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At least 127 records · Page 7

Profiles of Radiative Fluxes at ENA

Profiles of radiative fluxes observed at the Atmospheric Radiation Measurement (ARM)’s Eastern North Atlantic (ENA) observatory along with the ancillary measurements are reported. The below-cloud drizzle properties were derived by combining the data from the ceilometer and Ka-band ARM Zenith Radar (KAZR) following the technique explained by Ghate et al. (2021 JAMC). The cloud and drizzle water path values were derived from the brightness temperatures reported by the microwave radiometer following the technique of Cadeddu et al. (2020 AMT). The cloud water path was then scaled to the KAZR-reported radar reflectivity to calculate profiles of liquid water content (LWC). Following the analysis from Ghate et al. (2023 JGR), cloud droplet effective radius was calculated using the number concentration value of 100 cm-3. The cloud properties, along with the thermodynamic properties, served as an input to the Rapid Radiative Transfer Model (RRTM) to yield profiles of radiative fluxes at a 1-minute temporal and 50-m vertical resolution. The fluxes were then averaged to hourly temporal resolution for analysis. In Mitra et al. (2025 JClim), the calculated profiles were compared against those derived from the satellite measurements (SYN1deg). Flux profiles from the SYN1deg and the thermodynamic and cloud properties used for deriving them are also reported here. Both all-sky and clear-sky radiative flux profiles were calculated. Due to the large data volume, the surface and top-of-atmosphere (TOA) radiative fluxes for the six-year period, and the hourly profiles of the radiative fluxes for January 2018, are submitted here. Full profiles of radiative fluxes calculated from the thermodynamic and cloud properties measured at the ENA site at 1-minute temporal and 50-m vertical resolution for a six-year period are available from the authors. Six files here correspond to the following data: 1_ENARAD_CERES_with_cld_amount_timeseries.nc: Time-series of hourly values of RRTM-simulated values of upwelling and downwelling fluxes at the surface and TOA, observed boundary-layer cloud fractions, and upwelling and downwelling fluxes from the SYN1deg from July 2015 to January 2022. 2_CERES_2018_at_CERES_levels.nc: SYN1deg radiative fluxes at six levels for the year 2018. 3_ENARad_2018_at_CERES_levels.nc: RRTM calculated fluxes at the SYN1deg vertical levels for the year 2018. 4_ENARad_rrtminputs_hourly_201801.nc: Thermodynamic and cloud properties used as an input to the RRTM for January 2018. 5_CERES_inputs_hourly_201801.nc: Thermodynamic and cloud properties utilized by SYN1deg algorithm for January 2018. 6_ENARAD_hourly_201801.nc: Full profiles of hourly averaged radiative fluxes from the RRTM simulations for January 2018.

Atmosphere↗

Dynamical Interpolation of Mesoscale Flows in the TOPEX/Poseidon Diamond Surrounding the U.S. Joint Global Ocean Flux Study Bermuda Atlantic Time-Series Study Site

An open boundary ocean model is configured in a domain bounded by the four TOPEX/Poseidon (T/P) ground tracks surrounding the US Joint Global Ocean Flux Study Bermuda Atlantic Time-Series Study (BATS) site. This implementation facilitates prescription of model boundary conditions directly from altimetric measurements (both TIP and ERS-2). The expected error characteristics for a domain of this size with periodically updated boundary conditions are established with idealized numerical experiments using simulated data. A hindcast simulation is then constructed using actual altimetric observations during the period October 1992 through September 1998. Quantitative evaluation of the simulation suggests significant skill. The correlation coefficient between predicted sea level anomaly and ERS observations in the model interior is 0.89; that for predicted versus observed dynamic height anomaly based on hydrography at the BATS site is 0.73. Comparison with the idealized experiments suggests that the main source of error in the hindcast is temporal undersampling of the boundary conditions. The hindcast simulation described herein provides a basis for retrospective analysis of BATS observations in the context of the mesoscale eddy field.

McGillicuddy, Dennis J., Jr.↗

Dynamical Interpolation of Mesoscale Flows in the TOPEX/ Poseidon Diamond Surrounding the U.S. Joint Global Ocean Flux Study Bermuda Atlantic Time-Series Study Site

An open boundary ocean model is configured in a domain bounded by the four TOPEX/Poseidon (TIP) ground tracks surrounding the U.S. Joint Global Ocean Flux Study Bermuda Atlantic Time-series Study (BATS) site. This implementation facilitates prescription of model boundary conditions directly from altimetric measurements (both TIP and ERS-2). The expected error characteristics for a domain of this size with periodically updated boundary conditions are established with idealized numerical experiments using simulated data. A hindcast simulation is then constructed using actual altimetric observations during the period October 1992 through September 1998. Quantitative evaluation of the simulation suggests significant skill. The correlation coefficient between predicted sea level anomaly and ERS observations in the model interior is 0.89; that for predicted versus observed dynamic height anomaly based on hydrography at the BATS site is 0.73. Comparison with the idealized experiments suggests that the main source of error in the hindcast is temporal undersampling of the boundary conditions. The hindcast simulation described herein provides a basis for retrospective analysis of BATS observations in the context of the mesoscale eddy field.

McGillicuddy, D. J.↗

Ice Surface Elevation Changes in East Antarctica from Satellite Altimetry

Estimates of the overall mass balance and seasonal and inter-annual variations in the surface mass balance are obtainable from time-series of ice surface elevations measured by satellite altimetry. Beginning in 2001, NASA's ICESat laser altimeter and lidar mission will significantly improve the range accuracy, the orbit accuracy, and the spatial coverage for measurement of ice sheet elevations (to 86 S) , as compared to previous radar altimeters designed for ocean measurements The radar altimeters on Seasat and Geosat provided ice sheet measurements to 72 S, and on ERS-1 and ERS-2 to 81 S. Although radar altimetry has significant limitations in coverage (due to loss of tracking) and accuracy over sloping surfaces, information on ice-sheet surface-elevation changes has been derived for parts of Antarctica. Recently, the accuracy of the ice measurements by Seasat (3 months of 1978) and Geosat (1985 to 1989) have been improved by new calculations of the satellite orbit heights and other altimeter corrections. Residual orbit errors and inter-satellite biases are evaluated by crossover analysis and by global adjustments to an ocean surface derived from altimeter data. The standard deviation of the orbit error is less than 9 cm, and the long-term trend in the error appears to be less than 1 cm/yr. Orbit errors can be further reduced by adjustment to the ocean surface, but false signals of several cm/yr may be also introduced by the adjustments. These false signals are caused mainly by residual errors in the altimeter corrections over the ocean, and secondary by real changes in the ocean surface elevation. Maps of ice sheet elevation changes north of 72 S are derived from Seasat-Geosat crossovers and from 4.5 years of Geosat crossovers. A notable ice thinning rate of about 50 cm/yr is found at elevations below 2200 meters between 70 and 72 S to the East of the Amery ice shelf, in both the Seasat-Geosat and Geosat-Geosat time intervals Above 2200 meters, to the ridge around 95 E, the thinning is about 10 to 20 cm/yr. For the Seasat/Geosat interval, a thickening is noted on the area East of the ridge between about 95 E and 115 E. Preliminary results from analysis of ERS-1 and ERS-2 radar altimeter data are also described.

Zwally, H. Jay↗

NASA Tech Briefs, November 2003

Topics covered include: Computer Program Recognizes Patterns in Time-Series Data; Program for User-Friendly Management of Input and Output Data Sets; Noncoherent Tracking of a Source of a Data-Modulated Signal; Software for Acquiring Image Data for PIV; Detecting Edges in Images by Use of Fuzzy Reasoning; A Timer for Synchronous Digital Systems; Prototype Parts of a Digital Beam-Forming Wide-Band Receiver; High-Voltage Droplet Dispenser; Network Extender for MIL-STD-1553 Bus; MMIC HEMT Power Amplifier for 140 to 170 GHz; Piezoelectric Diffraction-Based Optical Switches; Numerical Modeling of Nanoelectronic Devices; Organizing Diverse, Distributed Project Information; Eigensolver for a Sparse, Large Hermitian Matrix; Modified Polar-Format Software for Processing SAR Data; e-Stars Template Builder; Software for Acoustic Rendering; Functionally Graded Nanophase Beryllium/Carbon Composites; Thin Thermal-Insulation Blankets for Very High Temperatures; Prolonging Microgravity on Parabolic Airplane Flights; Device for Locking a Control Knob; Cable-Dispensing Cart; Foam Sensor Structures Would be Self-Deployable and Survive Hard Landings; Real-Gas Effects on Binary Mixing Layers; Earth-Space Link Attenuation Estimation via Ground Radar Kdp; Wedge Heat-Flux Indicators for Flash Thermography; Measuring Diffusion of Liquids by Common-Path Interferometry; Zero-Shear, Low-Disturbance Optical Delay Line; Whispering-Gallery Mode-Locked Lasers; Spatial Light Modulators as Optical Crossbar Switches; Update on EMD and Hilbert-Spectra Analysis of Time Series; Quad-Tree Visual-Calculus Analysis of Satellite Coverage; Dyakonov-Perel Effect on Spin Dephasing in n-Type GaAs; Update on Area Production in Mixing of Supercritical Fluids; and Quasi-Sun-Pointing of Spacecraft Using Radiation Pressure.

Source record↗

Advances in Measuring Antarctic Sea-Ice Thickness and Ice-Sheet Elevations with ICESat Laser Altimetry

NASA's Ice, Cloud and Land Elevation Satellite (ICESat) has been measuring elevations of the Antarctic ice sheet and sea-ice freeboard elevations with unprecedented accuracy. Since February 20,2003, data has been acquired during three periods of laser operation varying from 36 to 54 days, which is less than the continuous operation of 3 to 5 years planned for the mission. The primary purpose of ICESat is to measure time-series of ice-sheet elevation changes for determination of the present-day mass balance of the ice sheets, study of associations between observed ice changes and polar climate, and estimation of the present and future contributions of the ice sheets to global sea level rise. ICESat data will continue to be acquired for approximately 33 days periods at 3 to 6 month intervals with the second of ICESat's three lasers, and eventually with the third laser. The laser footprints are about 70 m on the surface and are spaced at 172 m along-track. The on-board GPS receiver enables radial orbit determinations to an accuracy better than 5 cm. The orbital altitude is around 600 km at an inclination of 94 degrees with a 8-day repeat pattern for the calibration and validation period, followed by a 91 -day repeat period for the rest of the mission. The expected range precision of single footprint measurements was 10 cm, but the actual range precision of the data has been shown to be much better at 2 to 3 cm. The star-tracking attitude-determination system should enable footprints to be located to 6 m horizontally when attitude calibrations are completed. With the present attitude calibration, the elevation accuracy over the ice sheets ranges from about 30 cm over the low-slope areas to about 80 cm over areas with slopes of 1 to 2 degrees, which is much better than radar altimetry. After the first period of data collection, the spacecraft attitude was controlled to point the laser beam to within 50 m of reference surface tracks over the ice sheets. Detection of ice elevation changes over select areas of the ice sheet is demonstrated with using both crossover analysis and precise-repeat track analysis. Sea ice freeboard-height distributions over the Antarctic sea pack are derived over distances of 50 km and converted into maps of average freeboard thickness and sea-ice thickness.

Zwally, H. Jay↗

Data & Code from Phoenix CPPP Phase 2 Analysis

This data and code package supports the analysis presented in “Beyond Surface Cooling: Comprehensive Field Assessment of Reflective Pavement Thermal Performance in Phoenix, Arizona” and provides fully reproducible workflows for evaluating the thermal performance of cool pavement treatments in a hot urban environment. The dataset integrates multi-modal field measurements collected across residential and nonresidential settings, including mobile air temperature traverses, stationary air temperature monitoring, residential mean radiant temperature (MRT) measurements, subsurface temperature profiles, and controlled testbed observations. The data package contains raw and processed datasets in comma-separated value (CSV) format, accompanying metadata files describing site characteristics and measurement protocols, and R scripts (.R files) used for data cleaning, time synchronization, spatial and temporal matching, quality control filtering, statistical comparison, and figure generation. All analyses were conducted using R (version ≥ 4.2.0) with commonly available packages (e.g., tidyverse, lubridate, data.table, ggplot2). No proprietary software is required to reproduce results. Field campaigns were designed to quantify the effects of high-reflectance pavement coatings on surface temperature, near-surface air temperature, subsurface heat propagation, and radiative heat exposure. Temporal alignment procedures include standardized timestamp conversion and nearest-neighbor matching of high-frequency sensor measurements to stop-based metadata within defined tolerance windows to ensure comparability across instruments. The workflows generate summary statistics, treatment–control contrasts, depth-dependent thermal gradients, and time-series visualizations used in the associated publication. By integrating mobile, stationary, radiative, and subsurface measurements within a unified and transparent processing framework, this package enables comprehensive evaluation of cool pavement performance across multiple thermal exposure pathways and supports reuse in future urban heat mitigation and climate resilience studies.

AIR TEMPERATURE↗

Workflow for Process Automation of Soil Gas Results from an Automated Soil Gas-Sampling System for Application in Carbon Storage Projects

Conference presentation at Geoconvention, Calgary, Alberta, Canada, May 12–14, 2025. The Energy & Environmental Research Center (EERC) developed an automated workflow for processing soil gas measurements collected from the automated soil gas-sampling systems deployed across the project site. Raw soil gas measurements are collected from each station every 4 hours and automatically uploaded to a cloud database. The workflow begins by writing code to download the data to a workstation automatically, then the data are published to an online dashboard that visualizes the measurements in time-series plots and a process-based decision-making framework. This automated workflow accelerates the time from data acquisition to decision-making. It supports carbon storage project operators by preparing and delivering a live, standardized dataset for quick analysis and source attribution to provide assurance of containment and overall permit compliance.

02 PETROLEUM↗

A real-time statistical time-series analyzer

Device extracts average frequency of human speech and produces second, third, and fourth moments of instantaneous frequency about this average. It operates on electrical time representation of input signal, performs statistical analysis on zero-crossing of almost any signal, and does not require specialized personnel to operate it.

Stewart, C. H.↗

An introduction to chaotic and random time series analysis

The origin of chaotic behavior and the relation of chaos to randomness are explained. Two mathematical results are described: (1) a representation theorem guarantees the existence of a specific time-domain model for chaos and addresses the relation between chaotic, random, and strictly deterministic processes; (2) a theorem assures that information on the behavior of a physical system in its complete state space can be extracted from time-series data on a single observable. Focus is placed on an important connection between the dynamical state space and an observable time series. These two results lead to a practical deconvolution technique combining standard random process modeling methods with new embedded techniques.

Scargle, Jeffrey D.↗

Wavelet analysis introduction and application to radar scattering from water waves

Double-parameter expansions, leading to an instantaneous multiscale analysis, are used to obtain time-frequency graphs from time-series data for interpretation of scatterometer response to sea surface geometry. This method is used to define, as well as possible, one-dimensional signal input (elevation and slope). However, some important fundamental parameters, such as the asymmetric development of short scales in crests and troughs, the long-wave amplitude modulation, the different zero-crossings, and so forth, are easily extracted from the wavelet images.

Chapron, B.↗

Time-series photometric spot modeling. 2: Fifteen years of photometry of the bright RS CVn binary HR 7275

We present a time-dependent spot modeling analysis of 15 consecutive years of V-band photometry of the long-period (P(sub orb) = 28.6 days) RS CVn binary HR 7275. This baseline in time is one of the longest, uninterrupted intervals a spotted star has been observed. The spot modeling analysis yields a total of 20 different spots throughout the time span of our observations. The distribution of the observed spot migration rates is consistent with solar-type differential rotation and suggests a lower limit of the differential-rotation coefficient of 0.022 +/-0.004. The observed, maximum lifetime of a single spot (or spot group) is 4.5 years, the minimum lifetime is approximately one year, but an average spot lives for 2.2 years. If we assume that the mechanical shear by differential rotation sets the upper limit to the spot lifetime, the observed maximum lifetime in turn sets an upper limit to the differential-rotation coefficient, namely 0.04 +/- 0.01. This would be differential rotation just 5 to 8 times less than the solar value and one of the strongest among active binaries. We found no conclusive evidence for the existence of a periodic phenomenon that could be attributed to a stellar magnetic cycle.

Strassmeier, K. G.↗

(abstract) Mount Rainier: New Remote Sensing Observations of a Decade Volcano

Mount Rainier was selected as a Decade Volcano by the International Association of Volcanology and Chemistry of the Earth's Interior. The purpose of this selection is to focus scientific and public attention on Mount Rainier during the current decade, the United Nations-designated International Decade of Natural Hazard Reduction. The Mount Rainier science plan calls for remote sensing surveys to monitor the volcano. To date, we have conducted airborne surveys with visible and near-infrared, thermal infrared, and interferometric radar instruments. Our preliminary analysis of some night-time time-series thermal infrared survey data sets of the summit suggests that, aside from seasonal variations in snow cover, there have been no qualitative changes in the size or pattern of the summit hot spots. Day-time airborne surveys were done to record the current surface appearance of the volcano and map hydrothermal alteration in the summit region. An interferometric radar survey yielded a high-resolution digital elevation model (DEM) which serves as a base for the registration of the other remote sensing data sets. More importantly, the DEM documents the current topography of glaciers and valleys. Planned biannual radar survey of mount rainier will produce a data set from which seasonal changes in glacier and valley topography can be characterized. Such characterization is essential if we are to recognize geothermally induced changes in snow and ice cover.

infrared radar interferometry glaciers seasonal va↗

Development of a Rayleigh Scattering Diagnostic for Time-Resolved Gas Flow Velocity, Temperature, and Density Measurements in Aerodynamic Test Facilities

A molecular Rayleigh scattering technique is developed to measure time-resolved gas velocity, temperature, and density in unseeded turbulent flows at sampling rates up to 32 kHz. A high power continuous-wave laser beam is focused at a point in an air flow field and Rayleigh scattered light is collected and fiber-optically transmitted to the spectral analysis and detection equipment. The spectrum of the light, which contains information about the temperature and velocity of the flow, is analyzed using a Fabry-Perot interferometer. Photomultiplier tubes operated in the photon counting mode allow high frequency sampling of the circular interference pattern to provide time-resolved flow property measurements. An acoustically driven nozzle flow is studied to validate velocity fluctuation measurements, and an asymmetric oscillating counterflow with unequal enthalpies is studied to validate the measurement of temperature fluctuations. Velocity fluctuations are compared with constant temperature anemometry measurements and temperature fluctuations are compared with constant current anemometry measurements at the same locations. Time-series and power spectra of the temperature and velocity measurements are presented. A numerical simulation of the light scattering and detection process was developed and compared with experimental data for future use as an experiment design tool.

Mielke, Amy F.↗

Remote-Sensing Time Series Analysis, a Vegetation Monitoring Tool

The Time Series Product Tool (TSPT) is software, developed in MATLAB , which creates and displays high signal-to- noise Vegetation Indices imagery and other higher-level products derived from remotely sensed data. This tool enables automated, rapid, large-scale regional surveillance of crops, forests, and other vegetation. TSPT temporally processes high-revisit-rate satellite imagery produced by the Moderate Resolution Imaging Spectroradiometer (MODIS) and by other remote-sensing systems. Although MODIS imagery is acquired daily, cloudiness and other sources of noise can greatly reduce the effective temporal resolution. To improve cloud statistics, the TSPT combines MODIS data from multiple satellites (Aqua and Terra). The TSPT produces MODIS products as single time-frame and multitemporal change images, as time-series plots at a selected location, or as temporally processed image videos. Using the TSPT program, MODIS metadata is used to remove and/or correct bad and suspect data. Bad pixel removal, multiple satellite data fusion, and temporal processing techniques create high-quality plots and animated image video sequences that depict changes in vegetation greenness. This tool provides several temporal processing options not found in other comparable imaging software tools. Because the framework to generate and use other algorithms is established, small modifications to this tool will enable the use of a large range of remotely sensed data types. An effective remote-sensing crop monitoring system must be able to detect subtle changes in plant health in the earliest stages, before the effects of a disease outbreak or other adverse environmental conditions can become widespread and devastating. The integration of the time series analysis tool with ground-based information, soil types, crop types, meteorological data, and crop growth models in a Geographic Information System, could provide the foundation for a large-area crop-surveillance system that could identify a variety of plant phenomena and improve monitoring capabilities.

McKellip, Rodney↗

Update on EMD and Hilbert-Spectra Analysis of Time Series

This method is especially well suited for analyzing time-series data that represent nonstationary and nonlinear physical phenomena. The method is based principally on the concept of empirical mode decomposition (EMD), according to which any complicated signal (as represented by digital samples) can be decomposed into a finite number of functions, called "intrinsic mode functions" (IMFs), that admit well-behaved Hilbert transforms. The local energies and the instantaneous frequencies derived from the IMFs through Hilbert transforms can be used to construct an energy-frequency-time distribution, denoted a Hilbert spectrum.

Huang, Norden E.↗

A Dynamic Hierarchical Attention Framework for Multimodal Malware Detection

The increasing use of Android in the worldwide mobile ecosystem has come along with a significant increase in advanced malware, highlighting the critical necessity for efficient, scalable, and adaptable detection systems. Despite recent advancements in machine learning improving malware detection, the majority of current solutions are limited to one, two, or three data modalities, hence neglecting the comprehensive behavioral spectrum of contemporary multi-vector threats. This thesis presents the first comprehensive multimodal framework for Android malware detection, which combines textual, time-series (temporal), graph-based (structural), and visual information using an innovative hierarchical attention mechanism and Dynamic Fusion Controller (DFC). Our methodology consistently classifies and processes modalities as either sequential or structural, facilitating content-adaptive weighting and resilient cross-modal representation learning. We advance the implementation of cutting-edge time series techniques, such as MiniRocket, for malware detection, hence creating new opportunities for temporal analysis in cybersecurity. Comprehensive experimental assessment shows that our framework performs exceptionally well, with 99.46% classification accuracy and 97.15% detection accuracy, significantly outperforming existing approaches through effective multimodal integration and hierarchical attention mechanisms.

Nazmin, Tamanna↗

Workflow for Process Automation of Soil Gas Results from an Automated Soil Gas-Sampling System for Application in Carbon Storage Projects

Extended abstract for Geoconvention, Calgary, Alberta, Canada, May 12–14, 2025. The Energy & Environmental Research Center (EERC) developed an automated workflow for processing soil gas measurements collected from the automated soil gas-sampling systems deployed across the project site. Raw soil gas measurements are collected from each station every 4 hours and automatically uploaded to a cloud database. The workflow begins by writing code to download the data to a workstation automatically, then the data are published to an online dashboard that visualizes the measurements in time-series plots and a process-based decision-making framework. This automated workflow accelerates the time from data acquisition to decision-making. It supports carbon storage project operators by preparing and delivering a live, standardized dataset for quick analysis and source attribution to provide assurance of containment and overall permit compliance.

02 PETROLEUM↗