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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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At least 37 records · Page 2

Weather Data from BSEC Weather Stations

This dataset provides hourly measurements of temperature, humidity, rainfall, wind, and sunlight at Ambient Weather and OttHydro stations across Baltimore city. These surface weather stations were deployed by the Baltimore Social-Environmental Collaborative (BSEC) Urban Integrated Field Laboratory (UIFL) project, funded by the Department of Energy (DOE). This dataset will be periodically updated to include more stations and recent observations when available. Data File Information This dataset contains surface weather measurements data in comma-separated value (CSV) format and documents that describe the weather stations, locations, and measured parameters and units. data/BSEC-[STATIONID]_[SENSORTYPE]_hourly_[YEAR].csv Surface weather measurements data in CSV format, where STATIONID indicates the weather station, SENSORTYPE is the type of weather station ('AWS' = Ambient Weather Station and 'OTT' = 'OttHydro Station'), and YEAR indicate the year in which the measurements were made. Example data file name: BSEC-AAC_AWS_hourly_2023.csv. documents/Station_Locations.csv This CSV file provides location information and measurement start date for each surface weather station. documents/Weather_Station_Descriptions.pdf This document provides detailed description of the instruments along with their setup and accuracy of measurement. documents/File_Parameters.pdf This document describes the surface weather parameters and units of measurement.

Ambient Weather Stations↗

Understanding the Computing and Analysis Needs for Resiliency of Power Systems from Severe Weather Impacts

As the frequency and intensity of severe weather has increased, its effect on the electric grid has manifested in the form of significantly more and larger outages in the United States. This has become especially true for regions that were previously isolated from weather extremes. In this paper, we analyze the weather impacts on the electric power grid across a variety of weather conditions, draw correlations, and provide practical insights into the operational state of these systems. High resolution computational modeling of specific meteorological variables, computational approaches to solving power system models under these conditions, and the types of resiliency needs are highlighted as goal-oriented computing approaches are being built to address grid resiliency needs. An example analysis correlating outages to 1km day-ahead weather from two historical winter storms, calculated on a large cluster using a combination of interpolated and extrapolated inputs from multiple instrumented sites to workflows that produce primary meteorological outputs, is shown as initial proof of concept.

analysis↗

Predicting sedimentary bedrock subsurface weathering fronts and weathering rates

Although bedrock weathering strongly influences water quality and global carbon and nitrogen budgets, the weathering depths and rates within subsurface are not well understood nor predictable. Determination of both porewater chemistry and subsurface water flow are needed in order to develop more complete understanding and obtain weathering rates. In a long-term field study, we applied a multiphase approach along a mountainous watershed hillslope transect underlain by marine shale. Here we report three findings. First, the deepest extent of the water table determines the weathering front, and the range of annually water table oscillations determines the thickness of the weathering zone. Below the lowest water table, permanently water-saturated bedrock remains reducing, preventing deeper pyrite oxidation. Secondly, carbonate minerals and potentially rock organic matter share the same weathering front depth with pyrite, contrary to models where weathering fronts are stratified. Thirdly, the measurements-based weathering rates from subsurface shale are high, amounting to base cation exports of about 70 kmol c ha -1 y -1 , yet consistent with weathering of marine shale. Finally, by integrating geochemical and hydrological data we present a new conceptual model that can be applied in other settings to predict weathering and water quality responses to climate change.

58 GEOSCIENCES↗

Machine Learning-Based Investigation of the Associations between Residential Power Consumption and Weather Conditions

Machine learning feature selection analyses were conducted to understand the impact of various weather attributes on power electricity demand and its components in the northwest United States. Load profiles data were obtained from the Northwest Energy Efficiency Alliance (NEEA) and processed to yield hourly load profiles with the same temporal resolution as the weather conditions data obtained from the National Oceanic and Atmospheric Administration (NOAA) for representative weather stations. The data were divided into five seasons; for each season, for each load component, the influences of weather factors were evaluated and quantified using cross-correlation, principal component analysis, and mutual information evaluation; then predictive models were developed based on the ranked/screened factors using the regression tree (RT) approach. After multi-fold cross-validation, the optimal complexity/depth of the regress tree models is found to vary for different load components, and the prediction accuracy using RT and weather data can be higher than 80% for heating and refrigeration, or lower than 30% for vent and cooking. The study provides guidance on improvement of load profile generation, or even serves as a standalone predictive tool for approximating load profiles in balance authorities or climate zones where load profile data is absent.

load composite, load profiling, NEEA, mutual infor↗

NASA GSFC Space Weather Center - Innovative Space Weather Dissemination: Web-Interfaces, Mobile Applications, and More

The NASA GSFC Space Weather Center (http://swc.gsfc.nasa.gov) is committed to providing forecasts, alerts, research, and educational support to address NASA's space weather needs - in addition to the needs of the general space weather community. We provide a host of services including spacecraft anomaly resolution, historical impact analysis, real-time monitoring and forecasting, custom space weather alerts and products, weekly summaries and reports, and most recently - video casts. There are many challenges in providing accurate descriptions of past, present, and expected space weather events - and the Space Weather Center at NASA GSFC employs several innovative solutions to provide access to a comprehensive collection of both observational data, as well as space weather model/simulation data. We'll describe the challenges we've faced with managing hundreds of data streams, running models in real-time, data storage, and data dissemination. We'll also highlight several systems and tools that are utilized by the Space Weather Center in our daily operations, all of which are available to the general community as well. These systems and services include a web-based application called the Integrated Space Weather Analysis System (iSWA http://iswa.gsfc.nasa.gov), two mobile space weather applications for both IOS and Android devices, an external API for web-service style access to data, google earth compatible data products, and a downloadable client-based visualization tool.

Maddox, Marlo↗

Analyzing the Impact of Future Weather Data on Energy Consumption in Weatherization Assistant

This study supports the mission of the U.S. Department of Energy’s Weatherization Assistance Program (WAP), which aims to increase the energy efficiency of dwellings and reduce their total residential expenditures. Specifically, we examine how projected future climate conditions may affect residential building energy performance by integrating future weather data into the National Energy Audit Tool (NEAT). Since WAP evaluates the cost-effectiveness of retrofit measures over lifespans of up to 30 years, accounting for evolving climate conditions is increasingly important. To reflect future household energy demands, this study replaces historically based Typical Meteorological Year (TMY3) weather inputs with Future Typical Meteorological Year (fTMY) datasets derived from global climate model (GCM) projections. A simulation-based framework was established to enable NEAT analysis under future weather conditions. This workflow involves converting EPW-format weather files into JSON inputs compatible with NEAT and generating degree-hour metrics needed for load calculations. The fTMY dataset used in this study was developed by Oak Ridge National Laboratory through downscaling of six GCMs under different emission scenarios and covers the period from 2020 to 2100. In contrast, the TMY3 dataset is based on historical weather data from 1961 to 1990. Simulations were conducted for benchmark single-family prototype buildings across ASHRAE climate zones 1–7, which cover all regions of the U.S. except the subarctic Zone 8 in northern Alaska, evaluating both heating and cooling loads under TMY3 and fTMY conditions. Four foundation types were tested, while heating systems were standardized, as NEAT does not differentiate thermal energy load by HVAC system type in its load calculations. Results show that fTMY weather input consistently yield lower heating loads and higher cooling loads across most locations, aligning with expected climate warming trends. Notably, colder regions such as zones 6A, 6B, and 7 experience marked reductions in heating load, while warmer and transitional zones, such as 2A (Lufkin, TX) and 3C (San Francisco, CA), have substantial increases in cooling loads. Although this study does not directly assess the performance of retrofit measures under future climate conditions, it provides a critical foundation for doing so. By quantifying shifts in baseline (i.e., pre-retrofit case) energy loads between historical and future weather files, the study highlights the importance of integrating climate-responsive data into audit tools. These findings will inform future efforts to evaluate the long-term effectiveness and cost-effectiveness of weatherization measures under changing climate conditions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Relationships between CO 2 , thermodynamic limits on silicate weathering, and the strength of the silicate weathering feedback

Recent studies have suggested that thermodynamic limitations on chemical weathering rates exert a first-order control on riverine solute fluxes and by extension, global chemical weathering rates. As such, these limitations may play a prominent role in the regulation of carbon dioxide levels (pCO 2 ) over geologic timescales by constraining the maximum global weathering flux. In this study, we develop a theoretical scaling relationship between equilibrium solute concentrations and pCO 2 based on equilibrium constants and reaction stoichiometry relating primary mineral dissolution and secondary mineral precipitation. Here, we test this theoretical scaling relationship against reactive transport simulations of chemical weathering profiles under open-and closed-system conditions, representing partially and fully water-saturated regolith, respectively. Under open-system conditions, equilibrium bicarbonate concentrations vary as a power-law function of pCO 2 (y =kx n )where nis dependent on reaction stoichiometry and kis dependent on both reaction stoichiometry and the equilibrium constant. Under closed-system conditions, bicarbonate concentrations vary linearly with pCO 2 at low values and approach open-system scaling at high pCO 2 . To describe the potential role of thermodynamic limitations in the global silicate weathering feedback, we develop a new mathematical framework to assess weathering feedback strength in terms of both (1) steady-state atmospheric pCO 2 concentrations, and (2) susceptibility to secular changes in degassing rates and transient carbon cycle perturbations, which we term 1st and 2nd order feedback strength, respectively. Finally, we discuss the implications of these results for the effects of vascular land plant evolution on feedback strength, the potential role of vegetation in controlling modern solute fluxes, and the application of these frameworks to a more complete functional description of the silicate weathering feedback. Most notably, the dependence of equilibrium solute concentrations on pCO 2 may represent a direct weathering feedback largely independent of climate and modulated by belowground organic carbon respiration.

58 GEOSCIENCES↗

Alaska Native Weatherization Training and Jobs Program. First Steps Toward Tribal Weatherization – Human Capacity Development (Final Report)

The Alaska Native Weatherization Training and Jobs Project expanded weatherization services for tribal members’ homes in southeast Alaska while providing weatherization training and on the job training (OJT) for tribal citizens that lead to jobs and most probably careers in weatherization-related occupations. The program resulted in; (a) 80 Alaska Native citizens provided with skills training in five weatherization training units that were delivered in cooperation with University of Alaska Southeast, in accordance with the U.S. Department of Energy Core Competencies for Weatherization Training that prepared participants for employment in three weatherization-related occupations: Installer, Crew Chief, and Auditor; (b) 25 paid OJT training opportunities for trainees who successfully completed the training course; and (c) employed trained personnel that have begun to rehab on over 1,000 housing units for weatherization.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Degradation-related defect level in weathered silicon heterojunction modules characterized by deep level transient spectroscopy

Commercial silicon heterojunction photovoltaic modules, known as amorphous-silicon-based heterojunction with intrinsic thin-film layer (HIT) modules, show average degradation after 10 years in the field. HIT modules weathered outdoors in Colorado and Florida display mostly uniform decreases in intensity when mapped with photoluminescence (PL) imaging compared to a control module. Flash-table-based current-voltage curves show that degradation is dominated by voltage loss. Samples are cored from each of the modules, and deep level transient spectroscopy (DLTS) detects three electron-trap defect states in all modules with activation energies of electron emission from the defects of 0.07, 0.16, and 0.50 eV. DLTS measurements on the weathered modules show an additional deep-level, electron-trap defect state with an activation energy of 0.51 eV and a trap density of approximately 10 12 cm –3 . The capture rate is measured using varying short filling pulse times, and the resulting capture cross section is estimated to be 1.1x10 –16 cm 2 . The development of the weathering-related defect level correlates to decreases in carrier lifetime, PL intensity, and module voltage. Various depths of the space charge region are probed with increments in applied reverse bias and filling-pulse bias. Furthermore, this DLTS depth profiling shows a trend of trap density increasing with less applied reverse bias, suggesting that the weathering-related defect increases carrier recombination toward the interface between the bulk silicon wafer and the junction-forming amorphous-silicon passivation layers.

14 SOLAR ENERGY↗

Space Weather Forecasting at NASA GSFC Space Weather Research Center

The NASA GSFC Space Weather Research Center (http://swrc.gsfc.nasa.gov) is committed to providing research forecasts and notifications to address NASA's space weather needs - in addition to its critical role in space weather education. We provide a host of services including spacecraft anomaly resolution, historical impact analysis, real-time monitoring and forecasting, tailored space weather alerts and products, weekly summaries and reports, and most recently - video casts. In this presentation, we will focus on how near real-time data (both in space and on ground), in combination with modeling capabilities and an innovative dissemination system called the Integrated Space Weather Analysis System (iSWA http://iswa.gsfc.nasa.gov), enable space weather forecasting and quality space weather products provided by our Center. A few critical near real-time data streams for space weather forecasting will be identified and discussed.

CMEs↗

Evaluation of Extreme Weather Impacts on Utility-scale Photovoltaic Plant Performance in the United States

The global energy system is undergoing significant changes, including a shift in energy generating technologies to more renewable energy sources. However, the dependence of renewable energy sources on local environmental conditions could also increase disruptions in service through exposures to compound, extreme weather events. By fusing three diverse datasets (operations and maintenance tickets, weather data, and production data), this analysis presents a novel methodology to identify and evaluate performance impacts arising from extreme weather events across diverse geographical regions. Text analysis of maintenance tickets identified snow, hurricanes, and storms as the leading extreme weather events affecting photovoltaic plants in the United States. Statistical techniques and machine learning were then implemented to identify the magnitude and variability of these extreme weather impacts on site performance. Impacts varied between event and non-event days, with snow events causing the greatest reductions in performance (54.5%), followed by hurricanes (12.6%) and storms (1.1%). Machine learning analysis identified key features in determining if a day is categorized as low performing, such as low irradiance, geographic location, weather features, and site size. The analysis improves our understanding of compound, extreme weather event impacts on photovoltaic systems, which can inform planning activities, especially as the industry continues to expand into new geographic and climatic regions around the world.

14 SOLAR ENERGY↗

Investigating the role of anhydrous oxidative weathering on sedimentary rocks in the Transantarctic Mountains and implications for the modern weathering of sedimentary lithologies on Mars

We present that alteration of the uppermost surfaces of geologic materials is a pervasive process on planetary surfaces that is dependent upon factors including parent composition and the environment under which alteration is occurring. While rapid and pervasive in hot and humid climates on Earth, chemical weathering of rock surfaces has also been found to dominate in some of Earth's coldest and driest landscapes as well. Specifically, surfaces dominated by resistant fine-grained igneous rocks in the Antarctic preserve evidence of oxidative weathering processes, which represent the initial immature surface alteration processes that stagnate due to the lack of available water and kinetics necessary for the production of more mature alteration phases. In this study, we test the hypothesis that oxidative weathering also dominates the surfaces of sedimentary rocks throughout the Antarctic. We investigated the chemistry and mineralogy of a suite of sedimentary rocks from the Transantarctic Mountains ranging from fine-grained tuffs to coarse-grained sandstones and conglomerates. Additionally, our results show that, like the previously studied fine-grained igneous rocks in the Antarctic, sedimentary rocks generally showed only minor chemical weathering signatures at their surfaces relative to their interiors. However, unlike the igneous rocks in this earlier study, the sedimentary rocks exhibited a wide variety of non-systematic differences between surface and interior compositions. This variability of surface weathering signatures is equally as complex as the physical properties and compositions inherently present within these different sedimentary lithologies. Based on these analyses, it is apparent that oxidative weathering products do not dominate the surfaces of sedimentary rocks throughout the Transantarctic Mountains, which instead exhibit a wide array of weathering signatures that are likely dependent on both lithological and environmental factors. Considering that sedimentary lithologies are widespread across a significant fraction of the martian surface, our results suggest that observed alteration signatures limited to the surfaces of martian sedimentary rocks are most likely to be minor and to vary as a result of the lithological properties of the specific rock unit and not as a result of the widespread influences of the modern cold and dry climatic conditions.

58 GEOSCIENCES↗

Local finite-amplitude wave activity as an objective diagnostic of midlatitude extreme weather

Midlatitude extreme weather events are responsible for a large part of climate related damage, yet our understanding of these extreme events is limited, partly due to the lack of a theoretical basis for midlatitude extreme weather. In this letter, the local finite-amplitude wave activity (LWA) of Huang and Nakamura [2015] is introduced as a diagnostic of the 500-hPa geopotential height (Z500) to characterizing midlatitude weather events. It is found that the LWA climatology and its variability associated with the Arctic Oscillation (AO) agree broadly with the previously reported blocking frequency in literature. There is a strong seasonal and spatial dependence in the trend13 s of LWA in recent decades. While there is no observational evidence for a hemispheric-scale increase in wave amplitude, robust trends in wave activity can be identified at the regional scales, with important implications for regional climate change.

Chen, Gang↗

Extending Terrestrial Weather R2O/O2R to Space Weather at NASA's SPoRT Center

SPoRT (Short-Term Prediction Research and Transition Center)'s R2O/O2R (Research-to-Operations/Operations-to-Research) paradigm that has resulted in 15 plus years of success for terrestrial weather can be applied to space weather challenges. Given strong collaborations with NOAA (National Oceanic and Atmospheric Administration), SWPC (Space Weather Prediction Center), National Weather Service partners and seed-funded testbed activity, there is an opportunity to establish a bridge between NASA research community and operational forecasters for near-Earth applications. Starting local with strong space weather group at MSFC (Marshall Space Flight Center) and MAG4 (Magnetogram Forecast) with opportunities to strategically expand interaction to other groups generating space weather projects within NASA, university, and private sector community, using the Supercomputer for Satellite Simulations and Data Assimilation Studies (S4).

research-to-operations↗

Changes in fire weather climatology under 1.5 °C and 2.0 °C warming

Abstract The 2015 Paris Agreement led to a number of studies that assessed the impact of the 1.5 °C and 2.0 °C increases in global temperature over preindustrial levels. However, those assessments have not actively investigated the impact of these levels of warming on fire weather. In view of a recent series of high-profile wildfire events worldwide, we access fire weather sensitivity based on a set of multi-model large ensemble climate simulations for these low-emission scenarios. The results indicate that the half degree difference between these two thresholds may lead to a significantly increased hazard of wildfire in certain parts of the world, particularly the Amazon, African savanna and Mediterranean. Although further experiments focused on human land use are needed to depict future fire activity, considering that rising temperatures are the most influential factor in augmenting the danger of fire weather, limiting global warming to 1.5 °C would alleviate some risk in these parts of the world.

Son, Rackhun (ORCID:000000023366495X)↗

Multi-Model Future Typical Meteorological (fTMY) Weather Files for nearly every US County

Exploring climate-induced impacts on building energy consumption can provide valuable insights for sustainable energy planning and environmental management in the face of a changing climate. By utilizing future weather data statistically downscaled from the Intergovernmental Panel on Climate Change (IPCC) General Circulation Models (GCMs) from 2020-2100, this paper presents a broadening industry-consensus approach for generating future Typical Meteorological Year (fTMY) weather files through a combination of statistical downscaling and high-performance computing that generalizes across decades, multiple locations for a region, and varying climate models. Furthermore, these fTMY files have been generated for 3,128 US counties for capturing potential weather on a 20-year basis.

Building↗

ORBIT-2 Dataset for Scaling Exascale Vision Foundation Models for Weather and Climate Downscaling

This dataset release corresponds to the work conducted in ORBIT-2: Scaling Exascale Vision Foundation Models for Weather and Climate Downscaling, where large-scale AI methods were applied to improve climate and weather resolution. The collection integrates four widely used, publicly available datasets: ERA5, PRISM, DAYMET, and IMERG. To prepare the data for ORBIT-2 model training and evaluation, we applied a preprocessing pipeline that generates paired low-resolution and high-resolution samples, enabling supervised downscaling experiments. The transformation from coarse to fine scales was performed using bilinear regridding, consistent with the procedures described in WeatherBench2, a community benchmark for weather and climate AI models. This dataset supports the development and evaluation of foundation models designed for weather and climate downscaling at exascale. Additional details on methodology and applications can be found in Wang et al., ORBIT-2 (arXiv:2505.04802, 2025).

54 ENVIRONMENTAL SCIENCES↗