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At least 307 records · Page 17

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NASA NTRS2003

Crustal Deformation in Southcentral Alaska: The 1964 Prince William Sound Earthquake Subduction Zone

This article, for Advances in Geophysics, is a summary of crustal deformation studies in southcentral Alaska. In 1964, southcentral Alaska was struck by the largest earthquake (moment magnitude 9.2) occurring in historical times in North America and the second largest earthquake occurring in the world during the past century. Conventional and space-based geodetic measurements have revealed a complex temporal-spatial pattern of crustal movement. Numerical models suggest that ongoing convergence between the North America and Pacific Plates, viscoelastic rebound, aseismic creep along the tectonic plate interface, and variable plate coupling all play important roles in controlling both the surface and subsurface movements. The geodetic data sets include tide-gauge observations that in some cases provide records back to the decades preceding the earthquake, leveling data that span a few decades around the earthquake, VLBI data from the late 1980s, and GPS data since the mid-1990s. Geologic data provide additional estimates of vertical movements and a chronology of large seismic events. Some of the important features that are revealed by the ensemble of studies that are reviewed in this paper include: (1) Crustal uplift in the region that subsided by up 2 m at the time of the earthquake is as much as 1 m since the earthquake. In the Turnagain Arm and Kenai Peninsula regions of southcentral Alaska, uplift rates in the immediate aftermath of the earthquake reached 150 mm/yr , but this rapid uplift decayed rapidly after the first few years following the earthquake. (2) At some other locales, notably those away the middle of the coseismic rupture zone, postseismic uplift rates were initially slower but the rates decay over a longer time interval. At Kodiak Island, for example, the uplift rates have been decreasing at a rate of about 7mm/yr per decade. At yet other locations, the uplift rates have shown little time dependence so far, but are thought not to be sustainable throughout the several hundred year recurrence time for great earthquake. The nearly 10 mm/yr uplift rate at Seldovia on the Kenai Peninsula is an example.

Cohen, Steven C.↗

NASA NTRS1997

Postural perturbations: new insights for treatment of balance disorders

This article reviews the neural control of posture as understood through studies of automatic responses to mechanical perturbations. Recent studies of responses to postural perturbations have provided a new view of how postural stability is controlled, and this view has profound implications for physical therapy practice. We discuss the implications for rehabilitation of balance disorders and demonstrate how an understanding of the specific systems underlying postural control can help to focus and enrich our therapeutic approaches. By understanding the basic systems underlying control of balance, such as strategy selection, rapid latencies, coordinated temporal spatial patterns, force control, and context-specific adaptations, therapists can focus their treatment on each patient's specific impairments. Research on postural responses to surface translations has shown that balance is not based on a fixed set of equilibrium reflexes but on a flexible, functional motor skill that can adapt with training and experience. More research is needed to determine the extent to which quantification of automatic postural responses has practical implications for predicting falls in patients with constraints in their postural control system.

Review↗

NASA NTRS2005

Remote Sensing of Particulate Organic Carbon Pools in the High-Latitude Oceans

The general goal of this project was to characterize spatial distributions at basin scales and variability on monthly to interannual timescales of particulate organic carbon (POC) in the high-latitude oceans. The primary objectives were: (1) To collect in situ data in the north polar waters of the Atlantic and in the Southern Ocean, necessary for the derivation of POC ocean color algorithms for these regions. (2) To derive regional POC algorithms and refine existing regional chlorophyll (Chl) algorithms, to develop understanding of processes that control bio-optical relationships underlying ocean color algorithms for POC and Chl, and to explain bio-optical differentiation between the examined polar regions and within the regions. (3) To determine basin-scale spatial patterns and temporal variability on monthly to interannual scales in satellite-derived estimates of POC and Chl pools in the investigated regions for the period of time covered by SeaWiFS and MODIS missions.

Stramski, Dariusz↗

NASA NTRS2007

Evaluation of the Potential of NASA Multi-satellite Precipitation Analysis in Global Landslide Hazard Assessment

Landslides are one of the most widespread natural hazards on Earth, responsible for thousands of deaths and billions of dollars in property damage every year. In the U.S. alone landslides occur in every state, causing an estimated $2 billion in damage and 25- 50 deaths each year. Annual average loss of life from landslide hazards in Japan is 170. The situation is much worse in developing countries and remote mountainous regions due to lack of financial resources and inadequate disaster management ability. Recently, a landslide buried an entire village on the Philippines Island of Leyte on Feb 17,2006, with at least 1800 reported deaths and only 3 houses left standing of the original 300. Intense storms with high-intensity , long-duration rainfall have great potential to trigger rapidly moving landslides, resulting in casualties and property damage across the world. In recent years, through the availability of remotely sensed datasets, it has become possible to conduct global-scale landslide hazard assessment. This paper evaluates the potential of the real-time NASA TRMM-based Multi-satellite Precipitation Analysis (TMPA) system to advance our understanding of and predictive ability for rainfall-triggered landslides. Early results show that the landslide occurrences are closely associated with the spatial patterns and temporal distribution of rainfall characteristics. Particularly, the number of landslide occurrences and the relative importance of rainfall in triggering landslides rely on the influence of rainfall attributes [e.g. rainfall climatology, antecedent rainfall accumulation, and intensity-duration of rainstorms). TMPA precipitation data are available in both real-time and post-real-time versions, which are useful to assess the location and timing of rainfall-triggered landslide hazards by monitoring landslide-prone areas while receiving heavy rainfall. For the purpose of identifying rainfall-triggered landslides, an empirical global rainfall intensity-duration threshold is developed by examining a number of landslide occurrences and their corresponding TMPA precipitation characteristics across the world. These early results , in combination with TRMM real-time precipitation estimation system, may form a starting point for developing an operational early warning system for rainfall-triggered landslides around the globe.

Hong, Yang↗

NASA NTRS2006

Spatiotemporal Filtering Using Principal Component Analysis and Karhunen-Loeve Expansion Approaches for Regional GPS Network Analysis

Spatial filtering is an effective way to improve the precision of coordinate time series for regional GPS networks by reducing so-called common mode errors, thereby providing better resolution for detecting weak or transient deformation signals. The commonly used approach to regional filtering assumes that the common mode error is spatially uniform, which is a good approximation for networks of hundreds of kilometers extent, but breaks down as the spatial extent increases. A more rigorous approach should remove the assumption of spatially uniform distribution and let the data themselves reveal the spatial distribution of the common mode error. The principal component analysis (PCA) and the Karhunen-Loeve expansion (KLE) both decompose network time series into a set of temporally varying modes and their spatial responses. Therefore they provide a mathematical framework to perform spatiotemporal filtering.We apply the combination of PCA and KLE to daily station coordinate time series of the Southern California Integrated GPS Network (SCIGN) for the period 2000 to 2004. We demonstrate that spatially and temporally correlated common mode errors are the dominant error source in daily GPS solutions. The spatial characteristics of the common mode errors are close to uniform for all east, north, and vertical components, which implies a very long wavelength source for the common mode errors, compared to the spatial extent of the GPS network in southern California. Furthermore, the common mode errors exhibit temporally nonrandom patterns.

displacement↗

NASA NTRS2006

The International Reference Ionosphere - Climatological Standard for the Ionosphere

The International Reference Ionosphere (IRI) a joint project of URSI and COSPAR is the defacto standard for a climatological specification of ionospheric parameters. IRI is based on a wide range of ground and space data and has been steadily improved since its inception in 1969 with the ever-increasing volume of ionospheric data and with better mathematical descriptions of the observed global and temporal variation patterns. The IRI model has been validated with a large amount of data including data from the most recent ionospheric satellites (KOMPSAT, ROCSAT and TIMED) and data from global network of ionosondes. Several IRI teams are working on specific aspects of the IRI modeling effort including an improved representation of the topside ionosphere with a seamless transition to the plasmasphere, a new effort to represent the global variation of F2 peak parameters using the Neural Network (NN) technique, and the inclusion of several additional parameters in IRI, e.g., spread-F probability and ionospheric variability. Annual IRI workshops are the forum for discussions of these efforts and for all science activities related to IRI as well as applications of the IRI model in engineering and education. In this paper I will present a status report about the IRI effort with special emphasis on the presentations and results from the most recent IRI Workshops (Paris, 2004; Tortosa, 2005) and on the most important ongoing IRI activities. I will discuss the latest version of the IRI model, IRI-2006, highlighting the most recent changes and additions. Finally, the talk will review some of the applications of the IRI model with special emphasis on the use for radiowave propagation studies and communication purposes.

Bilitza, Dieter↗

NASA NTRS2009

Expert system for controlling plant growth in a contained environment

In a system for optimizing crop growth, vegetation is cultivated in a contained environment, such as a greenhouse, an underground cavern or other enclosed space. Imaging equipment is positioned within or about the contained environment, to acquire spatially distributed crop growth information, and environmental sensors are provided to acquire data regarding multiple environmental conditions that can affect crop development. Illumination within the contained environment, and the addition of essential nutrients and chemicals are in turn controlled in response to data acquired by the imaging apparatus and environmental sensors, by an ''expert system'' which is trained to analyze and evaluate crop conditions. The expert system controls the spatial and temporal lighting pattern within the contained area, and the timing and allocation of nutrients and chemicals to achieve optimized crop development. A user can access the ''expert system'' remotely, to assess activity within the growth chamber, and can override the ''expert system''.

May, George A.↗

NASA NTRS2011

Expert system for controlling plant growth in a contained environment

In a system for optimizing crop growth, vegetation is cultivated in a contained environment, such as a greenhouse, an underground cavern or other enclosed space. Imaging equipment is positioned within or about the contained environment, to acquire spatially distributed crop growth information, and environmental sensors are provided to acquire data regarding multiple environmental conditions that can affect crop development. Illumination within the contained environment, and the addition of essential nutrients and chemicals are in turn controlled in response to data acquired by the imaging apparatus and environmental sensors, by an "expert system" which is trained to analyze and evaluate crop conditions. The expert system controls the spatial and temporal lighting pattern within the contained area, and the timing and allocation of nutrients and chemicals to achieve optimized crop development. A user can access the "expert system" remotely, to assess activity within the growth chamber, and can override the "expert system".

May, George A.↗

NASA NTRS2011

Variation of Accumulation Rates Over the Last Eight Centuries on the East Antarctic Plateau Derived from Volcanic Signals in Ice Cores

Volcanic signatures in ice-core records provide an excellent means to date the cores and obtain information about accumulation rates. From several ice cores it is thus possible to extract a spatio-temporal accumulation pattern. We show records of electrical conductivity and sulfur from firn cores from the Norwegian-USA scientific traverse during the International Polar Year 2007-2009 (IPY) through East Antarctica. Major volcanic eruptions are identified and used to assess century-scale accumulation changes. The largest changes seem to occur in the most recent decades with accumulation over the period 1963- 2007/08 being up to 25 % different from the long-term record. There is no clear overall trend, some sites show an increase in accumulation over the period 1963 to present while others show a decrease. Almost all of the sites above 3200 m above sea level (asl) suggest a decrease. These sites also show a significantly lower accumulation value than large-scale assessments both for the period 1963 to present and for the long-term mean at the respective drill sites. The spatial accumulation distribution is influenced mainly by elevation and distance to the ocean (continentality), as expected. Ground-penetrating radar data around the drill sites show a spatial variability within 10-20 % over several tens of kilometers, indicating that our drill sites are well representative for the area around them. Our results are important for large-scale assessments of Antarctic mass balance and model validation.

Anschuetz, H.↗

NASA NTRS2012

Highlights of the First 15 Months of Aquarius Salinity Measurements

Aquarius satellite salinity measurements are resolving the major global and regional spatial patterns, and temporal variations, since the start of routine data collection on 25 August 2011. This description includes the principal seasonal variations over the first annual cycle as observed by the mission. In particular, we identify the evolution of low salinity anomalies associated with the Atlantic and Pacific intertropical convergence zones (ITCZ), major river outflows such as the Amazon, a seasonal low salinity anomaly in the Panama bight, and other features. We also explore the links that the salinity variations have with precipitation and surface currents. We then will describe the variations related to the presently evolving 2012 El Nino, now evident, as it progresses through the summer and fall 2012. We conclude with a brief summary of the Aquarius data products and validation

Lagerloef, Gary S. E.↗

NASA NTRS2013

From BASE-ASIA Toward 7-SEAS: A Satellite-Surface Perspective of Boreal Spring Biomass-Burning Aerosols and Clouds in Southeast Asia

In this paper, we present recent field studies conducted by NASA's SMART-COMMIT (and ACHIEVE, to be operated in 2013) mobile laboratories, jointly with distributed ground-based networks (e.g., AERONET, http://aeronet.gsfc.nasa.gov/ and MPLNET, http://mplnet.gsfc.nasa.gov/) and other contributing instruments over northern Southeast Asia. These three mobile laboratories, collectively called SMARTLabs (cf. http://smartlabs.gsfc.nasa.gov/, Surface-based Mobile Atmospheric Research & Testbed Laboratories) comprise a suite of surface remote sensing and in-situ instruments that are pivotal in providing high spectral and temporal measurements, complementing the collocated spatial observations from various Earth Observing System (EOS) satellites. A satellite-surface perspective and scientific findings, drawn from the BASE-ASIA (2006) field deployment as well as a series of ongoing 7-SEAS (2010-13) field activities over northern Southeast Asia are summarized, concerning (i) regional properties of aerosols from satellite and in situ measurements, (ii) cloud properties from remote sensing and surface observations, (iii) vertical distribution of aerosols and clouds, and (iv) regional aerosol radiative effects and impact assessment. The aerosol burden over Southeast Asia in boreal spring, attributed to biomass burning, exhibits highly consistent spatial and temporal distribution patterns, with major variability arising from changes in the magnitude of the aerosol loading mediated by processes ranging from large-scale climate factors to diurnal meteorological events. Downwind from the source regions, the tightly coupled-aerosolecloud system provides a unique, natural laboratory for further exploring the micro- and macro-scale relationships of the complex interactions. The climatic significance is presented through large-scale anti-correlations between aerosol and precipitation anomalies, showing spatial and seasonal variability, but their precise cause-and-effect relationships remain an open-ended question. To facilitate an improved understanding of the regional aerosol radiative effects, which continue to be one of the largest uncertainties in climate forcing, a joint international effort is required and anticipated to commence in springtime 2013 in northern Southeast Asia.

biomass burning aerosols↗

NASA NTRS2018

Observation Error Specification for Near-Surface Soil Moisture Assimilation: Does It Matter?

The observation error variances assumed in the data assimilation (DA) of remotely sensed near-surface soil moisture observations are known to have unrealistic spatial patterns. The temporal variability in the errors is also typically neglected. Soil moisture errors cannot be directly calculated at large scales, and the globally distributed errors are unknown. We apply several approaches to estimating the observation errors (R matrix) for near-surface soil moisture DA experiments, to establish whether the assumed errors are important to the DA performance, and hence whether uncertainty in the observation error specification is a likely source of uncertainty in soil moisture DA output.

Draper, Clara↗

NASA NTRS2020

Synergistic Use of SMAP and OCO-2 Data in Assessing the Responses of Ecosystem Productivity to the 2018 U.S. Drought

Soil moisture and gross primary productivity (GPP) estimates from the Soil Moisture Active Passive (SMAP) and solar-induced chlorophyll fluorescence (SIF) from the Orbiting Carbon Observatory-2 (OCO-2) provide new opportunities for understanding the relationship between soil moisture and terrestrial photosynthesis over large regions. Here we explored the potential of the synergistic use of SMAP and OCO-2 based data for monitoring the responses of ecosystem productivity to drought. We used complementary observational information on root-zone soil moisture and GPP (9 km) from SMAP and fine-resolution SIF (0.05°; GOSIF) derived from OCO-2 SIF soundings. We compared the spatial pattern and temporal evolution of anomalies of these variables over the conterminous U.S. during the 2018 drought, and examined to what extent they could characterize the drought-induced variations of flux tower GPP and crop yield data. Our results showed that SMAP GPP and GOSIF could well capture the spatial extent and dynamics of drought indicated by the U.S. Drought Monitor maps and the SMAP root-zone soil moisture deficit. Over the U.S. Southwest, monthly anomalies of soil moisture showed significant positive correlations with those of SMAP GPP (R2=0.44, p<0.001) and GOSIF (R2=0.76, p<0.001), demonstrating strong water availability constraints on plant productivity across dryland ecosystems. We further found that SMAP GPP and GOSIF captured the impact of drought on tower GPP and crop yield. Our results suggest that synergistic use of SMAP and OCO-2 data products can reveal the drought evolution and its impact on ecosystem productivity and carbon uptake at multiple spatial and temporal scales, and demonstrate the value of SMAP and OCO-2 for studying ecosystem function, carbon cycling, and climate change.

Soil Moisture Active Passive↗

DOE OSTI2020

Activity Time-Use Patterns and Experienced Satisfaction: Travel Behavioral Dynamics from the 2010–2013 American Time-Use Survey Data

Central to the theory of activity-based approaches is the role of time-use and its impacts on various decision processes related to individual activity-travel patterns, thereby determining ones’ daily well-being. This research aims at quantifying and investigating the underlying correlation of time-use and happiness using the repeated cross-section data from the 2010-2013 American Time Use Survey Well-Being module. The survey specifically records reported levels of activity satisfaction as measured through – happiness, meaningfulness, tiredness, sadness and stress experienced from activity participation. Using these scores, we first construct a composite degree of activity satisfaction that a person experiences using latent class cluster analysis. A series of regression models are then estimated to jointly analyze episodic duration and satisfaction separately for each of years from 2010-2013, by controlling for socioeconomics, household lifecycle stages (29-groups based on age, gender, marital status and presence of children), activity characteristics and global life and health assessment measures. Overall, model estimation results reveal a strong negative correlation between episodic duration and happiness from individual activity engagement patterns. This correlation pattern is temporally stable for the years 2010-2013, with minor variations. Results also suggest that household lifecycle stage has a major impact on activity time-use and satisfaction behavior. Further, single parent and younger couples (25 years to 45 years) with children are more likely to engage in longer and less happy episodes due to family commitments. The model findings also show a strong correlation between health conditions and activity happiness.

Ravulaparthy, Srinath↗

DOE OSTI2023

Feeder Power Disaggregation: A Data-Efficient Matrix Completion Approach: Preprint

This paper presents a data-driven algorithm for the feeder power disaggregation problem in distribution systems. Leveraging spatio-temporal power patterns in residential homes, residential power is discomposed into three components: sparse-switching loads, periodic loads, and photovoltaic generation, using two sparse matrices and a rank-one matrix. The matrix completion process is data-efficient because of the matrix sparsity and low rankness, along with the use of power system models. The proposed approach is tested using real-world residential datasets on a 33-bus distribution system, demonstrating accurate power disaggregation with efficient matrix completion.

distribution system↗

DOE OSTI2023

Quantifying and Understanding the Access Time to Dockless Micromobility: A Case Study in Washington, D.C.

Micromobility has been widely deployed in many cities. Similar as how access time/distance affects the travel demand to use public transit and informs transit system design, access time/distance to micromobility service measures its service efficiency and also serves as an equity indicator to inform city agencies from a regulation perspective. Though there is an increasing need to understand it, access to micromobility has not been sufficiently studied. This paper developed a framework to quantity the access time to dockless micromobility service (i.e., the minimum time needed to walk to reach the closest dockless micromobility vehicles). Based on the real-time vehicle location data collected from Washington, DC, this research quantified the access time to dockless micromobility, analyzed its spatial and temporal variation patterns and investigated its relationship with socio-demographic variables (i.e., population density, employment density and low-income population). The results revealed that the access time to dockless micromobility ranges between 0 to 4 minutes with the most frequently observed range of 0.5 to 1 minutes, and the city center area tends to have shorter access time than the outskirts areas. Results also indicate a quite stable access time level in DC with access time standard deviation of 0.2 to 0.5 minutes. After correlating the access time at census-block-group level with socio-demographic data, it was discovered that shorter access time usually aligns with larger population and employment density, and the proportion of low-income population was found not helpful with explaining the access time variation, which indicating a relatively equitable micromobility program.

access time↗

DOE OSTI2024

Effects of Temporal Light Modulation on Individuals Sensitive to Pattern Glare

Solid-state lighting systems can vary widely in the degree of temporal light modulation (TLM) of their light output. TLM is known to have visual, cognitive, and behavioral effects but there are few recommendations for limits on the acceptable TLM in everyday lighting systems and there is little information concerning individual differences in sensitivity. This paper is a re-analysis of previously presented data, focusing on two subgroups in a larger sample: those scoring low or high on the Wilkins Pattern Glare Sensitivity (PGS) test, which is a validated test that identifies people at high risk of visual stress. In conclusion, the results show that the PGS groups differed in their sensitivity to TLM conditions, despite short exposures and a restricted field of view.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Controls and variability of soil respiration temperature sensitivity across China

Understanding the temperature sensitivity (Q 10 ) of soil respiration is critical for benchmarking the potential intensity of regional and global terrestrial soil carbon fluxes-climate feedbacks. Although field observations have demonstrated the strong spatial heterogeneity of Q 10 , a significant knowledge gap still exists regarding to the factors driving spatial and temporal variabilities of Q 10 at regional scales. Here, therefore, we used a machine learning approach to predict Q 10 from 1994 to 2016 with a spatial resolution of 1 km across China from 515 field observations at 5 cm soil depth using climate, soil and vegetation variables. Predicted Q 10 varied from 1.54 to 4.17, with an area-weighted average of 2.52. There was no significant temporal trend for Q 10 (p = 0.32), but annual vegetation production (indicated by normalized difference vegetation index, NDVI) was positively correlated to it (p < 0.01). Spatially, soil organic carbon (SOC) was the most important driving factor in 62 % of the land area across China, and varied greatly, demonstrating soil controls on the spatial pattern of Q 10 . These findings highlighted different environmental controls on the spatial and temporal pattern of soil respiration Q 10 , which should be considered to improve global biogeochemical models used to predict the spatial and temporal patterns of soil carbon fluxes to ongoing climate change.

54 ENVIRONMENTAL SCIENCES↗