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NASA NTRSDate not supplied

Mapping Aerosol Lidar Ratios Over Ocean Using Constrained Retrievals and A Global Aerosol Model

The current NASA Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) algorithms assign one lidar ratio (i.e., extinction-to-backscatter ratio; LR) value globally for each of the seven tropospheric aerosol types. In a future data products release, the CALIPSO project aims to improve these algorithms through the development of regional and seasonal LR climatologies. In this work, aerosol LRs are inferred through Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) backscatter profiles constrained by collocated aerosol optical depth (AOD) from Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data. This analysis is subsampled for those profiles that are cloud-free and contain only one CALIOP-classified aerosol type (e.g., marine). The CALIOP profiles are then collocated with aerosol volume fractions obtained through Goddard Chemistry Aerosol Radiation and Transport (GOCART) model simulations. In this presentation, we show that the twelve-year (June 2006-August 2018) mean spatial distributions of inferred aerosol LRs for CALIOP-classified marine aerosols correspond inversely with patterns of GOCART sea salt volume fraction (SSVF). For example, smaller SSVFs (< 65%) and larger LRs (> 55 sr), are found near land masses. This is indicative of the influence of over-land aerosols (e.g., pollution and biomass burning smoke). In the remote oceans (i.e., regions likely less impacted by non-sea salt aerosols), larger SSVFs (> 95%) and smaller LRs (< 25 sr) are found. The developed relationship between the GOCART SSVFs and MODIS AOD constrained LRs (polynomial fit intersect values of ~56 sr for SSVF of 0% and ~21 sr for SSVF of 100%) is used to produce model-assisted climatological LR maps on seasonal scales. Additionally, we show maps of inferred LRs from constrained retrievals using the CALIPSO Ocean Derived Column Optical Depth (ODCOD) product and comparisons with those from the MODIS analyses. The technique demonstrated in this study not only benefits CALIPSO in the near-term, but similar methods can be applied to future spaceborne elastic backscatter lidars with collocated passive sensors, such as those associated with the upcoming NASA Atmosphere Observing System (AOS).

Travis Toth↗
NASA NTRS2013

Neutron Absorption Measurements Constrain Eucrite-Diogenite Mixing in Vesta's Regolith

The NASA Dawn Mission s Gamma Ray and Neutron Detector (GRaND) [1] acquired mapping data during 5 months in a polar, low altitude mapping orbit (LAMO) with approx.460-km mean radius around main-belt asteroid Vesta (264-km mean radius) [2]. Neutrons and gamma rays are produced by galactic cosmic ray interactions and by the decay of natural radioelements (K, Th, U), providing information about the elemental composition of Vesta s regolith to depths of a few decimeters beneath the surface. From the data acquired in LAMO, maps of vestan neutron and gamma ray signatures were determined with a spatial resolution of approx.300 km full-width-at-half-maximum (FWHM), comparable in scale to the Rheasilvia impact basin (approx.500 km diameter). The data from Vesta encounter are available from the NASA Planetary Data System. Based on an analysis of gamma-ray spectra, Vesta s global-average regolith composition was found to be consistent with the Howardite, Eucrite, and Diogenite (HED) meteorites, reinforcing the HED-Vesta connection [2-7]. Further, an analysis of epithermal neutrons revealed variations in the abundance of hydrogen on Vesta s surface, reaching values up to 400 micro-g/g [2]. The association of high concentrations of hydrogen with equatorial, low-albedo surface regions indicated exogenic delivery of hydrogen by the infall of carbonaceous chondrite (CC) materials. This finding was buttressed by the presence of minimally-altered CC clasts in howardites, with inferred bulk hydrogen abundances similar to that found by GRaND, and by studies using data from Dawn s Framing Camera (FC) and VIR instruments [8-10]. In addition, from an analysis of neutron absorption, spatial-variations in the abundance of elements other than hydrogen were detected [2].

Prettyman, T. H.↗
NASA NTRS2021

Trend Detection of Atmospheric Time Series: Incorporating Appropriate Uncertainty Estimates and Handling Extreme Events

This paper is aimed at atmospheric scientists without formal training in statistical theory. Its goal is to, 1) provide a critical review of the rationale for trend analysis of the time series typically encountered in the field of atmospheric chemistry; 2) describe a range of trend-detection methods; and 3) demonstrate effective means of conveying the results to a general audience. Trend detections in atmospheric chemical composition data are often challenged by a variety of sources of uncertainty, which often behave differently to other environmental phenomena such as temperature, precipitation rate, or stream flow, and may require specific methods depending on the science questions to be addressed. Some sources of uncertainty can be explicitly included in the model specification, such as autocorrelation and seasonality, but some inherent uncertainties are difficult to quantify, such as data heterogeneity and measurement uncertainty due to the combined effect of short- and long-term natural variability, instrumental stability, and aggregation of data from sparse sampling frequency. Failure to account for these uncertainties might result in an inappropriate inference of the trends and their estimation errors. On the other hand, the variation in extreme events might be interesting for different scientific questions, for example, the frequency of extremely high surface ozone events and their relevance to human health. In this study we aim to, 1) review trend detection methods for addressing different levels of data complexity in different chemical species; 2) demonstrate that the incorporation of scientifically interpretable covariates can outperform pure numerical curve fitting techniques in terms of uncertainty reduction and improved predictability; 3) illustrate the study of trends based on extreme quantiles that can provide insight beyond standard mean or median based trend estimates; and 4) present an advanced method of quantifying regional trends based on the inter-site correlations of multi-site data. All demonstrations are based on time series of observed trace gases relevant to atmospheric chemistry, but the methods can be applied to other environmental data sets.

Trace gas↗
NASA NTRS1987

Explorations of electric current system in solar active regions. I - Empirical inferences of the current flows

Techniques to identify sources of electric current systems and their channels of flow in solar active regions are explored. Measured photospheric vector magnetic fields together with high-resolution white-light and H-alpha filtergrams provide the data base to derive the current systems in the photosphere and chromosphere. As an example, the techniques are then applied to infer current systems in AR 2372 in early April 1980.

Ding, Y. J.↗
NASA NTRS1985

A cool anomaly off northern California - An investigation using IR imagery and in situ data

The OPTOMA (Ocean Prediction Through Observation, Modeling and Analysis) program is developing an ocean descriptive-predictive system for four-dimensional data assimilation. It is presently concerned with the mesoscale variability in the California Current System (CCS). The present paper has the objective to assess the relationship of surface temperature structure to subsurface temperature structure and flow fields. Surface temperature anomalies are related to the mesoscale horizontal advective and subsurface mass fields. The cool anomaly off northern California in summer 1982 is discussed, taking into account the temperature structure along transects, T-S variations and inferred water masses, variation of horizontal temperature patterns with depth, and synoptic information from IR data.

Rienecker, M. M.↗
NASA NTRS1995

Relating Radar Backscatter to Boreal Forest Canopy Parameters

During the first intensive field campaign for the Boreal Ecosystem Atmospheric Study (BOREAS) in August of 1993, AIRSAR data were acquired over the entire BOREAS study area. On of the objectives of the AIRSAR deployment was to examine the sensitivity of the radar signal to vegetation type and biomass distribution in the boreal forest and to develop algorithms for inferring vegetation parameters. During the experiment a set of ground measurements were also made to support the AIRSAR data analysis. The dominant stands in the study area consist of black spruce, young jack pine, old jack pine, and aspen. These stands represent a wide range of biomass and canopy architectural variations which can be distinguished in SAR images.

radar backscatter↗
NASA NTRS1983

Orbiter entry leeside heat-transfer data analysis

Heat-transfer data measured along the Space Shuttle Orbiter's leeward centerline and over the wing leeside surface during the STS-2 and STS-3 mission entries are presented. The flight data are compared with available wind-tunnel results. Flight heating levels are, in general, lower than those which are inferred from the wind-tunnel results. This result is apparently due to the flight leeside flowfield remaining laminar over a larger Reynolds number range than that of corresponding ground test results. The flight/wind-tunnel data comparisons confirm the adequacy of, and conservatism embodied in, the direct application of wind-tunnel data at flight conditions for the design of Orbiter leeside thermal protection.

Throckmorton, D. A.↗
NASA NTRS1971

Nature of the Martian surface as inferred from the particle-size distribution of lunar-surface material.

Analysis of lunar particle size distribution data indicates that the surface material is composed of two populations. One population is caused by comminution from the impact of the larger-sized meteorites, while the other population is caused by the melting of fine material by the impact of smaller-sized meteorites. The results are referred to Mars, and it is shown that the Martian atmosphere would vaporize the smaller incoming meteorites and retard the incoming meteorites of intermediate and large size, causing comminution and stirring of the particulate layer. The combination of comminution and stirring would result in fine material being sorted out by the prevailing circulation of the Martian atmosphere and the material being transported to regions where it could be deposited. As a result, the Martian surface in regions of prevailing upward circulation is probably covered by either a rubble layer or by desert pavement; regions of prevailing downward circulation are probably covered by sand dunes.

Mason, C. C.↗
NASA NTRS1979

Global model of longitude/UT variations in thermospheric composition and temperature based on mass spectrometer data

Measurements of N2, O, He, and Ar densities from neutral gas mass spectrometers on four satellites and inferred O2 and H densities from an ion mass spectrometer have been combined to produce a model of longitude/UT variations in thermospheric neutral composition and temperature. The longitude/UT model is an extension of the mass spectrometer-incoherent scatter thermospheric model (Hedin et al., 1977) and uses spherical harmonic terms dependent on geographic latitude, longitude, and UT. The combined longitude and UT variations reflect the influence of the geomagnetic field but indicate that the variations may not simply be represented in magnetic coordinates.

Hedin, A. E.↗
NASA NTRS1991

Data-driven backward chaining

The C Language Integrated Production System (CLIPS) cannot effectively perform sound and complete logical inference in most real-world contexts. The problem facing CLIPS is its lack of goal generation. Without automatic goal generation and maintenance, forward chaining can only deduce all instances of a relationship. Backward chaining, which requires goal generation, allows deduction of only that subset of what is logically true which is also relevant to ongoing problem solving. Goal generation can be mimicked in simple cases using forward chaining. However, such mimicry requires manual coding of additional rules which can assert an inadequate goal representation for every condition in every rule that can have corresponding facts derived by backward chaining. In general, for N rules with an average of M conditions per rule the number of goal generation rules required is on the order of N*M. This is clearly intractable from a program maintenance perspective. We describe the support in Eclipse for backward chaining which it automatically asserts as it checks rule conditions. Important characteristics of this extension are that it does not assert goals which cannot match any rule conditions, that 2 equivalent goals are never asserted, and that goals persist as long as, but no longer than, they remain relevant.

Haley, Paul↗
NASA NTRS1975

Determination of rotor harmonic blade loads from acoustic measurements

The magnitude of discrete frequency sound radiated by a rotating blade is strongly influenced by the presence of a nonuniform distribution of aerodynamic forces over the rotor disk. An analytical development and experimental results are provided for a technique by which harmonic blade loads are derived from acoustic measurements. The technique relates, on a one-to-one basis, the discrete frequency sound harmonic amplitudes measured at a point on the axis of rotation to the blade-load harmonic amplitudes. This technique was applied to acoustic data from two helicopter types and from a series of test results using the NASA-Langley Research Center rotor test facility. The inferred blade-load harmonics for the cases considered tended to follow an inverse power law relationship with harmonic blade-load number. Empirical curve fits to the data showed the harmonic fall-off rate to be in the range of 6 to 9 db per octave of harmonic order. These empirical relationships were subsequently used as input data in a compatible far field rotational noise prediction model. A comparison between predicted and measured off-axis sound harmonic levels is provided for the experimental cases considered.

Kasper, P. K.↗
NASA NTRS2000

1DVAR Analysis of Temperature and Humidity Using GPS Radio Occultation Data

The Global Positioning System enables positioning in 3 dimensions about our planet. It has been operational since 1994. Twenty-four satellites are used to aclile\,e this performance. The signals sent by these satellites are electromagnetic waves travelling through our atmosphere down to the small receivers used by the civilian community and the military. Because of varying meteorological conditions (namely, temperature and humidity changes along the ray path), the rays do not travel in a straight line. They bend towards the surface. As a consequence, the ray path between two points is longer than a straight line, and the time it takes for a signal to travel this distance is longer. In 1995, a small GPS receiver was launched on a satellite (GPS/MET). It become possible to perform radio occultations around the Earth: the source - one of the 24 GPS satellites - is seen by the receiver as it rises or sets around the other side of the Earth. When the source disappears, the receiver progressively loses the signals. By measuring accurately the time delay between the emission and the reception of the signal, it is possible to infer which part of the delay is due to the atmosphere. We use GPS/MET data to retrieve temperature and humidity profiles simultaneously. A specific method is implemented: it combines information from numerical forecasts and GPS observations in an optimal way. Comparing the result with an independent source of observations (weather balloons), we demonstrate that GPS data have the potential to improve weather analyses. We also show that improved temperature and humidity profiles can be obtained using information from a forecast model. This confirms results obtained in this study using simulated data.

Poli, Paul↗
NASA NTRS1994

The solar cycle variation of ozone in the stratosphere inferred from Nimbus 7 and NOAA 11 satellites

The combined Nimbus 7 solar backscattered ultraviolet (SBUV) and NOAA 11 SBUV/2 ozone data, covering a period of more than a solar cycle (about 15 years), are used to study the UV response of ozone in the stratosphere. The study shows that about 2% change in total column ozone and about 5-7% change in ozone mixing ratio in the upper stratosphere (0.7 to 2 hPa) may be attributed to the change in the solar UV flux over a solar cycle. In the upper stratosphere, where photochemical processes are expected to play a major role, the measured solar cycle variation of ozone is significantly larger than inferred either from the photochemical models or from the ozone response to the 27-day solar UV modulation. For example, the observed solar cycle related change in ozone mixing ratio at 2 hPa is about 1% for 1% change in the solar UV flux near 200 nm. The inferred change in ozone from either the photochemical models or from the 27-day ozone-UV response is about a factor of 2-3 lower than this value.

Chandra, S.↗
NASA NTRS1981

Snow water equivalent determination by microwave radiometry

One of the most important parameters for accurate snowmelt runoff prediction is snow water equivalent (SWE) which is contentionally monitored using observations made at widely scattered points in or around specific watersheds. Remote sensors which provide data with better spatial and temporal coverage can be used to improve the SWE estimates. Microwave radiation, which can penetrate through a snowpack, may be used to infer the SWE. Calculations made from a microscopic scattering model were used to simulate the effect of varying SWE on the microwave brightness temperature. Data obtained from truck mounted, airborne and spaceborne systems from various test sites were studied. The simulated SWE compares favorable with the measured SWE. In addition, whether the underlying soil is frozen or thawed can be discriminated successfully on the basis of the polarization of the microwave radiation.

Chang, A. T. C.↗
NASA NTRS2007

An Alternative Interpretation of the Relationship between the Inferred Open Solar Flux and the Interplanetary Magnetic Field

Photospheric observations at the Wilcox Solar Observatory (WSO) represent an uninterrupted data set of 32 years and are therefore unique for modeling variations in the magnetic structure of the corona and inner heliosphere over three solar cycles. For many years, modelers have applied a latitudinal correction factor to these data, believing that it provided a better estimate of the line-of-sight magnetic field. Its application was defended by arguing that the computed open flux matched observations of the interplanetary magnetic field (IMF) significantly better than the original WSO correction factor. However, no physically based argument could be made for its use. In this Letter we explore the implications of using the constant correction factor on the value and variation of the computed open solar flux and its relationship to the measured IMF. We find that it does not match the measured IMF at 1 AU except at and surrounding solar minimum. However, we argue that interplanetary coronal mass ejections (ICMEs) may provide sufficient additional magnetic flux to the extent that a remarkably good match is found between the sum of the computed open flux and inferred ICME flux and the measured flux at 1 AU. If further substantiated, the implications of this interpretation may be significant, including a better understanding of the structure and strength of the coronal field and I N providing constraints for theories of field line transport in the corona, the modulation of galactic cosmic rays, and even possibly terrestrial climate effects.

Riley, Pete↗
NASA NTRS2008

Safe Upper-Bounds Inference of Energy Consumption for Java Bytecode Applications

Many space applications such as sensor networks, on-board satellite-based platforms, on-board vehicle monitoring systems, etc. handle large amounts of data and analysis of such data is often critical for the scientific mission. Transmitting such large amounts of data to the remote control station for analysis is usually too expensive for time-critical applications. Instead, modern space applications are increasingly relying on autonomous on-board data analysis. All these applications face many resource constraints. A key requirement is to minimize energy consumption. Several approaches have been developed for estimating the energy consumption of such applications (e.g. [3, 1]) based on measuring actual consumption at run-time for large sets of random inputs. However, this approach has the limitation that it is in general not possible to cover all possible inputs. Using formal techniques offers the potential for inferring safe energy consumption bounds, thus being specially interesting for space exploration and safety-critical systems. We have proposed and implemented a general frame- work for resource usage analysis of Java bytecode [2]. The user defines a set of resource(s) of interest to be tracked and some annotations that describe the cost of some elementary elements of the program for those resources. These values can be constants or, more generally, functions of the input data sizes. The analysis then statically derives an upper bound on the amount of those resources that the program as a whole will consume or provide, also as functions of the input data sizes. This article develops a novel application of the analysis of [2] to inferring safe upper bounds on the energy consumption of Java bytecode applications. We first use a resource model that describes the cost of each bytecode instruction in terms of the joules it consumes. With this resource model, we then generate energy consumption cost relations, which are then used to infer safe upper bounds. How energy consumption for each bytecode instruction is measured is beyond the scope of this paper. Instead, this paper is about how to infer safe energy consumption estimations assuming that those energy consumption costs are provided. For concreteness, we use a simplified version of an existing resource model [1] in which an energy consumption cost for individual Java opcodes is defined.

Navas, Jorge↗
NASA NTRS1996

Evaluation of IGS Orbits with Satellite Laser Ranging

The accuracy with which orbits for the Global Positioning System (GPS) spacecraft, can be computed directly affects the accuracy of the resulting site coordinates and polar motion. Several groups routinely analyze GPS ground tracking data to compute precise orbits and terrestrial reference frame solutions. In this paper, we infer the accuracy of the orbits of two of the GPS satellites by comparing to independent laser ranges of subcentimeter accuracy obtained by a small but reasonably well distributed network of tracking sites. We find that all seven International GPS Service for Geodynamics (IGS) analysis centers achieve range residual root mean square (rms) errors at or below the 100 mm level. The best orbit solutions, from JPL, CODE, and the IGS combined product, yield a residual rms of about 50 mm. These residuals are consistent with three dimensional orbit errors of less than 150 mm. Estimating yaw rates for the spacecraft during shadow events, and using these estimates to compute the laser residual, significantly improves the fit. A small mean residual value of -15 to -30 mm seems to exist for most centers and laser sites which is not fully explained at present, but may be due to uncertainties in the corrections to the laser data, such as the reflector to spacecraft center of mass vector or small reference frame differences between the SLR sites and the GPS orbits.

Watkins, M. M.↗