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At least 559 records · Page 31

Radiative Flux Changes by Aerosols from North America, Europe, and Africa over the Atlantic Ocean: Measurements and Calculations from TARFOX and ACE-2

Aerosol effects on atmospheric radiative fluxes provide a forcing function that is a major source of uncertainty in understanding the past climate and predicting climate change. To help reduce this uncertainty, the 1996 Tropospheric Aerosol Radiative Forcing Experiment (TARFOX) and the 1997 second Aerosol Characterization Experiment (ACE-2) measured the properties and radiative effects of American, European, and African aerosols over the Atlantic. In TARFOX, radiative fluxes and microphysics of the American aerosol were measured from the UK C-130 while optical depth spectra, aerosol composition, and other properties were measured by the University of Washington C-131A and the CIRPAS Pelican. Closure studies show that the measured flux changes agree with those derived from the aerosol measurements using several modelling approaches. The best-fit midvisible single-scatter albedos (approx. 0.89 to 0.93) obtained from the TARFOX flux comparisons are in accord with values derived by independent techniques. In ACE-2 we measured optical depth and extinction spectra for both European urban-marine aerosols and free-tropospheric African dust aerosols, using sunphotometers on the R/V Vodyanitskiy and the Pelican. Preliminary values for the radiative flux sensitivities (Delta Flux / Delta Optical depth) computed for ACE-2 aerosols (boundary layer and African dust) over ocean are similar to those found in TARFOX. Combining a satellite-derived optical depth climatology with the aerosol optical model validated for flux sensitivities in TARFOX provides first-cut estimates of aerosol-induced flux changes over the Atlantic Ocean.

Russell, P. B.↗

Evaluating Ground-based Proxies for Solar Irradiance Variation

In order to determine what ground-based proxies are best for evaluating solar irradiance variation before the advent of space observations, it is necessary to test these proxies against space observations. We have tested sunspot number, total sunspot area, and sunspot umbral area against the Nimbus-7 measurements of total solar irradiance variation cover the eleven year period 1980-1990. The umbral area yields the best correlation and the total sunspot area yields the poorest. Reasons for expecting the umbral area to yield the best correlation are given, the statistical procedure followed to obtain the results is described, and the value of determining the best proxy is discussed. The latter is based upon the availability of an excellent database from the Greenwich Observatory obtained over the period 1876-1976, which can be used to estimate the total solar irradiance variation before sensitive space observations were available. The ground-based observations used were obtained at the Coimbra Solar Observatory. The analysis was done at Goddard using these data and data from the Nimbus-7 satellite.

Oegerle, William↗

Method bacterial endospore quantification using lanthanide dipicolinate luminescence

A lanthanide is combined with a medium to be tested for endospores. The dipicolinic acid released from the endospores binds the lanthanides, which have distinctive emission (i.e., luminescence) spectra, and are detected using photoluminescence. The concentration of spores is determined by preparing a calibration curve generated from photoluminescence spectra of lanthanide complex mixed with spores of a known concentration. A lanthanide complex is used as the analysis reagent, and is comprised of lanthanide ions bound to multidentate ligands that increase the dipicolinic acid binding constant through a cooperative binding effect with respect to lanthanide chloride. The resulting combined effect of increasing the binding constant and eliminating coordinated water and multiple equilibria increase the sensitivity of the endospore assay by an estimated three to four orders of magnitude over prior art of endospore detection based on lanthanide luminescence.

Ponce, Adrian↗

Design and Application of the Exploration Maintainability Analysis Tool

Conducting human exploration missions beyond Low Earth Orbit (LEO) will present unique challenges in the areas of supportability and maintainability. The durations of proposed missions can be relatively long and re-supply of logistics, including maintenance and repair items, will be limited or non-existent. In addition, mass and volume constraints in the transportation system will limit the total amount of logistics that can be flown along with the crew. These constraints will require that new strategies be developed with regards to how spacecraft systems are designed and maintained. NASA is currently developing Design Reference Missions (DRMs) as an initial step in defining future human missions. These DRMs establish destinations and concepts of operation for future missions, and begin to define technology and capability requirements. Because of the unique supportability challenges, historical supportability data and models are not directly applicable for establishing requirements for beyond LEO missions. However, supportability requirements could have a major impact on the development of the DRMs. The mass, volume, and crew resources required to support the mission could all be first order drivers in the design of missions, elements, and operations. Therefore, there is a need for enhanced analysis capabilities to more accurately establish mass, volume, and time requirements for supporting beyond LEO missions. Additionally, as new technologies and operations are proposed to reduce these requirements, it is necessary to have accurate tools to evaluate the efficacy of those approaches. In order to improve the analysis of supportability requirements for beyond LEO missions, the Space Missions Analysis Branch at the NASA Langley Research Center is developing the Exploration Maintainability Analysis Tool (EMAT). This tool is a probabilistic simulator that evaluates the need for repair and maintenance activities during space missions and the logistics and crew requirements to support those activities. Using a Monte Carlo approach, the tool simulates potential failures in defined systems, based on established component reliabilities, and then evaluates the capability of the crew to repair those failures given a defined store of spares and maintenance items. Statistical analysis of Monte Carlo runs provides probabilistic estimates of overall mission safety and reliability. This paper will describe the operation of the EMAT, including historical data sources used to populate the model, simulation processes, and outputs. Analysis results are provided for a candidate exploration system, including baseline estimates of required sparing mass and volume. Sensitivity analysis regarding the effectiveness of proposed strategies to reduce mass and volume requirements and improve mission reliability is included in these results.

Stromgren, Chel↗

Attitude Ground System (AGS) for the Magnetospheric Multi-Scale (MMS) Mission

MMS Overview Recall from Conrads presentation earlier today MMS launch: March 13, 2015 on an Atlas V from Space Launch Complex 40, Cape Canaveral, Florida MMS Observatory Separation: five minute intervals spinning at 3 rpm approximately 1.5 hours after launch MMS Science Goals: study magnetospheric plasma physics and understand the processes that cause power grids, communication disruptions and Aurora formation Mission: 4 identical spacecraft in tetrahedral formation with variable size1.2 x 12 RE in Phase 1, with apogee on dayside to observe bow shock1.2 x 25 RE in Phase 2, with apogee on night side to observe magneto tail Challenges Tight attitude control box, orbit and formation maintenance requirements Maneuvers on thrusters every two weeks Delta-H Spin axis direction and spin rate maintenance Delta-V Orbit and Formation maintenance Mission phase transitions AGS support Smart targeting prediction of Spin-Axis attitude in the presence of environmental torques to stay within the science attitude Determination of the spacecraft attitude and spin rate (sensitive to knowledge of inertia tensor)Calibrations to improve attitude determination results and improve orbit maneuvers Mass properties (Center of Mass, and inertia tensor for nutation and coning) Accelerometer bias (sensitive to the accuracy of the rate estimates) Sensor alignments.

Estimation and Calibration Support↗

Conceptual Feasibility Study of the Hyperloop Vehicle for Next-Generation Transport

The Hyperloop concept is proposed as a faster, cheaper alternative to high-speed rail and traditional short-haul aircraft. It consists of a passenger pod traveling through a tube under light vacuum while being propelled and levitated by a combination of permanent and electro-magnets. The concept addresses NASA's research thrusts for growth in demand, sustainability, and technology convergence for high-speed transport. Hyperloop is a radical departure from other advanced aviation concepts, however it remains an aeronautics concept that tackles the same strategic goals of low-carbon propulsion and ultra-effcient vehicles. System feasibility was investigated by building a multidisciplinary vehicle sizing model that takes into account aerodynamic, thermodynamic, structures, electromagnetic, weight, and mission analyses. The sizing process emphasized the strong coupling between the two largest systems: the tube and the passenger pod. The model was then exercised to examine Hyperloop from a technical and cost perspective. The structural sizing analysis of the travel tube demonstrates potential for signi cant capital cost reductions by considering an underwater route. Examination of varying passenger capacity indicates that the system can be operated with a wide range of passenger loads without significant change in operating expenses. Lastly, a high-level sizing study simulated variations in tube area, pressure, pod speed, and passenger capacity showing that there is a tube pressure that minimizes operating energy usage. The value of this optimal tube pressure is highly sensitive to numerous design details. These combined estimates of energy consumption, passenger throughput, and mission analyses all support Hyperloop as a faster and cheaper alternative to short-haul flights. The tools and expertise used to quantify these results also demonstrate how traditional aerospace design methods can be leveraged to handle the complex and coupled design process. Much of the technology development required for the Hyperloop is shared with next-generation aircraft. Furthermore, the substantial public interest and active commercial development make it an ideal candidate as an aircraft technology driver and test bed.

Hyperloop Vehicle↗

Cartesian Mesh Simulations for the Third AIAA Sonic Boom Prediction Workshop

Simulation results are presented for all cases from the Third AIAA Sonic Boom Prediction Workshop. An inviscid, embedded-boundary Cartesian-mesh flow solver is used in conjunction with adjoint-based mesh adaptation to compute nearfield pressure signatures. Specialized techniques are applied to maximize accuracy and minimize cost on Cartesian meshes. The Richardson-based error estimate highlights regions of the signatures most sensitive to mesh refinement. Timing results and coarse, medium, and fine mesh sizes for nearfield cases demonstrate that the parallel decomposition approach is efficient in both computational time and wall-clock. Pressure signals are propagated to the ground using an augmented Burgers’ equation solver to predict boom carpets. Ground signatures and loudness metrics are presented for a standard atmosphere as well as more realistic atmospheric profiles, which affect overall noise levels and can significantly widen the boom carpet. Mesh convergence studies show that high sampling frequencies, around 500 kHz, are required for propagation, and the sampling frequency increases at large off-track angles with longer acoustic ray paths and propagation times. The numerical methods yield accurate results for predicting low sonic boom signatures while being among the least computationally expensive of the workshop.

ARMD↗

Recovery of atmospheric water vapor total column abundance from imaging spectrometer data around 940 nm - Sensitivity analysis and application to Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data

Two simple techniques (Continuum Interpolated Band Ratio, CIBR, and Narrow/Wide ratio, N/W) to retrieve path precipitable water from AVIRIS high spectral resolution radiance data using the 940 nm water absorption band are compared. A sensitivity analysis was performed using the radiative transfer code LOWTRAN 7 to determine which one of these two approaches will provide a better estimate over land and water areas. The CIBR proved to be the technique less sensitive to perturbing effects, except for errors in visibility estimate. Both techniques were applied to AVIRIS radiance data acquired over Salton Sea, California. Resulting images confirmed that the use of a constant gray reflectance in the model led to a higher overestimation of the amount of water retrieved for N/W over vegetated areas. Validation was performed through comparison between an independent estimate of water vapor from concurrent Reagan sunphotometer measurements and AVIRIS estimates. Amounts retrieved using the N/W approach match more closely in situ measurements, even after adjusting model parameters for background reflectance, viewing geometry, and type of aerosol at the site.

Carrere, Veronique↗

Carbon-Temperature-Water Change Analysis for Peanut Production Under Climate Change: A Prototype for the AgMIP Coordinated Climate-Crop Modeling Project (C3MP)

Climate change is projected to push the limits of cropping systems and has the potential to disrupt the agricultural sector from local to global scales. This article introduces the Coordinated Climate-Crop Modeling Project (C3MP), an initiative of the Agricultural Model Intercomparison and Improvement Project (AgMIP) to engage a global network of crop modelers to explore the impacts of climate change via an investigation of crop responses to changes in carbon dioxide concentration ([CO2]), temperature, and water. As a demonstration of the C3MP protocols and enabled analyses, we apply the Decision Support System for Agrotechnology Transfer (DSSAT) CROPGRO-Peanut crop model for Henry County, Alabama, to evaluate responses to the range of plausible [CO2], temperature changes, and precipitation changes projected by climate models out to the end of the 21st century. These sensitivity tests are used to derive crop model emulators that estimate changes in mean yield and the coefficient of variation for seasonal yields across a broad range of climate conditions, reproducing mean yields from sensitivity test simulations with deviations of ca. 2% for rain-fed conditions. We apply these statistical emulators to investigate how peanuts respond to projections from various global climate models, time periods, and emissions scenarios, finding a robust projection of modest (<10%) median yield losses in the middle of the 21st century accelerating to more severe (>20%) losses and larger uncertainty at the end of the century under the more severe representative concentration pathway (RCP8.5). This projection is not substantially altered by the selection of the AgMERRA global gridded climate dataset rather than the local historical observations, differences between the Third and Fifth Coupled Model Intercomparison Project (CMIP3 and CMIP5), or the use of the delta method of climate impacts analysis rather than the C3MP impacts response surface and emulator approach.

climate change↗

Snow reflectance from Landsat-4 Thematic Mapper

In California 75 percent of the agricultural water supply comes from the melting Sierra Nevada snowpack. Basin-wide spectral albedo measurements from the Landsat-4 Thematic Mapper (TM) could be used to better forecast the timing of the spring runoff, because these data can be combined with solar radiation calculations to estimate the net radiation balance. The TM is better-suited for this purpose than the Multispectral Scanner because of its larger dynamic range. Saturation still occurs in bands 1-4, but is severe only in TM1 (0.45-0.52 micron). Snow reflectance in TM2 (0.43-0.61 micron) is typical of the visible wavelength region, where reflectance is almost insensitive to crystal size but sensitive to contamination. TM4 (0.78-0.90 micron) allows estimation of effective optical grain size and thereby spectral extension throughout the near-infrared. TM5 (1.57-1.78 microns) can discriminate clouds from snow.

Dozier, J.↗

Systems engineering and integration: Cost estimation and benefits analysis

Space Transportation Avionics hardware and software cost has traditionally been estimated in Phase A and B using cost techniques which predict cost as a function of various cost predictive variables such as weight, lines of code, functions to be performed, quantities of test hardware, quantities of flight hardware, design and development heritage, complexity, etc. The output of such analyses has been life cycle costs, economic benefits and related data. The major objectives of Cost Estimation and Benefits analysis are twofold: (1) to play a role in the evaluation of potential new space transportation avionics technologies, and (2) to benefit from emerging technological innovations. Both aspects of cost estimation and technology are discussed here. The role of cost analysis in the evaluation of potential technologies should be one of offering additional quantitative and qualitative information to aid decision-making. The cost analyses process needs to be fully integrated into the design process in such a way that cost trades, optimizations and sensitivities are understood. Current hardware cost models tend to primarily use weights, functional specifications, quantities, design heritage and complexity as metrics to predict cost. Software models mostly use functionality, volume of code, heritage and complexity as cost descriptive variables. Basic research needs to be initiated to develop metrics more responsive to the trades which are required for future launch vehicle avionics systems. These would include cost estimating capabilities that are sensitive to technological innovations such as improved materials and fabrication processes, computer aided design and manufacturing, self checkout and many others. In addition to basic cost estimating improvements, the process must be sensitive to the fact that no cost estimate can be quoted without also quoting a confidence associated with the estimate. In order to achieve this, better cost risk evaluation techniques are needed as well as improved usage of risk data by decision-makers. More and better ways to display and communicate cost and cost risk to management are required.

Dean, ED↗

Statistical estimates of the binary properties of rotational variables

ABSTRACT We present a model to estimate the average primary masses, companion mass ranges, the inclination limit for recognizing a rotational variable, and the primary mass spreads for populations of binary stars. The model fits a population’s binary mass function distribution and allows for a probability that some mass functions are incorrectly estimated. Using tests with synthetic data, we assess the model’s sensitivity to each parameter, finding that we are most sensitive to the average primary mass and the minimum companion mass, with less sensitivity to the inclination limit and little to no sensitivity to the primary mass spread. We apply the model to five populations of binary spotted rotational variables identified in ASAS-SN, computing their binary mass functions using RV data from APOGEE. Their average primary mass estimates are consistent with our expectations based on their CMD locations ($\sim 0.75 \, {\rm M}_{\odot }$ for lower main sequence primaries and $\sim 0.9$–$1.2 \, {\rm M}_{\odot }$ for RS CVn and sub-subgiants). Their companion mass range estimates allow companion masses down to $M_2/M_1\simeq 0.1$, although the main sequence population may have a higher minimum mass fraction ($\sim 0.4$). We see weak evidence of an inclination limit $\gtrsim 50^{\circ }$ for the main sequence and sub-subgiant groups and no evidence of an inclination limit in the other groups. No groups show strong evidence for a preferred primary mass spread. We conclude by demonstrating that the approach will provide significantly better estimates of the primary mass and the minimum mass ratio and reasonable sensitivity to the inclination limit with 10 times as many systems.

Phillips, Anya (ORCID:000900051914974X)↗

SMAP Radar Processing and Calibration

The Soil Moisture Active Passive (SMAP) mission is part of the NASA space-based Earth observation program, and consists of an L-band radar and radiometer scheduled for launch into sun synchronous orbit in late 2014. A joint effort of the Jet Propulsion Laboratory (JPL) and the Goddard Space Flight Center (GSFC), the SMAP mission draws heavily on the design and risk reduction heritage of the Hydrosphere State (Hydros) mission [1], [2]. The SMAP science and applications objectives are to: 1) understand processes that link the terrestrial water, energy and carbon cycles, 2) estimate global water and energy fluxes at the land surface, 3) quantify net carbon flux in boreal landscapes, 4) enhance weather and climate forecast skill, and 5) develop improved flood prediction and drought monitoring capability. To meet these science objectives, SMAP ground processing will combine the attributes of the radar and radiometer observations (in terms of their spatial resolution and sensitivity to soil moisture, surface roughness, and vegetation) to estimate soil moisture with 4% volumetric accuracy at a resolution of 10 km, and freeze-thaw state at a resolution of 1-3 km. Model sensitivities translate the soil moisture accuracy to a radar backscatter accuracy of 1 dB (1 sigma) at 3 km resolution and a brightness temperature accuracy of 1.3 K at 40 km resolution. This paper will describe the level 1 radar processing and calibration challenges and the choices made so far for the algorithms and software implementation.

Synthetic Aperture Radar (SAR),↗

Quantum Sensing of Displacements with Stabilized Gottesman-Kitaev-Preskill States

We demonstrate how recent protocols developed for the stabilization of Gottesman-Kitaev-Preskill states can be used for the estimation of two-quadrature displacement sensing, with sensitivities approaching the multivariate quantum Cramer-Rao bound. Thanks to the stabilization, this sensor is backaction evading and can function continuously without reset, making it well suited for the detection of itinerant signals. Additionally, we provide numerical simulations showing that the protocol can unconditionally surpass the Gaussian limit of displacement sensing with prior information, even in the presence of realistic noise. Our work shows how reservoir engineering in bosonic systems can be leveraged for quantum metrology, with potential applications in force sensing, waveform estimation, and quantum channel learning.

Labarca, Lautaro [Univ. of Sherbrooke, QC (Canada)↗

Emission measures derived from far ultraviolet spectra of T Tauri stars

Spectroscopic diagnostics based on UV emission line observations have been developed to study the solar chromosphere, transition region, and corona. The atmospheric properties that can be inferred from observations of total line intensities include the temperature, by identifying the ionic species present; the temperature distribution of the emission measure, from the absolute intensities; and the electron density of the source, from line intensity ratios sensitive to the electron density. In the present paper, the temperature distribution of the emission measure is estimated from observations of far UV emission line fluxes of the T Tauri stars, RW Aurigae and RU Lupi, made on the IUE. A crude estimate of the electron density of one star is obtained, using density-sensitive line ratios.

Cram, L. E.↗

Machine learning method for enforcing variable independence in background estimation with LHC data: ABCDisCoTEC

A novel solution is presented for the problem of estimating the backgrounds of a signal search using observed data while simultaneously maximizing the sensitivity of the search to the signal. The 'ABCD method' provides a reliable framework for background estimation by partitioning events into one signal-enhanced region (A) and three background-enhanced control regions (B, C, and D) via two smoothly varying, statistically independent variables. In practice, even slight correlations between the two variables can significantly undermine the method's performance. Thus, choosing appropriate variables by hand can present a formidable challenge, especially when background and signal differ only subtly. To address this issue, the ABCD with distance correlation (ABCDisCo) method was developed to construct two learned variables via a neural network trained to provide strong signal-background discrimination with small values of the distance correlation (DisCo) measure between the two learned variables. However, relying solely on minimizing the DisCo can result in learned variables that may not have distributions of background events that are smoothly varying and localized at extreme values, as necessary for the validity of the background estimation. The ABCDisCo training enhanced with closure (ABCDisCoTEC) method is introduced to solve this issue by directly minimizing the nonclosure, expressed as a dedicated differentiable loss term. This extended method is applied to a data set of proton-proton collisions at a center-of-mass energy of 13 TeV recorded by the CMS detector at the CERN Large Hadron Collider. Additionally, given the complexity of the minimization problem with constraints on multiple loss terms, the modified differential method of multipliers is applied and shown to greatly improve the stability and robustness of the ABCDisCoTEC method, compared to grid search hyperparameter optimization procedures.

Hayrapetyan, Aram [Yerevan Phys. Inst.]↗

Application of microelectronic technology to general aviation flight control

This paper presents several different methods that can be used to determine the aircraft orientation (attitude) without direct measurement. The methods combine state estimation techniques with measurements from solid state pressure sensors, accelerometers, and magnetometers to determine the aircraft state. The paper demonstrates how the estimation algorithms were validated and compared using flight test data, and it presents results of performance sensitivity analyses of sensor error, modeling inaccuracies, and wind disturbance effects on the attitude estimation errors. If implemented, the methods presented could make it possible to eliminate directional and vertical gyros and to change from many isolated sensors to an integrated, small, reliable sensing package for determining the aircraft state.

Sorensen, J. A.↗

Large-Scale Groundwater Monitoring in Brazil Assisted With Satellite-Based Artificial Intelligence Techniques

Here, we develop and test an artificial intelligence (AI)-based approach to monitor major Brazilian aquifers. The approach combines Gravity Recovery and Climate Experiment (GRACE) data and ground-based hydrogeological measurements from Brazil’s Integrated Groundwater Monitoring Network at hundreds of wells distributed in twelve aquifers across the country. We tested model ensembles based on three AI approaches: Extreme Gradient Boost, Light Gradient Boosting Model and CatBoost, followed by a Linear Regression (LR) step. The approach is further boosted with wavelet and seasonal decomposition processes applied to GRACE data. To determine the AI-based model’s sensitivity to data availability, we propose four experiments combining hydrogeological measurements from different aquifers. Groundwater storage estimates from the Global Land Data Assimilation System (GLDAS) are used as benchmark. A sensitivity analysis shows that the LR-based model ensemble is the best suited and to reproduce groundwater storage change in all studied Brazilian aquifers. Results show that the proposed approach outperforms GLDAS in all experiments, with an RMSE value of 2.68cm for the experiment that covers all monitored wells in Brazil. GLDAS resulted in RMSE=6.76cm. Using our AI model outputs, we quantified the groundwater storage change of two major aquifers, Urucuia and Bauru-Caiuá, over the past two decades: -31km 3 and -6km 3 , respectively. Water loss is driven by a prolonged drought across most of the country and intensification of groundwater pumping for irrigation. This study demonstrates that combining satellite data and AI can be a cost-effective alternative to monitor poorly equipped aquifers at the continental scale, with possible global replicability.

GRACE↗