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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Compounding effects of climate change and WUI expansion quadruple the likelihood of extreme-impact wildfires in California

Previous research has examined individual factors contributing to wildfire risk, but the compounding effects of these factors remain underexplored. Here, we introduce the “Integrated Human-centric Wildfire Risk Index (IHWRI)” to quantify the compounding effects of fire-weather intensification and anthropogenic factors—including ignitions and human settlement into wildland—on wildfire risk. While climatic trends increased the frequency of high-risk fire-weather by 2.5-fold, the combination of this trend with wildland-urban interface expansion led to a 4.1-fold increase in the frequency of conditions conducive to extreme-impact wildfires from 1990 to 2022 across California. More than three-quarters of extreme-impact wildfires—defined as the top 20 largest, most destructive, or deadliest events on record—originated within 1 km from the wildland-urban interface. The deadliest and most destructive wildfires—90% of which were human-caused—primarily occurred in the fall, while the largest wildfires—56% of which were human-caused—mostly took place in the summer. By integrating human activity and climate change impacts, we provide a holistic understanding of human-centric wildfire risk, crucial for policy development.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Daytime urban heat stress in North America reduced by irrigation

There is considerable uncertainty regarding the impact of irrigation on heat stress, partly stemming from the choice of heat stress index. Moreover, existing simulations are at scales that cannot appropriately resolve population centres or clouds and thus the potential for human impacts. Using multi-year convection-permitting and urban-resolving regional climate simulations, we demonstrate that irrigation alleviates summertime heat stress across more than 1,600 urban clusters in North America. This holds true for most physiologically relevant heat stress indices. The impact of irrigation varies by climate zone, with more notable irrigation signals seen for arid urban clusters that are situated near heavily irrigated fields. Through a component attribution framework, we show that irrigation-induced changes in wet-bulb temperature, often used as a moist heat stress proxy in the geosciences, exhibit an opposite sign to the corresponding changes in wet bulb globe temperature—a more complete index for assessing both indoor and outdoor heat risk—across climate zones. In contrast, the local changes in both wet-bulb and wet bulb globe temperature due to urbanization have the same sign. Here, our results demonstrate a complex relationship between irrigation and heat stress, highlighting the importance of using appropriate heat stress indices when assessing the potential for population-scale human impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Assessment of U.S. Urban Surface Temperature Using GOES-16 and GOES-17 Data: Urban Heat Island and Temperature Inequality

Abstract This study utilizes hourly land surface temperature (LST) data from the Geostationary Operational Environmental Satellite (GOES) to analyze the seasonal and diurnal characteristics of surface urban heat island intensity (SUHII) across 120 largest U.S. cities and their surroundings. Distinct patterns emerge in the classification of seasonal daytime SUHII and nighttime SUHII. Specifically, the enhanced vegetation index (EVI) and albedo (ALB) play pivotal roles in influencing these temperature variations. The diurnal cycle of SUHII further reveals different trends, suggesting that climate conditions, urban and nonurban land covers, and anthropogenic activities during nighttime hours affect SUHII peaks. Exploring intracity LST dynamics, the study reveals a significant correlation between urban intensity (UI) and LST, with LST rising as UI increases. Notably, populations identified as more vulnerable by the social vulnerability index (SVI) are found in high UI regions. This results in discernible LST inequality, where the more vulnerable communities are under higher LST conditions, possibly leading to higher heat exposure. This comprehensive study accentuates the significance of tailoring city-specific climate change mitigation strategies, illuminating LST variations and their intertwined societal implications.

Environmental Sciences & Ecology↗
DOE OSTI2022

Does Age, Residency, or Feeding Guild Coupled with a Drought Index Predict Avian Health during Fall Migration?

Birds are good indicators of environmental change and are often studied for responses to climate. Many studies focus on breeding birds, while fewer look at the migration period, which is a critical time for many birds. Birds are more susceptible to unusual climatic events during their migration due to the metabolic stress of long-distance movements. In the fall of 2020, an unusual cold weather event coupled with drought and wildfire smoke led to a large avian mortality event in New Mexico. Later analysis pointed to the mortality being largely due to starvation. This was the impetus for our research. We used 11 years of fall bird banding data from two locations, along with local drought indices, to determine what predicts avian health during the migration period. We used fat score data from over 15,000 individual birds to assess whether drought indices, age, diet, or residency influenced avian health using multiple logistic regression. We found that the probability of positive fat scores decreased as drought severity increased for younger, insectivorous, migratory birds. Insectivores had a higher probability of receiving a fat score greater than zero relative to local drought conditions, which is important, since many North American insectivores are in steep decline. Migratory birds showed a greater response than year-round residents, and older birds showed a lower but significant response compared to hatch-year birds. Our results suggest that migratory insectivores in the southwestern United States may be less resilient to drought-related climate change.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Ocean circulation and climate variability in the northern South China Sea during the Greek Minimum derived from coral Δ 14 C and Sr/Ca records

Ocean circulation transports heat, salt and nutrients, and has profound impacts on the marine environment and climate change. However, the seasonal to centennial variations of the paleocirculation of the South China Sea (SCS) and their driving forces are still unclear due to limited records. Here we reconstructed a high-resolution Δ 14 C record of a coral from Sanya to investigate the seasonal variations of the SCS ocean circulation around 2300 cal yr BP during a grand solar minimum (GSM) period. The seasonal Δ 14 C variability shows the influence of coastal upwelling caused by the East Asian Summer Monsoon (EASM) in summer and the effect of water intrusion from the western Pacific Ocean driven by the Kuroshio Intrusion (KI) in winter. Here we compiled the marine radiocarbon reservoir correction (ΔR) records since 2500 cal yr BP, which indicate a gradual decrease of upwelling significantly correlated with the EASM. Comparisons with other climate records suggest that both the EASM and KI may regulate the ocean circulation variability on centennial time scales. As a good index of the sea surface temperature (SST), our Sr/Ca record and spectral analysis results show a low temperature and a low frequency of El Niño-Southern Oscillation (ENSO) events around 2300 cal yr BP. Moreover, the composite coral Sr/Ca-SST and ENSO index records since 2500 cal yr BP show relatively low SST and weak ENSO during GSMs, supporting the modulation of tropical SST and ENSO by solar activity. Our study has provided high-resolution proxy data and revealed the driving forces of ocean circulation and climate change in the SCS at multiple time scales, which should be considered in further modeling work.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Using Convolutional Neural Network to Emulate Seasonal Tropical Cyclone Activity

Abstract It has been widely recognized that tropical cyclone (TC) genesis requires favorable large‐scale environmental conditions. Based on these linkages, numerous efforts have been made to establish an empirical relationship between seasonal TC activities and large‐scale environmental favorability in a quantitative way, which lead to conceptual functions such as the TC genesis index. However, due to the limited amount of reliable TC observations and complexity of the climate system, a simple analytic function may not be an accurate portrait of the empirical relationship between TCs and their ambiences. In this research, we use convolution neural networks (CNNs) to disentangle this complex relationship. To circumvent the limited amount of seasonal TC observation records, we implement transfer‐learning technique to train ensemble of CNNs first on suites of high‐resolution climate model simulations with realistic seasonal TC activities and large‐scale environmental conditions, and then on a state‐of‐the‐art reanalysis from 1950 to 2019. The trained CNNs can well reproduce the historical TC records and yields significant seasonal prediction skills when the large‐scale environmental inputs are provided by operational climate forecasts. Furthermore, by inputting the ensemble CNNs with 20th century reanalysis products and Phase 6 of the Coupled Model Intercomparison Project (CMIP6) simulations, we investigated TC variability and its changes in the past and future climates. Specifically, our ensemble CNNs project a decreasing trend of global mean TC activity in the future warming scenario, which is consistent with our future projections using high‐resolution climate model.

Meteorology & Atmospheric Sciences↗
DOE OSTI2022

Patterns and controls on island‐wide aboveground biomass accumulation in second‐growth forests of Puerto Rico

Abstract Understanding the heterogeneity of biomass accumulation in second‐growth tropical forests following land use abandonment is important for informing ecosystem carbon models and forest restoration efforts. There is an urgent need for a broad sample of second‐growth forests to enhance our knowledge of carbon accumulation in human‐dominated landscapes, especially for older forests. Puerto Rico has predominantly second‐growth forests, ranging in age from approximately 25 to more than 80 years. We used an island‐wide sample of airborne lidar from the NASA Goddard Lidar, Hyperspectral, and Thermal (G‐LiHT) Airborne Imager collected on March 2017, forest inventory data, and data on forest age, precipitation, soils, and land use to estimate aboveground biomass stocks in moist and wet, second‐growth tropical forests. Biomass accumulation rates in Puerto Rico were lower, on average, than in other Neotropical forests. Median biomass across >16,700 ha of older second‐growth forests was 105 Mg ha −1 , and sampled biomass rarely surpassed 250 Mg ha −1 . Differences in biomass by age were large and persistent across different substrates and land uses, with a plateau in the pattern of island‐wide biomass accumulation after about 33 years. A spatial regression model showed that multiple factors were related to biomass accumulation, including time since abandonment, geologic substrate, past land use as coffee or pasture, precipitation, topographic wetness index, and slope. Our findings have important consequences for the total carbon storage and expected climate mitigation benefits of large‐scale reforestation efforts, and highlight the value of airborne lidar for quantifying biomass variability in complex tropical landscapes. Abstract in Spanish is available with online material.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Data for Photosynthetic responses to temperature across the tropics: a meta-analytic approach

This data package contains raw data, data output, and code of photosynthetic temperature response curves from tropical forests. Data are used in "Photosynthetic responses to temperature across the tropics: a meta-analytic approach". The research investigates how photosynthetic optimum temperatures and shapes of photosynthetic temperature response curves varies across tropical forest climates and growth conditions. Growth climate variables include mean annual temperature, max and max temperature, diurnal temperature range, and aridity index. Meta-analysis combines 18 datasets with representation from Africa, Oceana, North American, and South America. Growth conditions analyzed considers deciduousness, successional status, light conditions, and whether plants are grown in situ or ex situ. All files, except for the raw datafile (Tropical_MetaAnalysis_Master_3.8.22_Edit.csv), have been processed using R code, which is provided.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Projected U.S. drought extremes through the twenty-first century with vapor pressure deficit

Global warming is expected to enhance drought extremes in the United States throughout the twenty-first century. Projecting these changes can be complex in regions with large variability in atmospheric and soil moisture on small spatial scales. Vapor Pressure Deficit (VPD) is a valuable measure of evaporative demand as moisture moves from the surface into the atmosphere and a dynamic measure of drought. Here, VPD is used to identify short-term drought with the Standardized VPD Drought Index (SVDI); and used to characterize future extreme droughts using grid dependent stationary and non-stationary generalized extreme value (GEV) models, and a random sampling technique is developed to quantify multimodel uncertainties. The GEV analysis was performed with projections using the Weather Research and Forecasting model, downscaled from three Global Climate Models based on the Representative Concentration Pathway 8.5 for present, mid-century and late-century. Results show the VPD based index (SVDI) accurately identifies the timing and magnitude short-term droughts, and extreme VPD is increasing across the United States and by the end of the twenty-first century. The number of days VPD is above 9 kPa increases by 10 days along California’s coastline, 30–40 days in the northwest and Midwest, and 100 days in California’s Central Valley.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Remote sensing of seasonal variation of LAI and fAPAR in a deciduous broadleaf forest

Climate change is affecting the phenology of terrestrial ecosystems. In deciduous forests, phenology in leaf area index (LAI) is the primary driver of seasonal variation in the fraction of absorbed photosynthetically active radiation (fAPAR), which drives photosynthesis. Remote sensing has been widely used to estimate LAI and fAPAR. However, while many studies have examined both empirical and model-based relationships among LAI, fAPAR, and spectral vegetation indices (SVI) from remote sensing, few studies have systematically and empirically examined how relationships among these variables change over the growing season. In this study, we examine how and why seasonal-scale covariation differs among time series of remotely sensed SVIs and both LAI and fAPAR based on current understanding and theory. To do this we use newly available remote sensing data sets in combination with time series of in-situ measurements and a canopy radiative transfer model to analyze how seasonal variation in canopy and environmental conditions affect relationships among remotely sensed SVIs, LAI, and fAPAR at a temperate deciduous forest site in central Massachusetts. Our results show that accounting for seasonal variation in canopy shadowing, which is driven by variation in solar zenith angle, improved remote sensing-based estimates of LAI, fAPAR, and daily total APAR. Specifically, we show that the phenology of SVIs is strongly influenced by seasonal variation in near infrared (NIR) reflectance arising from systematic variation in the canopy shadow fraction that is independent of changes in LAI or fAPAR. Therefore, results of this work provide a refined basis for understanding how remote sensing can be used to monitor and model the phenology of LAI, fAPAR, APAR, and gross primary productivity in temperate deciduous forests.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Low-GWP Refrigerants Status and Outlook

Refrigeration - including air conditioning (AC) – contributes substantially to the modern life of the 21st century and its economy. The food cold chain, air conditioning, healthcare and energy are examples of sectors for which refrigeration is indispensable. About 5 billion refrigeration systems – of different types and sizes– operate worldwide in different applications [1]. The dominant share of equipment providing refrigeration operate on the vapor-compression-cycle principle and use fluorocarbon refrigerants. Concerns about the environmental safety have become the driving force for refrigerant changes within the last 35 years. The phased-out schedule of stratospheric-ozone-depleting fluids was first formulated by the Montreal Protocol (MP) in 1987 and was made more stringent during the follow-up international meetings [2]. The affected chlorofluorocarbon (CFC) and hydrochlorofluorocarbon (HCFC) refrigerants were largely replaced by hydrofluorocarbons (HFCs).The 2016 Kigali Amendment to the MP [3] responses to the concerns about the Earth climate change. The refrigeration and AC sectors are attributed with about 7.8 % of global greenhouse gas emissions [4]. This contribution comes in the form of direct effect, which is related to refrigerant emissions from refrigeration systems (37 %), and in the form of indirect effect, which is related to CO2 emissions from fossil fuel power plants producing electricity to power refrigeration systems (63 %) [4]. The Kigali Amendment aims at reducing the direct effect. The effect a given molecule has on the climate change is quantified in a simplified manner by its Global Warming Potential (GWP), a relative index referencing the effect produced to that of the same mass of carbon dioxide released to the atmosphere. By definition, GWP of carbon dioxide is equal to one.While HFC refrigerants have on average a lower GWP than the CFCs and HCFCs they replaced, they are still potent greenhouse gases (GHGs). The Kigali Amendment phases down the use of HFCs by imposing a schedule for reducing a weighted GWP value to be implemented by a country through the year 2047 (Figure 1). It provides four paths depending on the country location and category assigned in the MP, and also prescribes a method for establishing the baseline consumption used for calculating GWP reductions. For developing countries, it is expected to bring the weighed GWP across all refrigeration applications down to about 300 from the baseline value of about 2000. The implementation of Kigali Amendment aims at reducing the future warming due to HFCs from the range of 0.3 °C to 0.5 °C to less than 0.1 °C [5]. While this reduction may seem to be small, it must be viewed in the context of the 2015 Paris Agreement [6], which calls for holding global warming to well below 2 °C and pursuing to limit global warming to 1.5 °C relative to pre-industrial levels [6]. Considering that average global temperatures reached 1 °C above pre-industrial levels for the first time in 2015 [7], the Earth is already within 1 °C of the “2 °C limit”.The low-GWP requirement narrows the pool of fluids that can be considered for application as a refrigerant [8]. This Informatory Note discusses low-GWP refrigerant options for major applications and presents their selection merits.

Yana Motta, Samuel↗
DOE OSTI2021

A deep learning hybrid predictive modeling (HPM) approach for estimating evapotranspiration and ecosystem respiration

Climate change is reshaping vulnerable ecosystems, leading to uncertain effects on ecosystem dynamics, including evapotranspiration (ET) and ecosystem respiration (R eco ). However, accurate estimation of ET and R eco still remains challenging at sparsely monitored watersheds, where data and field instrumentation are limited. In this study, we developed a hybrid predictive modeling approach (HPM) that integrates eddy covariance measurements, physically based model simulation results, meteorological forcings, and remote-sensing datasets to estimate ET and R eco in high space–time resolution. HPM relies on a deep learning algorithm and long short-term memory (LSTM) and requires only air temperature, precipitation, radiation, normalized difference vegetation index (NDVI), and soil temperature (when available) as input variables. We tested and validated HPM estimation results in different climate regions and developed four use cases to demonstrate the applicability and variability of HPM at various FLUXNET sites and Rocky Mountain SNOTEL sites in Western North America. To test the limitations and performance of the HPM approach in mountainous watersheds, an expanded use case focused on the East River Watershed, Colorado, USA. The results indicate HPM is capable of identifying complicated interactions among meteorological forcings, ET, and R eco variables, as well as providing reliable estimation of ET and R eco across relevant spatiotemporal scales, even in challenging mountainous systems. The study documents that HPM increases our capability to estimate ET and R eco and enhances process understanding at sparsely monitored watersheds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Multiscale Interactions between Local Short- and Long-Term Spatio-Temporal Mechanisms and Their Impact on California Wildfire Dynamics

California has experienced a surge in wildfires, prompting research into contributing factors, including weather and climate conditions. This study investigates the complex, multiscale interactions between large-scale climate patterns, such as the Boreal Summer Intraseasonal Oscillation (BSISO), El Niño Southern Oscillation (ENSO), and the Pacific Decadal Oscillation (PDO) and their influence on moisture and temperature fluctuations, and wildfire dynamics in California. The combined impacts of PDO and BSISO on intraseasonal fire weather changes; the interplay between fire weather index (FWI), relative humidity, vapor pressure deficit (VPD), and temperature in assessing wildfire risks; and geographical variations in the relationship between the FWI and climatic factors within California are examined. The study employs a multi-pronged approach, analyzing wildfire frequency and burned areas alongside climate patterns and atmospheric conditions. The findings reveal significant variability in wildfire activity across different climate conditions, with heightened risks during specific BSISO phases, La-Niña, and cool PDO. The influence of BSISO varies depending on its interaction with PDO. Temperature, relative humidity, and VPD show strong predictive significance for wildfire risks, with significant relationships between FWI and temperature in elevated regions (correlation, r > 0.7, p ≤ 0.05) and FWI and relative humidity along the Sierra Nevada Mountains (r ≤ -0.7, p ≤ 0.05).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Observations suggest that North African dust absorbs less solar radiation than models estimate

Abstract Desert dust accounts for a large fraction of shortwave radiation absorbed by aerosols, which adds to the climate warming produced by greenhouse gases. However, it remains uncertain exactly how much shortwave radiation dust absorbs. Here, we leverage in-situ measurements of dust single-scattering albedo to constrain absorption at mid-visible wavelength by North African dust, which accounts for approximately half of the global dust. We find that climate and chemical transport models overestimate North African dust absorption aerosol optical depth (AAOD) by up to a factor of two. This occurs primarily because models overestimate the dust imaginary refractive index, the effect of which is partially masked by an underestimation of large dust particles. Similar factors might contribute to an overestimation of AAOD retrieved by the Aerosol Robotic Network, which is commonly used to evaluate climate and chemical transport models. The overestimation of dust absorption by models could lead to substantial biases in simulated dust impacts on the Earth system, including warm biases in dust radiative effects.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Applying double cropping and interactive irrigation in the North China Plain using WRF4.5

Abstract. Irrigated cultivation exerts a significant influence on the local climate and the hydrological cycle. The North China Plain (NCP) is known for its intricate agricultural system, marked by expansive cropland, high productivity, compact rotation, a semi-arid climate, and intensive irrigation practices. As a result, there has been considerable attention on the potential impact of this intensive irrigated agriculture on the local climate. However, studying the irrigation impact in this region has been challenging due to the lack of an accurate simulation of crop phenology and irrigation practices within the climate model. By incorporating double cropping with interactive irrigation, our study extends the capabilities of the Weather Research Forecast (WRF) model, which has previously demonstrated commendable performance in simulating single-cropping scenarios. This allows for two-way feedback between irrigated crops and climate, further enabling the inclusion of irrigation feedback from both ground and vegetation perspectives. The improved crop modeling system shows significant enhancement in capturing vegetation and irrigation patterns, which is evidenced by its ability to identify crop stages, estimate field biomass, predict crop yield, and project monthly leaf area index. The improved simulation of large-scale irrigated crops in the NCP can further enhance our understanding of the intricate relationship between agricultural development and climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

PyDynamicWindow v1

This software is developed for researchers to evaluate the energy performance of of dynamic windows in the world-wide climate, and this first version focuses on thermochromic windows. We bring new indicators (necessity level and recommendation index) to the evaluation system for thermochromic windows. We estimate the majority users of this software tool will be non-commercial academic researchers. But commercial companies can also use it to optimize their products and estimate where their product has the most promising market.

Gao, Yuan↗
DOE OSTI2023

Soil fertility and drought interact to determine large variations in wood production for a hyperdominant Amazonian tree species

The productivity of the Amazon Rainforest is related to climate and soil fertility. However, the degrees to which these interactions influence multiannual to decadal variations in tree diameter growth are still poorly explored. To fill this gap, we used radiocarbon measurements to evaluate the variation in tree growth rates over the past decades in an important hyperdominant species, Eschweilera coriacea (Lecythidaceae), from six sites in the Brazilian Amazon that span a range of soil properties and climate. Using linear mixed-effects models, we show that temporal variations in mean annual diameter increment evaluated over a specific time period reflect interactions between soil fertility and the drought index (SPEI-Standardized Precipitation and Evapotranspiration Index). Our results indicate that the growth response of trees to drought is strongly dependent on soil conditions, a facet of forest productivity that is still underexplored, and which has great potential for improving predictions of future tropical tree growth in the face of projected climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Genome resequencing reveals demographic history and genetic architecture of seed salinity tolerance in Populus euphratica

Populus euphratica is a dominant tree species in desert riparian forests and possesses extraordinary adaptation to salinity stress. Exploration of its genomic variation and molecular underpinning of salinity tolerance is important for elucidating population evolution and identifying stress-related genes. Here, we identify approximately 3.15 million single nucleotide polymorphisms using whole-genome resequencing. The natural populations of P. euphratica in northwest China are divided into four distinct clades that exhibit strong geographical distribution patterns. Pleistocene climatic fluctuations and tectonic deformation jointly shaped the extant genetic patterns. A seed germination rate-based salinity tolerance index was used to evaluate seed salinity tolerance of P. euphratica and a genome-wide association study was implemented. A total of 38 single nucleotide polymorphisms were associated with seed salinity tolerance and were located within or near 82 genes. Expression profiles showed that most of these genes were regulated under salt stress, revealing the genetic complexity of seed salinity tolerance. Furthermore, DEAD-box ATP-dependent RNA helicase 57 and one undescribed gene (CCG029559) were demonstrated to improve the seed salinity tolerance in transgenic Arabidopsis. These results provide new insights into the demographic history and genetic architecture of seed salinity tolerance in desert poplar.

59 BASIC BIOLOGICAL SCIENCES↗