Search NASA⌕ Search

SEARCH · Search NASA

Results for “WEATHER”

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 613 records · Page 34

Development of typical solar years and typical wind years for efficient assessment of renewable energy systems across the U.S.

Weather data plays a critical role in renewable energy analysis. Compared to using multiple Actual Meteorological Years, simulations using a single typical year require significantly fewer computational resources. Previous efforts to create typical weather datasets for renewable energy analysis either lack justified or optimized strategies for selecting and weighting different weather parameters or are limited to a few specific locations. Here, in this study, we developed a dataset comprising Typical Solar Years (TSYs) and Typical Wind Years (TWYs) for over 2000 locations across the U.S., based on data from NASA's POWER project. The strategies for creating TSYs and TWYs were optimized based on the simulated outputs of various PV systems and wind turbines in 16 representative cities. This dataset provides an efficient means for the rapid evaluation and optimization of renewable energy systems throughout the entire U.S. Additionally, the optimal strategies identified in this study can be directly applied to create near-optimal TSYs and TWYs for most locations worldwide. However, readers can also employ the optimization approach presented in this work to develop optimal strategies tailored for particular regions.

NASA POWER↗

Investigating the effects of cooperative transmission expansion planning on grid performance during heat waves with varying spatial scales

There is growing recognition of the advantages of interregional transmission capacity to decarbonize electricity grids. A less explored benefit is potential performance improvements during extreme weather events. This study examines the impacts of cooperative transmission expansion planning using an advanced modeling chain to simulate power grid operations of the United States Western Interconnection in 2019 and 2059 under different levels of collaboration between transmission planning regions. Two historical heat waves in 2019 with varying geographical coverage are replayed under future climate change in 2059 to assess the transmission cooperation benefits during grid stress. The results show that cooperative transmission planning yields the best outcomes in terms of reducing wholesale electricity prices and minimizing energy outages both for the whole interconnection and individual transmission planning regions. Compared to individual planning, cooperative planning reduces wholesale electricity prices by 64.3 % and interconnection-wide total costs (transmission investments + grid operations) by 34.6 % in 2059. It also helps decrease greenhouse gas emissions by increasing renewable energy utilization. However, the benefits of cooperation diminish during the widespread heat wave when all regions face extreme electricity demand due to higher space cooling needs. Despite this, cooperative transmission planning remains advantageous, particularly for California Independent System Operator with significant diurnal solar generation capacity. This study suggests that cooperation in transmission planning is crucial for reducing costs and increasing reliability both during normal periods and extreme weather events. It highlights the importance of optimizing the strategic investments to mitigate challenges posed by wider-scale extreme weather events of the future.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Benefits assessment of cool skin and ventilated cavity skin: Saving energy and mitigating heat and grid stress

This study assessed the energy-saving and climate-adaptive potential of cool skin and ventilated cavity skin facade technologies in Seoul's high-rise apartment buildings. We created weather scenarios for historical, mid-term future, and long-term future conditions using Coordinated Regional Downscaling EXperiment (CORDEX) method. Building energy simulations were conducted on a South Korean high-rise apartment model to evaluate their performance under different weather conditions. The results indicate that cool skin and ventilated cavity skin technologies can save cooling energy during summers but lead to heating energy penalties in winters. Ventilated cavity skin outperforms cool skin, offering better cooling energy savings and reduced heating penalties. Combining both technologies yields the highest overall energy savings, with 7 %, 9 %, and 10 % cooling energy savings for cool skin, ventilated cavity skin, and the combined package, respectively. However, cool skin increases heating energy consumption by 5 %, while ventilated cavity skin has minimal impact on heating energy. These envelope technologies also reduce peak electricity demand by at least 5 %, 8 %, and 9 %, respectively. They contribute to heat stress reduction, enhance resilience, and decrease extreme heat risks for occupants during power outages by at least 18 % under various weather conditions. Considering the prevalence of aging high-rise apartments in South Korea, adopting these envelope renovation strategies can effectively reduce cooling loads, enhance thermal comfort, and boost resilience under future climates, while avoiding costly reconstruction.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Envelope-driven comfort risk in residential demand response

Residential demand response (DR) is a valuable resource for grid reliability, but remains challenging because the highly heterogeneous residential building stock leads to widely varying and hard-to-predict load and comfort responses during DR events. Although prior research has estimated the technical potential of DR-capable technologies for achieving energy demand savings, little is known about how they affect thermal comfort. In particular, it remains unclear how indoor thermal conditions due to DR depend on the thermal envelope characteristics of the housing stock. To address this gap, this study provides a systematic, location-specific assessment of indoor thermal performance during DR-events across the US housing stock using both typical DR weather data and detailed building metadata. We evaluate how envelope characteristics influence indoor temperatures during realistic simulated summer and winter DR events across 37 US locations, applying both temperature threshold and rate of temperature change criteria to estimate region-level probabilities of discomfort. Additionally, we show the impact of distinct weather patterns that intensify or abate thermal stress on comfort outcomes. Results show a near-universal overheating risk in summer DR events, where comfort outcomes are strongly influenced by rapid risk of comfort violations. In contrast, overall winter DR discomfort risk is lower, risk escalation is more gradual and shows greater sensitivity to event duration. These findings offer a data-driven quantification of comfort risk across diverse climates and building envelopes, demonstrating the need for region-specific DR scheduling and discomfort mitigation strategies tailored to local weather patterns and the performance of existing residential buildings.

Demand response↗

Organic sulfur fluxes and geomorphic control of sulfur isotope ratios in rivers

Pyrite oxidation plays a critical role in the relationship between weathering and climate, and its impact on the global carbon cycle has previously been constrained through inversion models utilizing observations of river sulfate ($SO^{2–}_{4}$) and its 34 S/ 32 S isotope ratio (δ 34 S SO4 ). However, measurements from some rivers have suggested that SSO4 can be substantially impacted by processes such as microbial sulfate reduction and/or sulfur assimilation and cycling, rather than simply reflecting a weighted mixture of lithologic sulfur sources. To study the prevalence and controls on $SO^{2–}_{4}$ transformations, in this study we measured dissolved major element concentrations and δ 34 S SO4 in river water samples from throughout western Iceland. Our analyses focused on samples from a small catchment hosting the Efri Haukadalsá river, a system with relatively uniform and isotopically constrained basaltic bedrock. We also measured sediment δ 34 S and sulfur speciation using sulfur K-edge X-ray absorption spectroscopy on sediment and vegetation samples from this catchment. Values of dissolved δ 34 S SO4 in the Efri Haukadalsá ranged from 2.5‰ to 23.7‰ and had a linear relationship with Cl – /$SO^{2–}_{4}$ ratios, indicating that $SO^{2–}_{4}$ predominantly derived from basalt weathering and meteoric precipitation. The lower δ 34 S SO4 values were found in fluvial valleys with V-shaped cross sections, while higher values of δ 34 S SO4 occurred in U-shaped, glacially eroded valleys with thick alluvial fills blanketing the valley floor. Spectroscopic observations identified organic sulfur phases in suspended river sediment, floodplain deposits, and vegetation. Mass balance calculations quantified the organic sulfur flux as less than 10% of $SO^{2–}_{4}$ export, and sediment δ 34 S values were comparable to river δ 34 S SO4 . We interpreted these isotopic and chemical patterns as reflecting differences in the availability of unweathered bedrock across the Efri Haukadalsá catchment, with V-shaped valleys having greater access to fresh sulfide-bearing minerals than alluviated U-shaped valleys; this interpretation is in contrast to one in which the elevated δ 34 S SO4 values reflect fractionation during sulfur transformations along alluvial reaches. These results validated the application of river inversion models for constraining weathering fluxes and affirmed that pyrite oxidation globally, even in the presence of river sulfur cycling, modulates the abundance of atmospheric carbon dioxide.

54 ENVIRONMENTAL SCIENCES↗

Variational data augmentation for a learning-based granular predictive model of power outages

As the trend in climate change continues, extreme weather events are expected to occur with increasing frequency and severity and pose a significant threat to the electric power infrastructure. Regardless of the efforts a utility puts towards hardening the grid, storm-induced damage to the utility assets such as cables and distributed energy resources (DERs) that are particularly vulnerable to such events is unavoidable. Access to a highly granular, in space and time, outage forecasting tool with long lead times (i.e., days ahead) will enhance the efficiency of service restoration efforts. Here, in this study, we propose to develop and implement a multi-model framework as an operational tool based on a granular and multi-day outage forecasting model using operational numerical weather prediction model forecasts and detailed component outage information. An innovative two-layered recurrent neural network, i.e., a long-short-term-memory (LSTM)-based variational autoencoder (VAE) framework and a sliding window are used to address the uneven distribution of different types of weather events and make better use of the time-series data. Case studies are performed to demonstrate the performance of the new framework.

54 ENVIRONMENTAL SCIENCES↗

The evolution of soil microstructure and micromineralogy along a soil age gradient on the Galápagos Islands (Ecuador)

The islands of the Galápagos archipelago are of different ages due to the combination of a geostationary volcanic hotspot and the eastward movement of the Nazca tectonic plate. Taking advantage of this, a soil chronosequence (1.5–1070 ka) has recently been established covering four of the islands. This was used to investigate the temporal development of soil microstructure and micromineralogy using micromorphological methods in combination with synchrotron-based mineralogical and geochemical microanalyses. Along the chronosequence, the microstructure changed from intergrain microaggregates in the young soils to angular blocky microaggregates in the older soils. In the young soils, a high amount of vitric scoria and weatherable minerals occur, but they quickly disappear with age, and micromass increased fast. The micromorphological studies as well as micro-XRD and micro-XRF revealed increasing heterogeneity of soil microstructure and micromineralogy due to weathering and pedogenic processes until intermediate soil age. In the oldest soils, the microstructure became more uniform again, de-mixing pedofeatures like clay coatings have completely disappeared, and kaolinite, hematite and gibbsite dominate the mineralogical composition. Our study shows that the development of soil microstructure mirrors macroscopic soil profile development showing increasing differentiation until intermediate developmental stages and receding heterogeneity in highly weathered soils.

54 ENVIRONMENTAL SCIENCES↗

Impact of environmental variables on the degradation of photovoltaic components and perspectives for the reliability assessment methodology

Backsheet cracking has been a major issue observed in the field; however, standardized qualification tests, such as IEC61215, are inadequate to reliably identify such failures of PV modules due to the lack of the critical weathering factors applied sequentially or in combination, such as those found in the service environments. To address this problem, in this work we investigated the effects of various environmental variables on the degradation and failure behaviors of the polyamide-based backsheet in PV modules retrieved from five different locations, encompassing a variety of climates, including humid subtropical, hot-summer Mediterranean, tropical savanna climate and hot arid. The correlations between the degradation indicators and the weathering variables were further demonstrated by principle components analysis (PCA). We found strong relationships between: carbonyl formation and reflected solar radiation; hydroxyl formation and module temperature; yellowness and NO2 concentration, while no simple correlation could be found between a specific weathering factor and cracking. By introducing additional stress factors to the aged polyamide-based backsheet films with the novel 'fragmentation test', we successfully reproduced the field cracking behaviour. This study has demonstrated that different degradation modes of PV components respond differently to the environmental stresses encountered in service. Thereby, any accelerated laboratory test based on a single set condition or lacking key environmental variables would be inadequate to assess the long-term performance of PV modules and components. A new reliability-based methodology is proposed to quantitatively link laboratory testing with field results for the service life prediction of PV materials.

14 SOLAR ENERGY↗

Characterizing photovoltaic backsheet adhesion degradation using the wedge and single cantilever beam tests, Part II: Accelerated tests

Photovoltaic (PV) backsheets provide critical moisture, mechanical, and electrical insulation to the backside of PV modules, but their continued functionality depends upon their ability to remain well adhered over years of harsh environmental exposure. A study of adhesive strength was conducted on several PV backsheet types exposed to indoor accelerated weathering. Two adhesion tests – the wedge test and single cantilever beam test – were used to measure adhesion energy in four backsheets: two with fluoropolymer-based outer (airside) layers – polyvinyl fluoride (PVF), polyvinylidene fluoride (PVDF) – and two with non-fluoropolymer-based outer layers–polyamide (PA) and polyethylene terephthalate (PET). The effects of changes in temperature, ultraviolet (UV) irradiance, relative humidity, and a periodic water spray were studied. The PET-, PVF- and PVDF-based backsheets all showed instances of debonding in an adhesive layer, which is commonly reported. Furthermore, for the PA-, PET-, and PVDF-based backsheets, adhesion energy dropped fairly rapidly with exposure, reaching very low levels by 4000 h. The PVF-based backsheet was relatively robust to weathering. Pull-off of an outer chalking layer in the PA- and PET-based backsheets suggested a sensitivity to UV. Adhesion in these two backsheets was also highly sensitive to changes in moisture level. Changes in UV irradiance and temperature did not show a statistically significant effect on adhesion loss for the exposure levels used. The present work is part of a two-part adhesion study on both field-weathered and indoor-exposed backsheets, and forms a basis for understanding adhesion degradation across a variety of backsheet types and degradation factors.

14 SOLAR ENERGY↗

Upper Troposphere Smoke Injection From Large Areal Fires

Abstract Large areal fires, such as those ignited following a nuclear detonation, can inject smoke into the upper troposphere and lower stratosphere. Detailed fire simulations allow for assessment of how local weather interacts with these fires and affects smoke lofting. In this study, we employ the fire simulation package in the Weather Research and Forecasting (WRF‐Fire) model, Version 4.0.1, to explore how smoke lofting from a fire burning a homogeneous fuel bed changes with varying local winds, relative humidity, and atmospheric boundary‐layer stability for two different‐sized areal fires. The presence of moisture has the greatest influence on the results by raising the altitude of lofting, while faster wind speeds dampen lofting and lower the injection height. Stably stratified conditions inhibit plume propagation compared with neutrally stratified conditions, although the impact of stability is not as strong as that of moisture and winds. These findings highlight the importance of using an appropriate atmospheric profile when simulating large fires, as the local weather can have a meaningful influence on smoke lofting.

54 ENVIRONMENTAL SCIENCES↗

Fewer Troughs, Not More Ridges, Have Led to a Drying Trend in the Western United States

High-amplitude ridges can enforce heat-trapping systems that persist through an entire season, contributing to drought events. However, the impacts of day-to-day weather system changes at the meso- and synoptic-scale are also important, albeit less well studied. Here, we identify five weather types (WTs) from 500-hPa geopotential height anomalies. These categories include WT4, which represents ridges and associated dry and warm anomalies, and WT3, which characterizes troughs and associated wetter- and colder-than-normal conditions and is the largest contributor to precipitation in the western U.S. While no discernable trend is evident for WT4 conditions, WT3 conditions have undergone a distinctive decrease in frequency at both annual and seasonal scales, thus a general drying trend across the west during this time period may be more significantly associated with fewer troughs rather than more ridges. Attribution analysis reveals that this decrease in wetter and colder weather is a likely result of anthropogenic forcing.

54 ENVIRONMENTAL SCIENCES↗

Modeling and observations of North Atlantic cyclones: Implications for U.S. Offshore wind energy

To meet the Biden-Harris administration's goal of deploying 30 GW of offshore wind power by 2030 and 110 GW by 2050, expansion of wind energy into U.S. territorial waters prone to tropical cyclones (TCs) and extratropical cyclones (ETCs) is essential. This requires a deeper understanding of cyclone-related risks and the development of robust, resilient offshore wind energy systems. Here, this paper provides a comprehensive review of state-of-the-science measurement and modeling capabilities for studying TCs and ETCs, and their impacts across various spatial and temporal scales. We explore measurement capabilities for environments influenced by TCs and ETCs, including near-surface and vertical profiles of critical variables that characterize these cyclones. The capabilities and limitations of Earth system and mesoscale models are assessed for their effectiveness in capturing atmosphere–ocean–wave interactions that influence TC/ETC-induced risks under a changing climate. Additionally, we discuss microscale modeling capabilities designed to bridge scale gaps from the weather scale (a few kilometers) to the turbine scale (dozens to a few meters). We also review machine learning (ML)-based, data-driven models for simulating TC/ETC events at both weather and wind turbine scales. Special attention is given to extreme metocean conditions like extreme wind gusts, rapid wind direction changes, and high waves, which pose threats to offshore wind energy infrastructure. Finally, the paper outlines the research challenges and future directions needed to enhance the resilience and design of next-generation offshore wind turbines against extreme weather conditions.

17 WIND ENERGY↗

Super-Resolution for Renewable Energy Resource Data with Climate Change Impacts (Sup3rCC)

The Super-Resolution for Renewable Energy Resource Data with Climate Change Impacts (Sup3rCC) data is a collection of 4km hourly wind, solar, temperature, humidity, and pressure fields for the contiguous United States under various climate change scenarios. Sup3rCC is downscaled Global Climate Model (GCM) data. The downscaling process was performed using a generative machine learning approach called sup3r: Super-Resolution for Renewable Energy Resource Data (linked below as "Sup3r GitHub Repo"). The data includes both historical and future weather years, although the historical years represent the historical climate, not the actual historical weather that we experienced. You cannot use Sup3rCC data to study historical weather events, although other sup3r datasets may be intended for this. The Sup3rCC data is intended to help researchers study the impact of climate change on energy systems with high levels of wind and solar capacity. Please note that all climate change data is only a representation of the possible future climate and contains significant uncertainty. Analysis of multiple climate change scenarios and multiple climate models can help quantify this uncertainty.

Array↗

Residential Natural Gas Demand Response Potential during Extreme Cold Events in Electricity-Gas Coupled Energy Systems

In regions where natural gas is used for both power generation and heating buildings, extreme cold weather events can place the electrical system under enormous stress and challenge the ability to meet residential heating and electric demands. Residential demand response has long been used in the power sector to curtail summer electric load, but these types of programs in general have not seen adoption in the natural gas sector during winter months. Natural gas demand response (NG-DR) has garnered interest given recent extreme cold weather events in the United States; however, the magnitude of savings and potential impacts—to occupants and energy markets—are not well understood. We present a case-study analysis of the technical potential for residential natural gas demand response in the northeast United States that utilizes diverse whole-building energy simulations and high-performance computing. Our results show that NG-DR applied to residential heating systems during extreme cold-weather conditions could reduce natural gas demand by 1–29% based on conservative and aggressive strategies, respectively. This indicates a potential to improve the resilience of gas and electric systems during stressful events, which we examine by estimating the impact on energy costs and electricity generation from natural gas. We also explore relationships between hourly indoor temperatures, demand response, and building envelope efficiency.

03 NATURAL GAS↗

Predicting Water Cycle Characteristics from Percolation Theory and Observational Data

The fate of water and water-soluble toxic wastes in the subsurface is of high importance for many scientific and practical applications. Although solute transport is proportional to water flow rates, theoretical and experimental studies show that heavy-tailed (power-law) solute transport distribution can cause chemical transport retardation, prolonging clean-up time-scales greatly. However, no consensus exists as to the physical basis of such transport laws. In percolation theory, the scaling behavior of such transport rarely relates to specific medium characteristics, but strongly to the dimensionality of the connectivity of the flow paths (for example, two- or three-dimensional, as in fractured-porous media or heterogeneous sediments), as well as to the saturation characteristics (i.e., wetting, drying, and entrapped air). In accordance with the proposed relevance of percolation models of solute transport to environmental clean-up, these predictions also prove relevant to transport-limited chemical weathering and soil formation, where the heavy-tailed distributions slow chemical weathering over time. The predictions of percolation theory have been tested in laboratory and field experiments on reactive solute transport, chemical weathering, and soil formation and found accurate. Recently, this theoretical framework has also been applied to the water partitioning at the Earth’s surface between evapotranspiration, ET, and run-off, Q, known as the water balance. A well-known phenomenological model by Budyko addressed the relationship between the ratio of the actual evapotranspiration (ET) and precipitation, ET/P, versus the aridity index, ET 0 /P, with P being the precipitation and ET 0 being the potential evapotranspiration. Existing work was able to predict the global fractions of P represented by Q and ET through an optimization of plant productivity, in which downward water fluxes affect soil depth, and upward fluxes plant growth. In the present work, based likewise on the concepts of percolation theory, we extend Budyko’s model, and address the partitioning of run-off Q into its surface and subsurface components, as well as the contribution of interception to ET. Using various published data sources on the magnitudes of interception and information regarding the partitioning of Q, we address the variability in ET resulting from these processes. The global success of this prediction demonstrated here provides additional support for the universal applicability of percolation theory for solute transport as well as guidance in predicting the component of subsurface run-off, important for predicting natural flow rates through contaminated aquifers.

54 ENVIRONMENTAL SCIENCES↗

PyDDA: A Pythonic Direct Data Assimilation Framework for Wind Retrievals

This software assimilates data from an arbitrary number of weather radars together with other spatial wind fields (eg numerical weather forecasting model data) in order to retrieve high resolution three dimensional wind fields. PyDDA uses NumPy and SciPy’s optimization techniques combined with the Python Atmospheric Radiation Measurement (ARM) Radar Toolkit (Py-ART) in order to create wind fields using the 3D variational technique (3DVAR). PyDDA is hosted and distributed on GitHub at https://github.com/openradar/PyDDA. PyDDA has the potential to be used by the atmospheric science community to develop high resolution wind retrievals from radar networks. These retrievals can be used for the evaluation of numerical weather forecasting models and plume modelling. This paper shows how wind fields from 2 NEXt generation RADar (NEXRAD) WSR-88D radars and the High Resolution Rapid Refresh can be assimilated together using PyDDA to create a high resolution wind field inside Hurricane Florence.

54 ENVIRONMENTAL SCIENCES↗

Mastering Workforce Outreach and Engagement

To meet the goals for homes weatherized with the $3.5 billion in Bipartisan Infrastructure Law funds, weatherization will require significant expansion of its workforce. This hands-on session will explore ready-to-use workforce outreach and engagement tools designed to empower your workforce development efforts and equip you with the knowledge and skills needed to maximize the impact of these essential tools in advancing workforce development within weatherization.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION,↗

Advancing ocean monitoring and knowledge for societal benefit: the urgency to expand Argo to OneArgo by 2030

The ocean plays an essential role in regulating Earth’s climate, influencing weather conditions, providing sustenance for large populations, moderating anthropogenic climate change, encompassing massive biodiversity, and sustaining the global economy. Human activities are changing the oceans, stressing ocean health, threatening the critical services the ocean provides to society, with significant consequences for human well-being and safety, and economic prosperity. Effective and sustainable monitoring of the physical, biogeochemical state and ecosystem structure of the ocean, to enable climate adaptation, carbon management and sustainable marine resource management is urgently needed. The Argo program, a cornerstone of the Global Ocean Observing System (GOOS), has revolutionized ocean observation by providing real-time, freely accessible global temperature and salinity data of the upper 2,000m of the ocean (Core Argo) using cost-effective simple robotics. For the past 25 years, Argo data have underpinned many ocean, climate and weather forecasting services, playing a fundamental role in safeguarding goods and lives. Argo data have enabled clearer assessments of ocean warming, sea level change and underlying driving processes, as well as scientific breakthroughs while supporting public awareness and education. Building on Argo’s success, OneArgo aims to greatly expand Argo’s capabilities by 2030, expanding to full-ocean depth, collecting biogeochemical parameters, and observing the rapidly changing polar regions. Providing a synergistic subsurface and global extension to several key space-based Earth Observation missions and GOOS components, OneArgo will enable biogeochemical and ecosystem forecasting and new long-term climate predictions for which the deep ocean is a key component. Driving forward a revolution in our understanding of marine ecosystems and the poorly-measured polar and deep oceans, OneArgo will be instrumental to assess sea level change, ocean carbon fluxes, acidification and deoxygenation. Emerging OneArgo applications include new views of ocean mixing, ocean bathymetry and sediment transport, and ecosystem resilience assessment. Implementing OneArgo requires about $100 million annually, a significant increase compared to present Argo funding. OneArgo is a strategic and cost-effective investment which will provide decision-makers, in both government and industry, with the critical knowledge needed to navigate the present and future environmental challenges, and safeguard both the ocean and human wellbeing for generations to come.

ARGO↗