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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

A Comparison of Perturbed Initial Conditions and Multiphysics Ensembles in a Severe Weather Episode in Spain

Ensembles of numerical model forecasts are of interest to operational early warning forecasters as the spread of the ensemble provides an indication of the uncertainty of the alerts, and the mean value is deemed to outperform the forecasts of the individual models. This paper explores two ensembles on a severe weather episode in Spain, aiming to ascertain the relative usefulness of each one. One ensemble uses sensible choices of physical parameterizations (precipitation microphysics, land surface physics, and cumulus physics) while the other follows a perturbed initial conditions approach. The results show that, depending on the parameterizations, large differences can be expected in terms of storm location, spatial structure of the precipitation field, and rain intensity. It is also found that the spread of the perturbed initial conditions ensemble is smaller than the dispersion due to physical parameterizations. This confirms that in severe weather situations operational forecasts should address moist physics deficiencies to realize the full benefits of the ensemble approach, in addition to optimizing initial conditions. The results also provide insights into differences in simulations arising from ensembles of weather models using several combinations of different physical parameterizations.

severe weather↗
NASA NTRS2015

Predicting Space Weather Effects on Close Approach Events

The NASA Robotic Conjunction Assessment Risk Analysis (CARA) team sends ephemeris data to the Joint Space Operations Center (JSpOC) for conjunction assessment screening against the JSpOC high accuracy catalog and then assesses risk posed to protected assets from predicted close approaches. Since most spacecraft supported by the CARA team are located in LEO orbits, atmospheric drag is the primary source of state estimate uncertainty. Drag magnitude and uncertainty is directly governed by atmospheric density and thus space weather. At present the actual effect of space weather on atmospheric density cannot be accurately predicted because most atmospheric density models are empirical in nature, which do not perform well in prediction. The Jacchia-Bowman-HASDM 2009 (JBH09) atmospheric density model used at the JSpOC employs a solar storm active compensation feature that predicts storm sizes and arrival times and thus the resulting neutral density alterations. With this feature, estimation errors can occur in either direction (i.e., over- or under-estimation of density and thus drag). Although the exact effect of a solar storm on atmospheric drag cannot be determined, one can explore the effects of JBH09 model error on conjuncting objects' trajectories to determine if a conjunction is likely to become riskier, less risky, or pass unaffected. The CARA team has constructed a Space Weather Trade-Space tool that systematically alters the drag situation for the conjuncting objects and recalculates the probability of collision for each case to determine the range of possible effects on the collision risk. In addition to a review of the theory and the particulars of the tool, the different types of observed output will be explained, along with statistics of their frequency.

Space Weather↗
NASA NTRS2016

A Mathematical Model and Algorithm for Routing Air Traffic Under Weather Uncertainty

A central challenge in managing today's commercial en route air traffic is the task of routing the aircraft in the presence of adverse weather. Such weather can make regions of the airspace unusable, so all affected flights must be re-routed. Today this task is carried out by conference and negotiation between human air traffic controllers (ATC) responsible for the involved sectors of the airspace. One can argue that, in so doing, ATC try to solve an optimization problem without giving it a precise quantitative formulation. Such a formulation gives the mathematical machinery for constructing and verifying algorithms that are aimed at solving the problem. This paper contributes one such formulation and a corresponding algorithm. The algorithm addresses weather uncertainty and has closed form, which allows transparent analysis of correctness, realism, and computational costs.

uncertainty↗
NASA NTRS2015

Forecasting Space Weather Events for a Neighboring World

Shortly after NASA's Mars Atmosphere and Volatile EvolutioN mission (MAVEN) spacecraft entered Mars' orbit on 21 September 2014, scientists glimpsed the Martian atmosphere's response to a front of solar energetic particles (SEPs) and an associated coronal mass ejection (CME). In response to some solar flares and CMEs, streams of SEPs burst from the solar atmosphere and are further accelerated in the interplanetary medium between the Sun and the planets. These particles deposit their energy and momentum into anything in their path, including the Martian atmosphere and MAVEN particle detectors. MAVEN scientists had been alerted to the likely CME-Mars encounter by a space weather prediction system that had its origins in space weather forecasting for Earth but now forecasts space weather for Earth's neighboring planets. The two Solar Terrestrial Relations Observatory spacecraft and Solar Heliospheric Observatory observed a CME on 26 September, with a trajectory that suggested a Mars intercept. A computer model developed for solar wind prediction, the Wang-Sheeley-Arge-Enlil cone model [e.g., Zheng et al., 2013; Parsons et al., 2011], running in real time at the Community Coordinated Modeling Center (CCMC) located at NASA Goddard since 2006, showed the CME propagating in the direction of Mars (Figure 1). According to MAVEN particle detectors, the disturbance and accompanying SEP enhancement at the leading edge of the CME reached Mars at approximately 17 hours Universal Time on 29 September 2014. Such SEPs may have a profound effect on atmospheric escape - they are believed to be a possible means for driving atmospheric loss. SEPs can cause loss of Mars' upper atmosphere through several loss mechanisms including sputtering of the atmosphere. Sputtering occurs when atoms are ejected from the atmosphere due to impacts with energetic particles.

space weather↗
NASA NTRS2017

Extratropical Weather Systems on Mars: Radiatively-Active Water Ice Effects

Extratropical, large-scale weather disturbances, namely transient, synoptic-period,baroclinic barotropic eddies - or - low- (high-) pressure cyclones (anticyclones), are components fundamental to global circulation patterns for rapidly rotating, differentially heated, shallow atmospheres such as Earth and Mars. Such "wave-like" disturbances that arise via (geophysical) fluid shear instability develop, mature and decay, and travel west-to-east in the middle and high latitudes within terrestrial-like planetary atmospheres. These disturbances serve as critical agents in the transport of heat and momentum between low and high latitudes of the planet. Moreover, they transport trace species within the atmosphere (e.g., water vapor/ice, other aerosols (dust), chemical species, etc). Between early autumn through early spring, middle and high latitudes on Mars exhibit strong equator-to-pole mean temperature contrasts (i.e., "baroclinicity"). Data collected during the Viking era and observations from both the Mars Global Surveyor (MGS) and Mars Reconnaissance Orbiter (MRO) indicate that such strong baroclinicity supports vigorous, large-scale eastward traveling weather systems [Banfield et al., 2004; Barnes et al., 1993]. A good example of traveling weather systems, frontal wave activity and sequestered dust activity from MGS/MOC image analyses is provided in Figure 1 (cf. Wang et al. [2005]). Utilizing an upgraded and evolving version of the NASA Ames Research Center (ARC) Mars global climate model, investigated here are key dynamical and physical aspects of simulated northern hemisphere (NH) large-scale extratropica lweather systems,with and without radiatively-active water ice clouds. Mars Climate Model:

cyclones↗
NASA NTRS2017

UTM Weather Presentation

Presentation highlighting how weather affected UAS operations during the UTM field tests. Research to develop UAS weather translation models with a description of current and future work for UTM weather.

UTM↗
NASA NTRS2015

Integration of Dynamic Weather Routes Automation with Air/Ground Data Communications

The Dynamic Weather Routes (DWR) toolcontinuously and automatically analyzes airborne flights in en route airspace to identify flights where a route correction could save significant flight time and still avoid weather. A partnership between NASA, American Airlines (AA), and the FAA has enabled testing of DWR in real-world air traffic operations. En route Data Communications (Data Comm) could significantly reduce the controller and pilot workload needed to communicate DWR route changes under today’s voice-based operations and thereby enable more timely and frequent high-value corrections to weather avoidance routes. Sample data from the DWR trial at AA illustrate how Data Comm could improve DWR operations. Two operating concepts that integrate DWR with Data Comm are described:(1) route corrections are initiated by air traffic control and implemented using Airborne Reroutes and Data Comm, and (2) route corrections are initiated by the dispatcher and pilot and implemented via Data Comm. Both concepts align with Federal Aviation Administration (FAA) plans for implementation ofData Comm in en route airspace.

weather avoidance↗
NASA NTRS2021

Evaluation of Clouds, Radiation, and Precipitation in CMIP6 Models Using Global Weather States Derived from ISCCP-H Cloud Property Data

A clustering methodology is applied to cloud optical depth cloud top pressure (TAU-PC) histograms from the new, 1-degree resolution, ISCCP-H dataset, to derive an updated global Weather State (WS) dataset. Then, PC-TAU histograms from current-climate CMIP6 model simulations are assigned to the ISCCP-H WSs along with their concurrent radiation and precipitation properties, to evaluate model cloud, radiation, and precipitation properties in the context of the Weather States. The new ISCCP-H analysis produces WSs that are very similar to those previously found in the lower resolution ISCCP-D dataset. The main difference lies in the splitting of the ISCCP-D thin stratocumulus WS between the ISCCP-H shallow cumulus and stratocumulus WSs, which results in the reduction by one of the total WS number. The evaluation of the CMIP6 models against the ISCCP-H Weather States, shows that, in the ensemble mean, the models are producing an adequate representation of the frequency and geographical distribution of the WSs, with measurable improvements compared to the WSs derived for the CMIP5 ensemble. However, the frequency of shallow cumulus clouds continues to be underestimated, and, in some WSs the good agreement of the ensemble mean with observations comes from averaging models that significantly overpredict and underpredict the ISCCP-H WS frequency. In addition, significant biases exist in the internal cloud properties of the model WSs, such as the model underestimation of cloud fraction in middle-top clouds and secondarily in midlatitude storm and stratocumulus clouds, that result in an underestimation of cloud SW cooling in those regimes.

Clouds↗
NASA NTRS2022

CMEs and SEPs During November–December 2020: A Challenge for Real-Time Space Weather Forecasting

Predictions of coronal mass ejections (CMEs) and solar energetic particles (SEPs) are a central issue in space weather forecasting. In recent years, interest in space weather predictions has expanded to include impacts at other planets beyond Earth as well as spacecraft scattered throughout the heliosphere. In this sense, the scope of space weather science now encompasses the whole heliospheric system, and multipoint measurements of solar transients can provide useful insights and validations for prediction models. In this work, we aim to analyze the whole inner heliospheric context between two eruptive flares that took place in late 2020, that is, the M4.4 flare of 29 November and the C7.4 flare of 7 December. This period is especially interesting because the STEREO-A spacecraft was located ∼60° east of the Sun–Earth line, giving us the opportunity to test the capabilities of “predictions at 360°” using remote-sensing observations from the Lagrange L1 and L5 points as input. We simulate the CMEs that were ejected during our period of interest and the SEPs accelerated by their shocks using the WSA–Enlil–SEPMOD modeling chain and four sets of input parameters, forming a “mini-ensemble.” We validate our results using in situ observations at six locations, including Earth and Mars. We find that, despite some limitations arising from the models' architecture and assumptions, CMEs and shock-accelerated SEPs can be reasonably studied and forecast in real time at least out to several tens of degrees away from the eruption site using the prediction tools employed here.

Coronal mass ejections↗
NASA NTRSDate not supplied

Extracting Lessons of Human Performance and Resilience Management from a Study of Weather-Related Safety Risks and Incidents Reported to NASA's Aviation Safety Reporting System (ASRS)

We present a study of weather-related incident reports submitted to NASA’s Aviation Safety Reporting System (ASRS) by air carrier pilots and air traffic controllers in the US. Using specific examples, we examine the weather-related risks reported and the relevant aspects of human performance and resilience management exhibited during these incidents. We describe our methods of lesson extraction to maximize learning, including the use of advance algorithms, and we conclude with a review of the weather-related risks encountered and the resilient practices employed to mitigate them.

resilience↗
DOE OSTI2025

Comparative analysis of thermal management systems in electric vehicles at extreme weather conditions: Case study on Nissan Leaf 2019 Plus, Chevrolet Bolt 2020 and Tesla Model 3 2020

With the surge in electric vehicle (EV) adoption and the need for extended driving ranges, optimizing energy efficiency, particularly through thermal management, is critical, especially in extreme weather. Managing the substantial energy needed for cabin climate control and battery temperature regulation can increase energy demands by over 50 %, severely limiting range. This study conducts a comparative analysis of thermal management systems (TMS) in three popular EV vehicles, 2020 Chevrolet Bolt, 2019 Nissan Leaf Plus, and 2020 Tesla Model 3, evaluating their distinct TMS configurations and performance under varied weather conditions. Using both numerical simulations and experimental data collected on a controlled test bench at Argonne National Laboratory, we assess how TMS architecture and operational modes influence energy consumption and range. A comprehensive TMS model was developed, integrating cabin and battery thermal sub-models in the Autonomie software platform, to simulate temperature fluctuations and range impacts. Cabin climate was modeled using a mono-zonal approach, while battery cell temperature distribution was estimated through a 2D nodal structure. Each vehicle's distinct TMS setup was evaluated: the Chevrolet Bolt and Tesla Model 3 use a dual evaporator vapor compression cycle with a PTC heater for the cabin and a coolant loop for battery thermal management; the Nissan Leaf Plus employs a heat pump with a PTC heater for the cabin and air-cooling for the battery. Tests conducted at ambient temperatures of 35°C, 22°C, -7°C, and -18°C reveal significant differences in energy use and range reduction across both configurations and conditions. At 35°C, the Tesla Model 3, Chevrolet Bolt, and Nissan Leaf Plus have a range reduction of 8%, 9%, and 13%, respectively, due to air conditioning. In winter, heating technology is paramount; at -7°C, the Nissan Leaf's heat pump configuration achieves a lower range reduction (19.3%) compared to the Tesla and Chevrolet Bolt PTC heaters, which reduce range by 28.3% and 31%, respectively. Further, this study provides valuable insights for automotive engineers, EV technology researchers, and thermal management system designers aiming to enhance electric vehicle performance by understanding how different weather conditions and TMS architectures impact energy consumption and driving range.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Review of the August 1972 and March 1989 (Allen) Space Weather Events: Can We Learn Anything New From Them?

Abstract Updated summaries of the August 1972 and March 1989 space weather events have been constructed. The features of these two events are compared to the Carrington 1859 event and a few other major space weather events. It is concluded that solar active regions release energy in a variety of forms (X‐rays, EUV photons, visible light, coronal mass ejection (CME) plasmas and fields) and they in turn can produce other energetic effects (solar energetic particles (SEPs), magnetic storms) in a variety of ways. It is clear that there is no strong one‐to‐one relationship between these various energy sinks. The energy is often distributed differently from one space weather event to the next. Concerning SEPs accelerated at interplanetary CME (ICME) shocks, it is concluded that the Fermi mechanism associated with quasi‐parallel shocks is relatively weak and that the gradient drift mechanism (electric fields) at quasi‐perpendicular shocks will produce harder spectra and higher fluxes. If the 4 August 1972 intrinsic magnetic cloud condition (southward interplanetary magnetic field instead of northward) and the interplanetary Sun to 1 au conditions were different, a 4 August 1972 magnetic storm and magnetospheric dawn‐to‐dusk electric fields substantially larger than the Carrington event would have occurred. Under these special interplanetary conditions, a Miyake et al. (2012), https://doi.org/10.1038/nature11123 ‐like extreme SEP event may have been formed. The long duration complex 1989 storm was probably greater than the Carrington storm in the sense that the total ring current particle energy was larger.

Tsurutani, Bruce T.↗
DOE OSTI2025

Deep Roots Supply Reactivity and Enhance Silicate Weathering in the Bedrock Vadose Zone

In upland environments, roots commonly extend deep below soil into partially saturated bedrock. This Bedrock Vadose Zone (BVZ) has been shown to store and circulate water, host organic carbon respiration and serve as a critical source of rock-derived nutrients. However, the extent to which deep roots influence chemical weathering rates remains poorly understood. Here, we report 4 years of depth-resolved major ion chemistry over a 16-m thick BVZ hosting a deep rhizosphere in a catchment subject to a Mediterranean climate. These data allow development and validation of a reactive transport model (RTM), revealing that the timescales of water storage and drainage in the BVZ are sufficient to facilitate substantial chemical weathering of the shale bedrock. However, observed solute concentrations are only reproduced by the RTM when we explicitly include measured rates of CO 2(g) production meters below soil driven by the deeply rooted forest. By combining direct observations and a process-based RTM we conclude that the carbon respiration promoted by deep roots significantly enhances chemical weathering rates in the BVZ, constituting 43% ± 3% of total solute flux from the base of the BVZ to the water table.

Osorio‐Leon, Ivan D. [University of Illinois Urban↗
DOE OSTI2025

Sensitivity of Regional WRF‐Chem Air Quality and Weather Simulations to Biomass‐Burning Emission Data Sets: A Case Study of the Impact of Canadian Wildfire on the US°

This study focuses on the period from June 26 to 29, 2023, when record‐breaking Canadian wildfires severely impacted air quality in the Midwest United States. Using the Weather Research and Forecasting Model with Chemistry (WRF‐Chem) and four biomass‐burning data sets (Fire Inventory from NCAR version 1, Fire Inventory from NCAR version 2.5, Quick Fire Emissions Data set [QFED], and Regional ABI‐VIIRS Emission), we analyzed aerosol transport from Canada to the US and assessed the model's accuracy in predicting PM 2.5 , O 3 , CO and aerosol weather feedback. Model simulations were compared with ground‐based and remote sensing observations as well as field measurements from the Community Research on Climate and Urban Science (CROCUS) project. Our findings show that the movement of a low‐pressure system from the Great Lakes to the Atlantic, combined with the high‐pressure system over the Atlantic, caused the transport of aerosols from Canadian wildfires to the US. Results show WRF‐Chem significantly underestimated key atmospheric components: aerosol optical depth (AOD) by over 50%, PM 2.5 by 65%–90% and peak O 3 concentrations by 50%–55% across four biomass burning data sets. Additionally, CO and NO 2 concentrations were underpredicted. The substantial underestimation of PM 2.5 led to an overestimation of temperature by up to 3.6 °C primarily due to excessive downward shortwave radiation, which resulted from the underestimation of direct aerosol effects and an increase in sensible heat flux. Among the biomass‐burning data sets, QFED produced the most accurate AOD and PM 2.5 predictions due to improved wildfire emission estimates, leading to a 1.0 to 1.5 °C reduction in temperature overestimation during the daytime. These findings underscore the need for improving wildfire emission estimates for trace gases and aerosols to enhance air quality and weather feedback predictions.

WRF-chem model↗
DOE OSTI2026

A New Phase for Space Weather

As we move into the declining phase of solar cycle 25, the sunspot number is going down but space weather impacts are not disappearing. Solar energetic particle events, large x-ray flares, and geomagnetic storms are still happening and the declining phase will bring a different balance of hazards. The need for space weather science, space weather applications, and an interface between research, application, and stakeholder communities has not passed. Observations and insights from solar cycle 25 will continue to help us prepare for solar cycle 26, so that we approach the next solar maximum with better predictions, better understanding of outcomes, and a stronger community enabling more confident mitigation and clearer outreach.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Gaps and ways forward in atmospheric blocking and extreme weather research

Atmospheric blocking often results in significant weather extremes, such as heatwaves, droughts, cold spells, and floods in mid-latitude regions. However, the physical processes behind blocking and its response to climate change are not well understood, which undermines predictions and decision-making for climate mitigation and adaptation. As a phenomenon with a timescale at the interface of weather and climate, blocking interacts with various elements of the climate system and connects short-term weather events to long-term climate extremes. Understanding atmospheric blocking is crucial, given that climate change may impact its frequency, duration, and geographic distribution. This perspective discusses new experimental approaches to improve our understanding of this important subject.

Wang, Lei [Purdue University, West Lafayette, IN (↗
DOE OSTI2024

Typical and extreme weather datasets for studying the resilience of buildings to climate change and heatwaves

We present unprecedented datasets of current and future projected weather files for building simulations in 15 major cities distributed across 10 climate zones worldwide. The datasets include ambient air temperature, relative humidity, atmospheric pressure, direct and diffuse solar irradiance, and wind speed at hourly resolution, which are essential climate elements needed to undertake building simulations. The datasets contain typical and extreme weather years in the EnergyPlus weather file (EPW) format and multiyear projections in comma-separated value (CSV) format for three periods: historical (2001–2020), future mid-term (2041–2060), and future long-term (2081–2100). The datasets were generated from projections of one regional climate model, which were bias-corrected using multiyear observational data for each city. The methodology used makes the datasets among the first to incorporate complex changes in the future climate for the frequency, duration, and magnitude of extreme temperatures. These datasets, created within the IEA EBC Annex 80 “Resilient Cooling for Buildings”, are ready to be used for different types of building adaptation and resilience studies to climate change and heatwaves.

54 ENVIRONMENTAL SCIENCES↗