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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Reconstruction of Central European daily weather types back to 1763

Weather type classifications (WTCs) are a simple tool to analyse variations in weather patterns. Long series of WTCs could be used to address decadal changes in weather as a basis for studying changes in variability or extremes or for addressing contributions of sea-surface temperature or external forcings using climate models. However, there is no long series of daily objective weather types (WTs). A new method (Shortest Mahalanobis Distance, SMD) using daily European weather data is developed to reconstruct WTCs back in time. Here the SMD method is applied on the Cluster Analysis of Principal Components (CAP9) classification used by MeteoSwiss. The CAP9 daily WT time series (computed with ERA-40) is used as reference over the 1958–1998 period. Daily data (temperature, mean sea level pressure and pressure tendency) from 13 European stations covering the period 1763–2009 are used for the reconstruction. The reference CAP9 is reduced from nine to seven types so the new daily WTC is called CAP7. As an assessment, CAP7 is compared to the original classification CAP9 and to the same WTs computed with the Twentieth Century Reanalysis (20CR and 20CRv2c). Over the reference period up to 90% of all the daily WTs can be correctly reproduced in the new WTC compared to the original series, with higher reliability in winter than in summer. In addition, the reliability of the classification is increasing from 1763 onward. The annual occurrence of each type reveals some trends, mostly a decrease in the number of cyclonic days and an increase of cyclonic days.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

The impact of depth-dependent water content on steady state weathering and eroding systems

Models for weathering and regolith formation are normally built on the assumption of constant rates of water advection in the zone of water-saturated pores, and constant water content of those pores, but it is common that weathering occurs in the water-unsaturated zone where lateral flow occurs. Hence, water content in pores varies with depth. Here we model mineral weathering profiles while accounting for depth-dependent water content. Like previous models, a mineral equilibrates with water over a length ξ that depends on dissolution and advection rates, but a new lengthscale λ is introduced to describe the decrease of water content with depth. Steady states of the regolith thickness can be attained for any finite λ and non-zero velocity v E of erosion at the land surface. The type of mineral depletion profile developed over geological timescales depends on coupling between weathering and erosion: for slow erosion, a completely developed profile (CDP) is observed, in which the mineral-depleted zone at the top of the regolith has thickness of order λ ; as v E increases, there is a transition to an incompletely developed profile (IDP), in which partial mineral depletion at the land surface is constrained to a narrow range of velocities; when v E exceeds the advance rate of weathering under far from equilibrium conditions, the profile transitions to an unstable regime that exposes bedrock. In general, the reaction front (RF) thickness and the velocity where CPD transitions to IDP depend on the interplay of both water infiltration and chemical equilibration over the timescale of water residence in regolith. The RF thickness roughly equals a correlation length χ defined as half the harmonic average of ξ and λ . In cases of limited water infiltration, water-mineral equilibration is achieved within the length λ , so that the RF thickness is controlled by hydrological properties and is independent of dissolution and advection rates. In the opposite endmember, water infiltrates to large depths and the effects of physical and chemical parameters on RF thickness are the same as in previous geochemical models. The relaxation time for reaching a steady state is shown to be ~ χ / v E . We discuss the effects of physical and chemical parameters in CDPs and IDPs in those endmembers and show an application to a CDP in granitic regolith.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A review of future weather data for assessing climate change impacts on buildings and energy systems

The effectiveness of climate change impact assessments and the development of adaptation strategies depend on the availability of high-quality future weather data. However, significant gaps exist between the needs of the energy research community and the focus of the climate modeling community, primarily due to a historical lack of communication and collaboration between the two groups. Here, to address this issue, this work provides a comprehensive overview of the critical aspects involved in creating future weather data for building and energy system modeling, including emissions scenarios, general circulation models, downscaling methods, categories of future weather data, and uncertainties in climate simulations. Moreover, it critically evaluates the applicability and suitability of various types of future weather data in five key application scenarios: energy use analysis, resilience analysis, HVAC design, utility-scale analysis, and renewable energy analysis. Finally, this work presents recommendations for high-level actions and research directions to foster collaboration between the energy research and climate modeling communities and to promote the integration of future weather data into energy codes and the design practices of buildings and energy systems.

Climate change↗
DOE OSTI2015

Vulnerability and adaptation to severe weather events in the American southwest

Climate change can induce changes in the frequency of severe weather events representing a threat to socio-economic development. It is thus of uttermost importance to understand how the vulnerability to the weather of local communities is determined and how adaptation public policies can be effectively put in place. We focused our empirical analysis on the American Southwest. Results show that, consistently with the predictions of an investment model, economic characteristics signaling local economic growth in the near future decrease the level of vulnerability. We also show that federal governments transfers and grants neither work to support recovery from and adaptation to weather events nor to distribute their costs over a broader tax base. Finally, we show that communities relying on municipal bonds to finance adaptation and recovery policies can benefit from local acknowledgment of the need for such policies and that they do not have to pay lenders a premium for the risk induced by weather events. In conclusion, our findings suggest that determinants of economic growth support lower vulnerability to the weather and increase options for financing adaptation and recovery policies, but also that only some communities are likely to benefit from those processes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Detecting Sub-Micron Space Weathering Effects in Lunar Grains With Synchrotron Infrared Nanospectroscopy

Space weathering processes induce changes to the physical, chemical, and optical properties of space-exposed soil grains. For the Moon, space weathering causes reddening, darkening, and diminished contrast in reflectance spectra over visible and near-infrared wavelengths. The physical and chemical changes responsible for these optical effects occur on scales below the diffraction limit of traditional far-field spectroscopic techniques. Recently developed super-resolution spectroscopic techniques provide an opportunity to understand better the optical effects of space weathering on the sub-micrometer length scale. This paper uses synchrotron infrared nanospectroscopy to examine depth-profile samples from two mature lunar soils in the mid-infrared, 1,500 –700 cm -1 (6.7–14.3 μm). Overall, our findings are broadly consistent with prior bulk observations and theoretical models of space weathered spectra of lunar materials. These results provide a direct spatial link between the physical/chemical changes in space-exposed grain surfaces and spectral changes of space weathered bodies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Aerosols and their Impact on Radiation, Clouds, Precipitation & Severe Weather Events

Aerosols, the tiny particles suspended in the atmosphere, have been in the forefront of environmental and climate change sciences as the primary atmospheric pollutant and external force affecting Earth’s weather and climate. There are two dominant mechanisms by which aerosols affect weather and climate: aerosol-radiation interactions (ARI) and aerosol-cloud interactions (ACI). ARI arises from aerosol scattering and absorption, which alters the radiation budgets of the atmosphere and surface, while ACI is rooted to the fact that aerosols serve as cloud condensation nuclei and ice nuclei. Both ARI and ACI are coupled with atmospheric dynamics to produce a chain of complex interactions with a large range of meteorological variables that influence both weather and climate. Elaborated here are the impacts of aerosols on the radiation budget, clouds (microphysics, structure, and lifetime), precipitation, and severe weather events (lightning, thunderstorms, hail, and tornados). Depending on environmental variables and aerosol properties, the effects can be both positive and negative, posing the largest uncertainties in the external forcing of the climate system. This has considerably hindered our ability in projecting future climate changes and in doing accurate numerical weather predictions.

aerosol↗
DOE OSTI2020

Identification of Worst Impact Zones for Power Grids During Extreme Weather Events Using Q-learning

Both the frequency and intensity of extreme weather events have been trending higher in recent years, leading to significant infrastructure damage in the electric grid. The impact of these extreme weather events is desired to be analyzed and quantified to help transmission and distribution system operators prepare for and prevent significant damage and subsequent loss of power. In this paper, we develop an approach that models the impact of extreme weather on the grid and identifies the worst impact zone using Q-learning (a reinforcement learning approach). The identification results reveal grid vulnerability to weather events and provide insights for system operators to help achieve optimal resource allocation and crew dispatch to minimize the adverse impacts of extreme weather. Simulation studies are conducted on the IEEE 123-node system to demonstrate the performance of the proposed approach.

distribution system↗
DOE OSTI2013

Weather-Corrected Performance Ratio

Photovoltaic (PV) system performance depends on both the quality of the system and the weather. One simple way to communicate the system performance is to use the performance ratio (PR): the ratio of the electricity generated to the electricity that would have been generated if the plant consistently converted sunlight to electricity at the level expected from the DC nameplate rating. The annual system yield for flat-plate PV systems is estimated by the product of the annual insolation in the plane of the array, the nameplate rating of the system, and the PR, which provides an attractive way to estimate expected annual system yield. Unfortunately, the PR is, again, a function of both the PV system efficiency and the weather. If the PR is measured during the winter or during the summer, substantially different values may be obtained, making this metric insufficient to use as the basis for a performance guarantee when precise confidence intervals are required. This technical report defines a way to modify the PR calculation to neutralize biases that may be introduced by variations in the weather, while still reporting a PR that reflects the annual PR at that site given the project design and the project weather file. This resulting weather-corrected PR gives more consistent results throughout the year, enabling its use as a metric for performance guarantees while still retaining the familiarity this metric brings to the industry and the value of its use in predicting actual annual system yield. A testing protocol is also presented to illustrate the use of this new metric with the intent of providing a reference starting point for contractual content.

14 SOLAR ENERGY↗
DOE OSTI2016

Final Report, University of California Merced: Uranium and strontium fate in waste-weathered sediments: Scaling of molecular processes to predict reactive transport

Objectives of the Project: 1. Determine the process coupling that occurs between mineral transformation and contaminant (U and Sr) speciation in acid-uranium waste weathered Hanford sediments. 2. Establish linkages between molecular-scale contaminant speciation and meso-scale contaminant lability, release and reactive transport. 3. Make conjunctive use of molecular- to bench-scale data to constrain the development of a mechanistic, reactive transport model that includes coupling of contaminant sorption-desorption and mineral transformation reactions. Hypotheses Tested: Uranium and strontium speciation in legacy sediments from the U-8 and U-12 Crib sites can be reproduced in bench-scale weathering experiments conducted on unimpacted Hanford sediments from the same formations; Reactive transport modeling of future uranium and strontium releases from the vadose zone of acid-waste weathered sediments can be effectively constrained by combining molecular-scale information on contaminant bonding environment with grain-scale information on contaminant phase partitioning, and meso-scale kinetic data on contaminant release from the waste-weathered porous media; Although field contamination and laboratory experiments differ in their diagenetic time scales (decades for field vs. months to years for lab), sediment dissolution, neophase nucleation, and crystal growth reactions that occur during the initial disequilibrium induced by waste-sediment interaction leave a strong imprint that persists over subsequent longer-term equilibration time scales and, therefore, give rise to long-term memory effects. Enabling Capabilities Developed: Our team developed an iterative measure-model approach that is broadly applicable to elucidate the mechanistic underpinnings of reactive contaminant transport in geomedia subject to active weathering.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Local Weather Station Design and Development for Cost-Effective Environmental Monitoring and Real-Time Data Sharing

Current weather monitoring systems often remain out of reach for small-scale users and local communities due to their high costs and complexity. This paper addresses this significant issue by introducing a cost-effective, easy-to-use local weather station. Utilizing low-cost sensors, this weather station is a pivotal tool in making environmental monitoring more accessible and user-friendly, particularly for those with limited resources. It offers efficient in-site measurements of various environmental parameters, such as temperature, relative humidity, atmospheric pressure, carbon dioxide concentration, and particulate matter, including PM 1, PM 2.5, and PM 10. The findings demonstrate the station’s capability to monitor these variables remotely and provide forecasts with a high degree of accuracy, displaying an error margin of just 0.67%. Furthermore, the station’s use of the Autoregressive Integrated Moving Average (ARIMA) model enables short-term, reliable forecasts crucial for applications in agriculture, transportation, and air quality monitoring. Furthermore, the weather station’s open-source nature significantly enhances environmental monitoring accessibility for smaller users and encourages broader public data sharing. With this approach, crucial in addressing climate change challenges, the station empowers communities to make informed decisions based on real-time data. In designing and developing this low-cost, efficient monitoring system, this work provides a valuable blueprint for future advancements in environmental technologies, emphasizing sustainability. The proposed automatic weather station not only offers an economical solution for environmental monitoring but also features a user-friendly interface for seamless data communication between the sensor platform and end users. This system ensures the transmission of data through various web-based platforms, catering to users with diverse technical backgrounds. Furthermore, by leveraging historical data through the ARIMA model, the station enhances its utility in providing short-term forecasts and supporting critical decision-making processes across different sectors.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2006

CFDP Performance over Weather-Dependent Ka-Band Channel

This study presents an analysis of the delay performance of the CCSDS File Delivery Protocol (CFDP) over weather-dependent Ka-band channel. The Ka-band channel condition is determined by the strength of the atmospheric noise temperature, which is weather dependent. Noise temperature data collected from the Deep Space Network (DSN) Madrid site is used to characterize the correlations between good and bad channel states in a two-state Markov model. Specifically, the probability distribution of file delivery latency using the CFDP deferred Negative Acknowledgement (NAK) mode is derived and quantified. Deep space communication scenarios with different file sizes and bit error rates (BERs) are studied and compared. Furthermore, we also examine the sensitivity of our analysis with respect to different data sampling methods. Our analysis shows that while the weather-dependent channel only results in fairly small increases in the average number of CFDP retransmissions required, the maximum number of transmissions required to complete 99 percentile, on the other hand, is significantly larger for the weather-dependent channel due to the significant correlation of poor weather states.

weather↗
NASA NTRS2014

The Main Pillar: Assessment of Space Weather Observational Asset Performance Supporting Nowcasting, Forecasting and Research to Operations

Space weather forecasting critically depends upon availability of timely and reliable observational data. It is therefore particularly important to understand how existing and newly planned observational assets perform during periods of severe space weather. Extreme space weather creates challenging conditions under which instrumentation and spacecraft may be impeded or in which parameters reach values that are outside the nominal observational range. This paper analyzes existing and upcoming observational capabilities for forecasting, and discusses how the findings may impact space weather research and its transition to operations. A single limitation to the assessment is lack of information provided to us on radiation monitor performance, which caused us not to fully assess (i.e., not assess short term) radiation storm forecasting. The assessment finds that at least two widely spaced coronagraphs including L4 would provide reliability for Earth-bound CMEs. Furthermore, all magnetic field measurements assessed fully meet requirements. However, with current or even with near term new assets in place, in the worst-case scenario there could be a near-complete lack of key near-real-time solar wind plasma data of severe disturbances heading toward and impacting Earth's magnetosphere. Models that attempt to simulate the effects of these disturbances in near real time or with archival data require solar wind plasma observations as input. Moreover, the study finds that near-future observational assets will be less capable of advancing the understanding of extreme geomagnetic disturbances at Earth, which might make the resulting space weather models unsuitable for transition to operations.

Extreme events↗
NASA NTRS2016

Airspace Technology Demonstration 3 (ATD-3): Dynamic Weather Routes (DWR) Technology Transfer Document Summary Version 1.0

Airspace Technology Demonstration #3 (ATD-3) is part of NASA's Airspace Operations and Safety Program (AOSP) - specifically, its Airspace Technology Demonstrations (ATD) Project. ATD-3 is a multiyear research and development effort which proposes to develop and demonstrate automation technologies and operating concepts that enable air navigation service providers and airspace users to continuously assess weather, winds, traffic, and other information to identify, evaluate, and implement workable opportunities for flight plan route corrections that can result in significant flight time and fuel savings in en route airspace. In order to ensure that the products of this tech-transfer are relevant and useful, NASA has created strong partnerships with the FAA and key industry stakeholders. This summary document and accompanying technology artifacts satisfy the first of three Research Transition Products (RTPs) defined in the Applied Traffic Flow Management (ATFM) Research Transition Team (RTT) Plan. This transfer consists of NASA's legacy Dynamic Weather Routes (DWR) work for efficient routing for en-route weather avoidance. DWR is a ground-based trajectory automation system that continuously and automatically analyzes active airborne aircraft in en route airspace to identify opportunities for simple corrections to flight plan routes that can save significant flying time, at least five minutes wind-corrected, while avoiding weather and considering traffic conflicts, airspace sector congestion, special use airspace, and FAA routing restrictions. The key benefit of the DWR concept is to let automation continuously and automatically analyze active flights to find those where simple route corrections can save significant time and fuel. Operators are busy during weather events. It is more effective to let automation find the opportunities for high-value route corrections.

ATD-3↗
NASA NTRS2015

Dynamic Weather Routes: Two Years of Operational Testing at American Airlines

The Dynamic Weather Routes (DWR) tool continuously analyzes active flights in en-route airspace and finds simple route corrections to achieve more time- and fuel-efficient routes around convective weather. A strong partnership between NASA, American Airlines (AA), and the Federal Aviation Administration has enabled testing of DWR in real-world air traffic operations. NASA and AA have been conducting a trial of DWR at AA’s Integrated Operations Center in Fort Worth, Texas since July 2012. This paper describes test results based on AA’s use of DWR for their flights in and around Fort Worth Center (ZFW). Results indicate an actual savings of 3,290 flying minutes for 526 AA revenue flights from January 2013 through September 2014. Of these, 48 flights each indicate a savings of 15 minutes or more. Potential savings for all flights in ZFW airspace, corrected for savings flights achieve today through normal pilot requests and controller clearances, is about 100,000 flying minutes for 15,000 flights in 2013. Results indicate that AA flights with DWR in use realize about 20 percent more savings than non-AA flights. A weather forecast analysis examines the extent to which DWR routes rated acceptable by AA users remain clear of downstream weather. A sector congestion analysis indicates congestion could be reduced 19-38 percent if all flights fly DWR routes rather than nominal weather-avoidance routes.

Trajectory Automation↗
NASA NTRS2015

Initial Analysis of and Predictive Model Development for Weather Reroute Advisory Use

In response to severe weather conditions, traffic management coordinators (TMCs) reroute air traffic around regions of airspace affected by the severe weather. Presently, acceptable reroutes are specified by issuing reroute advisories. Advisories, based on reroutes published in the National Severe Weather Playbook, consist of several routes describing routing options. These reroutes are selected by TMCs based on their understanding of weather conditions and their previous experience dealing with similar weather conditions. Providing recommendations and analysis of available reroute options could assist the TMCs in making rerouting decisions. While reroute advisories have historically been based on Playbook plays, plays are frequently modified or combined to generate an advisory. Thus, it is natural to present rerouting suggestions to TMCs as modified Playbook plays. The challenge here is to compare advisory subroutes and play subroutes in a meaningful way in order to map advisories back to the Playbook plays upon which they may have been based. In this work, several subroute comparison metrics are presented and discussed. One of these metrics is then used to match advisories to Playbook plays. With the development and implementation of NextGen technologies, there is currently a trend of moving away from the pre-defined Playbook plays (and related advisories) in favor of a more precise specification of trajectories using GPS based navigation tools, such as area navigation (RNAV). Moving towards ubiquitous use of RNAV routes, the objective of rerouting flights will be met with more precisely specified and accurately flown RNAV routes. In the final version of this paper, significant RNAV routes will be identified by finding RNAV routes that are flown frequently. This will require a trajectory comparison technique to compare actually flown flight tracks to specified RNAV routes. The metrics developed here will be used or modified for this task.

weather required reroutes↗
NASA NTRS2020

Data Science for Weather Impacts on Crop Yield

Private businesses in sectors, such as food, energy, and retail, as well as public sector and federal agencies are interested in the predictive understanding of weather impacts on crop yield, which is an important aspect of food security. Scientific literature has mainly examined how crop yield is impacted by growing season-averaged weather indices. Although a few studies did consider weather extremes in their analysis, their scope was either restricted to measuring their conditional relationship with yield or the extreme event types considered were limited. Selection of regression models, whether the more commonly used linear approaches or nonlinear methods, have not been appropriately justified in this context. Here, we develop data-driven methods to examine two inter-related hypotheses for improved scientific understanding and enhanced predictive modeling. The first hypothesis, that extreme weather indices have a statistically significant information content in them is found to be valid based on linear and nonlinear methods for pairwise dependence. The second hypothesis, examines the value addition of nonlinear regression methods, and suggests that linear approaches may not alone be adequate. The results of this study can inform scientific understanding, generation and relevance of indices and end-to-end risk assessment systems in the context of climate impacts on crop yield. An immediate application may be in the context of NASA Earth Exchange (NEX) which facilitates the generation and dissemination of impacts relevant weather data and indices using a multitude of satellite-derived data sets and model outputs.

Data mining, food security, weather impacts↗
NASA NTRS2023

Space Weathering at the Moon

In this paper we summarize the substantial recent progress in understanding space weathering that has occurred through technical innovations in the laboratory and in space, including employment of ultra-high-resolution imaging of lunar samples, a wave of new remote sensing observations, samples returned from asteroid regolith, and new methods for simulating space weathering to gain insight into its mechanisms. The paper begins with a summary of space weathering processes and their observed effects on lunar samples (Section 2). It then describes new insights gleaned from remote sensing at a broadened range of wavelengths (Section 3.1) and from observations of special lunar environments where space weathering inputs vary, such as the intensity of solar wind at lunar swirls or in permanent shadow in polar regions (Section 3.2). We then outline how laboratory simulations have informed the understanding of space weathering mechanisms and rates (Section 4). Finally, we discuss the integrated observations and simulations and the current state of our knowledge (Section 5) and make suggestions for future investigations (Section 6).

moon↗
DOE OSTI2020

Identification of Worst Impact Zones for Power Grids During Extreme Weather Events Using Q-Learning: Preprint

Both the frequency and intensity of extreme weather events have been trending higher in recent years, leading to significant infrastructure loss in the electric grid. The impact of these extreme weather events is desired to be analyzed and quantified in order to help transmission and distribution system operators to prepare and prevent significant losses. In this paper, we developed an approach that models the impact of extreme weather on the power grid and identifies the worst impact zone using Q-learning (a reinforcement learning approach). The identification results reveal grid vulnerability to weather events and provide insights for system operators to help achieve optimal resource allocation and crew dispatch in order to minimize the adverse impact of extreme weather. Simulation studies are conducted on the IEEE 123-node system to demonstrate the performance of the proposed approach.

24 POWER TRANSMISSION AND DISTRIBUTION↗