four important epistemic variables (this limitation specified in the NASA-LUQC is reflective of practical engineering situations where not all epistemic variables can be refined due to time/budget constraints) that significantly affect system-level performance. The most significant contribution of this paper is the development of the sequential refine- ment methodology, where epistemic variables for refinement are not identified all-at-once. Instead, only one variable is first identified, and then, Bayesian inference and global sensi- tivity calculations are repeated to identify the next important variable. This procedure is continued until all 4 variables are identified and the refinement in the system-level perfor- mance is computed. The advantages of the proposed sequential refinement methodology over the all-at-once uncertainty refinement approach are explained, and then applied to the NASA Langley Uncertainty Quantification Challenge problem.

Uncertainty↗
NASA NTRS2017

On Tidal Inference in the Diurnal Band

Standard methods of tidal inference should be revised to account for a known resonance that occurs mostly within the K(sub 1) tidal group in the diurnal band. The resonance arises from a free rotational mode of Earth caused by the fluid core. In a set of 110 bottom-pressure tide stations, the amplitude of the P(sub 1) tidal constituent is shown to be suppressed relative to K(sub 1), which is in good agreement with the resonance theory. Standard formulas for the K(sub 1) nodal modulation remain essentially unaffected. Two examples are given of applications of the refined inference methodology: one with monthly tide gauge data and one with satellite altimetry. For some altimeter-constrained tide models, an inferred P(sub 1) constituent is found to be more accurate than a directly determined one.

Ray, R. D.↗
NASA NTRS2017

A Framework for Inferring Taxonomic Class of Asteroids.

Introduction: Taxonomic classification of asteroids based on their visible / near-infrared spectra or multi band photometry has proven to be a useful tool to infer other properties about asteroids. Meteorite analogs have been identified for several taxonomic classes, permitting detailed inference about asteroid composition. Trends have been identified between taxonomy and measured asteroid density. Thanks to NEOWise (Near-Earth-Object Wide-field Infrared Survey Explorer) and Spitzer (Spitzer Space Telescope), approximately twice as many asteroids have measured albedos than the number with taxonomic classifications. (If one only considers spectroscopically determined classifications, the ratio is greater than 40.) We present a Bayesian framework that provides probabilistic estimates of the taxonomic class of an asteroid based on its albedo. Although probabilistic estimates of taxonomic classes are not a replacement for spectroscopic or photometric determinations, they can be a useful tool for identifying objects for further study or for asteroid threat assessment models. Inputs and Framework: The framework relies upon two inputs: the expected fraction of each taxonomic class in the population and the albedo distribution of each class. Luckily, numerous authors have addressed both of these questions. For example, the taxonomic distribution by number, surface area and mass of the main belt has been estimated and a diameter limited estimate of fractional abundances of the near earth asteroid population was made. Similarly, the albedo distributions for taxonomic classes have been estimated for the combined main belt and NEA (Near Earth Asteroid) populations in different taxonomic systems and for the NEA population specifically. The framework utilizes a Bayesian inference appropriate for categorical data. The population fractions provide the prior while the albedo distributions allow calculation of the likelihood an albedo measurement is consistent with a given taxonomic class. These inputs allows calculation of the probability an asteroid with a specified albedo belongs to any given taxonomic class.

Asteroids↗
NASA NTRS2017

BrO and Inferred Bry Profiles over the Western Pacific: Relevance of Inorganic Bromine Sources and a Bry Minimum in the Aged Tropical Tropopause Layer

We report measurements of bromine monoxide (BrO) and use an observationally constrained chemical box model to infer total gas-phase inorganic bromine (Br(sub y)) over the tropical western Pacific Ocean (tWPO) during the CONTRAST field campaign (January-February 2014). The observed BrO and inferred Bry profiles peak in the marine boundary layer (MBL), suggesting the need for a bromine source from sea-salt aerosol (SSA), in addition to organic bromine (CBry ). Both profiles are found to be C-shaped with local maxima in the upper free troposphere (FT). The median tropospheric BrO vertical column density (VCD) was measured as 1.6 x 10(exp 13) molec cm(exp -2), compared to model predictions of 0.9 x 10(exp 13) molec cm(exp -2) in GEOS-Chem (CBr(sub y) but no SSA source), 0.4 x 10(exp 13) molec cm(exp -2) in CAM-Chem (CBr(sub y) and SSA), and 2.1 x 10(exp 13) molec cm(exp -2) in GEOS-Chem (CBry and SSA). Neither global model fully captures the Cshape of the Br(sun y) profile. A local Br(sub y) maximum of 3.6 ppt (2.9-4.4 ppt; 95% confidence interval, CI) is inferred between 9.5 and 13.5 km in air masses influenced by recent convective outflow. Unlike BrO, which increases from the convective tropical tropopause layer (TTL) to the aged TTL, gas-phase Br(sub y) decreases from the convective TTL to the aged TTL. Analysis of gas-phase Br(sub y) against multiple tracers (CFC-11, H2O/O3 ratio, and potential temperature) reveals a Br(sub y) minimum of 2.7 ppt (2.3-3.1 ppt; 95% CI) in the aged TTL, which agrees closely with a stratospheric injection of 2.6 +/- 0.6 ppt of inorganic Br(sub y) (estimated from CFC-11 correlations), and is remarkably insensitive to assumptions about heterogeneous chemistry. Bry increases to 6.3 ppt (5.6-7.0 ppt; 95% CI) in the stratospheric "middleworld" and 6.9 ppt (6.5-7.3 ppt; 95% CI) in the stratospheric "overworld". The local Br(sub y) minimum in the aged TTL is qualitatively (but not quantitatively) captured by CAM-Chem, and suggests a more complex partitioning of gas-phase and aerosol Br(sub y) species than previously recognized. Our data provide corroborating evidence that inorganic bromine sources (e.g., SSA-derived gas-phase Br(sub y) ) are needed to explain the gas-phase Br(sub y) budget in the upper free troposphere and TTL. They are also consistent with observations of significant bromide in Upper Troposphere-Lower Stratosphere aerosols. The total Br(sub y) budget in the TTL is currently not closed, because of the lack of concurrent quantitative measurements of gas-phase Br(sub y) species (i.e., BrO, HOBr, HBr, etc.) and aerosol bromide. Such simultaneous measurements are needed to (1) quantify SSA-derived Br(sub y) in the upper FT, (2) test Br(sub y) partitioning, and possibly explain the gas-phase Br(sub y) minimum in the aged TTL, (3) constrain heterogeneous reaction rates of bromine, and (4) account for all of the sources of Br(sub y) to the lower stratosphere.

Atmospheric Chemistry; bromine; troposphere; CONTR↗
NASA NTRS2019

Using Deep Learning to Automate Inference of Meteoroid Pre-Entry Properties

Properly assessing the asteroid threat depends on the knowledge of asteroid pre-entry parameters, such as size, velocity, mass, density, and strength. Although a vast number of possible bodies to study exist, such characterization of asteroid populations is currently limited by substantial costs associated with space rendezvous missions and rare meteorite findings. As asteroids fragment, ablate, and decelerate in the atmosphere, they emit light detectable by ground-based and space-borne instruments. Earth’s atmosphere, thus, becomes an accessible laboratory that enables impactor risk assessments by facilitating inference of the pre-entry parameters. These asteroid pre-entry conditions are typically deduced by modeling the entry and breakup physics that best reproduce the observed light or energy deposition curve. However, this process requires extensive manual trial-and-error of uncertain modeling parameters. Automating meteor modeling and inference would improve property distributions used in risk assessments and enable population characterization as more light curves become more readily available through the presence of space assets and ground-based camera networks. We previously developed a genetic algorithm to automate meteor modeling by using the fragment-cloud model (FCM) to search for the values of the FCM input parameters (e.g., diameter) that generate energy deposition profiles that match the observed one. Now, we apply deep learning to infer asteroid diameter, velocity, and density from observed energy deposition curves. We trained and tested our neural network models with synthetic energy deposition curves modeled using the FCM rubble pile implementation. We present an application of a 1D convolutional neural network and compare its performance to other attempted regressors and machine learning techniques, such as a fully connected neural network and Random Forest regression, to demonstrate its capabilities. We validate our model weights and approach using the Chelyabinsk, Tagish Lake, Benešov, Košice, and Lost City meteors.

Tarano, Ana Maria↗