Search NASA⌕ Search

SEARCH · Search NASA

Results for “Temporal Study”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Calculation of rf-induced temporal jitter in ultrafast electron diffraction

A significant contribution to the temporal resolution of an ultrafast electron diffraction (UED) instrument is arrival time jitter caused by amplitude and phase variation of radio-frequency (rf) cavities. In this paper, we present a semianalytical approach for calculating rf-induced temporal jitter from klystron and rf cavity parameters. Our approach allows fast estimation of temporal jitter for MeV-UED beamlines and can serve as a virtual timing tool when shot-to-shot measurements of rf amplitude and phase jitters are available. A simulation study for the SLAC MeV-UED instrument is presented, and the temporal resolution of several beamline configurations is compared.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Meta Biome: a multiscale model integrating agent-based and metabolic networks to reveal spatial regulation in gut mucosal microbial communities

ABSTRACT Mucosal microbial communities (MMCs) are complex ecosystems near the mucosal layers of the gut essential for maintaining health and modulating disease states. Despite advances in high-throughput omics technologies, current methodologies struggle to capture the dynamic metabolic interactions and spatiotemporal variations within MMCs. In this work, we presentMetaBiome, a multiscale model integrating agent-based modeling (ABM), finite volume methods, and constraint-based models to explore the metabolic interactions within these communities. Integrating ABM allows for the detailed representation of individual microbial agents each governed by rules that dictate cell growth, division, and interactions with their surroundings. Through a layered approach—encompassing microenvironmental conditions, agent information, and metabolic pathways—we simulated different communities to showcase the potential of the model. Using ourin-silicoplatform, we explored the dynamics and spatiotemporal patterns of MMCs in the proximal small intestine and the cecum, simulating the physiological conditions of the two gut regions. Our findings revealed how specific microbes adapt their metabolic processes based on substrate availability and local environmental conditions, shedding light on spatial metabolite regulation and informing targeted therapies for localized gut diseases.MetaBiome provides a detailed representation of microbial agents and their interactions, surpassing the limitations of traditional grid-based systems. This work marks a significant advancement in microbial ecology, as it offers new insights into predicting and analyzing microbial communities. IMPORTANCE Our study presents a novel multiscale model that combines agent-based modeling, finite volume methods, and genome-scale metabolic models to simulate the complex dynamics of mucosal microbial communities in the gut. This integrated approach allows us to capture spatial and temporal variations in microbial interactions and metabolism that are difficult to study experimentally. Key findings from our model include the following: (i) prediction of metabolic cross-feeding and spatial organization in multi-species communities, (ii) insights into how oxygen gradients and nutrient availability shape community composition in different gut regions, and (iii) identification of spatiallyregulated metabolic pathways and enzymes inE. coli. We believe this work represents a significant advance in computational modeling of microbial communities and provides new insights into the spatial regulation of gut microbiome metabolism. The multiscale modeling approach we have developed could be broadly applicable for studying other complex microbial ecosystems.

Microbiology↗
NASA NTRS1987

Variation in the thickness of ejecta cover on Mars with increasing crater density

Even relatively young surfaces on Mars have superposed craters and must carry a dusting of impact debris. For increasingly more ancient surfaces, deposits of ejecta generally increase in thickness, and the signatures of the geology beneath become more obscured. Although nothing can be done about this obscuration, these newer deposits can be described, temporally and spatially, and thereby avoid falsely interpreting the geology beneath. The task of temporal and spatial characterization was begun by considering the areal variability of ejecta cover with increasing exposure to meteorite bombardment. This study establishes a baseline for evaluating the quality and distribution of exposures of strata lying temporally beneath the ejecta. Of special interest is the distribution of ejecta overlying surfaces that have never sustained a direct impact by a large meteorite, for these retain the volcanic and sedimentary stratigraphy in its most pristine state.

Woronow, A.↗
NASA NTRS2014

Data Albums: An Event Driven Search, Aggregation and Curation Tool for Earth Science

One of the largest continuing challenges in any Earth science investigation is the discovery and access of useful science content from the increasingly large volumes of Earth science data and related information available. Approaches used in Earth science research such as case study analysis and climatology studies involve gathering discovering and gathering diverse data sets and information to support the research goals. Research based on case studies involves a detailed description of specific weather events using data from different sources, to characterize physical processes in play for a specific event. Climatology-based research tends to focus on the representativeness of a given event, by studying the characteristics and distribution of a large number of events. This allows researchers to generalize characteristics such as spatio-temporal distribution, intensity, annual cycle, duration, etc. To gather relevant data and information for case studies and climatology analysis is both tedious and time consuming. Current Earth science data systems are designed with the assumption that researchers access data primarily by instrument or geophysical parameter. Those who know exactly the datasets of interest can obtain the specific files they need using these systems. However, in cases where researchers are interested in studying a significant event, they have to manually assemble a variety of datasets relevant to it by searching the different distributed data systems. In these cases, a search process needs to be organized around the event rather than observing instruments. In addition, the existing data systems assume users have sufficient knowledge regarding the domain vocabulary to be able to effectively utilize their catalogs. These systems do not support new or interdisciplinary researchers who may be unfamiliar with the domain terminology. This paper presents a specialized search, aggregation and curation tool for Earth science to address these existing challenges. The search tool automatically creates curated "Data Albums", aggregated collections of information related to a specific science topic or event, containing links to relevant data files (granules) from different instruments; tools and services for visualization and analysis; and information about the event contained in news reports, images or videos to supplement research analysis. Curation in the tool is driven via an ontology based relevancy ranking algorithm to filter out non-relevant information and data.

Ramachandran, Rahul↗
NASA NTRS2024

Characterizing the 2019-2021 Drought in La Plata River Basin With GLDAS and SMAP

Study region The La Plata River Basin (LPRB) is an area of interest, as there was a significant drought event from 2019 to 2021. With the LPRB being the second largest river basin in South America, this drought affected all aspects of life for over 100 million people who inhabit this area. Study focus In this study, we utilized satellite and model datasets to examine spatial and temporal variability of hydrological anomalies throughout the basin before and during the drought event. These variable anomalies, such as precipitation and groundwater, are derived from the Global Land Data Assimilation System (GLDAS). Additionally, the Soil Moisture Active Passive (SMAP) observations were used in the spatial and temporal analysis of the drought. The water loss was calculated using the Mann-Kendall test to assess the changes in anomalies for the terrestrial water storage throughout the basin and subbasins. New hydrological insights for the region The main insight from this study is the agreement of the GLDAS anomalies with the SMAP data throughout the drought. The variable anomalies all decreased and showed alignment with the downscaled 1 km SMAP which shows alignment with the trends from in-situ observations. It was also found that the Upper Parana subbasin lost the most water over the drought period. These products improve understanding of the spatial variability within the entire basin and facilitate understanding of droughts and resources to assist in the future management of water resources.

La Plata Basin↗
NASA NTRS1986

Development of algorithms for understanding the temporal and spatial variability of the earth's radiation balance

A brief description is given of how temporal and spatial variability in the earth's radiative behavior influences the goals of satellite radiation monitoring systems and how some previous systems have addressed the existing problems. Then, results of some simulations of radiation budget monitoring missions are presented. These studies led to the design of the Earth Radiation Budget Experiment (ERBE). A description is given of the temporal and spatial averaging algorithms developed for the ERBE data analysis. These algorithms are intended primarily to produce monthly averages of the net radiant exitance on regional, zonal, and global scales and to provide insight into the regional diurnal variability of radiative parameters such as albedo and long-wave radiant exitance. The algorithms are applied to scanner and nonscanner data for up to three satellites. Modeling of dialy shortwave albedo and radiant exitance with satellite samling that is insufficient to fully account for changing meteorology is discussed in detail. Studies performed during the ERBE mission and software design are reviewed. These studies provide quantitative estimates of the effects of temporally sparse and biased sampling on inferred diurnal and regional radiative parameters. Other topics covered include long-wave diurnal modeling, extraction of a regional monthly net clear-sky radiation budget, the statistical significance of observed diurnal variability, quality control of the analysis, and proposals for validating the results of ERBE time and space averaging.

Brooks, D. R.↗
DOE OSTI2024

Implications of increased spatial and trophic overlap between juvenile Pacific salmon and Sablefish in the northern California Current

Abstract Objective The study was designed to assess long-term variability in the distribution of juvenile Pacific salmon Oncorhynchus spp. and Sablefish Anoplopoma fimbria. The study also evaluated whether Sablefish and Pacific salmon shared food resources and looked to characterize Sablefish during an understudied period of their life cycle. Methods To meet the objectives, the study used data from 26 years of surface trawls conducted in Oregon and Washington coastal waters (1998–2023). Spatial–temporal models were used to measure changes in abundance and distribution of Pacific salmon and Sablefish along with covariates of ocean temperature. The study evaluated trophic characteristics of Pacific salmon and Sablefish from 2020 for differences. The temporal variation in size and diets of Sablefish were also analyzed, along with energy density of fish caught in 2020. Result The spatial–temporal model demonstrated that there has been a nearshore expansion of juvenile Sablefish over the past 26 years that was correlated with increased ocean temperature. The nearshore expansion of Sablefish resulted in increased spatial and trophic overlap with juvenile Pacific salmon. While feeding in nearshore waters, juvenile Sablefish demonstrated competitive feeding advantages over juvenile Pacific salmon during a critical phase of salmonid early marine life history. Juvenile Sablefish exhibited significant ontogenetic diet and energetic shifts, and even the smallest (68–80 mm fork length) were piscivorous. Conclusions If juvenile Sablefish numbers continue to increase relative to Pacific salmon, they could exert more competitive pressure, especially if food resources become limited. Pacific salmon may experience adverse effects from competition, regardless of whether or not juvenile Sablefish, which have recently expanded into nearshore waters, successfully recruit to the adult population.

Daly, Elizabeth A. (ORCID:0000000195334457)↗
NASA NTRS2014

Exploring Lightning Jump Characteristics

This study is concerned with the characteristics of storms exhibiting an abrupt temporal increase in the total lightning flash rate (i.e., lightning jump, LJ). An automated storm tracking method is used to identify storm "clusters" and total lightning activity from three different lightning detection systems over Oklahoma, northern Alabama and Washington, D.C. On average and for different employed thresholds, the clusters that encompass at least one LJ (LJ1) last longer, relate to higher Maximum Expected Size of Hail, Vertical Integrated Liquid and lightning flash rates (area-normalized) than the clusters that did not exhibit any LJ (LJ0). The respective mean values for LJ1 (LJ0) clusters are 80 min (35 min), 14 mm (8 mm), 25 kg per square meter (18 kg per square meter) and 0.05 flash per min per square kilometer (0.01 flash per min per square kilometer). Furthermore, the LJ1 clusters are also characterized by slower decaying autocorrelation functions, a result that implies a less "random" behavior in the temporal flash rate evolution. In addition, the temporal occurrence of the last LJ provides an estimate of the time remaining to the storm's dissipation. Depending of the LJ strength (i.e., varying thresholds), these values typically range between 20-60 min, with stronger jumps indicating more time until storm decay. This study's results support the hypothesis that the LJ is a proxy for the storm's kinematic and microphysical state rather than a coincidental value.

lightning jump↗
NASA NTRS1993

Temporal Changes in Endmember Abundances, Liquid Water and Water Vapor Over Vegetation at Jasper Ridge

In this study, a Modtran-based calibration approach was used to map liquid water and atmospheric water vapor and retrieve surface reflectance from three AVIRIS scenes acquired in 1992 over the Jasper Ridge Biological Preserve. Temporal trends in endmember fractions, liquid water and atmospheric water vapor were investigated also. The combination of spectral mixture analysis and the Modtran based atmospheric/liquid water models was used to develop a unique vegetation community description.

liquid↗
DOE OSTI2023

Data initiatives for ocean-driven melt of Antarctic ice shelves

Ocean-driven melt of Antarctic ice shelves is an important control on mass loss from the ice sheet, but is complex to study due to significant variability in melt rates both spatially and temporally. Here we assess the strengths and weakness of satellite and field-based observations as tools for testing models of ice-shelf melt. We discuss how the complementary use of field, satellite and model data can be a powerful but underutilised tool for studying melt processes. Finally, we identify some community initiatives working to collate and publish coordinated melt rate datasets, which can be used in future for validating satellite-derived maps of melt and evaluating processes in numerical simulations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2013

X-ray Follow-ups of XSS J12270-4859: A Low-mass X-ray Binary with Gamma-ray Fermi-LAT Association

Context. XSS J1227.0-4859 is a peculiar, hard X-ray source recently positionally associated to the Fermi-LAT source 1FGL J1227.9- 4852/2FGL J1227.7-4853. Multi-wavelength observations have added information on this source, indicating a low-luminosity lowmass X-ray binary (LMXB), but its nature is still unclear. Aims. To progress in our understanding, we present new X-ray data from a monitoring campaign performed in 2011 with the XMM-Newton, RXTE, and Swift satellites and combine them with new gamma-ray data from the Fermi and AGILE satellites. We complement the study with simultaneous near-UV photometry from XMM-Newton and with previous UV/optical and near-IR data. Methods. We analysed the temporal characteristics in the X-rays, near-UV, and gamma rays and studied the broad-band spectral energy distribution from radio to gamma rays. Results. The X-ray history of XSS J1227 over 7 yr shows a persistent and rather stable low-luminosity (6 × 1033 d2 1 kpcerg s−1) source, with flares and dips being peculiar and permanent characteristics. The associated Fermi-LAT source 2FGL J1227.7-4853 is also stable over an overlapping period of 4.7 yr. Searches for X-ray fast pulsations down to msec give upper limits to pulse fractional amplitudes of 15−25% that do not rule out a fast spinning pulsar. The combined UV/optical/near-IR spectrum reveals a hot component at approximately 13 kK and a cool one at approximately 4.6 kK. The latter would suggest a late-type K2−K5 companion star, a distance range of 1.4−3.6 kpc, and an orbital period of 7-9 h. A near-UV variability (6 h) also suggests a longer orbital period than previously estimated. Conclusions. The analysis shows that the X-ray and UV/optical/near-IR emissions are more compatible with an accretion-powered compact object than with a rotational powered pulsar. The X-ray to UV bolometric luminosity ratio could be consistent with a binary hosting a neutron star, but the uncertainties in the radio data may also allow an LMXB black hole with a compact jet. In this case, it would be the first associated with a high-energy gamma-ray source.

deMartino, D.↗
NASA NTRS2018

NASA's Black Marble Nighttime Lights Product Suite

NASA's Black Marble nighttime lights product suite (VNP46) is available at 500 meters resolution since January 2012 with data from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) onboard the Suomi National Polar-orbiting Platform (SNPP). The retrieval algorithm, developed and implemented for routine global processing at NASA's Land Science Investigator-led Processing System (SIPS), utilizes all high-quality, cloud-free, atmospheric-, terrain-, vegetation-, snow-, lunar-, and stray light-corrected radiances to estimate daily nighttime lights (NTL) and other intrinsic surface optical properties. Key algorithm enhancements include: (1) lunar irradiance modeling to resolve non-linear changes in phase and libration; (2) vector radiative transfer and lunar bidirectional surface anisotropic reflectance modeling to correct for atmospheric and BRDF (Bidirectional Reflectance Distribution Function) effects; (3) geometric-optical and canopy radiative transfer modeling to account for seasonal variations in NTL; and (4) temporal gap-filling to reduce persistent data gaps. Extensive benchmark tests at representative spatial and temporal scales were conducted on the VNP46 time series record to characterize the uncertainties stemming from upstream data sources. Initial validation results are presented together with example case studies illustrating the scientific utility of the products. This includes an evaluation of temporal patterns of NTL dynamics associated with urbanization, socioeconomic variability, cultural characteristics, and displaced populations affected by conflict. Current and planned activities under the Group on Earth Observations (GEO) Human Planet Initiative are aimed at evaluating the products at different geographic locations and time periods representing the full range of retrieval conditions.

Suomi-NPP↗
DOE OSTI2018

Dynamic assessment of urban economy-environment-energy system using system dynamics model: A case study in Beijing

Highlights: • We combine System Dynamics model and Geographic Information System to analyze the energy-environment-economy (3E) system both temporally and spatially, which explicitly explore the interaction of economics, energy, and environment and effects of the key influencing factors. • Beijing is selected as a case study. • Alternative scenarios, e.g., current, technology, energy and environment scenarios are explored and compared. • Simulation results shows that, current scenario is not sustainable; technology scenario is applicable to economic growth; environment scenario maintains a balanced path of development for long term stability. Economic development, accompanying with environmental damage and energy depletion, becomes essential nowadays. There is a complicated and comprehensive interaction between economics, environment and energy. Understanding the operating mechanism of Energy-Environment-Economy model (3E) and its key factors is the inherent part in dealing with the issue. In this paper, we combine System Dynamics model and Geographic Information System to analyze the energy-environment-economy (3E) system both temporally and spatially, which explicitly explore the interaction of economics, energy, and environment and effects of the key influencing factors. Beijing is selected as a case study to verify our SD-GIS model. Alternative scenarios, e.g., current, technology, energy and environment scenarios are explored and compared. Simulation results shows that, current scenario is not sustainable; technology scenario is applicable to economic growth; environment scenario maintains a balanced path of development for long term stability. Policy-making insights are given based on our results and analysis.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2014

How Well Do Satellite AOD Observations Represent the Spatial and Temporal Variability of PM2.5 Concentration for the United States?

Due to their extensive spatial coverage, satellite Aerosol Optical Depth (AOD) observations have been widely used to estimate and predict surface PM2.5 concentrations. While most previous studies have focused on establishing relationships between collocated, hourly or daily AOD and PM2.5 measurements, in this study, we instead focus on the comparison of the large-scale spatial and temporal variability between satellite AOD and PM2.5 using monthly mean measurements. A newly developed spectral analysis technique e Combined Maximum Covariance Analysis (CMCA) is applied to Moderate Resolution Imaging Spectroradiometer (MODIS), Multi-angle Imaging Spectroradiometer (MISR), Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Ozone Monitoring Instrument (OMI) AOD datasets and Environmental Protection Agency (EPA) PM2.5 data, in order to extract and compare the dominant modes of variability. Results indicate that AOD and PM2.5 agree well in terms of interannual variability. An overall decrease is found in both AOD and PM2.5 across the United States, with the strongest signal over the eastern US. With respect to seasonality, good agreement is found only for Eastern US, while for Central and Western US, AOD and PM2.5 seasonal cycles are largely different or even reversed. These results are verified using Aerosol Robotic Network (AERONET) AOD observations and differences between satellite and AERONET are also examined. MODIS and MISR appear to have the best agreement with AERONET. In order to explain the disagreement between AOD and PM2.5 seasonality, we further use Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) extinction profile data to investigate the effect of two possible contributing factors, namely aerosol vertical distribution and cloud-free sampling. We find that seasonal changes in aerosol vertical distribution, due to the seasonally varying mixing height, is the primary cause for the AOD and PM2.5 seasonal discrepancy, in particular, the low AOD but high PM2.5 observed during the winter season for Central and Western US. In addition, cloud-free sampling by passive sensors also induces some bias in AOD seasonality, especially for the Western US, where the largest seasonal change in cloud fraction is found. The seasonal agreement between low level (below 500 m AGL), all sky CALIOP AOD and PM2.5 is significantly better than column AOD from MODIS, MISR, SeaWiFS and OMI. In particular, the correlation between low level, all sky AOD and PM2.5 seasonal cycles increases to above 0.7 for Central and Western US, as opposed to near zero or negative correlation for column, clear sky AOD. This result highlights the importance of accounting for the seasonally varying aerosol profiles and cloud-free sampling bias when using column AOD measurements to infer surface PM2.5 concentrations.

MODIS (radiometry)↗
DOE OSTI2025

Graph-Based Prediction of Spatio-Temporal Vaccine Hesitancy From Insurance Claims Data

Growing vaccine hesitancy is contributing to the decline in immunization rates for highly contagious, vaccine-preventable childhood diseases. Therefore, there has been a significant interest in understanding how hesitancy is spreading at higher spatio-temporal resolutions, enabling more targeted interventions. Motivated by this, we study the problem of prediction of vaccine hesitancy at the ZIP Code level, referred to as the VaxHesitancy problem. A significant challenge for this problem is the lack of high-resolution data that indicates hesitancy. Here, we develop a hybrid VaxHesSTL framework that combines a Graph Neural Network (GNN) and a Recurrent Neural Network (RNN) to address the VaxHesitancy problem. The GNN uses a ZIP Code-level network to capture spatial signals from neighboring areas, while the RNN models the temporal dynamics present in the data. We train and evaluate VaxHesSTL using a large dataset, namely the All-Payer Claims Databases (APCD), for Virginia, consisting of insurance claims from over five million individuals for six years. We find that an aggregated contact network or graph, developed from a detailed activity-based population network, plays an important role in the performance of VaxHesSTL, compared to graph models based solely on spatial proximity. Experiments demonstrate that VaxHesSTL outperforms a range of state-of-the-art baselines, which rely solely on historical time series data without accounting for spatial relationships. Since hesitancy data at higher spatial resolution is often unavailable or hard to get, we incorporate an active learning approach with our VaxHesSTL framework to optimize the training set without compromising the prediction performance. We find that hesitancy data for only 18% of ZIP Codes selected by active learning allows us to forecast hesitancy for all the ZIP Codes in the Virginia.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Quantification of Off-Channel Inundated Habitat for Pacific Chinook Salmon ( Oncorhynchus tshawytscha ) along the Sacramento River, California, Using Remote Sensing Imagery

Off-channel areas are one of the most impacted aquatic habitats by humans globally, as extensive agricultural and urban development has limited them to roughly 10% of historical extent. This is also true for California’s Sacramento River Valley, where historically frequent widespread inundation has been reduced to a few off-channel water bodies along the mid-Sacramento River. This remaining shallow-water habitat provides crucial ecological benefits to multiple avian and fish species, but especially to floodplain-adapted species such as Chinook salmon (Oncorhynchus tshawytscha). Characterizing spatiotemporal off-channel dynamics, including inundation extent and residence time, is fundamental to better understanding the intrinsic value of such habitats and their potential to support recovery actions. Remote sensing techniques have been increasingly used to map surface water at regional and local scales, with improved resolutions. As such, this study maps off-channel inundation areas and describes their temporal dynamics by analyzing pixel-based time- series of multiple water indices, modified Normalized Difference Water Index (mNDWI) and the Automated Water Extraction Index (AWEI), generated from LandSat-8 and Sentinel-2 data between 2013–2021. Quantified off-channel area was similar with each water index and method used, but improved performance was associated with Sentinel-2 products and AWEI index to identify wetted areas under lower mainstem discharges. Results indicate an uneven distribution of off-channel habitat in the study area, with limited inundated areas in upstream reaches (<16% of total off-channel area for greater flows). In addition, much less habitat exists for flows under 400 m 3 /s, an important migration cue for endangered winter-run Chinook salmon, limiting juvenile access to areas with enhanced rearing conditions. Off-channel habitat residence times averaged between 7 and 16 days, primarily defined by the rate of receding flows, with rapid flow recession providing marginal off-channel habitat. This study shows reasonable performance of moderate resolution LandSat-8 and Sentinel-2 remote sensing imagery to characterize shallow-water inundated habitat in higher-order rivers, and as a method to inform restoration and native fish recovery efforts.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2018

Global-scale Evaluation of SMAP, SMOS and ASCAT Soil Moisture Products Using Triple Collocation

Global-scale surface soil moisture products are currently available from multiple remote sensing platforms. Footprint-scale assessments of these products are generally restricted to limited number of densely-instrumented validation sites. However, by taking active and passive soil moisture products together with a third independent soil moisture estimates via land surface modeling, triple collocation (TC) can be applied to estimate the correlation metric of satellite soil moisture products (versus an unknown ground truth) over a quasi-global domain. Here, an assessment of Soil Moisture Active Passive (SMAP), Soil Moisture Ocean Salinity (SMOS) and Advanced SCATterometer (ASCAT) surface soil moisture retrievals via TC is presented. Considering the potential violation of TC error assumptions, the impact of active-passive and satellite-model error cross correlations on the TC-derived inter-comparison results is examined at in situ sites using quadruple collocation analysis. In addition, confidence intervals for the TC-estimated correlation metric are constructed from moving-block bootstrap sampling designed to preserve the temporal persistence of the original (unevenly-sampled) soil moisture time-series. This study is the first to apply TC to obtain a robust global-scale cross-assessment of SMAP, SMOS and ASCAT soil moisture retrieval accuracy in terms of anomaly temporal correlation. Our results confirm the overall advantage of SMAP (with a global average anomaly correlation of 0.76) over SMOS (0.66) and ASCAT (0.63) that has been established in several recent regional, ground-based studies. SMAP is also the best-performing product over the majority of applicable land pixels (52%), although SMOS and ASCAT each shows advantage in distinct geographic regions.

global-scale↗
DOE OSTI2021

Characterizing patterns and variability of building electric load profiles in time and frequency domains

The rapid development of advanced metering infrastructure provides a new data source—building electrical load profiles with high temporal resolution. Electric load profile characterization can generate useful information to enhance building energy modeling and provide metrics to represent patterns and variability of load profiles. Such characterizations can be used to identify changes to building electricity demand due to operations or faulty equipment and controls. In this study, we proposed a two-path approach to analyze high temporal resolution building electrical load profiles: (1) time-domain analysis and (2) frequency-domain analysis. Furthermore, the commonly adopted time-domain analysis can extract and quantify the distribution of key parameters characterizing load shape such as peak-base load ratio and morning rise time, while a frequency-domain analysis can identify major periodic fluctuations and quantify load variability. We implemented and evaluated both paths using whole-year 15-minute interval smart meter data of 188 commercial office building in Northern California. The results from these two paths are consistent with each other and complementary to represent full dynamics of load profiles. The time- and frequency-domain analyses can be used to enhance building energy modeling by: (1) providing more realistic assumptions about building operation schedules, and (2) validating the simulated electric load profiles using the developed variability metrics against the real building load data.

24 POWER TRANSMISSION AND DISTRIBUTION↗