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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

What drives embodied carbon policy? A global perspective on adoption

Abstract Embodied carbon refers to the greenhouse gas emission associated with the lifecycle of buildings. Embodied carbon policies are critical for addressing the environmental impact of construction materials and advancing climate goals. Despite their importance, the adoption of embodied carbon policies has been limited globally, influenced by economic, environmental, institutional, and trade factors. This study employs structural equation modeling to analyze 37 countries, testing ten hypotheses across four categorical factors. The base model reveals the significant influence of environmental vulnerability and institutional frameworks on policy adoption, while robustness models confirm the critical role of trade dependencies and economic competitiveness in shaping national embodied carbon strategies. Findings underscore that countries with high climate vulnerability and strong institutional support are more likely to adopt embodied carbon policies. Conversely, trade-reliant nations face challenges balancing competitiveness and sustainability. Policy implications suggest the need for international collaboration to align trade policies with carbon reduction goals, targeted support for vulnerable nations, and the integration of embodied carbon considerations into existing climate frameworks. These results offer a roadmap for policymakers to design more effective and equitable embodied carbon policies, fostering global progress toward sustainable construction and decarbonization.

Hu, Ming (ORCID:0000000325831161)↗
DOE OSTI2024

Comparing Gravity Waves in a Kilometer‐Scale Run of the IFS to AIRS Satellite Observations and ERA5

Abstract Atmospheric gravity waves (GWs) impact the circulation and variability of the atmosphere. Sub‐grid scale GWs, which are too small to be resolved, are parameterized in weather and climate models. However, some models are now available at resolutions at which these waves become resolved and it is important to test whether these models do this correctly. In this study, a GW resolving run of the European Center for Medium‐Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS), run with a 1.4 km average grid spacing (TCo7999 resolution), is compared to observations from the Atmospheric Infrared Sounder (AIRS) instrument, on NASA's Aqua satellite, to test how well the model resolves GWs that AIRS can observe. In this analysis, nighttime data are used from the first 10 days of November 2018 over part of Asia and surrounding regions. The IFS run is resampled with AIRS's observational filter using two different methods for comparison. The ECMWF ERA5 reanalysis is also resampled as AIRS, to allow for comparison of how the high resolution IFS run resolves GWs compared to a lower resolution model that uses GW drag parametrizations. Wave properties are found in AIRS and the resampled models using a multi‐dimensional S‐Transform method. Orographic GWs can be seen in similar locations at similar times in all three data sets. However, wave amplitudes and momentum fluxes in the resampled IFS run are found to be significantly lower than in the observations. This could be a result of horizontal and vertical wavelengths in the IFS run being underestimated.

Meteorology & Atmospheric Sciences↗
DOE OSTI2020

The Coupled Influence of Thermal Physiology and Biotic Interactions on the Distribution and Density of Ant Species along an Elevational Gradient

A fundamental tenet of biogeography is that abiotic and biotic factors interact to shape the distributions of species and the organization of communities, with interactions being more important in benign environments, and environmental filtering more important in stressful environments. This pattern is often inferred using large databases or phylogenetic signal, but physiological mechanisms underlying such patterns are rarely examined. We focused on 18 ant species at 29 sites along an extensive elevational gradient, coupling experimental data on critical thermal limits, null model analyses, and observational data of density and abundance to elucidate factors governing species’ elevational range limits. Thermal tolerance data showed that environmental conditions were likely to be more important in colder, more stressful environments, where physiology was the most important constraint on the distribution and density of ant species. Conversely, the evidence for species interactions was strongest in warmer, more benign conditions, as indicated by our observational data and null model analyses. Our results provide a strong test that biotic interactions drive the distributions and density of species in warm climates, but that environmental filtering predominates at colder, high-elevation sites. Such a pattern suggests that the responses of species to climate change are likely to be context-dependent and more specifically, geographically-dependent.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Causal Interactions between Southern Ocean Polynyas and High-Latitude Atmosphere–Ocean Variability

Abstract Weddell Sea open-ocean polynyas have been observed to occasionally release heat from the deep ocean to the atmosphere, indicating that their sporadic appearances may be an important feature of high-latitude atmosphere–ocean variability. Yet, observations of the phenomenon are sparse and many standard-resolution models represent these features poorly, if at all. We use a fully coupled, synoptic-scale preindustrial control simulation of the Energy Exascale Earth System Model (E3SMv0-HR) to effectively simulate open-ocean polynyas and investigate their role in the climate system. Our approach employs statistical tests of Granger causality to diagnose local and remote drivers of, and responses to, polynya heat loss on interannual to decadal time scales. First, we find that polynya heat loss Granger causes a persistent increase in surface air temperature over the Weddell Sea, strengthening the local cyclonic wind circulation. Along with responding to polynyas, atmospheric conditions also facilitate their development. When the Southern Ocean experiences a rapid poleward shift in the circumpolar westerlies following a prolonged negative phase of the southern annular mode (SAM), Weddell Sea salinity increases, promoting density destratification and convection in the water column. Finally, we find that the reduction of surface heat fluxes during periods of full ice cover is not fully compensated by ocean heat transport into the high latitudes. This imbalance leads to a buildup of ocean heat content that supplies polynya heat loss. These results disentangle the complex, coupled climate processes that both enable the polynya’s existence and respond to it, providing insights to improve the representation of these highly episodic sea ice features in climate models.

Kaufman, Zachary S.↗
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 OSTI2020

Influence of Time and Frequency Domain Wave Forcing on the Power Estimation of a Wave Energy Converter Array

Industry-specific tools for analyzing and optimizing the design of wave energy converters (WECs) and associated power systems are essential to advancing marine renewable energy. This study aims to quantify the influence of phase information on the device power output of a virtual WEC array. We run the phase-resolving wave model FUNWAVE-TVD (Total Variation Diminishing) to generate directional waves at the PacWave South site offshore from Newport, Oregon, where future WECs are expected to be installed for testing. The two broad cases presented correspond to mean wave climates during warm months (March–August) and cold months (September–February). FUNWAVE-TVD time series of sea-surface elevation are then used in WEC-Sim, a time domain numerical model, to simulate the hydrodynamic response of each device in the array and estimate their power output. For comparison, WEC-Sim is also run with wave energy spectra calculated from the FUNWAVE-TVD simulations, which do not retain phase information, and with wave spectra computed using the phase-averaged model Simulating WAves Nearshore (SWAN). The use of spectral data in WEC-Sim requires a conversion from frequency to time domain by means of random superposition of wave components, which are not necessarily consistent because of the linear assumption implicit in this method. Thus, power response is characterized by multiple realizations of the wave climates.

13 HYDRO ENERGY↗
DOE OSTI2023

Data-driven predictions of the time remaining until critical global warming thresholds are reached

Leveraging artificial neural networks (ANNs) trained on climate model output, we use the spatial pattern of historical temperature observations to predict the time until critical global warming thresholds are reached. Although no observations are used during the training, validation, or testing, the ANNs accurately predict the timing of historical global warming from maps of historical annual temperature. The central estimate for the 1.5 °C global warming threshold is between 2033 and 2035, including a ±1σ range of 2028 to 2039 in the Intermediate (SSP2-4.5) climate forcing scenario, consistent with previous assessments. However, our data-driven approach also suggests a substantial probability of exceeding the 2 °C threshold even in the Low (SSP1-2.6) climate forcing scenario. While there are limitations to our approach, our results suggest a higher likelihood of reaching 2 °C in the Low scenario than indicated in some previous assessments—though the possibility that 2 °C could be avoided is not ruled out. Explainable AI methods reveal that the ANNs focus on particular geographic regions to predict the time until the global threshold is reached. Our framework provides a unique, data-driven approach for quantifying the signal of climate change in historical observations and for constraining the uncertainty in climate model projections. Given the substantial existing evidence of accelerating risks to natural and human systems at 1.5 °C and 2 °C, our results provide further evidence for high-impact climate change over the next three decades.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Temporal variabilities of soil carbon dioxide fluxes from cornfield impacted by temperature and precipitation changes through high-frequent measurement and DAYCENT modelling

Soil carbon dioxide (CO 2 ) emissions from the field of corn (Zea mays L.) play an important role in global warming. This study investigated temporal variability of soil CO 2 fluxes (R s ) with soil temperature (T s ) and moisture (θ) and built DAYCENT models for predicting future impacts of climate changes on R s using the measured high-frequency data. R s trend was tested by Mann–Kendall and Sen Estimator. Predicted R s s under different climate scenarios were compared using Parallel-line Analysis. Herein, the findings indicated that daily R s exponentially increased with T s constrained by θ. During the θ of 27–31%, there was a strong exponential relationship between R s and T s , but the relationship was weaker for the θ of 38–41% and 22–26%. Soil environmental index (SEI, T s × θ) significantly impacted R s with linear regression R s 0.5 = 0.4599 + 0.002059 × SEI in 2008, 2009 and 2011. At the diurnal scale, there were different trends in R s s and relationships among R s and T s and θ in different years. Predicted yearly R s s, root R s s and corn yield in 2014–2049 increased with an increase in temperature scenarios, but the R s s significantly increased as temperature rose by 1°C or higher. Predicted yearly R s s, root R s s and yield reduced with precipitation scenario increase, and the root R s s and yield significantly diminished as precipitation increased by 15 and 30%. Predicted yearly R s from cornfields had a significantly increasing trend. Future research is needed to explore methods for mitigating cornfield R s and evaluating sensitivities of different cropland R s s to temperature changes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Contrasting Stratospheric Smoke Mass and Lifetime From 2017 Canadian and 2019/2020 Australian Megafires: Global Simulations and Satellite Observations

Stratospheric injections of carbonaceous aerosols and combustion gases by extreme wildfires have become increasingly common. Recent “megafires,” particularly large and intense fires, delivered particulate burdens to the lower stratosphere comparable to those of moderate volcanic eruptions. The 2017 Canadian megafire generated four large Pyrocumulonimbi (pyroCbs), injecting up to ≈0.3 Tg of smoke in the lower stratosphere. Even more extreme, the 2019/2020 Australian event produced a pyroCb activity resulting in stratospheric smoke intrusions of ≈1 Tg. To understand their contrasting behavior, we present global climate simulations of the atmospheric response to these events, applying smoke burdens informed by remote observations. Model outcomes, compared to satellite data of smoke transport, reproduce reasonably well the initial plume rise, at 0.2–0.3 km/day, attaining heights of ≈20 km in Canada and above 30 km in Australia. Global dispersal of the plume occurs within about 3 weeks in both cases, consistent with observations. Smoke removal timescales, ≈5 months for the Canadian megafire, agree with remote measurements. During the Australian megafire, observations indicate stratospheric injections three times as large, and models predict comparatively longer smoke lifetimes, ≈16 months. After the latter event, atmospheric optical depths and radiative cooling achieved values close to those measured following the Pinatubo eruption. Sensitivity tests of model assumptions indicate, in accord with prior studies, that smoke burden, injection heights, and black carbon content can determine plume evolution and possible climate impacts. An empirical relation between peak heights of stratospheric plumes and lifetimes is derived that can help assess megafire impacts on the stratosphere, climate and the Earth system

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Understanding the Roles of Convective Trigger Functions in the Diurnal Cycle of Precipitation in the NCAR CAM5

The wrong diurnal cycle of precipitation is a common weakness of current global climate models (GCMs). To improve the simulation of the diurnal cycle of precipitation and understand what physical processes control it, we test a convective trigger function described in Xie et al. (2019) with additional optimizations in the NCAR Community Atmosphere Model version 5 (CAM5). The revised trigger function consists of three modifications: 1) replacing the Convective Available Potential Energy (CAPE) trigger with a dynamic CAPE (dCAPE) trigger, 2) allowing convection to originate above the top of planetary boundary layer (i.e., the unrestricted air parcel launch level - ULL), and 3) optimizing the entrainment rate and threshold value of the dynamic CAPE generation rate for convection onset based on observations. Results from 1°-resolution simulations show that the revised trigger can alleviate the long-standing GCM problem of too early maximum precipitation during the day and missing the nocturnal precipitation peak that is observed in many regions, including the U.S. southern Great Plains (SGP). The revised trigger also improves the simulation of the propagation of precipitation systems downstream of the Rockies and the Amazon region. A further composite analysis over the SGP unravels the mechanisms through which the revised trigger affects convection. Additional sensitivity tests show that both the peak time and the amplitude of the diurnal cycle of precipitation are sensitive to the entrainment rate and dCAPE threshold values.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

High-Resolution Modeling of the Gulf of Mexico using E3SM

Coastal ocean modeling is a high priority in the DOE‘s Energy Exascale Earth System Model (E3SM). The goal is to accurately predict the risk of damage to coastal resources and infrastructure due to a changing climate in the coming decades. North American coastal communities are areas of particular interest, as this fits under the topic of US national security and planning assessments in a changing climate. LANL Institutional Computing time for the Tier 1 allocation ”Coastal Ocean and Sea Ice Modeling” have been used for development and testing of numerical methods needed for E3SM coastal applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Evaluation of Atmospheric Boundary Layer Height From Wind Profiling Radar and Slab Models and Its Responses to Seasonality of Land Cover, Subsidence, and Advection

In this study, we evaluated the effect of land cover, atmospheric subsidence, and advection on the annual dynamics of atmospheric boundary layer (ABL) height from two contrasting sites. The first site is the Walker Branch forest, a deciduous forest of temperate climate, complex topography, and cloudy summers. The second site is the Sacramento-San Joaquin River Delta, a site of Mediterranean climate, flat terrain on a local scale, and clear summers. After testing a new algorithm to calculate ABL heights from 915 MHz radar wind profilers, we evaluated a hierarchy of three slab models to recreate the diurnal and annual patterns of ABL growth. We found that the lower ABL heights in the Delta, particularly during late summer, are driven by the combined effects of increased atmospheric subsidence and marine air advection. In both sites, the annual pattern of ABL height was strongly correlated to total daily incoming radiation, and in the Delta, the annual pattern of ABL height closely followed the seasonal patterns of sensible heat flux from a mosaic of different land covers. A land composite of latent and sensible heat fluxes obtained through a meso-network of eddy covariance measurements and the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) mission resulted in higher model skill, thus showing that land cover heterogeneity is an important driver of ABL growth. To conclude, model simulations show that in the Delta, restoring agricultural land to wetlands with large open water areas could result in a reduction of ABL height during those months with low subsidence and advection.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Hyper‐Local Temperature Prediction Using Detailed Urban Climate Informatics

The accurate modeling of urban microclimate is a challenging task given the high surface heterogeneity of urban land cover and the vertical structure of street morphology. Recent years have witnessed significant efforts in numerical modeling and data collection of the urban environment. Nonetheless, it is difficult for the physical‐based models to fully utilize the high‐resolution data under the constraints of computing resources. The advancement in machine learning (ML) techniques offers the computational strength to handle the massive volume of data. In this study, we proposed a modeling framework that uses ML approach to estimate point‐scale street‐level air temperature from the urban‐resolving meso‐scale climate model and a suite of hyper‐resolution urban geospatial data sets, including three‐dimensional urban morphology, parcel‐level land use inventory, and weather observations from a sensor network. We implemented this approach in the City of Chicago as a case study to demonstrate the capability of the framework. The proposed approach vastly improves the resolution of temperature predictions in cities, which will help the city with walkability, drivability, and heat‐related behavioral studies. Moreover, we tested the model's reliability on out‐of‐sample locations to investigate the modeling uncertainties and the application potentials to the other areas. This study aims to gain insights into next‐gen urban climate modeling and guide the observation efforts in cities to build the strength for the holistic understanding of urban microclimate dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Ice processes in Antarctica: identification via multi-wavelength active and passive measurements and model evaluation (Final Report)

This project is based on new multi-frequency radar observations collected during the AWARE field campaign in 2016 at McMurdo Station by the ARM Mobile facility. Three scientific goals have been achieved. We have developed ice and mixed-phase cloud microphysics retrievals from multi-wavelength radar observations and ancillary observations, generally applicable at ARM sites. These technique generally better characterize the size of the ice crystals, their equivalent water content and the degree of riming better than using single wavelength techniques. We have characterized ice microphysical properties and ice processes via multi-frequency signatures. We have identified a unique mode in the McMurdo dataset appearing at quite cold temperature that we have attributed to riming processes. Triple frequency radar measurements unfortunately were available only for a short period but our work lays the foundation for building climatological and testing their replicability in models. Simultaneously case studies from the AWARE campaign have been exploited to evaluate and improve the NASA GISS ModelE3 climate model, including selection of case studies for combined goals of (i) running side-by-side using large-eddy simulation (LES) and ModelE3 in single-column model (SCM) mode and (ii) fingerprinting cloud processes in multi-wavelength radar observations. The different components of this work have contributed to 15 published papers with two currently under review.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Spanning the Gap From Bulk to Bin: A Novel Spectral Microphysics Method

Microphysics methods for climate models and numerical weather prediction typically track one, two, or three moments of a droplet size distribution for various categories of liquid, ice, and aerosol. Such methods rely on conversion parameters between these categories, which introduces uncertainty into predictions. While higher-fidelity options such as bin and Lagrangian schemes exist, they require too many degrees of freedom for climate modeling applications and introduce numerical challenges. Here we introduce a flexible spectral microphysics method based on collocation of basis functions. This method generalizes to a linear bulk scheme when using few basis functions and to a smoothed bin scheme with more degrees of freedom. Tested in an idealized box setting, the method improves spectral accuracy for droplet collision-coalescence and may eliminate the need for precipitation autoconversion rates required by bulk methods; furthermore, it generalizes well to multimodal distributions with less complexity than a bin method. The potential to extend this collocation representation to multiple hydrometeor classes suggests a path forward to unify liquid, ice, and aerosol microphysics in a single, flexible, computational framework for climate modeling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Automatic and rapid calibration of urban building energy models by learning from energy performance database

Urban building energy modeling (UBEM) is attracting increasing attention in the energy modeling filed. Unlike modeling a single building using detailed building systems information, UBEM generally uses limited high-level building stock data to infer default assumptions about building characteristics and operations. Additionally, this practice inherently brings uncertainty to UBEM. This study introduced a novel method of automatic and rapid calibration of UBEM based on the annual electricity and natural gas energy use data by learning the correlations between crucial model input parameters and the building energy use from the reference building models. A case study was presented to calibrate 72 large office buildings built before 1978 in San Francisco. Seventeen model parameters were selected and Monte Carlo sampling was used to create 1000 samples that reasonably represent the parameter space. Then 1000 simulations were performed for the reference building model to create an energy performance database. The results showed that by learning from the energy performance database, it took less than four simulation runs on average to calibrate a building model. After the calibration, the distributions of each parameter were obtained to replace their single predefined default values. For example, the default lighting power density of 21.39 W/m 2 was calibrated to be 7.50 W/m 2 on average. The case study successfully demonstrated the effectiveness of the novel calibration method for UBEM in the mild climate. The method will be further tested in future for other climate zones and other building types.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Natural variation in growth and yield to waterlogging across climate-diverse pennycress accessions

Many winter annual crops, such as pennycress ( Thlaspi arvense L.), are subjected to heavy precipitation events during their growing season. Therefore, it is essential to identify pennycress accessions with natural variation in flooding resilience. We used climate modeling data to assess spring soil moisture levels in the geographic origins of 471 natural pennycress accessions. We selected 34 accessions with variation in predicted soil moisture and tested survivability under prolonged waterlogging at the rosette stage. It took seven weeks for the first accessions to die, indicating that pennycress is hardy to prolonged waterlogging at the vegetative stage. Furthermore, we chose ‘susceptible’ and ‘tolerant’ accessions to waterlog for one week at the reproductive stage, the growth stage aligned with spring rainfall. Six accessions had significantly reduced seed weight at maturity and two had minimal impacts on growth and seed yield after waterlogging and can be further explored for adaptive traits.

59 BASIC BIOLOGICAL SCIENCES↗