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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 1,585 records · Page 88
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Jet stream winds - Enhanced aircraft data acquisition and analysis over Southwest Asia

A project is described for providing the accurate initial and verification analyses for the jet stream in regions where general circulation models are known to have large systematic errors, either due to the extreme sparsity of data or to incorrect physical parameterizations. For this purpose, finely spaced aircraft-based meteorological data for the Southwest Asian regions collected for three 10-day periods in the winter of 1988-1989 will be used, together with corresponding data for the North American regions used as a control, to rerun the assimilation cycles and forecast models of the NMC and the NASA Goddard Laboratory for Atmospheres. Data for Southeast Asia will be collected by three carriers with extensive wide-body routes crossing the total region, while data for the North American region will be obtained from the archives of ACARS and GTS.

Tenenbaum, J.↗
NASA NTRS2017

Using the Coronal Evolution to Successfully Forward Model CMEs' In Situ Magnetic Profiles

Predicting the effects of a coronal mass ejection (CME) impact requires knowing if impact will occur, which part of the CME impacts, and its magnetic properties. We explore the relation between CME deflections and rotations, which change the position and orientation of a CME, and the resulting magnetic profiles at 1 AU. For 45 STEREO-era, Earth-impacting CMEs, we determine the solar source of each CME, reconstruct its coronal position and orientation, and perform a ForeCAT (Forecasting a CME's Altered Trajectory) simulation of the coronal deflection and rotation. From the reconstructed and modeled CME deflections and rotations, we determine the solar cycle variation and correlations with CME properties. We assume no evolution between the outer corona and 1 AU and use the ForeCAT results to drive the ForeCAT In situ Data Observer (FIDO) in situ magnetic field model, allowing for comparisons with ACE and Wind observations. We do not attempt to reproduce the arrival time. On average FIDO reproduces the in situ magnetic field for each vector component with an error equivalent to 35 percent of the average total magnetic field strength when the total modeled magnetic field is scaled to match the average observed value. Random walk best fits distinguish between ForeCAT's ability to determine FIDO's input parameters and the limitations of the simple flux rope model. These best fits reduce the average error to 30 percent.The FIDO results are sensitive to changes of order a degree in the CME latitude, longitude, and tilt, suggesting that accurate space weather predictions require accurate measurements of a CME's position and orientation.

Kay, C.↗
NASA NTRS1981

Mesoscale aspects of jet streak coupling and implications for the short term forecasting of severe convective storms

An analysis of a tornado outbreak in Wichita Falls, Texas was analyzed. The coupling of upper and lower tropospheric jet streaks, leading to severe storm outbreaks is illustrated. The high resolution SESAME data sets indicate that mass and momentum adjustments which couple upper and lower tropospheric jets occur within a 3 to 6 hr time frame over a 100 to 500 km domain, and establish the role of isallobaric forcing in the storm development. It is suggested that the output rate of data from the existing 12 hr network be increased to provide better temporal resolution of wind, mass and moisture data.

Uccellini, L. W.↗
NASA NTRS1991

Research on diabatic initialization

The objective was to contribute to the improvement of the analyses of irrotational wind and moisture fields in the trophics through advancement in the technique of initialization by incorporating diabatic effects. Significant accomplishments made during the period May 1990 to April 1991 in the following areas are presented: (1) estimation of the uncertainty of daily synoptic analyses in the tropics; (2) normal modes of Laplace's tidal equations for zonal wavenumber zero; and (3) tropical initialization to ameliorate the spin-up problem of precipitation forecasts. The focus of current research and plans for next year are also presented.

Kasahara, Akira↗
NASA NTRS2013

Range-Specific High-resolution Mesoscale Model Setup

This report summarizes the findings from an AMU task to determine the best model configuration for operational use at the ER and WFF to best predict winds, precipitation, and temperature. The AMU ran test cases in the warm and cool seasons at the ER and for the spring and fall seasons at WFF. For both the ER and WFF, the ARW core outperformed the NMM core. Results for the ER indicate that the Lin microphysical scheme and the YSU PBL scheme is the optimal model configuration for the ER. It consistently produced the best surface and upper air forecasts, while performing fairly well for the precipitation forecasts. Both the Ferrier and Lin microphysical schemes in combination with the YSU PBL scheme performed well for WFF in the spring and fall seasons. The AMU has been tasked with a follow-on modeling effort to recommended local DA and numerical forecast model design optimized for both the ER and WFF to support space launch activities. The AMU will determine the best software and type of assimilation to use, as well as determine the best grid resolution for the initialization based on spatial and temporal availability of data and the wall clock run-time of the initialization. The AMU will transition from the WRF EMS to NU-WRF, a NASA-specific version of the WRF that takes advantage of unique NASA software and datasets. 37

Watson, Leela R.↗
NASA NTRSDate not supplied

A Study of the Kinematic and Dynamic Processes associated with Mesoscale Snowbands in a Midwest United States Snowstorm on 5 February 2020

Mesoscale snowbands are frequently responsible for dumping large amounts of snow over a relatively small region and pose a considerable forecasting challenge. The present study focuses on the mesoscale snowbands observed on 5 February 2020 over the Midwest United States. In order to improve the forecasting of mesoscale snowbands, it is important to understand the processes that organize these features. To this end, we are investigating the kinematic and dynamic processes that shape the mesoscale snowbands using a combination of high-altitude airborne radar, in-situ aircraft measurements, surface observations, and model simulations. This presentation will primarily focus on the three-dimensional structure of the mesoscale snowbands in terms of EXRAD reflectivity and horizontal winds. The horizontal winds are retrieved from the EXRAD scanning-beam Doppler velocities using a VAD technique. These winds, in combination with virtual potential temperature taken from the HRRR operational analysis, are used to compute the bulk Richardson number in order to investigate any contributions to banding features that might be tied to Kelvin-Helmholtz instability. Our analysis does not support the presence of Kelvin-Helmholtz instability. That said, low, but not subcritical, Richardson numbers were found near the top of some banding features in this event and it is possible that the model analysis is smoothing out the virtual potential temperature fields. Finally, we present arguments for using a flight module designed to sample the along-band structures with particular emphasis on observing generating cells and low-level microphysics.

Charles N. Helms↗
DOE OSTI2018

Predicting Atmospheric Green's Functions using the Weather Research and Forecasting Model

This report shows the results of constructing predictive atmospheric models for the Source Physics Experiments 1-6. Historic atmospheric data are combined with topography to construct an atmospheric model that corresponds to the predicted (or actual) time of a given SPE event. The models are ultimately used to construct atmospheric Green's functions to be used for subsequent analysis. We present three atmospheric models for each SPE event: an average model based on ten one-hour snap shots of the atmosphere and two extrema models corresponding to the warmest, coolest, windiest, etc. atmospheric snap shots. The atmospheric snap shots consist of wind, temperature, and pressure profiles of the atmosphere for a one-hour time window centered at the time of the predicted SPE event, as well as nine additional snap shots for each of the nine preceding years, centered at the time and day of the SPE event.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Control and Size Energy Storage for Managing Energy balance of Variable Generation Resources

This paper presents control algorithms and sizing strategies for using energy storage to manage energy balance for variable generation resources. The control objective is to minimize the hourly generation imbalance between the actual and the scheduled generation of the wind farm. Three control algorithms are compared: tracking power imbalance, post-compensation, and pre-compensation. Measurement data from a wind farm located in South-central Washington State are used in the study. The results show that tracking power imbalance yields the best performance by keeping the hourly energy imbalances zero. However, the energy storage system (ESS) will be significantly oversized. Post-compensation reduces power rating of the ESS but the hourly imbalance may not be kept as zero when large and long-lasting energy imbalances occur. A linear regression forecasting algorithm is developed for the pre-compensation algorithm to pre-charge or pre-discharge the ESS based on predicted energy imbalances. The performance comparison shows that the pre-compensation method significantly reduces the size of the ESS while maintaining satisfactory performance.

ENERGY MANAGEMENT↗
DOE OSTI2023

Supercell Low-Level Mesocyclones: Origins of Inflow and Vorticity

Abstract The development and intensification of low-level mesocyclones in supercell thunderstorms have often been attributed, at least in part, to augmented streamwise vorticity generated baroclinically in the forward flank of supercells. However, the ambient streamwise vorticity of the environment (often quantified via storm-relative helicity), especially near the ground, is particularly skillful at discriminating between nontornadic and tornadic supercells. This study investigates whether the origins of the inflow air into supercell low-level mesocyclones, both horizontally and vertically, can help explain the dynamical role of environmental versus storm-generated vorticity in the development of low-level mesocyclone rotation. Simulations of supercells, initialized with wind profiles common to supercell environments observed in nature, show that the air bound for the low-level mesocyclone primarily originates from the ambient environment (rather than from along the forward flank) and from very close to the ground, often in the lowest 200–400 m of the atmosphere. Given that the near-ground environmental air comprises the bulk of the inflow into low-level mesocyclones, this likely explains the forecast skill of environmental streamwise vorticity in the lowest few hundred meters of the atmosphere. The low-level mesocyclone does not appear to require much augmentation from the development of additional horizontal vorticity in the forward flank. Instead, the dominant contributor to vertical vorticity within the low-level mesocyclone is from the environmental horizontal vorticity. This study provides further context to the ongoing discussion regarding the development of rotation within supercell low-level mesocyclones. Significance Statement Supercell thunderstorms produce the majority of tornadoes, and a defining characteristic of supercells is their rotating updraft, known as the “mesocyclone.” When the mesocyclone is stronger at lower altitudes, the likelihood of tornadoes increases. The purpose of this study is to understand if the rotation of the mesocyclone in supercells is due to horizontal spin present in the ambient environment or whether additional horizontal spin generated by the storm itself primarily drives this rotation. Our results suggest that inflow air into supercells and low-level mesocyclone rotation are mainly due to the properties of the environmental inflow air, especially near the ground. This hopefully provides further context to how our community views the development of low-level mesocyclones in supercells.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Stochastic Methods Applied to Power System Operations with Renewable Energy: A Review

Renewable energy resources have been rapidly integrated into power systems in many parts of the world, contributing to a cleaner and more sustainable supply of electricity. Wind and solar resources also introduce new challenges for system operations and planning in terms of economics and reliability because of their variability and uncertainty. Operational strategies based on stochastic optimization have been developed recently to address these challenges. In general terms, these stochastic strategies either embed uncertainties into the scheduling formulations (e.g., the unit commitment [UC] problem) in probabilistic forms or develop more appropriate operating reserve strategies to take advantage of advanced forecasting techniques. Other approaches to address uncertainty are also proposed, where operational feasibility is ensured within an uncertainty set of forecasting intervals. In this report, a comprehensive review is conducted to present the state of the art through Spring 2015 in the area of stochastic methods applied to power system operations with high penetration of renewable energy. Chapters 1 and 2 give a brief introduction and overview of power system and electricity market operations, as well as the impact of renewable energy and how this impact is typically considered in modeling tools. Chapter 3 reviews relevant literature on operating reserves and specifically probabilistic methods to estimate the need for system reserve requirements. Chapter 4 looks at stochastic programming formulations of the UC and economic dispatch (ED) problems, highlighting benefits reported in the literature as well as recent industry developments. Chapter 5 briefly introduces alternative formulations of UC under uncertainty, such as robust, chance-constrained, and interval programming. Finally, in Chapter 6, we conclude with the main observations from our review and important directions for future work.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1984

The rationale and suggested approaches for research geosynchronous satellite measurements for severe storm and mesoscale investigations

The measurements from current and planned geosynchronous satellites provide quantitative estimates of temperature and moisture profiles, surface temperature, wind, cloud properties, and precipitation. A number of significant observation characteristics remain, they include: (1) temperature and moisture profiles in cloudy areas; (2) high vertical profile resolution; (3) definitive precipitation area mapping and precipitation rate estimates on the convective cloud scale; (4) winds from low level cloud motions at night; (5) the determination of convective cloud structure; and (6) high resolution surface temperature determination. Four major new observing capabilities are proposed to overcome these deficiencies: a microwave sounder/imager, a high resolution visible and infrared imager, a high spectral resolution infrared sounder, and a total ozone mapper. It is suggested that the four sensors are flown together and used to support major mesoscale and short range forecasting field experiments.

Shenk, W. E.↗
DOE OSTI2023

Extreme windstorms in the Northeastern USA in the contemporary and future climate

Cold-season windstorms represent an important, and potentially changing, geophysical hazard in the Northeastern United States. Here we employ an integrated research methodology including both a storyline approach, where three intense windstorms from the current climate are subjected to pseudo-global warming (PGW) experiments, and a long-term transient simulation using the Weather Research and Forecasting (WRF) model. An ensemble of WRF simulations is built for each windstorm using different planetary boundary layer and microphysical parameterizations. The fidelity assessment suggests all ensemble members capture the windstorm evolution in contemporary climate. The configuration with highest fidelity is used in the PGW experiments performed with perturbed temperature fields, constant relative humidity, and deiced Great Lakes. These perturbation simulations indicate some evidence for a reduction of sea level pressure and increases in wind speed over and downwind of the Great Lakes and over the Atlantic Ocean plus an increase in precipitation accumulation but a reduction in snow coverage. These changes are spatially inhomogeneous in terms of magnitude and sign but are consistent with changes in potential vorticity. Alberta Clippers and Colorado Lows dominate the cyclones responsible for historical windstorms and thus are sampled in the PGW simulations. However, the transient simulation suggests an increasing role for tropical cyclones that undergo transition to extratropical cyclones. Furthermore, this reinforces the value of combining information from both PGW perturbation experiments within a storyline context and transient simulations when seeking to quantify the future risk associated with cold-season windstorms under changing climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Carbon‐Neutral Pathways for the United States

Abstract The Intergovernmental Panel on Climate Change (IPCC) Special Report on Global Warming of 1.5°C points to the need for carbon neutrality by mid‐century. Achieving this in the United States in only 30 years will be challenging, and practical pathways detailing the technologies, infrastructure, costs, and tradeoffs involved are needed. Modeling the entire U.S. energy and industrial system with new analysis tools that capture synergies not represented in sector‐specific or integrated assessment models, we created multiple pathways to net zero and net negative CO 2 emissions by 2050. They met all forecast U.S. energy needs at a net cost of 0.2–1.2% of GDP in 2050, using only commercial or near‐commercial technologies, and requiring no early retirement of existing infrastructure. Pathways with constraints on consumer behavior, land use, biomass use, and technology choices (e.g., no nuclear) met the target but at higher cost. All pathways employed four basic strategies: energy efficiency, decarbonized electricity, electrification, and carbon capture. Least‐cost pathways were based on >80% wind and solar electricity plus thermal generation for reliability. A 100% renewable primary energy system was feasible but had higher cost and land use. We found multiple feasible options for supplying low‐carbon fuels for non‐electrifiable end uses in industry, freight, and aviation, which were not required in bulk until after 2035. In the next decade, the actions required in all pathways were similar: expand renewable capacity 3.5 fold, retire coal, maintain existing gas generating capacity, and increase electric vehicle and heat pump sales to >50% of market share. This study provides a playbook for carbon neutrality policy with concrete near‐term priorities.

Williams, James H.↗
DOE OSTI2019

Uncertainty Propagation in Coupled Atmosphere–Wave–Ocean Prediction System: A Study of Hurricane Earl (2010)

This study focuses on understanding the evolution of Hurricane Earl (2010) with respect to random perturbations in the storm’s initial strength, size, and asymmetry in wind distribution. We rely on the Unified Wave Interface-Coupled Model (UWIN-CM), a fully coupled atmosphere–wave–ocean system to generate a storm realization ensemble, and use polynomial chaos (PC) expansions to build surrogate models for time evolution of both the maximum wind speed and minimum sea level pressure in Earl. The resulting PC surrogate models provide statistical insights on probability distributions of model responses throughout the simulation time span. Statistical analysis of rapid intensification (RI) suggests that initial perturbations having intensified and counterclockwise-rotated winds are more likely to undergo RI. In addition, for the range of initial conditions considered RI seems mostly sensitive to azimuthally averaged maximum wind speed and asymmetry orientation, rather than storm size and asymmetry magnitude; this is consistent with global sensitivity analysis of PC surrogate models. Finally, we combine initial condition perturbations with a stochastic kinetic energy backscatter scheme (SKEBS) forcing in the UWIN-CM simulations and conclude that the storm tracks are substantially influenced by the SKEBS forcing perturbations, whereas the perturbations in initial conditions alone had only limited impact on the storm-track forecast.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Impacts, processes and projections of the quasi-biennial oscillation

In the tropical stratosphere, deep layers of eastward and westward winds encircle the globe and descend regularly from the upper stratosphere to the tropical tropopause. With a complete cycle typically lasting almost 2.5 years, this quasi-biennial oscillation (QBO) is arguably the most predictable mode of atmospheric variability that is not linked to the changing seasons. Here, the QBO affects climate phenomena outside the tropical stratosphere, including ozone transport, the North Atlantic Oscillation and the Madden–Julian Oscillation, and its high predictability could enable better forecasts of these phenomena if models can accurately represent the coupling processes. Climate and forecasting models are increasingly able to simulate stratospheric oscillations resembling the QBO, but exhibit common systematic errors such as weak amplitude in the lowermost tropical stratosphere. Uncertainties about the waves that force the oscillation, particularly the momentum fluxes from small-scale gravity waves excited by deep convection, make its simulation challenging. Improved representation of the processes governing the QBO is expected to lead to better forecasts of the oscillation and its impacts, increased understanding of unusual events such as the two QBO disruptions observed since 2016, and more reliable future projections of QBO behaviour under climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Data-Driven Transition Path Analysis Yields a Statistical Understanding of Sudden Stratospheric Warming Events in an Idealized Model

Abstract Atmospheric regime transitions are highly impactful as drivers of extreme weather events, but pose two formidable modeling challenges: predicting the next event (weather forecasting) and characterizing the statistics of events of a given severity (the risk climatology). Each event has a different duration and spatial structure, making it hard to define an objective “average event.” We argue here that transition path theory (TPT), a stochastic process framework, is an appropriate tool for the task. We demonstrate TPT’s capacities on a wave–mean flow model of sudden stratospheric warmings (SSWs) developed by Holton and Mass, which is idealized enough for transparent TPT analysis but complex enough to demonstrate computational scalability. Whereas a recent article (Finkel et al. 2021) studied near-term SSW predictability, the present article uses TPT to link predictability to long-term SSW frequency. This requires not only forecasting forward in time from an initial condition, but also backward in time to assess the probability of the initial conditions themselves. TPT enables one to condition the dynamics on the regime transition occurring, and thus visualize its physical drivers with a vector field called the reactive current . The reactive current shows that before an SSW, dissipation and stochastic forcing drive a slow decay of vortex strength at lower altitudes. The response of upper-level winds is late and sudden, occurring only after the transition is almost complete from a probabilistic point of view. This case study demonstrates that TPT quantities, visualized in a space of physically meaningful variables, can help one understand the dynamics of regime transitions.

Meteorology & Atmospheric Sciences↗
NASA NTRS2021

The impact of Los Angeles Basin pollution and stratospheric intrusions on the surrounding San Gabriel Mountains as seen by surface measurements, lidar, and numerical models

In this work, the impact of Los Angeles Basin pollution transport and stratospheric intrusions on the surface ozone levels observed in the San Gabriel Mountains is investigated based on a combination of surface and lidar measurements as well as WRF-Chem (Weather Research and Forecasting with Chemistry) and WACCM (Whole Atmosphere Community Climate Model) runs. The number of days with observed surface ozone levels exceeding the National Ambient Air Quality Standards exhibit a clear seasonal pattern, with a maximum during summer, when models suggest a minimum influence of stratospheric intrusions and the largest impact from Los Angeles Basin pollution transport. Additionally, measured and modeled surface ozone and PM10 were analyzed as a function of season, time of the day, and wind direction. Measurements and models are in good qualitative agreement, with maximum surface ozone observed for southwest and west winds. For the prevailing summer wind direction, slightly south of the ozone maximum and corresponding to south-southwest winds, lower ozone levels were observed. Back trajectories suggest that this is associated with transport from the central Los Angeles Basin, where titration limits the amount of surface ozone. A quantitative comparison of the lidar profiles with WRF-Chem and WACCM models revealed good agreement near the surface, with models showing an increasing positive bias as function of altitude, reaching 75 % at 15 km above sea level. Finally, three selected case studies covering the different mechanisms affecting the near-surface ozone concentration over the San Gabriel Mountains, namely stratospheric intrusions and pollution transport, are analyzed based on surface and ozone lidar measurements, as well as co-located ceilometer measurements and models.

Impact↗
DOE OSTI2018

Balancing Needs Assessment Using Advanced Probabilistic Forecasts

This paper presents a comprehensive approach to predict Balancing Authority (BA) regulation and load following requirements in order to improve BA control performance. In this paper the Pacific Northwest National Laboratory’s (PNNL) “ramp and uncertainty prediction tool (RUT) and day-ahead regulation prediction (DARP) tool” were upgraded to incorporate advanced probabilistic forecast information provided by AWS Truepower. The proposed methodology has been tested and validated using actual California Independent System Operator (CAISO) data. Simulation confirmed that integration probabilistic forecast information can reduce the predicted regulation range by about 12-31%. This means that BAs can procure fewer balancing resources without compromising their reliability and control performance requirements.

Regulation, Solar Generation, Wind Generation, Con↗