SEARCH · Search NASA

Results for “TEMPORAL RESOLUTION”

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.

SourceResearch connectionFrom yearThrough year

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

At least 253 records · Page 14

All sources NASA NTRS DOE OSTI

DOE OSTI2024

Gridded Sub-daily Climate Forcings for North America Based on Daymet and GSWP3 (Daymet-GSWP3)

To support high spatial and temporal resolution land surface modeling, this dataset provides 3-hourly time step historic weather forcing at 1-km spatial resolution for the entire North America. The latest Daymet V4 data provides gridded historic daily weather observations at 1-km spatial resolution from 1980 to 2014. Using sub-daily temporal information from the Global Soil Wetness Project Phase 3 (GSWP3), Daymet was further temporally downscaled to 3-hourly time steps and provided in the format required for land surface model simulations. The process of temporal downscaling preserves the relative magnitude in each sub-daily time step from GSWP3 while maintaining the total and average values from Daymet for each day. This results in a blended 1980-2014 Daymet-GSWP3 dataset. Available variables include surface air temperature, precipitation, specific humidity, shortwave and longwave radiation, wind speed, and pressure. These data can be used as a high-resolution meteorological forcing dataset to support high-resolution land surface modeling where accurate meteorological forcing datasets built from historic observations and/or reanalysis datasets are desirable.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Gridded Sub-daily Climate Forcings for North America Based on Daymet and GSWP3 (Daymet-GSWP3)

54 ENVIRONMENTAL SCIENCES↗

NASA NTRSDate not supplied

Assessment of High Resolution Commercial Satellite Geolocation Accuracy

Commercial companies such as Maxar, PlanetScope, and BlackSky have launched many satellites with revisit times ranging from two hours to one day and have built large archives of high resolution (1-3 m) Earth observing data. The high temporal resolution and global coverage of these satellites makes commercial satellite images ideal for scientists studying rapidly changing processes such as flooding and fires. A key step in assessing changes in these images is co-registration of various images to each other. High geolocation accuracy (at most 0.5 pixels of offset) allows for easy co-registration of images across different times and sensors. Here, we assess the latest PlanetScope imagery and evaluate it for geolocation accuracy. For our assessment, we compare the target image to a reference image with known geolocation accuracy (WorldView imagery) and determine the offset between these images by shifting them to maximize their Pearson Cross-Correlation (PCC) value. Offsets required to maximize the PCC give the geolocation accuracy of the target image relative to the reference image. Previously, our global assessment of Planet data revealed large variability in geolocation accuracy from one continent to another. The measured root mean squared errors (RMSEs) range from 5.4 m in North America to 14.9 m in Africa. We have updated this previous assessment to include both their newest SuperDove series as well as a more robust assessment of the temporal stability of PlanetScope's geolocation accuracy.

Alana G. Semple↗

DOE OSTI2026

A call to standardize metrics for monitoring baleen whales near marine construction activities

Effective monitoring is necessary to protect marine mammal species during the construction of offshore infrastructure. The tools for detecting or monitoring marine mammals span traditional (e.g., visual observers, optical cameras), to newer (e.g., passive acoustic monitoring, infrared cameras, tags), and emerging (e.g., satellite imagery, environmental DNA, dimethyl sulfide concentration) technologies. Some are better suited for use during offshore development; however, peer-reviewed literature does not typically evaluate and report on the performance of these various technologies. We define a minimum set of metrics related to efficacy (i.e., confusion matrix, precision and recall, probability of missed mitigation), detection range (i.e., maximum and reliable detection range, spatial resolution), and data delivery (i.e., detection latency, system reliability, temporal resolution) that we recommend are needed to assess the utility of monitoring technologies for this purpose. Following a literature review of relevant studies, we highlight which publications reported these metrics and used multiple technologies to compare relative performance. We also emphasize the benefits of multi-modal approaches and recommend performance assessments through modeling or large-scale collaborative field testing. These metrics will standardize data collection, reporting, and analysis; promote consistent and comparable results; and foster collaboration among developers, regulatory agencies, and scientists. This may lead to the co-development of technology that achieves multiple goals, has greater application, and can answer research questions while collecting data to fulfill permitting requirements. These metrics may also inform decisions on what systems regulatory agencies might consider using and reduce monitoring costs, which is critical to support the marine sector's rapid growth alongside marine mammal conservation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Meteorological and Hydrological Drought Analysis Datasets for Livneh, ClimRR, and TGW

The current dataset contains data upload links to the following SPI & SRI drought analysis data over CONUS: Climate Forcing and Simulation Scenario: Livneh (https://www.nature.com/articles/sdata201542): Historical ClimRR (https://climrr.anl.gov/climrrdata): Historical, Mid-Century, End-Century TGW (https://tgw-data.msdlive.org/): Historical, Mid-Century, End-Century Analysis Period: Vary by Climate Forcing Drought Type: Meteorological (Precipitation) and Hydrological (Runoff) Drought (3-Month SRI) Output Format: NetCDF and CSV Spatial Resolution: 1/16th Degree for NetCDF and HUC4 for CSV Temporal Resolution: Monthly

Tidwell, Vincent C [Pacific Northwest National Lab↗

NASA NTRS1982

Advances in solar radio astronomy

The status of the observations and interpretations of the sun's radio emission covering the entire radio spectrum from millimeter wavelengths to hectometer and kilometer wavelengths is reviewed. Emphasis is given to the progress made in solar radio physics as a result of recent advances in plasma and radiation theory. It is noted that the capability now exists of observing the sun with a spatial resolution of approximately a second of arc and a temporal resolution of about a millisecond at centimeter wavelengths and of obtaining fast multifrequency two-dimensional pictures of the sun at meter and decameter wavelengths. A summary is given of the properties of nonflaring active regions at millimeter, centimeter, and meter-decameter wavelengths. The properties of centimeter wave bursts are discussed in connection with the high spatial resolution observations. The observations of the preflare build-up of an active region are reviewed. High spatial resolution observations (a few seconds of arc to approximately 1 arcsec) are discussed, with particular attention given to the one- and two-dimensional maps of centimeter-wavelength burst sources.

Kundu, M. R.↗

NASA NTRS2012

Tropical Rainfall Measuring Mission (TRMM) Precipitation Data and Services for Research and Applications

Precipitation is a critical component of the Earth's hydrological cycle. Launched on 27 November 1997, TRMM is a joint U.S.-Japan satellite mission to provide the first detailed and comprehensive data set of the four-dimensional distribution of rainfall and latent heating over vastly under-sampled tropical and subtropical oceans and continents (40 S - 40 N). Over the past 14 years, TRMM has been a major data source for meteorological, hydrological and other research and application activities around the world. The purpose of this short article is to inform that the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) provides TRMM archive and near-real-time precipitation data sets and services for research and applications. TRMM data consist of orbital data from TRMM instruments at the sensor s resolution, gridded data at a range of spatial and temporal resolutions, subsets, ground-based instrument data, and ancillary data. Data analysis, display, and delivery are facilitated by the following services: (1) Mirador (data search and access); (2) TOVAS (TRMM Online Visualization and Analysis System); (3) OPeNDAP (Open-source Project for a Network Data Access Protocol); (4) GrADS Data Server (GDS); and (5) Open Geospatial Consortium (OGC) Web Map Service (WMS) for the GIS community. Precipitation data application services are available to support a wide variety of applications around the world. Future plans include enhanced and new services to address data related issues from the user community. Meanwhile, the GES DISC is preparing for the Global Precipitation Measurement (GPM) mission which is scheduled for launch in 2014.

Liu, Zhong↗

NASA NTRS2018

TPSAS-NF1676L-30290-DND

The Summer 2017 Ozone Water Land Environmental Transition Study (OWLETS) mission set out to compare the differences in ozone concentrations between inland measurements of air quality, specifically at Langley Research Center (LaRC), and measurements taken over water, specifically on the Chesapeake Bay Bridge Tunnel (CBBT), as well as the vertical profiles above each location. Current weather models often predict a gradient in ozone concentration between land and ocean and this campaign attempted to capture this difference using hand-held Personal Ozone Monitors (POMs) in correspondence to ozonesondes and LIDAR measurements. The Tropospheric Emissions: Monitoring of Pollution (TEMPO) is the first geostationary satellite that will take hourly measurements to monitor air pollutants across North America using solar backscatter. The small footprint allows for higher spatial resolution readings of many parameters including O3, NO2 , and aerosol. TEMPO’s higher resolution readings would benefit from validation techniques on the ground. Validation methods usually include comparison to air quality monitoring stations, but they could also incorporate other forms of validation such as comparison to small sensors. In cooperation with TEMPO, OWLETS aims to provide the user community high resolution temporal and spatial, both horizontal and vertical, variability of O3 simultaneously over the land and water during various air quality events to improve forecast models and air quality satellite retrievals. Together, these missions will improve spatial resolution and capture temporal variability of air quality over North America.

Emily Gargulinski↗

NASA NTRSDate not supplied

Geometric Assessment of PlanetScope Imagery

Commercial companies such as Maxar, Planet Labs, and BlackSky have built large archives of high resolution (1-3 m) Earth observing data. The high temporal resolution and global coverage of these satellites makes commercial satellite images ideal for scientists studying rapidly changing processes such as flooding and fires. The high spatial resolution allows scientists to push studies to a fine scale such as monitoring agricultural growth experiments or detecting vehicles for traffic management. Scientists using these data need to know geolocation accuracy, band-to-band registration (BBR), and pixel footprint size to best determine appropriate applications as well as what extra steps they will need to take to use the data. Here, we find those key geometric properties for images from Planet Labs’ SuperDove constellation. Geolocation accuracy is assessed relative to WorldView images at globally distributed cities, band-to-band registration (BBR) is examined for every image we acquired (200+ images), and pixel footprint sizes are calculated from edge responses of the images over Cal/Val sites in China, India, or USA both near launch time and 1+ years after launch. We find that SuperDove geolocation is highly self-consistent with average global offsets among SuperDove images of 3.80 m (1.27 pixels). Despite this self-consistency, relative geolocation accuracy (with WorldView images as reference) varies by location from 3.20 m – 28.09 m mean offset. SuperDove BBR is sub-pixel and varies by band, with a mean radial offset relative to red band varying from 0.39 - 1.13 m. SuperDove image footprint size improves after 1+ years in orbit, with an average footprint size of 3.41 pixels (10.24 m) soon after launch and 3.23 pixels (9.7 m) 1+ years after launch. The BBR and self-consistency offsets are relatively small, given the large footprint sizes. A similarly extensive investigation is in progress for Planet Labs’ Dove-R series.

Alana G. Semple↗

NASA NTRS2017

Joint Assimilation of SMOS Brightness Temperature and GRACE Terrestrial Water Storage Observations for Improved Soil Moisture Estimation

Observations from recent soil moisture missions (e.g. SMOS) have been used in innovative data assimilation studies to provide global high spatial (i.e. 40 km) and temporal resolution (i.e. 3-days) soil moisture profile estimates from microwave brightness temperature observations. In contrast with microwave-based satellite missions that are only sensitive to near-surface soil moisture (0 - 5 cm), the Gravity Recovery and Climate Experiment (GRACE) mission provides accurate measurements of the entire vertically integrated terrestrial water storage column but, it is characterized by low spatial (i.e. 150,000 km2) and temporal (i.e. monthly) resolutions. Data assimilation studies have shown that GRACE-TWS primarily affects (in absolute terms) deeper moisture storages (i.e., groundwater). This work hypothesizes that unprecedented soil water profile accuracy can be obtained through the joint assimilation of GRACE terrestrial water storage and SMOS brightness temperature observations. A particular challenge of the joint assimilation is the use of the two different types of measurements that are relevant for hydrologic processes representing different temporal and spatial scales. The performance of the joint assimilation strongly depends on the chosen assimilation methods, measurement and model error spatial structures. The optimization of the assimilation technique constitutes a fundamental step toward a multi-variate multi-resolution integrative assimilation system aiming to improve our understanding of the global terrestrial water cycle.

Soil Moisture↗

NASA NTRS1999

Local Data Integration in East Central Florida

The Applied Meteorology Unit has configured a Local Data Integration System (LDIS) for east central Florida which assimilates in-situ and remotely-sensed observational data into a series of high-resolution gridded analyses. The ultimate goal for running LDIS is to generate products that may enhance weather nowcasts and short-range (less than 6 h) forecasts issued in support of the 45th Weather Squadron (45 WS), Spaceflight Meteorology Group (SMG), and the Melbourne National Weather Service (NWS MLB) operational requirements. LDIS has the potential to provide added value for nowcasts and short-ten-n forecasts for two reasons. First, it incorporates all data operationally available in east central Florida. Second, it is run at finer spatial and temporal resolutions than current national-scale operational models such as the Rapid Update Cycle and Eta models. LDIS combines all available data to produce grid analyses of primary variables (wind, temperature, etc.) at specified temporal and spatial resolutions. These analyses of primary variables can be used to compute diagnostic quantities such as vorticity and divergence. This paper demonstrates the utility of LDIS over east central Florida for a warm season case study. The evolution of a significant thunderstorm outflow boundary is depicted through horizontal and vertical cross section plots of wind speed, divergence, and circulation. In combination with a suitable visualization too], LDIS may provide users with a more complete and comprehensive understanding of evolving mesoscale weather than could be developed by individually examining the disparate data sets over the same area and time.

Case, Jonathan L.↗

DOE OSTI2025

Hayward Fault Creep From Coda Wave Interferometry

Understanding creep is essential for assessing seismic hazards along the creeping Hayward Fault, which threatens the San Francisco area. Current 1-D monitoring methods, like creepmeters and theodolites, provide limited measurements with low spatial resolution. InSAR offers higher 2-D spatial sampling but lower temporal resolution. We introduce a novel method using coda wave interferometry (CWI) to monitor creep in 2-D with high resolution. By calculating changes in ambient seismic noise travel times, we relate these measurements to creep offsets, bridging the gap between existing methods. Applied to seismic data from 2021 around the Hayward Fault, our CWI-derived offsets aligned with creepmeter measurements, revealing continuous and episodic creep. A 2-D regionalization identified a spatial boundary between these regimes, corroborating previous findings. This approach could enhance seismic monitoring and improve understanding of fault mechanics and earthquake risks.

Luckie, Thomas William [Sandia National Laboratori↗

NASA NTRS2006

Implications of RHESSI Observations for Solar Flare Models and Energetics

Observations of solar flares in X-rays and gamma-rays provide the most direct information about the hottest plasma and energetic electrons and ions accelerated in flares. The Ramaty High Energy Solar Spectroscopic Imager (RHESSI) has observed over 18000 solar flares in X-rays and gamma-rays since its launch in February of 2002. RHESSI observes the full Sun at photon energies from as low as 3 keV to as high as 17 MeV with a spectral resolution on the order of 1 keV. It also provides images in arbitrary bands within this energy range with spatial resolution as good as 3 seconds of arc. Full images are typically produced every 4 seconds, although higher time resolution is possible. This unprecedented combination of spatial, spectral, and temporal resolution, spectral range and flexibility has led to fundamental advances in our understanding of flares. I will show RHESSI and coordinated observations that confirm coronal magnetic reconnection models for eruptive flares and coronal mass ejections, but also present new puzzles for these models. I will demonstrate how the analysis of RHESSI spectra has led to a better determination of the energy flux and total energy in accelerated electrons, and of the energy in the hot, thermal flare plasma. I will discuss how these energies compare with each other and with the energy contained in other flare-related phenomena such as interplanetary particles and coronal mass ejections.

Holman, Gordon D.↗

NASA NTRS2018

Improving Soil Moisture Estimation through the Joint Assimilation of SMOS and GRACE Satellite Observations

Observations from recent soil moisture dedicated missions (e.g. SMOS or SMAP) have been used in innovative data assimilation studies to provide global high spatial (i.e., approximately10-40 km) and temporal resolution (i.e., daily) soil moisture profile estimates from microwave brightness temperature observations. These missions are only sensitive to near-surface soil moisture 0-5 cm). In contrast, the Gravity Recovery and Climate Experiment (GRACE) mission provides accurate measurements of the entire vertically integrated terrestrial water storage (TWS) column but, it is characterized by low spatial (i.e., 150,000 km2) and temporal (i.e., monthly) resolutions. Data assimilation studies have shown that GRACE-TWS primarily affects (in absolute terms) deeper moisture storages (i.e., groundwater). In this presentation I will review benefits and drawbacks associated to the assimilation of both types of observations. In particular, I will illustrate the benefits and drawbacks of their joint assimilation for the purpose of improving the entire profile of soil moisture (i.e., surface and deeper water storages).

Girotto, Manuela↗

NASA NTRS1997

Measured Spacecraft Dynamic Effects on Atmospheric Science Instruments

On September 1991, NASA launched the Upper Atmosphere Research Satellite. In addition to its atmospheric science mission, spacecraft dynamic effects on science measurements were analyzed. The investigation included two in-flight experiments to determine how each on-board instrument, subsystem and environmental disturbance contributed to the spacecraft dynamic response and how these disturbances affected science measurements. Three case studies are presented which show the impact of spacecraft dynamic response on science measurements. In the first case, correlation of independent atmospheric meridional wind measurements taken by two instruments with the spacecraft dynamic response demonstrated that excessive vibration (exceeding instrument pointing requirements) resulted in wind measurement disagreement. In the second case, solar array disturbances produced a spacecraft response signature on radiometer measurements. The signature explicitly demonstrated that if an instrument has sufficient spatial and temporal resolution, spacecraft dynamic response could impact measurements. In the final case, correlation of an instrument's fine sun sensor data and CO2 measurements demonstrated the effect of temporal and spatial sampling resolution and active pointing control on science measurements. The sun sensor had a frequency modulated characteristic due to spacecraft vibration and the periodic scanning of another instrument which was not present on the CO2 measurements.

Woodard, Stanley E.↗

DOE OSTI2026

Rolling Root Mean Square Based Multimodal Anomaly Detection for Real Time Monitoring of Smart Grid

Reliable real-time monitoring is valuable for maintaining the operational integrity of modern electrical smart grids. Deployment of heterogeneous sensing technologies in substations has enabled high-resolution, multichannel waveform monitoring, but also introduces challenges for anomaly detection due to noise, baseline drift, and modality-dependent signal characteristics. In this work, we present a computationally efficient unsupervised method for multimodal event detection based on Rolling Root Mean Square based Event Detection (RRMSED). The method is developed using in-house, field deployed sensors collecting data at a utility substation. The sensing system comprises voltage and current sensors, triaxial accelerometers, and magnetometers, collectively capturing electrical, vibrational, and magnetic waveform measurements at high temporal resolution. RRMSED operates by extracting rolling RMS energy features and their first-order temporal differences from consecutive waveform segments for each channel and then applying channel-specific statistical thresholds learned from historical data. A persistence-based exceedance logic is employed to robustly identify transient events while suppressing impulsive noise, and to provide precise temporal localization with high resolution. The framework is designed for continuous server-side operation and can be deployed in real time without requiring complex models. Experiments on simulated waveform data with known ground truth demonstrate low false positive (FP) and false negative (FN) rates. Application to real substation data shows RRMSED to identify events that are not captured by conventional monitoring indicators including fast transient detection algorithm currently deployed in the system. These results indicate that rolling RMS based features provide an effective and practical basis for real-time multimodal event detection in smart-grid substations.

Mukherjee, Subrata [ORNL] (ORCID:0000000309930338)↗

NASA NTRS2016

Monitoring Interannual Variation in Global Crop Yield Using Long-Term AVHRR and MODIS Observations

Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) data have been extensively applied for crop yield prediction because of their daily temporal resolution and a global coverage. This study investigated global crop yield using daily two band Enhanced Vegetation Index (EVI2) derived from AVHRR (1981-1999) and MODIS (2000-2013) observations at a spatial resolution of 0.05deg (approx.5 km). Specifically, EVI2 temporal trajectory of crop growth was simulated using a hybrid piecewise logistic model (HPLM) for individual pixels, which was used to detect crop phenological metrics. The derived crop phenology was then applied to calculate crop greenness defined as EVI2 amplitude and EVI2 integration during annual crop growing seasons, which was further aggregated for croplands in each country, respectively. The interannual variations in EVI2 amplitude and EVI2 integration were combined to correlate to the variation in cereal yield from 1982-2012 for individual countries using a stepwise regression model, respectively. The results show that the confidence level of the established regression models was higher than 90% (P value < 0.1) in most countries in the northern hemisphere although it was relatively poor in the southern hemisphere (mainly in Africa). The error in the yield predication was relatively smaller in America, Europe and East Asia than that in Africa. In the 10 countries with largest cereal production across the world, the prediction error was less than 9% during past three decades. This suggests that crop phenology-controlled greenness from coarse resolution satellite data has the capability of predicting national crop yield across the world, which could provide timely and reliable crop information for global agricultural trade and policymakers.

Crop phenology↗

NASA NTRS1986

The AXAF CCD imaging spectrometer

The AXAF CCD Imaging Spectrometer (ACIS) is currently being defined as a possible focal plane instrument to be flown on the Advanced X-ray Astrophysics Facility (AXAF). The imaging spectrometer consists of an array of charge coupled devices (CCD's) to be placed at the focus of the AXAF mirrors. The array will provide high angular resolution (0.5 arc seconds), moderate spectral resolution (150 eV) over the energy range 0.1 to 10 keV, temporal resolution down to 60 microseconds, and single photon quantum detection efficiencies of up to 90 percent. X-ray sensitivity for a point source exceeds 10 to the -15th ergs/sq cm sec for a 10 to the 5th sec exposure. When used in conjunction with the objective gratings, the array will yield wavelength resolution of up to 200.

Garmire, G. P.↗