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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.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

ARM Lead Mentor Selection Process

The Atmospheric Radiation Measurement (ARM) Program was created in 1989 with funding from the U.S. Department of Energy (DOE) to develop several highly instrumented ground stations to study cloud-formation processes and their influence on radiative transfer. This scientific infrastructure provides for fixed sites, mobile facilities, an aerial facility, and a data archive available for use by scientists worldwide through the ARM Climate Research Facility—a scientific user facility. The ARM Climate Research Facility currently operates more than 300 instrument systems that provide ground-based observations of the atmospheric column. To keep ARM at the forefront of climate observations, the ARM infrastructure depends heavily on instrument scientists and engineers, known as Mentors. Mentors must have an excellent understanding of instrumentation theory and operation for their instrument areas and have comprehensive knowledge of critical scale-dependent atmospheric processes. They must also possess the technical and analytical skills to develop new data retrievals that provide innovative approaches for creating research-quality data sets. The ARM Facility seeks the best overall qualified candidate, or team when appropriate, that can fulfill Mentor requirements in a timely manner. The roles and responsibilities of the ARM Instrument Operations Manager are provided in Appendix A. The key role and responsibilities and detailed responsibilities of ARM Lead Mentors are provided in Appendix B and Appendix C, respectively.

47 OTHER INSTRUMENTATION↗
NASA NTRSDate not supplied

Enabling Interoperability in Earth System Digital Twins (ESDT): Integrating Observations, Models, and AI for Actionable Insights Through NASA'S Intelligent Systems Technology Program

NASA’s Intelligent Systems Technology Program (IST) is driving a paradigm shift in Earth science through the development of Earth System Digital Twins (ESDT). These integrated information systems create a dynamic "digital replica" of the Earth by harmonizing continuous, multi-source observations with high-fidelity models and state-of-the-art artificial intelligence (AI) that enable “What now?”, “What next?”, and “What if?” scenario building. These scenarios are reflected in NASA IST’s series of ESDTs, from the Coastal Zone Digital Twin that integrates complex data on the current state of the Chesapeake Bay to the Terrestrial Environmental Rapid-Replication and Assimilation Hydrometeorological (TerraHydro) AI-based ESDT that forecasts water movement across Earth’s surface, to the Agriculture Land Information System (AgLIS) which can be used to assess optimal planting dates and crop yield estimates. By bridging the gap between vast data archives and actionable insights, these projects enable a system-of-systems approach to understanding complex, interacting Earth processes. This poster will highlight recent innovations and future directions from NASA’s ESDT initiatives: Continuous Data Assimilation & Multi-Source Fusion. A core requirement of the ESDT work is the transition from static models to dynamic "living" replicas. This involves creating frameworks for the continual assimilation of near-real-time data from uncoordinated, heterogeneous sources, including satellite observations and airborne assets, and ground-based Internet of Things (IoT) sensors. These systems link design, operational status, and environmental data, ensuring the digital twin accurately reflects the current state of the physical Earth system. High-Fidelity Hybrid Modeling & Computational Acceleration to enable interactive "what-if" explorations, programs are moving beyond traditional, slow physical solvers by developing fast surrogate machine learning models and Deep Generative Models (DGMs). These hybrid approaches use neural networks to emulate complex physics, such as cloud feedback or ocean dynamics, at a fraction of the original computing cost, often leveraging advanced hardware like Graphics Processing Units (GPUs) to achieve the necessary scale. Federated Ecosystems & Interoperable Frameworks rather than building isolated tools, NASA IST is moving toward federated ESDTs and reusable analytic collaborative frameworks. This theme focuses on interoperability standards and common ontologies that allow specialized digital twins to interact and share data. This system-of-systems architecture supports multi-discipline investigations, such as analyzing how upstream watershed changes impact downstream urban flooding or how wildfire emissions affect regional air quality. By leveraging these advancements, ESDTs empower researchers and decision-makers to conduct real-time analysis and run complex hypothetical scenarios, ultimately improving our understanding of Earth’s evolving systems and informing critical real-world applications.

Earth System↗
NASA NTRS1993

Diagnostics development for the Electric Propulsion Orbital Platform

We describe the development of the diagnostics systems for the first flight of the Electric Propulsion Orbital Platform (EPOP), which will center around the in-flight characterization of a 1.8 kW hydrogen arcjet system. In particular, we discuss a spacecraft communications experiment involving ground-to-spacecraft communications of the EPOP carrier; electrical probe measurements in the arcjet plume; and spectrally resolved plume imaging measurements of the same plume. The communications experiment is designed to measure small noise on the communications link which results from arcjet operation. The other two measurements primarily serve the purpose of characterization of the plume plasma. These measurements will be compared to similar measurements performed in a ground chamber to establish whether systematic differences exist between ground-based and in-flight performance of the arcjet system.

Ruyten, Wilhelmus M.↗
NASA NTRSDate not supplied

An Overview of Experiments and Modeling of Polysiloxane-Coated Thermal Protection Systems for Missions to Mars, Titan, and Beyond.

Phenolic Impregnated Carbon Ablator (PICA) gained heritage during the historic Stardust mission, where it successfully returned samples from a comet’s tail and has since been instrumental in delivering payloads to the surface of Mars [1-3]. Most recently, PICA enabled the safe return of samples collected from asteroid Bennu as part of the OSIRIS-REx mission. This rich legacy underscores PICA’s critical role in allowing NASA’s most ambitious exploration missions. However, the friable nature of its phenolic phase presents challenges during handling and pre-launch activities. To mitigate this issue, PICA is coated with a polysiloxane resin system, which serves to suppress particulate dispersion and thereby safeguard spacecraft components. A comprehensive understanding of the polysiloxane resin’s behavior is imperative, as it profoundly shapes the material response of PICA during atmospheric entry by influencing its thermal and oxidative stability. This influence extends to thermocouple plugs embedded within thermal protection systems. These plugs have demonstrated their significance in missions such as Mars Science Laboratory (MSL) and Mars 2020, where the MEDLI and MEDLI2 instrumentation suites delivered in-valuable insights into the performance of thermal protection systems during entry into the Martian atmosphere [4]. Looking ahead, missions such as Dragonfly, set to descend into Titan’s dense atmosphere, aim to leverage advanced sensor technologies to further refine our understanding of thermal protection response [5]. Moreover, thermocouple plugs play an essential role in validating cutting-edge material response models, such as those pioneered under NASA’s Entry Systems Modeling Project (ESM), designed, in-part, to predict the operational integrity of thermal protection systems under the extreme stresses of atmospheric entry. To achieve these modeling goals, ground-based experiments are crucial to provide the foundational data necessary for developing and refining these predictive tools. To this end, an extensive test campaign was conducted at the Hypersonic Materials Environmental Test System (HyMETS) to investigate the high-temperature behavior of the polysiloxane resin in an air environment [6]. These experiments revealed critical phenomena, including the formation of a silicon oxycarbide layer that enhances oxidation resistance, moderates surface temperatures, and alters in-depth thermal response. Building on these findings, subsequent tests were designed to simulate atmospheric entry conditions in reactive gases, such as CO2 and N2, to mimic the environments of Mars and Titan, respectively, as well as non-reactive gases representing the atmospheres of the Ice Giants (Neptune and Uranus). A heating rate dependent decomposition mechanism has been identified for the polysiloxane resin under oxidizing conditions (Fig. 1). In the initial stage, the resin and the underlying thermal protection system undergo pyrolysis, rapidly generating a thin amorphous silicon oxycarbide interwoven with carbonaceous char and residual fibers from PICA. During the second stage, the nascent oxide layer establishes a robust, oxidation-resistant thermal barrier coating, which significantly impedes heat transfer to the underlying carbonaceous char, resulting in a stagnation of the surface temperature. A key factor contributing to this thermal resistance is the low recombination efficiency of atomic oxygen (γ), which further diminishes the heat load on the material’s interior layers [7]. Moreover, as the surface temperature stagnates, the silicon oxycarbide phase separates into distinct regions of silica and free graphite. Ultimately, when the heat flux reaches a critical threshold, a third stage is triggered, leading to the breakdown of the coating through carbothermal reduction, exposing the underlying char layer. This exposure leads to a dramatic surface temperature spike, driven by highly exothermic reactions between atomic oxygen and the char layer, further accelerating material degradation. A detailed mass and heat transfer model of PICA coated with polysiloxane resin was implemented in the Porous material Analysis Toolbox based on OpenFOAM, PATO [8]. The initial stage was considered negligible in this model because the resin decomposition occurs rapidly within a thin surface layer. Instead, the coating was directly considered as an oxygen-resistant thermal barrier coating. For the second stage, the thin amorphous silicon oxycarbide was treated as a pure silica surface to simplify the thermochemical behavior. The model ac-counts for surface equilibrium processes using representative elements of the coating-environment system. For the third stage, specific boundary conditions were developed to estimate the onset and progression of the coating removal. Two-dimensional material response simulations were conducted to compare uncoated and coated PICA using boundary conditions calibrated with HyMETS data. Fig. 2 illustrates that the simulations closely align with experimental data, successfully reproducing measured temperature profiles. This work will include the latest advancements in the coating model, including the calibration of recombination of atomic oxygen at the surface during the second phase. These simulated results will be further validated against additional CO2 data points from HyMETS, reinforcing the models’ predictive capabilities. These mechanisms and their effects on thermal protection systems, including thermochemical behavior and thermocouple probe performance in extreme environments, provide crucial insights for optimizing spacecraft designs that safeguard scientific payload and ensure mission success in future planetary exploration endeavors.

Active Oxidation↗
NASA NTRS2026

Mechanical Properties of Carbon Fiber Reinforced Composites Exposed to Cryogenic Conditions and Space Radiation via Simulation and Testing

As NASA missions extend beyond low Earth orbit, increasing reliance is placed on carbon fiber reinforced polymer (CFRP) composites for spacecraft structures where mass efficiency, durability, and long-term reliability are critical. In service, these materials are subjected to a combination of ultraviolet radiation, vacuum, ionizing radiation, atomic oxygen, and extreme thermal excursions under sustained mechanical loading. Flight systems such as the Boeing Starliner and SpaceX Dragon employ external composite structures that will experience these environments for extended durations. Although prior spaceflight and ground studies have reported limited changes in bulk mechanical properties, the synergistic effects of these environments on composite microstructure, particularly at the fiber matrix interphase, remain insufficiently characterized and represent a potential qualification and reliability risk. This study investigates the effects of short-term cryogenic exposure on a radiation shielding carbon epoxy composite, SC2020, as a ground-based analog for space relevant thermal extremes. The SC2020 material system has previously flown on the International Space Station under the Materials International Space Station Experiment (MISSE) program. Composite specimens were exposed to liquid nitrogen for 6 and 24 hours and evaluated using a multiscale characterization framework that combined ASTM D3039 tensile testing, Atomic Force Microscopy (AFM) based interphase analysis, and helium gas permeability measurements. Tensile testing showed no statistically significant or permanent degradation in global strength or modulus following cryogenic exposure. In contrast, AFM measurements revealed reductions in interphase modulus, weakened adhesion, and increased nanoscale heterogeneity, indicating localized degradation mechanisms not captured by conventional bulk testing. Gas permeability measurements showed a progressive increase in helium diffusion with exposure duration, consistent with micro-void formation or partial interfacial debonding. The results indicate that cryogenic exposure initiates degradation at the fiber matrix interphase while leaving global mechanical properties largely unchanged over short durations. These findings underscore the importance of multiscale diagnostics for identifying early-stage damage mechanisms that may influence long term performance and qualification margins for spaceflight composite structures. The data presented establish a cryogenic baseline for comparison with forthcoming MISSE flight exposure results and support ongoing NASA Established Program to Stimulate Competitive Research (EPSCoR) efforts aimed at improving composite qualification methodologies, risk assessment, and reliability prediction for space environments.

composite reliability↗
DOE OSTI2026

Importance of Spatially Continuous Urban Surface Properties in Urban‐Resolving Earth System Modeling

Accurate representation of urban properties and processes at higher resolutions in global modeling systems is essential for advancing our ability to capture the complexities of urban systems and informing effective resilience strategies. However, the prescription of coarse global-scale urban properties in most state-of-the-art Earth system models (ESMs) is limiting their potential for capturing urban signals as they advance toward kilometer-scale simulation capabilities. To bridge this gap in inadequate urban property representation and to advance urban-resolving Earth system modeling, this work integrates the newly-developed global 1 km-resolution facet-level urban surface property data set, U-Surf, into the land component of Community Earth System Model (CESM)—Community Terrestrial System Model (CTSM). The land-only CTSM simulations are validated against satellite measurements, ground-based urban weather stations, flux tower observations, and reanalysis data. Results demonstrate that the enhanced urban properties allow improved simulations of urban meteorology and surface energy fluxes compared to the default coarse-resolution categorical urban canopy parameters. Spatial scaling analysis reveals regime-dependent information loss during resolution aggregation, as well as substantial scale-dependent variations in urban surface energy flux representation. Furthermore, these findings have critical implications for coupled Earth system modeling when including the effect of land-atmosphere interaction. This work establishes a foundation for future urban-resolving kilometer-scale ESM development, which will enable systematic intra- and inter-city comparisons that inform urban adaptation strategies across diverse global urban environments.

Cheng, Yifan [University of Illinois Urbana-Champa↗
DOE OSTI2026

Wind and Temperature Consensus at Horn Point, HU-Beltsville, Piney Run (Maryland) in support of CoURAGE

The Maryland Department of the Environment (MDE) operates a ground-based atmospheric profiling network consisting of collocated radar wind profilers (RWP) and radio acoustic sounding systems (RASS) as part of its Ambient Air Monitoring Program. This network provides continuous observations of wind and temperature structure in the lower troposphere to support air quality forecasting, regulatory analysis, and atmospheric research. The network currently includes three fixed sites across Maryland: Horn Point (HP, lower eastern shore) [38.587525°,-76.141006°], Howard University-Beltsville (HUB, central Maryland) [39.055277°, -76.878632°], and Piney Run (PR, western Maryland) [39.705950°, -79.012000°] The network is designed to capture regional variability in atmospheric transport and boundary-layer processes. These systems measure vertical profiles of horizontal wind speed and direction using Doppler radar techniques, with observations typically spanning from ~100 m above ground level up to approximately 2.5–4 km. Measurements are derived from the Doppler shift of backscattered electromagnetic signals, enabling retrieval of wind vectors at multiple altitudes with high temporal resolution (e.g., 30-minute averages reported every 6 minutes). Each radar wind profiler is paired with a Radio Acoustic Sounding System (RASS) to provide profiles of virtual temperature in the lower atmosphere (~100–200 m AGL) by measuring the propagation speed of acoustic waves. Together, the RWP/RASS system yields a coupled data set of thermodynamic and kinematic atmospheric structure, including additional parameters such as vertical velocity, radial velocity, signal-to-noise ratio, and spectral width for advanced analysis. There are two types of files for each station: wind data (files with a "w" prefix) and virtual temperature RASS data (files with a "t" prefix). The wind data files are in the format wYYDDD.cns, where YY is the 2-digit year and DDD is the day of the year. The RASS virtual temperature data files are in the format tYYDDD.cns. Each record has the following header structure: Line 1 : Station Name RASS files Line 2 : RASS rev DeTect_2.0, WINDS files Line 2 : WINDS rev ATI 5.1 Line 3 : N latitude, W longitude, and site elevation (m) Line 4 : Date and begin time of consensus: yy mm dd hh mn ss plus # minutes to add to get UTC Line 5 : Consensus averaging time (minutes); number of beams; number of range gates Line 6 : Number of records required to make consensus (num) total number of records (tot) and the consensus window size (m/s) in the format: num:tot (window) RASS files Line 7 : no. of coded cells, no. of spec, pulse width (ns), and inter-pulse period (µs), WINDS files Line 7 : No. of coded cells, no. of spectra, pulse width (ns), and inter-pulse period (µs), each with a pair of values: first value is for oblique beams, second for vertical RASS files Line 8 : Full scale Doppler value (m/s) Delay to first gate (ns) Number of gates Spacing of gates (ns), WINDS files Line 8 : Full scale Doppler velocity (m/s), oblique and vertical Vertical correction applied to oblique beams? (0 = no, 1 = yes) Delay to first gate (ns), oblique and vertical Number of gates, oblique and vertical Spacing of gates (ns), oblique and vertical Line 9 : Azimuth and elevation (9s indicate vertical beam not used) RASS files Line 10, values : HT = Height above ground (km), T = Uncorrected virtual temperature consensus (deg C), Tc = Corrected virtual temperature consensus (deg C), W = Vertical wind consensus (9s indicate vertical beam not used, w-component, positive upward, m/s), CNT = Number of records that made consensus (for the 3 values in same order), SNR = Average signal to noise ratio (dB) of records in consensus (same order) WINDS files Line 10, values : HT = Height above ground (km), SPD = Wind speed (m/s), DIR = Wind direction (deg E of N from N), RAD = Radial velocities for each beam (m/s) in order given in azimuth and elevation line (positive toward radar; 9s indicate vertical beam not used, CNT = Number of records that made consensus, SNR = Average signal to noise ratio (dB) of records in consensus

{"wind speed and direction",temperature}↗
NASA NTRS1992

Flight service environmental effects on composite materials and structures

NASA Langley and the U.S. Army have jointly sponsored programs to assess the effects of realistic flight environments and ground-based exposure on advanced composite materials and structures. Composite secondary structural components were initially installed on commercial transport aircraft in 1973; secondary and primary structural components were installed on commercial helicopters in 1979; and primary structural components were installed on commercial aircraft in the mid-to-late 1980's. Service performance, maintenance characteristics, and residual strength of numerous components are reported. In addition to data on flight components, 10 year ground exposure test results on material coupons are reported. Comparison between ground and flight environmental effects for several composite material systems are also presented. Test results indicate excellent in-service performance with the composite components during the 15 year period. Good correlation between ground-based material performance and operational structural performance has been achieved.

Dexter, H. Benson↗
NASA NTRS1993

The Telecommunications and Data Acquisition Report

This quarterly publication provides archival reports on developments in programs managed by JPL's Office of Telecommunications and Data Acquisition (TDA). In space communications, radio navigation, radio science, and ground-based radio and radar astronomy, it reports on activities of the Deep Space Network (DSN) in planning, supporting research and technology, implementation, and operations. Also included are standards activity at JPL for space data and information systems and reimbursable DSN work performed for other space agencies through NASA. The preceding work is all performed for NASA's Office of Space Communications (OSC). The TDA Office also performs work funded by another NASA program office through and with the cooperation of OSC. This is the Orbital Debris Radar Program with tile Office of Space Systems Development. The TDA Office is directly involved in several tasks that directly support the Office of Space Science (OSS), with OSC funding DSN operational support. In radio science, The TDA Progress Report describes the spacecraft radio science program conducted using tile DSN. For the High-Resolution Microwave Survey (HRMS), the report covers implementation and operations for searching the microwave spectrum. In solar system radar, it reports on the uses of the Goldstone Solar System Radar for scientific exploration of the planets, their rings and satellites, asteroids, and comets. In radio astronomy, the areas off support include spectroscopy, very long baseline interferometry, and astrometry.

Edward C Posner↗
NASA NTRS2026

Tracing the Source of Carbon Oxides on the Large Moons of Uranus

The Uranian moons Ariel, Umbriel, Titania, and Oberon are enriched in CO 2 mixed with CO, but the origin(s) of these carbon oxides, be they primarily native or radiolytic, remain(s) uncertain. Using data collected by NIRSpec on the James Webb Space Telescope (JWST), we measured the spectral signature of CO 2 and other carbon oxides to help disentangle these hypotheses. Through comparison to laboratory data, we find that many of the detected spectral features are consistent with CO 2 ice, including 12 CO2 scattering peaks (4.15–4.26 μm), multilobe 13 CO 2 bands (4.35–4.43 μm), and CO 2 biphonon and triphonon modes (4.80–5.25 μm). Our measurements show that CO 2 and CO are concentrated on the trailing hemispheres of the inner moons Ariel and Umbriel, potentially supporting a radiolytic production hypothesis, consistent with prior ground-based results. However, many of the identified spectral features are only observed in thick crystalline ice deposits measured in the laboratory, which may be difficult to form via radiolysis of carbon-bearing material mixed in icy regoliths. Similarly, the data exhibit weak 4.02 and 4.40 μm bands, hinting at the presence of carbonate minerals and 13 CO 2 clathrates, respectively, possibly formed in the interiors of these moons. Furthermore, JWST has revealed that CO 2 is widespread at Uranus, present in its system of rings, ring moons, and irregular satellites, consistent with its largest moons accreting CO 2 and other carbon oxides from the Uranian subnebula. We conclude that exposed carbon oxides are potentially native, with their surface distributions shaped by charged particle irradiation and seasonal sublimation–condensation cycles.

Ice spectroscopy↗
DOE OSTI2026

A Novel Segmentation Algorithm for the ARM User Facility All-Sky Imagers Using Machine Learning Applications

Cloud cover plays a pivotal role in modulating the Earth's energy budget through the reflection of incoming solar radiation and the trapping of outgoing longwave radiation. Ground-based all-sky imagers offer an objective assessment of cloud cover that can be used to estimate solar irradiance, classify cloud types, track cloud movement, and serve as a benchmark 10 for the evaluation of satellite and reanalysis data products. The Atmospheric Radiation Measurement (ARM) user facility has utilized all-sky imagers for more than 25 years to monitor cloud cover and augment its comprehensive suite of atmospheric measurements. Following the retirement of its Total Sky Imager (TSI), ARM recently deployed the TSI’s successor, the All Sky Imager (ASI-16 camera systems). To provide a smooth transition and continuity to the vast amount of knowledge gathered by the TSI over the years, while addressing typical deployment issues, we developed a novel pixel segmentation algorithm, 15 the ASI Sky Cover (ASISKYCOVER). ASISKYCOVER builds on the different strengths and properties of the TSI processing algorithm while integrating machine learning techniques, ensuring data validity and accuracy across diverse atmospheric conditions. It enhances cloud cover characterization with new features such as artifact detection and uncertainty quantification. ASISKYCOVER also includes cloud cover estimates for near-zenith (narrow field-of-view) and reduces susceptibility to false detections. This study introduces ASISKYCOVER, details its algorithm framework, and demonstrates its capabilities using a 20 year-long dataset from the ARM Southern Great Plains site. Comparisons with co-located TSI data and other ARM measurements, such as zenith-pointing radars and lidars, are presented, underscoring the ASISKYCOVER’s potential to improve cloud cover analyses and data evaluation efforts, as well as to be integrated into higher-level data products that synergize instrument suites to generate new and insightful information

Silber, Israel↗
NASA NTRS2010

Evaluation of Anomaly Detection Capability for Ground-Based Pre-Launch Shuttle Operations

This chapter will provide a thorough end-to-end description of the process for evaluation of three different data-driven algorithms for anomaly detection to select the best candidate for deployment as part of a suite of IVHM (Integrated Vehicle Health Management) technologies. These algorithms were deemed to be sufficiently mature enough to be considered viable candidates for deployment in support of the maiden launch of Ares I-X, the successor to the Space Shuttle for NASA's Constellation program. Data-driven algorithms are just one of three different types being deployed. The other two types of algorithms being deployed include a "nile-based" expert system, and a "model-based" system. Within these two categories, the deployable candidates have already been selected based upon qualitative factors such as flight heritage. For the rule-based system, SHINE (Spacecraft High-speed Inference Engine) has been selected for deployment, which is a component of BEAM (Beacon-based Exception Analysis for Multimissions), a patented technology developed at NASA's JPL (Jet Propulsion Laboratory) and serves to aid in the management and identification of operational modes. For the "model-based" system, a commercially available package developed by QSI (Qualtech Systems, Inc.), TEAMS (Testability Engineering and Maintenance System) has been selected for deployment to aid in diagnosis. In the context of this particular deployment, distinctions among the use of the terms "data-driven," "rule-based," and "model-based," can be found in. Although there are three different categories of algorithms that have been selected for deployment, our main focus in this chapter will be on the evaluation of three candidates for data-driven anomaly detection. These algorithms will be evaluated upon their capability for robustly detecting incipient faults or failures in the ground-based phase of pre-launch space shuttle operations, rather than based oil heritage as performed in previous studies. Robust detection will allow for the achievement of pre-specified minimum false alarm and/or missed detection rates in the selection of alert thresholds. All algorithms will also be optimized with respect to an aggregation of these same criteria. Our study relies upon the use of Shuttle data to act as was a proxy for and in preparation for application to Ares I-X data, which uses a very similar hardware platform for the subsystems that are being targeted (TVC - Thrust Vector Control subsystem for the SRB (Solid Rocket Booster)).

Martin, Rodney Alexander↗
DOE OSTI2026

Observed Land Surface Influence on Atmospheric Heat and Moisture Profiles During Interstorms

Land-atmospheric (L-A) feedbacks have historically been studied using models whose structure and parameterizations influence outcomes and insights. The representation of L-A feedbacks based on observations alone remains an ongoing challenge for understanding boundary layer development and precipitation. To address this gap, we use ground-based passive remote sensing and in-situ observations to present an analysis of the atmosphere during 103 interstorm soil moisture drydown events spanning nine warm seasons (2016–2024) in the U.S. Southern Great Plains region. By separating events based on local L-A coupling signals and characterizing the profiles of atmospheric heat and moisture to surface energy flux behavior, we investigate the physical mechanisms linking land surface processes to boundary layer development. We find that during interstorm drydowns, the atmospheric column follows a consistent pattern: moisture increases within the boundary layer, peaks near its top, and declines rapidly above, while warming occurs through the depth. Drydowns that shift toward evaporation produce stronger and deeper thermodynamic responses than cases dominated by sensible heating, which are weaker and shallower. Additionally, moisture is accumulated faster within the boundary layer during shorter drydowns, with longer drydowns representing slower, moisture-limited growth. Drydowns with wetter initial soil moisture will sustain stronger moistening within and above the boundary layer, accelerating buoyancy growth and convective potential toward the next storm. These results provide observational evidence linking surface flux evolution to boundary layer thermodynamics and offer a process-level benchmark for evaluating coupled L-A representations in models and demonstrating the influence of soil moisture on short-term weather forecasting skill.

Zhang, M. S. [Massachusetts Inst. of Technology (M↗
DOE OSTI2026

Terrestrial Gamma‐Ray Flash Following Intense Negative Return Stroke Observed With BIMAP‐3D

We report ground-based observations of a terrestrial gamma-ray flash (TGF) associated with a strong negative cloud-to-ground lightning strike (-CG) which occurred near Los Alamos National Laboratory (LANL) in New Mexico, USA. Gamma photons were detected by the Terrestrial High-energy Observations of Radiation (THOR) instrument, developed at the University of California, Santa Cruz, which has been hosted at LANL since 2022. Simultaneous measurements were also made with the 3-Dimensional Broadband Interferometric Mapping and Polarization (BIMAP-3D) system, which includes 3D lightning mapping, two fast antennas, and an additional plastic scintillator. Additional field change waveforms were obtained from the Earth Networks Total Lightning Network (ENTLN). The lightning initiated about 1 km above the ground, leading to a powerful -CG with an ENTLN peak current of −237 kA and bipolar field change matching the recently described “energetic compact stroke” (ECS) shape. The TGF was then observed ∼35 µs after the start of the return stroke. We also observe an electric field pulse likely produced by the TGF either in isolation or by coupling to the lightning channel. Based on modeling of the radiated electric field and photon propagation through the atmosphere we infer that the TGF source was on the order of 1⁢0 17 photons. This TGF and associated lightning are extremely similar to some recently reported ECS TGFs in coastal Japan in winter, but we report the first observation of this phenomenon outside of Japan in a different climate, terrain, and season.

58 GEOSCIENCES↗
DOE OSTI2026

The Vera C. Rubin Observatory Data Preview 1

We present Rubin Data Preview 1 (DP1), the first data from the National Science Foundation–Department of Energy Vera C. Rubin Observatory, comprising raw and calibrated single-epoch images, coadds, difference images, detection catalogs, and ancillary data products. DP1 is based on 1792 optical–near-infrared exposures acquired over 48 distinct nights by the Rubin Commissioning Camera (LSSTComCam) on the Simonyi Survey Telescope at the Summit Facility on Cerro Pachón, Chile in late 2024. DP1 covers ∼15 deg 2 distributed across seven roughly equal-sized noncontiguous fields, each independently observed in six broad photometric bands, ugrizy. The median FWHM of the point-spread function across all bands is approximately 1"14, with the sharpest images reaching about 0." 58. The 5σ point-source depths for coadded images in the deepest field, the Extended Chandra Deep Field South, are u = 24.55, g = 26.18, r = 25.96, i = 25.71, z = 25.07, and y = 23.1. Other fields are no more than 2.2 mag shallower in any band, where they have nonzero coverage. DP1 contains approximately 2.3 million distinct astrophysical objects, of which 1.6 million are extended in at least one band in coadds, and 431 solar system objects, of which 93 are new discoveries. DP1 is approximately 3.5 TB in size and is available to Vera C. Rubin Observatory data rights holders via the Rubin Science Platform, a cloud-based environment for the analysis of petascale astronomical data. While small compared to future LSST releases, its high quality and diversity of data support a broad range of early science investigations ahead of full operations in 2026.

Ground-based astronomy↗
NASA NTRS1984

The Telecommunications and Data Acquisition Report

Tracking and ground-based navigation; communications, spacecraft-ground; station control and system technology; capabilities for new projects; networks consolidation program; and network sustaining are described.

Posner, E. C.↗
NASA NTRSDate not supplied

NASA POWER: Providing Analysis-Ready, Cloud-Optimized Data for AI /ML Training and Applications in Earth Science

As global demand for sustainable development grows, the integration of Earth Observation (EO) data into decision making frameworks has become a primary objective for the scientific community. The NASA Prediction of Worldwide Energy Resources (POWER) project serves as a bridge between NASA EO data and the specialized needs of the renewable energy, sustainable infrastructure and agroclimatology communities. In this poster presentation we will present an overview of POWER data products and services along with its use in diverse research to decision-making workflows. By providing over 40 years of high-resolution historical, hourly and daily solar and meteorological data, POWER transforms satellite observations and global model reanalysis into actionable, Analysis-Ready Dataset (ARD). Currently, the project delivers over 250 industry-friendly parameters to the users from different NASA datasets like CERES SYN1Deg, MERRA-2, and IMERG alongside downscaled CMIP6 climate model data, fulfilling over 16 million requests from 50,000 unique users monthly. To ensure data quality and traceability, these parameters are rigorously validated against the ground-based observations from the Baseline Surface Radiation Network (BSRN) and the Global Surface Summary of the Day (GSOD) – these results will be discussed in the presentation. A newly introduced web-based PaRameter Uncertainty ViEwer (PRUVE) tool will be presented that provides an online validation platform to the users that benchmarks satellite-based and assimilation data products against these surface measurements. To reduce technical barriers to data adoption, POWER data is accessible through RESTful APIs, ESRI ArcGIS Image Services, a web-based Data Access Viewer tool, allowing users to visualize, validate and apply the dataset. For efficient data delivery POWER data is cloud-optimized into Zarr datastore accessible through NASA managed Amazon S3 ensures high-performance allowing users to integrate EO directly into operational pipelines. These customized services will be presented. Use cases from application will be presented from the energy sector - such as for design of generation systems, performance monitoring of solar power plants, in infrastructure sector- optimizing building energy efficiency and thermal comfort, in agriculture – such as driving crop simulation and yield forecasting models to enable climate resilient farming. Furthermore, the shift toward machine learning (ML) in EO research that has positioned POWER as a key provider for training datasets which will be discussed. Use-cases will be presented to showcase how NASA data is enabling the development of predictive tools for climate variability and resource management. The poster will present POWER’s future plans including technology development to enhance data traceability and reproducibility and improving I/O performance to support the rapid integration of new EO products, ensuring that POWER remains a robust scalable backend for the evolving landscape of AI-driven Earth Science. Additionally, POWER is developing an AI Agent and an MCP-Server to enable industry AI-Agentic workflows.

Neha Khadka↗
NASA NTRSDate not supplied

Preliminary Assessment of the Impact on the V-Band Oxygen Channels From Satellite Communication Uplinks

We calculate the percentage of time that an ATMS-like instrument [1] will be illuminated by the uplink beam of one of the proposed V-band communication system and estimate the damage resulting from such exposure. Using a combination of openly available information and educated guesses about the location and characteristics of the up/down link terminals, we constructed the ground segment of a hypothetical high-speed communication network. The space segment of the network was constructed from the orbital data of the existing Starlink constellation [2] of 6223 communication satellites (comsats) which is used as strawman to represent any other possible constellation of communication satellites. It is shown that without a very delicate balance of frequency allocations (science vs telecommunications), coupled with extremely steep and deep bandpass-defining filters, and strict adherence to the agreed limits (i.e. no out-of-band transmissions) the deployment of the telecommunication network leads to almost-complete loss of some important geophysical data. For the analysis we use the spectral characteristics of the ATMS instrument with the ephemeris for the NOAA-21 satellite [3]. The analysis is conducted for the USA and the simulation covers 8 consecutive days in July 2024. Effective and accurate microwave remote sensing of the atmosphere depends on the availability of interference-free spectrum windows at frequencies which are prescribed by physical processes [e.g. 4]. The family of resonant lines of the oxygen molecule near 60 GHz provides a unique opportunity to sample the vertical distribution of temperature and density from space, and it has been exploited for weather and climate studies from polar-orbiting satellites since 1978 (MSU on TIROS-N [5]). It remains a staple in the payloads operated by Russia, China, USA, Japan, France, India, UK, Ukraine [6] which are built around a common blueprint: a few wide-band (hundreds of MHz) channels around 50 GHz to sample the atmosphere and the surface while several more channels with high spectral resolution (few MHz) sample the individual resonant lines. Accurate retrieval of the environmental parameters depends upon the data provided by both sets of channels, and the their location in frequency space is not arbitrary and cannot be altered at will [7, 8]. The introduction of 5G technology in 2019 has driven telecommunication companies to request more bandwidth to be dedicated to their devices. This additional bandwidth is only available in spectral regions traditionally reserved for environmental and astrophysical research, such as the V-band between 50 and 60 GHz for up/downlink between satellites in low-earth orbits and terminals connected to fiberoptics network for distribution to high-speed local internet services. The power broadcast by the uplink communication leg is many orders of magnitude greater than the natural thermal signal emitted from the Earth scene. If the ground antenna were to perfectly align with the passive instrument’s antenna, the spaceborne receiver would suffer permanent, irreparable damage. While a direct boresight-to-boresight conjunction is extremely unlikely (even with a large constellation of satellites the fraction of the celestial sphere occupied by the satellites remains minuscule) the finite size of the ground station’s antenna beam in the sky suggests that the ATMS will be in the near background (as seen from the ground station) of one of the communication satellites and will be illuminated by either the main lobe or the near sidelobes of the uplink antenna more often than it is desirable. For our analysis we first calculate the position of the ATMS with respect to each of the ground stations at a resolution of 0.2 sec, then calculate the position of each of the comsats which are at least 25 deg above the station’s local horizon; finally we calculate the angle between the line-of-sight of the ATMS and the line-of-sight of the comsat. We assume that the gain pattern of the ground station is circularly symmetric; the angle-off-station-boresight then provides an attenuation of the uplink power which we use to assess the likely effect upon the passive instrument’s operations. We assume that each ground station can communicate with all the comsats in its field of view; this implies that, on average, a ground station can engage with 46 comsats simultaneously. The analysis is repeated for the case when the uplink broadcast within the ATMS passive channels (in-band scenario) and for the case when the uplink is limited to frequencies adjacent to the ATMS channels (out-of-band scenario). The antenna of the ground station is modelled as having a HPBW (Half-Power Beam Width) of 0.16 deg and EIRP (Equivalent Isotropic Radiated Power) of 70 dBW. We account for the geometric dissipation of the signal caused by the satellite orbital altitude, the attenuation induced by atmospheric gasses at 51 GHz and the mismatch between the circular polarization of the ground-based transmitting antenna and the linear polarization of the satellite-borne receiving antenna. The damages on ATMS are estimated from bench-level measurement conducted at the ATMS’ manufacturer facilities [unpublished].

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