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At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Role of Tropical Atlantic SST Variability as a Modulator of El Nino Teleconnections

The present study suggests that the off-equatorial North Atlantic (NATL) SST warming plays a significant role in modulating El Niño teleconnection and its impact on the North Atlantic and European regions. The El Niño events accompanied by NATL SST warming exhibit south-north dipole pattern over the Western Europe to Atlantic, while the ENSO teleconnection pattern without NATL warming exhibits a Rossby wave-like pattern confined over the North Pacific and western Atlantic. Especially, the El Niño events with NATL warming show positive (negative) geopotential-height anomalies over the North Atlantic (Western Europe) which resemble the negative phase of the NAO. Consistently, it is shown using a simple statistical model that NATL SSTA in addition to the tropical Pacific SSTA leads to better prediction on regional climate variation over the North Atlantic and European regions. This role of NATL SST on ENSO teleconnection is also validated and discussed in a long term simulation of coupled global circulation model (CGCM).

Teleconnection↗
NASA NTRS2015

Near-Earth Asteroids 2006 RH120 And 2009 BD: Proxies For Maximally Accessible Objects?

Near-Earth Object Human Space Flight Accessible Targets Study(NHATS): http://neo.jpl.nasa.govnhats/. As of mid-July 2015: 1,434 of the 12,778 currently known NEAs are more astrodynamically accessible than is Mars (requiring less Delta v and or less flight time for round-trip missions). Within those 1,434 NEAs: 605 NEAs can be visited round-trip for less Delta v (9 km/s) than the lunar surface. 51 NEAs can be visited round-trip for less v (5 km/s) than low circular lunar orbit. NEO population statistical models:Tens of thousands of NEAs greater than 100 m yet to be discovered. At least several million NEAs less than or equal to100 m in size (down to approximately 3 m in size) yet to be discovered. How accessible are the NEAs that haven't yet been discovered?

Mission Design↗
NASA NTRS2014

Ocean Surface Carbon Dioxide Fugacity Observed from Space

We have developed and validated a statistical model to estimate the fugacity (or partial pressure) of carbon dioxide (CO2) at sea surface (pCO2sea) from space-based observations of sea surface temperature (SST), chlorophyll, and salinity. More than a quarter million in situ measurements coincident with satellite data were compiled to train and validate the model. We have produced and made accessible 9 years (2002-2010) of the pCO2sea at 0.5 degree resolutions daily over the global ocean. The results help to identify uncertainties in current JPL Carbon Monitoring System (CMS) model-based and bottom-up estimates over the ocean. The utility of the data to reveal multi-year and regional variability of the fugacity in relation to prevalent oceanic parameters is demonstrated.

Liu, W. Timothy↗
NASA NTRS2016

Climate Change Adaptation Activities at the NASA John F. Kennedy Space Center, FL., USA

In 2010, the Office of Strategic Infrastructure and Earth Sciences established the Climate Adaptation Science Investigators (CASI) program to integrate climate change forecasts and knowledge into sustainable management of infrastructure and operations needed for the NASA mission. NASA operates 10 field centers valued at $32 billion dollars, occupies 191,000 acres and employs 58,000 people. CASI climate change and sea-level rise forecasts focus on the 2050 and 2080 time periods. At the 140,000 acre Kennedy Space Center (KSC) data are used to simulate impacts on infrastructure, operations, and unique natural resources. KSC launch and processing facilities represent a valued national asset located in an area with high biodiversity including 33 species of special management concern. Numerical and advanced Bayesian and Monte Carlo statistical modeling is being conducted using LiDAR digital elevation models coupled with relevant GIS layers to assess potential future conditions. Results are provided to the Environmental Management Branch, Master Planning, Construction of Facilities, Engineering Construction Innovation Committee and our regional partners to support Spaceport development, management, and adaptation planning and design. Potential impacts to natural resources include conversion of 50% of the Center to open water, elevation of the surficial aquifer, alterations of rainfall and evapotranspiration patterns, conversion of salt marsh to mangrove forest, reductions in distribution and extent of upland habitats, overwash of the barrier island dune system, increases in heat stress days, and releases of chemicals from legacy contamination sites. CASI has proven successful in bringing climate change planning to KSC including recognition of the need to increase resiliency and development of a green managed shoreline retreat approach to maintain coastal ecosystem services while maximizing life expectancy of Center launch and payload processing resources.

plant communities↗
NASA NTRS2017

An Overview of the Orbital Debris and Meteoroid Environments, Their Effects on Spacecraft, and What Can We Do About It?

Because of the high speeds needed for orbital space flight, hypervelocity impacts with objects in space are a constant risk to spacecraft. This includes natural debris - meteoroids - and the debris remnants of our own activities in space. A number of space surveillance assets are used to measure and track spacecraft, used upper stages, and breakup debris. However, much of the debris and meteoroids encountered by spacecraft in Earth orbit is not easily measured or tracked. For every man-made object that we can track, there are hundreds of small debris that are too small to be tracked but still large enough to damage spacecraft. In addition, even if we knew today's environment with perfect knowledge, the debris environment is dynamic and would change tomorrow. This means that much of the risk from both meteoroids and anthropogenic debris is statistical in nature. NASA uses and maintains a number of instruments to statistically monitor the meteoroid and orbital debris environments, and uses this information to compute statistical models for use by spacecraft designers and operators. Because orbital debris is a result of human activities, NASA has led the US government in formulating national and international strategies that space users can employ to limit the growth of debris in the future. This talk will summarize the history and current state of meteoroid and space debris measurements and modeling, how the environment influences spacecraft design and operations, how we are designing the experiments of tomorrow to improve our knowledge, and how we are working internationally to preserve the space environment for the future.

Matney, Mark↗
NASA NTRS2016

Aboveground Biomass Variability Across Intact and Degraded Forests in the Brazilian Amazon

Deforestation rates have declined in the Brazilian Amazon since 2005, yet degradation from logging, re, and fragmentation has continued in frontier forests. In this study we quantified the aboveground carbon density (ACD) in intact and degraded forests using the largest data set of integrated forest inventory plots (n 359) and airborne lidar data (18,000 ha) assembled to date for the Brazilian Amazon. We developed statistical models relating inventory ACD estimates to lidar metrics that explained70 of the variance across forest types. Airborne lidar-ACD estimates for intact forests ranged between 5.0 +/- 2.5 and 31.9 +/- 10.8 kg C m(exp -2). Degradation carbon losses were large and persistent. Sites that burned multiple times within a decade lost up to 15.0 +/- 0.7 kg C m(-2)(94%) of ACD. Forests that burned nearly15 years ago had between 4.1 +/- 0.5 and 6.8 +/- 0.3 kg C m(exp -2) (22-40%) less ACD than intact forests. Even for low-impact logging disturbances, ACD was between 0.7 +/- 0.3 and 4.4 +/- 0.4 kg C m(exp -2)(4-21%) lower than unlogged forests. Comparing biomass estimates from airborne lidar to existing biomass maps, we found that regional and pan-tropical products consistently overestimated ACD in degraded forests, under-estimated ACD in intact forests, and showed little sensitivity to res and logging. Fine-scale heterogeneity in ACD across intact and degraded forests highlights the benefits of airborne lidar for carbon mapping. Differences between airborne lidar and regional biomass maps underscore the need to improve and update biomass estimates for dynamic land use frontiers, to better characterize deforestation and degradation carbon emissions for regional carbon budgets and Reduce Emissions from Deforestation and forest Degradation(REDD+).

Longo, Marcos↗
NASA NTRS2017

Daily Kilometer-Scale MODIS Satellite Maps of PM2.5 Describe Wintertime Episodes

The San Joaquin Valley (SJV) suffers from severe health-endangering episodes of PM2.5 aerosol loadings in wintertime; episodes last approximately 5 days and differ in geographical distribution and composition. PM2.5 stations are scattered; consequently the use of remote sensing to map variable regional patterns of these varying respirable aerosol concentrations is desirable. High-precision AOT retrievals can capture column particulate loading. However,PM2.5 mapping is challenging due to several reasons: particularly thin mixed layers (ML) and thus relatively low aerosol optical thickness (AOT) close to current measurement limits, variable and a typical composition of the aerosols, and complex surface bidirectional reflectance. However, the West does present some advantages in analysis. Air basins are isolated from long-distance transport, and experience predominant strong meteorological subsidence. Thus these Western basin regions have fewer problematic cases of overriding aerosol layers detached from the surface. To counter such local overriding, Chu et al. have described an approach for the Eastern US, and He et al have described a synoptic classification approach useful in Shanghai. The Bay Area Air Quality Management District (BAAQMD) expands our experience with the use of AOT, with lower PM2.5 and several isolated sub-basins. We have prepared daily maps of episodes in each region. We present also a sequence of increasingly detailed statistical models, AOT initially appears to contribute little information; however, inclusion of weather information reveals its utility. Lyapustin and Wang's MultiAngle Implementation of Atmospheric Correction (MAIAC) retrieval for AOT provided the most useful operational remote sensing information for these regions. It provides high (1-km) spatial resolution maps and a high percentage of availability. Empirical regression methods have found that random effects regression models (aka mixed effects models, ME) employing AOT provide good estimates of ground PM2.5 concentrations.Here, we attempt to extend these methods and evaluate the usefulness of AOT with greater physical analysis, based on DISCOVER-AQ4 experience.

Chatfield, Robert B.↗
NASA NTRS2017

Temperature Increase Reduces Global Yields of Major Crops in Four Independent Estimates

Wheat, rice, maize, and soybean provide two-thirds of human caloric intake. Assessing the impact of global temperature increase on production of these crops is therefore critical to maintaining global food supply, but different studies have yielded different results. Here, we investigated the impacts of temperature on yields of the four crops by compiling extensive published results from four analytical methods: global grid-based and local point-based models, statistical regressions, and field-warming experiments. Results from the different methods consistently showed negative temperature impacts on crop yield at the global scale, generally underpinned by similar impacts at country and site scales. Without CO2 fertilization, effective adaptation, and genetic improvement, each degree-Celsius increase in global mean temperature would, on average, reduce global yields of wheat by 6.0%, rice by 3.2%, maize by 7.4%, and soybean by 3.1%. Results are highly heterogeneous across crops and geographical areas, with some positive impact estimates. Multi-method analyses improved the confidence in assessments of future climate impacts on global major crops and suggest crop- and region-specific adaptation strategies to ensure food security for an increasing world population.

Zhao, Chuang↗
NASA NTRS2017

An Unobtrusive System to Measure, Assess, and Predict Cognitive Workload in Real-World Environments

Across many careers, individuals face alternating periods of high and low attention and cognitive workload, which can result in impaired cognitive functioning and can be detrimental to job performance. For example, some professions (e.g., fire fighters, emergency medical personnel, doctors and nurses working in an emergency room, pilots) require long periods of low workload (boredom), followed by sudden, high-tempo operations during which they may be required to respond to an emergency and perform at peak cognitive levels. Conversely, other professions (e.g., air traffic controllers, market investors in financial industries, analysts) require long periods of high workload and multitasking during which the addition of just one more task results in cognitive overload resulting in mistakes. An unobtrusive system to measure, assess, and predict cognitive workload could warn individuals, their teammates, or their supervisors when steps should be taken to augment cognitive readiness. In this talk I will describe an approach to this problem that we have found to be successful across work domains including: (1) a suite of unobtrusive, field-ready neurophysiological, physiological, and behavioral sensors that are chosen to best suit the target environment; (2) custom algorithms and statistical techniques to process and time-align raw data originating from the sensor suite; (3) probabilistic and statistical models designed to interpret the data into the human state of interest (e.g., cognitive workload, attention, fatigue); (4) and machine-learning techniques to predict upcoming performance based on the current pattern of events, and (5) display of each piece of information depending on the needs of the target user who may or may not want to drill down into the functioning of the system to determine how conclusions about human state and performance are determined. I will then focus in on our experimental results from our custom functional near-infrared spectroscopy sensor, designed to operate in real-world environments to be worn comfortably (e.g., positioned into a baseball cap or a surgeons cap) to measure changes in brain blood oxygenation without adding burden to the individual being assessed.

workload collection↗
NASA NTRS2017

The Potential Impact of Satellite-Retrieved Cloud Parameters on Ground-Level PM2.5 Mass and Composition

Satellite-retrieved aerosol optical properties have been extensively used to estimate ground-level fine particulate matter (PM2.5) concentrations in support of air pollution health effects research and air quality assessment at the urban to global scales. However, a large proportion, approximately 70%, of satellite observations of aerosols are missing as a result of cloud-cover, surface brightness, and snow-cover. The resulting PM2.5 estimates could therefore be biased due to this non-random data missingness. Cloud-cover in particular has the potential to impact ground-level PM2.5 concentrations through complex chemical and physical processes. We developed a series of statistical models using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) aerosol product at 1 km resolution with information from the MODIS cloud product and meteorological information to investigate the extent to which cloud parameters and associated meteorological conditions impact ground-level aerosols at two urban sites in the US: Atlanta and San Francisco. We find that changes in temperature, wind speed, relative humidity, planetary boundary layer height, convective available potential energy, precipitation, cloud effective radius, cloud optical depth, and cloud emissivity are associated with changes in PM2.5 concentration and composition, and the changes differ by overpass time and cloud phase as well as between the San Francisco and Atlanta sites. A case-study at the San Francisco site confirmed that accounting for cloud-cover and associated meteorological conditions could substantially alter the spatial distribution of monthly ground-level PM2.5 concentrations.

MAIAC AO↗
NASA NTRS2011

Failure Modes in Capacitors When Tested Under a Time-Varying Stress

Steady step surge testing (SSST) is widely applied to screen out potential power-on failures in solid tantalum capacitors. The test simulates the power supply's on and off characteristics. Power-on failure has been the prevalent failure mechanism for solid tantalum capacitors for decoupling applications. On the other hand, the SSST can also be reviewed as an electrically destructive test under a time-varying stress. It consists of rapidly charging the capacitor with incremental voltage increases, through a low resistance in series, until the capacitor under test is electrically shorted. Highly accelerated life testing (HALT) is usually a time-efficient method for determining the failure mechanism in capacitors; however, a destructive test under a time-varying stress like SSST is even more effective. It normally takes days to complete a HALT test, but it only takes minutes for a time-varying stress test to produce failures. The advantage of incorporating specific time-varying stress into a statistical model is significant in providing an alternative life test method for quickly revealing the failure modes in capacitors. In this paper, a time-varying stress has been incorporated into the Weibull model to characterize the failure modes. The SSST circuit and transient conditions to correctly test the capacitors is discussed. Finally, the SSST was applied for testing polymer aluminum capacitors (PA capacitors), Ta capacitors, and multi-layer ceramic capacitors with both precious metal electrode (PME) and base-metal-electrodes (BME). It appears that testing results are directly associated to the dielectric layer breakdown in PA and Ta capacitors and are independent on the capacitor values, the way the capacitors being built, and the manufactures. The testing results also reveal that ceramic capacitors exhibit breakdown voltages more than 20 times the rated voltage, and the breakdown voltages are inverse proportional to the dielectric layer thickness. The possibility of ceramic capacitors in front-end decoupling applications to block the surge noise from a power supply is also discussed.

Liu, David (Donhang)↗
NASA NTRS2018

Cumulative Distribution of Ballistic Impact Failures of Common Twisted-Pair Data Cables at Orbital Speeds

Data wire cable runs are a significant presence on the exterior of the International Space Station (ISS), and continued ISS mission support requires detailed assessment of cables due to micrometeoroid and orbit debris (MMOD) impact. These data wire cables are twisted-pair cables consisting of two 22AWG stranded conductors and fillers inside a tight fitting braided copper shield. The copper shield and its contents are covered with a jacket that has a nominal outer diameter of 3.76 mm and beta-cloth tape. The ISS engineering community has identified two loss-of-function mechanisms for these cables: open circuits due to severed conductors within the cable, and short circuits due to contact between conductors or grounded components. As these data cables are low power systems, short circuits are not expected to burn away the contact, so both open and short circuits are considered permanent loss-of-function for the cable. A total of ninety-seven impact experiments have been performed into these cables to develop a statistical model for the failure of these cables to be used in reliability studies. The experimental work has yielded cumulative distribution functions for these cables for steel and aluminum components of the orbital debris environment at representative speeds and impact obliquities.

Miller, Joshua E.↗
NASA NTRS2016

Photon Counting Detector Array Algorithms for Deep Space Optical Communications

For deep-space optical communications systems utilizing an uplink optical beacon, a single-photon-counting detector array on the flight terminal can be used to simultaneously perform uplink tracking and communications as well as accurate downlink pointing at photon-starved (pW/sq. m) power levels. In this paper, we discuss concepts and algorithms for uplink signal acquisition, tracking, and parameter estimation using a photon-counting camera. Statistical models of detector output data and signal processing algorithms are presented, incorporating realistic effects such as Earth background and detector/readout blocking. Analysis and simulation results are validated against measured laboratory data using state-of-the-art commercial photon-counting detector arrays, demonstrating sub-microradian tracking errors under channel conditions representative of deep space optical links.

beacon tracking↗
NASA NTRS2021

Interpretation of Zerodur® Strength Data

Recent, detailed fractographic analysis of Zerodur® strength test specimens prepared by linear grinding and etching with a proprietary process indicated low frequency damage to be the strength limiting defects Recent, detailed fractographic analysis of Zerodur® strength test specimens prepared by linear grinding and etching with a proprietary process indicated low frequency damage to be the strength limiting defects [1]. The 2-parameter Weibull distribution is usually assumed when working with ceramic and glasses such as Zerodur®, although 3-parameter behavior is occasionally considered [2]. Detailed statistical modeling of the Zerodur® strength data with the was initial perspective of a 3-parameter Weibull distribution gave unsatisfying results [3]. The subsequent fractographic investigation indicated [1] that the usual assumption of many small, random, noninteracting flaws [4] was not represented, but instead, less frequent, aligned flaws along etching ridges parallel to the grinding direction were present, Figure 1. It was thus concluded that the strength of Zerodur® as prepared was not Weibull distributed. The flaws represent a sparse flaw population relative to typical grinding damage, but an extensive occurrence (high frequency) of handling damage. We examine the type of distribution present and explain the appearance of a 3-parameter distribution.

Glass, ceramic, strength, Weibull, distribution, m↗
NASA NTRS2014

Ocean surface carbon dioxide fugacity observed from space

We have developed and validated a statistical model to estimate the fugacity (or partial pressure) of carbon dioxide (CO2) at sea surface (pCO2sea) from space-based observations of sea surface temperature (SST), chlorophyll, and salinity. More than a quarter million in situ measurements coincident with satellite data were compiled to train and validate the model. We have produced and made accessible 9 years (2002–2010) of the pCO2sea at 0.5 degree resolutions daily over the global ocean. The results help to identify uncertainties in current JPL Carbon Monitoring System (CMS) model-based and bottom-up estimates over the ocean. The utility of the data to reveal multi-year and regional variability of the fugacity in relation to prevalent oceanic parameters is demonstrated.

Xie, Xiaosu↗
NASA NTRS2019

Exploiting OMI NO2 Satellite Observations to Infer Fossil-fuel CO2 Emissions from U.S. Megacities

Fossil-fuel CO2 emissions and their trends in eight U.S. megacities during 2006–2017 are inferred by combining satellite-derived NOX emissions with bottom-up city-specific NOX-to-CO2 emission ratios. A statistical model is fit to a collection NO2 plumes observed from the Ozone Monitoring Instrument (OMI), and is used to calculate top-down NOX emissions. Decreases in OMI-derived NOX emissions are observed across the eight cities from 2006 to 2017 (−17% in Miami to −58% in Los Angeles), and are generally consistent with long-term trends of bottom-up inventories (−25% in Miami to −49% in Los Angeles), but there are some interannual discrepancies. City-specific NOX-to-CO2 emission ratios, used to calculate inferred CO2, are estimated through annual bottom-up inventories of NOX and CO2 emissions disaggregated to 1 × 1 km2 resolution. Over the study period, NOX-to-CO2 emission ratios have decreased by ~40% nationwide (−24% to −51% for our studied cities), which is attributed to a faster reduction in NOX when compared to CO2 due to policy regulations and fuel type shifts. Combining top-down NOX emissions and bottom-up NOX-to-CO2 emission ratios, annual fossil-fuel CO2 emissions are derived. Inferred OMI-based top-down CO2 emissions trends vary between +7% in Dallas to −31% in Phoenix. For 2017, we report annual fossil-fuel CO2 emissions to be: Los Angeles 113 ± 49 Tg/yr; New York City 144 ± 62 Tg/yr; and Chicago 55 ± 24 Tg/yr. A study in the Los Angeles area, using independent methods, reported a 2013–2016 average CO2 emissions rate of 104 Tg/yr and 120 Tg/yr, which suggests that the CO2 emissions from our method are in good agreement with other studies' top-down estimates. We anticipate future remote sensing instruments – with better spatial and temporal resolution – will better constrain the NOX-to-CO2 ratio and reduce the uncertainty in our method.

Ozone Monitoring Instrument (OMI)↗
NASA NTRS2020

Concept for an On-orbit Capture and Orientation Module for Potential Mars Sample Return

An orbiting sample Capture and Orient Module (COM) architecture for a Capture, Contain, and Return System (CCRS) payload concept for an Earth Return Orbiter (ERO) was developed to enable on-orbit capture, orientation, and transfer of a Mars sample container into a containment vessel for potential Mars Sample Return (MSR). The module is composed of a capture mechanism for containing the Orbiting Sample (OS), a capture cone to capture and contain the OS, an orientation mechanism to orient the OS, an External Transfer Mechanism (ETM) to cage the OS during capture and assemble it into the containment vessel, a capture trigger to trigger capture mechanism and ETM closure during OS capture, and a sensing system to inspect the OS and confirm capture and orientation. Statistical modeling and simulations of the OS during capture were performed to analyze the time to contact and perturbations to the spacecraft at first contact. A half-scale functional prototype of the module was developed to demonstrate end-to-end operation.

Younse, Paulo↗
NASA NTRS2022

Multisensor Machine Learning to Retrieve High Spatiotemporal Resolution Land Surface Temperature

Climate change is making heat waves more frequent, long-lasting, and severe. While multiple satellite types provide data to monitor surface temperature, geostationary (GEO) sensors provide near-continuous, continental-scale observations which can better capture the diurnal variability of land surface temperature (LST) than intermittent observations from low-earth orbit (LEO) sensors. However, standard products from GEO satellites are available at coarsened spatial and temporal resolutions compared to the native sensor resolution. Using datasets from the NASA Earth Exchange, we leveraged co-located, co-temporal observations from LEO and GEO satellites to learn a data-driven mapping using a convolutional neural network. The resulting NASA Earth eXchange Artificial Intelligence LST (NEXAI-LST) achieved a mean absolute error of 1.73 K relative to the target LEO product and improves on both spatial and temporal resolution [2 km, 10 minute] compared to the GEO full disk standard product [10 km, hourly]. In validation against measurements from a ground-based sensor network, NEXAI-LST achieves similar or better fit than both LEO and GEO standard products, while depending none of the prior knowledge of land surface and atmospheric states required by physical-statistical models. Further, application of the model to unseen LEO and GEO satellites demonstrates robust generalization of the model across spatial region, time of day, and sensor. In support of NASA’s open-source science initiative, we make our NEXAI-LST product, model, and codes available to facilitate data exploration and further studies.

Kate Marie Duffy↗