Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “time resolution data”

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 289 records · Page 16

Contributions of GRACE to Climate Monitoring

The NASA/German Gravity Recovery and Climate Experiment (GRACE) was launched in March 2002. Rather than looking downward, GRACE continuously monitors the locations of and precise distance between twin satellites which orbit in tandem about 200 km apart. Variations in mass near Earth's surface cause heterogeneities in its gravity field, which in turn affect the orbits of satellites. Thus scientists can use GRACE data to map Earth's gravity field with enough accuracy to discern month to month changes caused by ocean circulation and redistribution of water stored on and in the land. Other gravitational influences, such as atmospheric circulation, post-glacial rebound, and solid earth movements are either independently determined and removed or are negligible on a monthly to sub-decadal timescale. Despite its coarse spatial (>150,000 sq km at mid-latitudes) and temporal (approx monthly) resolutions, GRACE has enabled significant advancements in the oceanic, hydrologic, and cryospheric science, and has great potential for climate monitoring, because it is the only global observing system able to measure ocean bottom pressures, total terrestrial water storage, and ice mass changes. The best known GRACE results are estimates of Greenland and Antarctic ice sheet loss rates. Previously, scientists had estimated ice mass losses using ground and satellite based altimetry and surface mass balance estimates based on snowfall accumulation and glacier discharge. While such measurements are still very useful for their spatial detail, they are imperfectly correlated with large-scale ice mass changes, due to snow and ice compaction and incomplete spatial coverage. GRACE enables scientists to generate monthly time series of Greenland and Antarctic ice mass, which have confirmed the shrinking of the polar ice sheets, one of the most obvious and indisputable manifestations of climate change. Further, GRACE has located and quantified hot spots of ice loss in southeastern Greenland and western Antarctica. For 2002 to present, the rate of ice mass loss has been 200 to 300 GT/yr in Greenland and 70 to 210 GT/yr in Antarctica, and some scientists are suggesting that the rates are accelerating. Similarly, GRACE has been used to monitor mass changes in alpine glaciers. Tamisiea et al. first characterized glacier melt along the southern coast of Alaska, more recently estimated to be occurring at a rate of 84 GT/yr. Chen et al. estimated that Patagonian glaciers are melting at a rate of 28 GT/yr, and estimated that the high mountains of central Asia lose ice at a rate of 47 GT/yr. Tapley et al. and Wahr et al. presented the first GRACE based estimates of changes in column-integrated terrestrial water storage (TWS; the sum of ground-water, soil moisture, surface waters, snow, ice, and water stored in vegetation) at continental scales. Since then, dozens of studies have shown that GRACE based estimates of regional to continental scale TWS variations agree with independent information, and some innovative uses of GRACE data have been developed. Rodell et al. (2004) and Swenson and Wahr (2006) demonstrated that by combining GRACE derived terrestrial water storage changes with observations of precipitation and runoff in a river basin scale water budget, it was possible to produce new estimates of evapotranspiration and atmospheric moisture convergence, essential climate variables that are difficult to estimate accurately. Similarly, GRACE has been used to constrain estimates of global river discharge and the contribution of changes in TWS to sea level rise. Crowley et al. observed a negative correlation between interannual TWS anomalies in the Amazon and the Congo River basin. Yeh et al. and Rodell et al. estimated regionally averaged groundwater storage variations based on GRACE and auxiliary observations. Rodell et al. and Tiwari et al. applied that method to quantify massive groundwater depletion in northern India caused by over reliance on aquifers for irration, and Famiglietti et al. found a similar situation in California's Central Valley. Zaitchik et al. and Lo et al. described approaches to use GRACE to constrain hydrological models, enabling integration of GRACE data with other observations and achieving much higher spatial and temporal resolutions than GRACE alone. Such approaches are now supporting applications including drought and water resources monitoring. Oceanography has likewise benefitted from the independent nature of GRACE observations. One application is measurement of the mass component of sea level rise, which complements radar altimetry and in situ measurements. GRACE also measures ocean bottom pressures (OBP), which help to refine understanding and modeling of ocean circulation and the ocean's fresh water budget, among other things. For example, Hayakawa et al. showed that GRACE observes OBP patterns absent from the background models of oceanic variability. Morison et al. used GRACE to describe important decadal scale shifts in circulation and an ongoing trend of freshening of the western Arctic, important indicators of climate variability. The research of Song and Zlotnicki and Chambers and Willis on GRACE-derived ocean bottom pressures in the sub-polar gyre led to the discovery of an ENSO teleconnection and a long-term change in OBP in the North Pacific sub-polar gyre that was not predicted by an ocean model. Further, Chambers and Willis were able to identify an internal redistribution of mass between Atlantic and Pacific Oceans lasting at least six years, which was not predicted by ocean models and was the first direct evidence of sustained mass transport from one ocean basin to another on periods longer than a year. Boening et al. observed a record increase in OBP over part of the southeastern Pacific in late 2009 and early 2010, primarily caused by wind stress curl associated with a strong and persistent anticyclone and likely related to the concurrent Central Pacific El Nino. GRACE has far surpassed its 5-year design lifetime, but it will likely succumb to the aging of batteries and instrument systems sometime in the next few years. NASA has begun initial development of a follow-on to GRACE with very similar design, which could launch as soon as 2016 and would provide continuity in the data record while improving resolution slightly. Higher resolution time variable gravity missions are also on the drawing board .

Rodell, Matthew↗

RUSHMAPS: Real-Time Uploadable Spherical Harmonic Moment Analysis for Particle Spectrometers

RUSHMAPS is a new onboard data reduction scheme that gives real-time access to key science parameters (e.g. moments) of a class of heliophysics science and/or solar system exploration investigation that includes plasma particle spectrometers (PPS), but requires moments reporting (density, bulk-velocity, temperature, pressure, etc.) of higher-level quality, and tolerates a lowpass (variable quality) spectral representation of the corresponding particle velocity distributions, such that telemetry use is minimized. The proposed methodology trades access to the full-resolution velocity distribution data, saving on telemetry, for real-time access to both the moments and an adjustable-quality (increasing quality increases volume) spectral representation of distribution functions. Traditional onboard data storage and downlink bandwidth constraints severely limit PPS system functionality and drive cost, which, as a consequence, drives a limited data collection and lower angular energy and time resolution. This prototypical system exploit, using high-performance processing technology at GSFC (Goddard Space Flight Center), uses a SpaceCube and/or Maestro-type platform for processing. These processing platforms are currently being used on the International Space Station as a technology demonstration, and work is currently ongoing in a new onboard computation system for the Earth Science missions, but they have never been implemented in heliospheric science or solar system exploration missions. Preliminary analysis confirms that the targeted processor platforms possess the processing resources required for realtime application of these algorithms to the spectrometer data. SpaceCube platforms demonstrate that the target architecture possesses the sort of compact, low-mass/power, radiation-tolerant characteristics needed for flight. These high-performing hybrid systems embed unprecedented amounts of onboard processing power in the CPU (central processing unit), FPGAs (field programmable gate arrays), and DSP (digital signal processing) elements. The fundamental computational algorithm de constructs 3D velocity distributions in terms of spherical harmonic spectral coefficients (which are analogous to a Fourier sine-cosine decomposition), but uses instead spherical harmonics Legendre polynomial orthogonal functions as a basis for the expansion, portraying each 2D angular distribution at every energy or, geometrically, spherical speed-shell swept by the particle spectrometer. Optionally, these spherical harmonic spectral coefficients may be telemetered to the ground. These will provide a smoothed description of the velocity distribution function whose quality will depend on the number of coefficients determined. Successfully implemented on the GSFC-developed processor, the capability to integrate the proposed methodology with both heritage and anticipated future plasma particle spectrometer designs is demonstrated (with sufficiently detailed design analysis to advance TRL) to show specific science relevancy with future HSD (Heliophysics Science Division) solar-interplanetary, planetary missions, sounding rockets and/or CubeSat missions.

Figueroa-Vinas, Adolfo↗

Calibration of urban building energy model using smart meter data for district peak load prediction

Urban building energy modeling (UBEM) is a powerful approach to assessing baseline building energy performance and retrofits with new technologies across building stocks in cities. However, the accuracy of UBEM is often constrained by the limited availability of reliable data about building characteristics and operations, such as envelope efficiency levels, HVAC system performance, and end-use load patterns. Existing research has performed UBEM calibration using annual or monthly energy consumption data, which falls short when higher-resolution time series applications are needed, such as peak load prediction for utility operation planning. This study presents a new framework for calibrating building energy models at urban scale using smart meter data, targeting the accurate prediction of summer peak electricity loads to support robust grid planning. The framework first integrates various data sources to enhance baseline input assumptions for building models, and then calibrates the baseline models through a pattern-matching approach. A case study using CityBES and two years of AMI data from over 9000 residential customers in Portland, Oregon, demonstrated the workflow and its effectiveness. The calibrated models achieved a daily peak load mean absolute percentage error of 2.6 % during the heatwave in the calibration year, and 2.0 % in the validation year using another year of AMI data. Using the calibrated models, we analyzed the demand flexibility potential of the district building stock as an application of UBEM calibration. The findings affirm the appropriate use of UBEM for peak electric load forecasting and demand side management at the utility distribution system level.

AMI data↗

Impact of Automation Support on the Conflict Resolution Task in a Human-in-the-Loop Air Traffic Control Simulation

To determine the capabilities and limitations of human operators and automation in separation assurance roles, the second of three Human-in-the-Loop (HITL) part-task studies investigated air traffic controllers ability to detect and resolve conflicts under varying task sets, traffic densities, and run lengths. Operations remained within a single sector, staffed by a single controller, and explored, among other things, the controllers responsibility for conflict resolution with or without their involvement in the conflict detection task. Furthermore, these conditions were examined across two different traffic densities; 1x (current-day traffic) and a 20 increase above current-day traffic levels (1.2x). Analyses herein offer an examination of the conflict resolution strategies employed by controllers. In particular, data in the form of elapsed time between conflict detection and conflict resolution are used to assess if, and how, the controllers involvement in the conflict detection task affected the way in which they resolved traffic conflicts.

human-in-the-loop simulation↗

Resolution Enhancement of MODIS-Derived Water Indices for Studying Persistent Flooding

Monitoring coastal marshes for persistent flooding and salinity stress is a high priority issue in Louisiana. Remote sensing can identify environmental variables that can be indicators of marsh habitat conditions, and offer timely and relatively accurate information for aiding wetland vegetation management. Monitoring activity accuracy is often limited by mixed pixels which occur when areas represented by the pixel encompasses more than one cover type. Mixtures of marsh grasses and open water in 250m Moderate Resolution Imaging Spectroradiometer (MODIS) data can impede flood area estimation. Flood mapping of such mixtures requires finer spatial resolution data to better represent the cover type composition within 250m MODIS pixel. Fusion of MODIS and Landsat can improve both spectral and temporal resolution of time series products to resolve rapid changes from forcing mechanisms like hurricane winds and storm surge. For this study, using a method for estimating sub-pixel values from a MODIS time series of a Normalized Difference Water Index (NDWI), using temporal weighting, was implemented to map persistent flooding in Louisiana coastal marshes. Ordinarily NDWI computed from daily 250m MODIS pixels represents a mixture of fragmented marshes and water. Here, sub-pixel NDWI values were derived for MODIS data using Landsat 30-m data. Each MODIS pixel was disaggregated into a mixture of the eight cover types according to the classified image pixels falling inside the MODIS pixel. The Landsat pixel means for each cover type inside a MODIS pixel were computed for the Landsat data preceding the MODIS image in time and for the Landsat data succeeding the MODIS image. The Landsat data were then weighted exponentially according to closeness in date to the MODIS data. The reconstructed MODIS data were produced by summing the product of fractional cover type with estimated NDWI values within each cover type. A new daily time series was produced using both the reconstructed 250-m MODIS, with enhanced features, and the approximated daily 30-m high-resolution image based on Landsat data. The algorithm was developed and tested over the Calcasieu-Sabine Basin, which was heavily inundated by storm surge from Hurricane Ike to study the extent and duration of flooding following the storm. Time series for 2000-2009, covering flooding events by Hurricane Rita in 2005 and Hurricane Ike in 2008, were derived. High resolution images were formed for all days in 2008 between the first cloud free Landsat scene and the last cloud-free Landsat scene. To refine and validate flooding maps, each time series was compared to Louisiana Coastwide Reference Monitoring System (CRMS) station water levels adjusted to marsh to optimize thresholds for MODIS-derived time series of NDWI. Seasonal fluctuations were adjusted by subtracting ten year average NDWI for marshes, excluding the hurricane events. Results from different NDWI indices and a combination of indices were compared. Flooding persistence that was mapped with higher-resolution data showed some improvement over the original MODIS time series estimates. The advantage of this novel technique is that improved mapping of extent and duration of inundation can be provided.

Underwood, L. W.↗

Solar wind plasma periodicities observed at 1 AU by IMP 8

The IMP 8 spacecraft has been in Earth orbit since 1973, gathering plasma data over one complete 22-year solar cycle. These data are being examined to look for periodicities at time scales ranging from several hours to the entire span of the data set. A 1.3-year periodicity in the radial speed observed by IMP 8 and Voyager 2 has already been reported for the years from 1987 to 1993. The periodogram method, useful for unevenly sampled data such as the IMP 8 plasma data, has been used to search for other periods. It is interesting to note that the 13-year period is not present in the out-of-the-ecliptic component of the velocity (Vz), although a 1-year period is very obvious both visually and on the periodogram. Both components show a very strong peak associated with the 11-year solar cycle variation. This work will be extended to the thermal speed (a measure of the wind's temperature) and density, although the frequent correlations between these parameters and the velocity are expected to cause similar results. Additionally, the fine resolution data will be examined for shorter time periods than are visible using the hourly average data which are appropriate for longer periods. A comparison with periods observed at other spacecraft may also be made.

Paularena, K. I.↗

Compact, High Energy 2-micron Coherent Doppler Wind Lidar Development for NASA's Future 3-D Winds Measurement from Space

This paper presents an overview of 2-micron laser transmitter development at NASA Langley Research Center for coherent-detection lidar profiling of winds. The novel high-energy, 2-micron, Ho:Tm:LuLiF laser technology developed at NASA Langley was employed to study laser technology currently envisioned by NASA for future global coherent Doppler lidar winds measurement. The 250 mJ, 10 Hz laser was designed as an integral part of a compact lidar transceiver developed for future aircraft flight. Ground-based wind profiles made with this transceiver will be presented. NASA Langley is currently funded to build complete Doppler lidar systems using this transceiver for the DC-8 aircraft in autonomous operation. Recently, LaRC 2-micron coherent Doppler wind lidar system was selected to contribute to the NASA Science Mission Directorate (SMD) Earth Science Division (ESD) hurricane field experiment in 2010 titled Genesis and Rapid Intensification Processes (GRIP). The Doppler lidar system will measure vertical profiles of horizontal vector winds from the DC-8 aircraft using NASA Langley s existing 2-micron, pulsed, coherent detection, Doppler wind lidar system that is ready for DC-8 integration. The measurements will typically extend from the DC-8 to the earth s surface. They will be highly accurate in both wind magnitude and direction. Displays of the data will be provided in real time on the DC-8. The pulsed Doppler wind lidar of NASA Langley Research Center is much more powerful than past Doppler lidars. The operating range, accuracy, range resolution, and time resolution will be unprecedented. We expect the data to play a key role, combined with the other sensors, in improving understanding and predictive algorithms for hurricane strength and track. 1

Singh, Upendra N.↗

MAPSAT compared to other earth-sensing concepts

The instrument systems and operational capabilities of MAPSAT are discussed. The satellite is based on LANDSAT technology and includes the following concepts: global coverage on a continuous basis; open data dissemination in reasonable time and cost; variable resolution, swath-width, stereoscopic and multispectral capabilities; 1:50,000-scale image mapping with a 20-m contour interval; continuity with LANDSAT-1,-2, and -3 including the same basic data transmission and reception system; and one-dimensional data processing.

Colvocoresses, A. P.↗

Plasma Waves Observed in the Cusp Turbulent Boundary Layer: An Analysis of High Time Resolution Wave and Particle Measurements from the Polar Spacecraft

The boundary layer located in the cusp and adjacent to the magnetopause is a region that is quite turbulent and abundant with waves. The Polar spacecraft's orbit and sophisticated instrumentation are ideal for studying this region of space. Our analysis of the waveform data obtained in this turbulent boundary layer shows broadband magnetic noise extending up to a few kilohertz (but less than the electron cyclotron frequency); sinusoidal bursts (a few tenths of a second) of whistler mode waves at around a few tens of hertz, a few hundreds of hertz, and just below the electron cyclotron frequency; and bipolar pulses, interpreted as electron phase-space holes. In addition, bursts of electron cyclotron harmonic waves are occasionally observed with magnetic components. We show evidence of broadband electrostatic bursts covering a range of approx. 3 to approx. 25 kHz (near but less than the plasma frequency) occurring in packets modulated at the frequency of some of the whistler mode waves. On the basis of high time resolution particle data from the Polar HYDRA instrument, we show that these bursts are consistent with generation by the resistive medium instability. The most likely source of the whistler mode waves is the magnetic reconnection site closest to the spacecraft, since the waves are observed propagating both toward and away from the Earth, are bursty, which is often the case with reconnection, and do not fit on the theoretical cold plasma dispersion relation curve.

Pickett, J. S.↗

Single-Chip FPGA Azimuth Pre-Filter for SAR

A field-programmable gate array (FPGA) on a single lightweight, low-power integrated-circuit chip has been developed to implement an azimuth pre-filter (AzPF) for a synthetic-aperture radar (SAR) system. The AzPF is needed to enable more efficient use of data-transmission and data-processing resources: In broad terms, the AzPF reduces the volume of SAR data by effectively reducing the azimuth resolution, without loss of range resolution, during times when end users are willing to accept lower azimuth resolution as the price of rapid access to SAR imagery. The data-reduction factor is selectable at a decimation factor, M, of 2, 4, 8, 16, or 32 so that users can trade resolution against processing and transmission delays. In principle, azimuth filtering could be performed in the frequency domain by use of fast-Fourier-transform processors. However, in the AzPF, azimuth filtering is performed in the time domain by use of finite-impulse-response filters. The reason for choosing the time-domain approach over the frequency-domain approach is that the time-domain approach demands less memory and a lower memory-access rate. The AzPF operates on the raw digitized SAR data. The AzPF includes a digital in-phase/quadrature (I/Q) demodulator. In general, an I/Q demodulator effects a complex down-conversion of its input signal followed by low-pass filtering, which eliminates undesired sidebands. In the AzPF case, the I/Q demodulator takes offset video range echo data to the complex baseband domain, ensuring preservation of signal phase through the azimuth pre-filtering process. In general, in an SAR I/Q demodulator, the intermediate frequency (fI) is chosen to be a quarter of the range-sampling frequency and the pulse-repetition frequency (fPR) is chosen to be a multiple of fI. The AzPF also includes a polyphase spatial-domain pre-filter comprising four weighted integrate-and-dump filters with programmable decimation factors and overlapping phases. To prevent aliasing of signals, the bandwidth of the AzPF is made 80 percent of fPR/M. The choice of four as the number of overlapping phases is justified by prior research in which it was shown that a filter of length 4M can effect an acceptable transfer function. The figure depicts prototype hardware comprising the AzPF and ancillary electronic circuits. The hardware was found to satisfy performance requirements in real-time tests at a sampling rate of 100 MHz.

Gudim, Mimi↗

Visual and genetic stock identification of a test fishery to forecast Columbia River spring Chinook salmon stocks 2 weeks into the future

Abstract Modern fisheries management strives to balance opposing goals of protection for weak stocks and opportunity for harvesting healthy stocks. Test fisheries can aid management of anadromous fishes if they can forecast the strength and timing of an annual run with adequate time to allow fisheries planning. Integration of genetic stock identification (GSI) can further maximize utility of test fisheries by resolving run forecasts into weak‐ and healthy‐stock subcomponents. Using 5 years (2017–2022) of test fishery data, our study evaluated accuracy, resolution, and lead time of predictions for stock‐specific run timing and abundance of Columbia River spring Chinook salmon ( Oncorhynchus tshawytscha ). We determined if this test fishery (1) could use visual stock identification (VSI) to forecast at the coarse stock resolution (i.e., classification of “lower” vs. “upriver” stocks) upon which current management is based and (2) could be enhanced with GSI to forecast at higher stock resolution. VSI accurately identified coarse stocks (83.3% GSI concordance), and estimated a proxy for abundance (catch per unit effort, CPUE) of the upriver stock in the test fishery that was correlated ( R 2 = 0.90) with spring Chinook salmon abundance at Bonneville dam (Rkm 235). Salmon travel rates (~8.6 Rkm/day) provided predictions with 2‐week lead time prior to dam passage. Importantly, GSI resolved this predictive ability as finely as the hatchery broodstock level. Lower river stock CPUE in the test fishery was correlated with abundance at Willamette Falls (Rkm 196, R 2 = 0.62), but could not be as finely resolved as achieved for upriver stocks. We described steps to combine VSI and GSI to provide timely in‐season information and with prediction accuracy of ~12.4 mean absolute percentage error and high stock resolution to help plan Columbia River mainstem fisheries.

Hess, Jon E.↗

Application of VISSR Atmospheric Sounder (VAS) data

Sounding data which were derived from VAS radiance measurements and anticipated increased time and space resolution of the mesoscale environment are outlined. The new data presents problems which are not encounted when using conventional measurements because of the irregular spacing of the data, biases in the data, and errors due to cloud contaminated measurements. These problems are addressed and an analysis technique which utilizes LFM guess fields to produce a consistent four dimensional data set which describes the mesoscale environment over a large area is presented.

Jedlovec, G. J.↗

Gridded Sub-daily Climate Forcings for North America Based on Daymet and ERA5 (Daymet-ERA5)

To support high spatial and temporal resolution land surface modeling, this dataset provides 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 2024. Using sub-daily temporal information from the ECMWF ERA5 reanalysis, Daymet was further temporally downscaled to 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 hourly time step from ERA5 while maintaining the total and average values from Daymet for each day. This results in a blended 1980-2024 Daymet-ERA5 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↗

Demonstration of an AI-driven workflow for dynamic x-ray spectroscopy

X-ray absorption near edge structure (XANES) spectroscopy is a powerful technique for characterizing the chemical state and symmetry of individual elements within materials, but requires collecting data at many energy points which can be time-consuming. While adaptive sampling methods exist for efficiently collecting spectroscopic data, they often lack domain-specific knowledge about the structure of XANES spectra. Here we demonstrate a knowledge-injected Bayesian optimization approach for adaptive XANES data collection that incorporates understanding of spectral features like absorption edges and pre-edge peaks. We show this method accurately reconstructs the absorption edge of XANES spectra using only 15–20% of the measurement points typically needed for conventional sampling, while maintaining the ability to determine the x-ray energy of the sharp peak after the absorption edge with errors less than 0.03 eV, the absorption edge with errors less than 0.1 eV; and overall root-mean-square errors less than 0.005 compared to traditionally sampled spectra. Our experiments on battery materials and catalysts demonstrate the method’s effectiveness for both static and dynamic XANES measurements, improving data collection efficiency and enabling better time resolution for tracking chemical changes. This approach advances the degree of automation in XANES experiments, reducing the common errors of under- or over-sampling points near the absorption edge and enabling dynamic experiments that require high temporal resolution or limited measurement time.

Bayesian optimization↗

Fractal dimension of optical cirrus in Stripe82

ABSTRACT The geometric characteristics of dust clouds provide important information on the physical processes that structure such clouds. One of such characteristics is the 2D fractal dimension D of a cloud projected on to the sky plane. In previous studies, which were mostly based on infrared (IR) data, the fractal dimension of individual clouds was found to be in a range from 1.1 to 1.7 with a preferred value of 1.2–1.4. In this work, we use data from Stripe82 of the Sloan Digital Sky Survey to measure the fractal dimension of the cirrus clouds. This is done here for the first time for optical data with significantly better resolution as compared to IR data. To determine the fractal dimension, the perimeter-area method is employed. We also consider IR (IRAS and Herschel) counterparts of the corresponding optical fields to compare the results between the optical and IR. We find that the averaged fractal dimension across all clouds in the optical is $\langle D \rangle =1.69^{+0.05}_{-0.05}$ which is significantly larger than the fractal dimension of its IR counterparts $\langle D\rangle =1.38^{+0.07}_{-0.06}$. We examine several reasons for this discrepancy (choice of masking and minimal contour level, image and angular resolution, etc.) and find that for approximately half of our fields the different angular resolution (point spread function) of the optical and IR data can explain the difference between the corresponding fractal dimensions. For the other half of the fields, the fractal dimensions of the IR and visual data remain inconsistent, which can be associated with physical properties of the clouds, but further physical simulations are required to prove it.

79 ASTRONOMY AND ASTROPHYSICS↗

Artificial Intelligence-Driven Management of Sustainable Energy Resources: Visibility, Operation, and Control

The rapid global transition toward sustainable energy resources (SERs) is reshaping how modern power systems are observed, optimized, and controlled. While SERs have significantly advanced decarbonization, their weather dependence, variability, and inverter-dominated characteristics challenge traditional, centralized, and deterministic grid operation. At the same time, the proliferation of high-resolution data from inverters, smart meters, and sensors offers unprecedented visibility into system dynamics. Yet, it also exceeds the analytical capability of conventional model-based approaches. Artificial intelligence (AI) provides a new foundation for addressing these challenges by bridging physical laws with data-driven learning, enabling accurate state awareness, adaptive operation, and coordinated control across distributed assets. This article examines how AI transforms the management of SER-rich power systems along three critical dimensions: 1) enhancing visibility by inferring behind-the-meter (BTM) activities, assessing SER flexibility, and reconstructing system states from sparse or noisy measurements; 2) improving operation through AI-enhanced SER service provision, volt/var control (VVC), and dynamic operating envelopes (DOE) for efficiency and security; and 3) advancing control by embedding learning-based intelligence into inverter coordination, voltage and frequency regulation, and long-term dispatch. Together, these developments reveal how AI can convert the variability of SERs from an operational challenge into a source of flexibility, resilience, and intelligence, paving the way toward sustainable, adaptive, and self-optimizing power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Final technical report for DE-SC0022255: Discovering Physically Meaningful Structures from Climate Extreme Data

The past two decades have witnessed natural disasters and extreme weather events that affect millions of people. At the same time, the data volume from high-resolution climate models, satellite, in-situ and ground-based measurements have substantially increased to petabyte scales. These new and readily accessible datasets create the previously missing pipeline required for scientific machine learning (ML) and therefore new opportunities for improved understanding and prediction capability of climate extreme events. This project developed a deep latent variable model framework to discover physically meaningful hidden structures from high-dimensional, spatiotemporal climate extreme data.

97 MATHEMATICS AND COMPUTING↗

A new high-speed solar radio spectrograph for meter and decameter wavelengths

The design and characteristics of a high resolution, digital solar spectrograph are discussed. The spectrometer operates in the 10 to 80 MHz range. The primary considerations in the design of the spectrograph were: (1) optimun sensitivity, (2) wide dynamic range, (3) flexibility in time and frequency resolution, and (4) modern data handling techniques with a simple computer interface.

Mosier, S. R.↗