Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “climate sciences”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Linking species traits and demography to explain complex temperature responses across levels of organization

Significance Microbes regulate nutrient flux and carbon storage within ecosystems, making them essential to the global carbon cycle and ecosystem responses to climate change. Understanding how climate change will alter microbial communities and how this will feed back to influence the pace of climate change requires linking processes across levels of organization, from individual organisms to whole ecosystems. We show that the physical characteristics (traits) of protist species influence how their populations will respond to changes in temperature. These species-level temperature responses also alter the composition, dynamics, and functioning of whole microbial communities. Using traits to understand how complex, multilevel microbial processes change with temperature can help us anticipate possible consequences of rapid global climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Pervasive alterations to snow-dominated ecosystem functions under climate change

Climate change projections consistently demonstrate that warming temperatures and dwindling seasonal snowpack will elicit cascading effects on ecosystem function and water resource availability. Despite this consensus, little is known about potential changes in the variability of ecohydrological conditions, which is also required to inform climate change adaptation and mitigation strategies. Considering potential changes in ecohydrological variability is critical to evaluating the emergence of trends, assessing the likelihood of extreme events such as floods and droughts, and identifying when tipping points may be reached that fundamentally alter ecohydrological function. Using a single-model Large Ensemble with sophisticated terrestrial ecosystem representation, we characterize projected changes in the mean state and variability of ecohydrological processes in historically snow-dominated regions of the Northern Hemisphere. Widespread snowpack reductions, earlier snowmelt timing, longer growing seasons, drier soils, and increased fire risk are projected for this century under a high-emissions scenario. In addition to these changes in the mean state, increased variability in winter snowmelt will increase growing-season water deficits and increase the stochasticity of runoff. Thus, with warming, declining snowpack loses its dependable buffering capacity so that runoff quantity and timing more closely reflect the episodic characteristics of precipitation. This results in a declining predictability of annual runoff from maximum snow water equivalent, which has critical implications for ecosystem stress and water resource management. So our results suggest that there is a strong likelihood of pervasive alterations to ecohydrological function that may be expected with climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Historical evaluation and future projections of compound heatwave and drought extremes over the conterminous United States in CMIP6 *

Abstract Independently, both droughts and heatwaves can induce severe impacts on human and natural systems. However, when these two climate extremes occur concurrently in a given region, their compound impacts are often more pronounced. With the improvement in both the spatiotemporal resolution and representation of complex climate processes in the global climate models (GCMs), they are increasingly used to study future changes in these extremes and associated regional impacts. However, GCM selection for such impact assessments is generally based on historical performance and/or future mean changes, without considering individual or compound extremes. In contrast, this study evaluates historical performance and projected changes in heatwaves, droughts, and compound heatwave-droughts using an ensemble of GCMs from the latest Phase 6 of Coupled Models Intercomparison Project at a regional scale across the conterminous United States. Additionally, we explore the inter-model differences in the projected changes that are associated with various characteristics of extremes and the choice of drought indices. Our analysis reveals considerable variation among the GCMs, as well as substantial differences in the projected changes based on the choice of drought indices and region of interest. For example, the projected increases in both the frequency and intensity of drought and associated compound extreme days, based on the standardized precipitation evapotranspiration index far exceed those derived from the standard precipitation index. Further, the largest changes in the frequency of compound extremes are projected over the Southwest, South Central, and parts of the Southeast while the smallest changes are projected over the Northeast. Overall, this study provides important insights for the interpretation and selection of GCMs for future assessment studies that are crucial for the development of regional adaptation strategies in the face of climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Economic Valuation of Coccidioidomycosis (Valley Fever) Projections in the United States in Response to Climate Change

Coccidioidomycosis, or valley fever, is an infectious fungal disease currently endemic to the southwestern United States. Symptoms of valley fever range in severity from flu-like illness to severe morbidity and mortality. Warming temperatures and changes in precipitation patterns may cause the area of endemicity to expand northward throughout the western United States, putting more people at risk for contracting valley fever. This may increase the health and economic burdens from this disease. We developed an approach to describe the relationship between climate conditions and valley fever incidence using historical data and generated projections of future incidence in response to both climate change and population trends using the Climate Change Impacts and Risk Analysis (CIRA) framework developed by the U.S. Environmental Protection Agency. We also developed a method to estimate economic impacts of valley fever that is based on case counts. For our 2000–15 baseline time period, we estimated annual medical costs, lost income, and economic welfare losses for valley fever in the United States were 400,000 USD per case, and the annual average total cost was 3.9 billion USD per year. For a high greenhouse gas emission scenario and accounting for population growth, we found that total annual costs for valley fever may increase up to 164% by year 2050 and up to 380% by 2090. By the end of the twenty-first century, valley fever may cost 620,000 USD per case and the annual average total cost may reach $18.5 billion per year. This work contributes to the broader effort to monetize climate change–attributable damages in the United States.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Removing the Effects of Tropical Dynamics from North Pacific Climate Variability

Teleconnections from the Tropics energize variations of the North Pacific climate, but detailed diagnosis of this relationship has proven difficult. Simple univariate methods, such as regression on El Niño-Southern Oscillation (ENSO) indices, may be inadequate since the key dynamical processes involved -- including ENSO diversity in the Tropics, re-emergence of mixed layer thermal anomalies, and oceanic Rossby wave propagation in the North Pacific -- have a variety of overlapping spatial and temporal scales. Here we use a multivariate Linear Inverse Model to quantify tropical and extra-tropical multi-scale dynamical contributions to North Pacific variability, in both observations and CMIP6 models. In observations, we find that the Tropics are responsible for almost half of the seasonal variance, and almost three quarters of the decadal variance, along the North American coast and within the subtropical front region northwest of Hawaii. SST anomalies that are generated by local dynamics within the Northeast Pacific have much shorter time scales, consistent with transient weather forcing by Aleutian low anomalies. Variability within the Kuroshio-Oyashio Extension (KOE) region is considerably less impacted by the Tropics, on all time scales. Consequently, without tropical forcing the dominant pattern of North Pacific variability would be a KOE pattern, rather than the Pacific Decadal Oscillation (PDO). In contrast to observations, most CMIP6 historical simulations produce North Pacific variability that maximizes in the KOE region, with amplitude significantly higher than observed. Correspondingly, the simulated North Pacific in all CMIP6 models is shown to be relatively insensitive to the Tropics, with a dominant spatial pattern generally resembling the KOE pattern, not the PDO.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Supply and Demand Drivers of Global Hydrogen Deployment in the Transition toward a Decarbonized Energy System

The role of hydrogen in energy system decarbonization is being actively examined by the research and policy communities. We evaluate the potential ‘hydrogen economy’ in global climate change mitigation scenarios using the Global Change Analysis Model (GCAM). We consider major hydrogen production methods in conjunction with delivery options to understand how hydrogen infrastructure affects its deployment. We also consider a rich set of hydrogen end-use technologies and vary their costs to understand how demand technologies affect deployment. We find that the availability of hydrogen transmission and distribution infrastructure primarily affects the hydrogen production mix, particularly the share produced centrally versus onsite, whereas assumptions about end-use technology primarily affect the scale of hydrogen deployment. In effect, hydrogen can be a distributed energy vector, enabled by onsite renewable electrolysis and, to a lesser extent, by onsite industrial production using natural gas with carbon capture and storage (CCS). While the share of hydrogen in final energy is small relative to the share of other major energy carriers in our scenarios, hydrogen enables decarbonization in difficult-to-electrify end uses such as industrial high-temperature heat. Its contribution to greenhouse gas mitigation increases as the climate objective is tightened.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

On the Links Between Ice Nucleation, Cloud Phase, and Climate Sensitivity in CESM2

Ice nucleation in mixed-phase clouds has been identified as a critical factor in projections of future climate. Here we explore how this process influences climate sensitivity using the Community Earth System Model 2 (CESM2). We find that ice nucleation affects simulated cloud feedbacks over most regions and levels of the troposphere, not just extratropical low clouds. However, with present-day global mean cloud phase adjusted to replicate satellite retrievals, similar total cloud feedback is attained whether ice nucleation is simulated as aerosol-sensitive, insensitive, or absent. These model experiments all result in a strongly positive total cloud feedback, as in the default CESM2. A microphysics update from CESM1 to CESM2 had substantially weakened ice nucleation, due partly to a model issue. Our findings indicate that this update reduced global cloud phase bias, with CESM2's high climate sensitivity reflecting improved mixed-phase cloud representation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Increased drought and extreme events over continental United States under high emissions scenario

The frequency, severity, and extent of climate extremes in future will have an impact on human well-being, ecosystems, and the effectiveness of emissions mitigation and carbon sequestration strategies. The specific objectives of this study were to downscale climate data for US weather stations and analyze future trends in meteorological drought and temperature extremes over continental United States (CONUS). We used data from 4161 weather stations across the CONUS to downscale future precipitation projections from three Earth System Models (ESMs) participating in the Coupled Model Intercomparison Project Phase Six (CMIP6), specifically for the high emission scenario SSP5 8.5. Comparing historic observations with climate model projections revealed a significant bias in total annual precipitation days and total precipitation amounts. The average number of annual precipitation days across CONUS was projected to be 205 ± 26, 184 ± 33, and 181 ± 25 days in the BCC, CanESM, and UKESM models, respectively, compared to 91 ± 24 days in the observed data. Analyzing the duration of drought periods in different ecoregions of CONUS showed an increase in the number of drought months in the future (2023–2052) compared to the historical period (1989–2018). The analysis of precipitation and temperature changes in various ecoregions of CONUS revealed an increased frequency of droughts in the future, along with longer durations of warm spells. Eastern temperate forests and the Great Plains, which encompass the majority of CONUS agricultural lands, are projected to experience higher drought counts in the future. Drought projections show an increasing trend in future drought occurrences due to rising temperatures and changes in precipitation patterns. Our high-resolution climate projections can inform policy makers about the hotspots and their anticipated future trajectories.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Considering Climate Change Scenarios in Site Resilience Planning

This paper was prepared in support of the U.S. Department of Energy’s Federal Energy Management Program. The paper serves as a resource for site-level personnel who are performing energy and water resilience planning at their sites and who need to identify and incorporate data that may help them assess risks to infrastructure and operations as a result of future climate change impacts. Specifically, the paper is a high-level look at available scenarios of future climate that can be incorporated into assessments based on U.S. regional models.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Climate change–induced stress disrupts ectomycorrhizal interaction networks at the boreal–temperate ecotone

The interaction networks formed by ectomycorrhizal fungi (EMF) and their tree hosts, which are important to both forest recruitment and ecosystem carbon and nutrient retention, may be particularly susceptible to climate change at the boreal–temperate forest ecotone where environmental conditions are changing rapidly. Here, we quantified the compositional and functional trait responses of EMF communities and their interaction networks with two boreal ( Pinus banksiana and Betula papyrifera ) and two temperate ( Pinus strobus and Quercus macrocarpa ) hosts to a factorial combination of experimentally elevated temperatures and reduced rainfall in a long-term open-air field experiment. The study was conducted at the B4WarmED (Boreal Forest Warming at an Ecotone in Danger) experiment in Minnesota, USA, where infrared lamps and buried heating cables elevate temperatures (ambient, +3.1 °C) and rain-out shelters reduce growing season precipitation (ambient, ~30% reduction). EMF communities were characterized and interaction networks inferred from metabarcoding of fungal-colonized root tips. Warming and rainfall reduction significantly altered EMF community composition, leading to an increase in the relative abundance of EMF with contact-short distance exploration types. These compositional changes, which likely limited the capacity for mycelial connections between trees, corresponded with shifts from highly redundant EMF interaction networks under ambient conditions to less redundant (more specialized) networks. Further, the observed changes in EMF communities and interaction networks were correlated with changes in soil moisture and host photosynthesis. Collectively, these results indicate that the projected changes in climate will likely lead to significant shifts in the traits, structure, and integrity of EMF communities as well as their interaction networks in forest ecosystems at the boreal–temperate ecotone.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Disproportionate control on aerosol burden by light rain

Atmospheric aerosols are of great climatic and environmental importance due to their effects on the Earth’s radiative energy balance and air quality. Aerosol concentrations are strongly influenced by rainfall via wet removal. Global climate models have been used to quantify their climate and health effects. However, they commonly suffer from a well-known problem of ‘too much light rain and too little heavy rain’. The impact of simulated rainfall intensities on aerosol burden at the global scale is still unclear. In this study, we show that rainfall intensity has profound impacts on aerosol burden, and light rain has a disproportionate control on it. By improving the representation of convection, the light-rain (1–20 mm d –1 ) frequency in two state-of-the-art global climate models is reduced. As a result, the aerosol burden is increased globally, especially over the tropics and subtropics, by as much as 0.3 in aerosol optical depth in tropical rain belts. It is attributed to the dominant contribution of light rain to the accumulated wet removal by its frequent occurrence despite its weak intensity. The implication of these findings is that understanding the nature of aerosol scavenging by rainfall is critical to aerosol–climate interaction and its impact on climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Invisible ship tracks show large cloud sensitivity to aerosol

Cloud reflectivity is sensitive to atmospheric aerosol concentrations because aerosols provide the condensation nuclei on which water condenses. Increased aerosol concentrations due to human activity affect droplet number concentration, liquid water and cloud fraction, but these changes are subject to large uncertainties. Ship tracks, long lines of polluted clouds that are visible in satellite images, are one of the main tools for quantifying aerosol–cloud interactions. However, only a small fraction of the clouds polluted by shipping show ship tracks. Here we show that even when no ship tracks are visible in satellite images, aerosol emissions change cloud properties substantially. We develop a new method to quantify the effect of shipping on all clouds, showing a cloud droplet number increase and a more positive liquid water response when there are no visible tracks. We directly detect shipping-induced cloud property changes in the trade cumulus regions of the Atlantic, which are known to display almost no visible tracks. Our results indicate that previous studies of ship tracks were suffering from selection biases by focusing only on visible tracks from satellite imagery. The strong liquid water path response we find translates to a larger aerosol cooling effect on the climate, potentially masking a higher climate sensitivity than observed temperature trends would otherwise suggest.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Internal variability and forcing influence model–satellite differences in the rate of tropical tropospheric warming

Climate-model simulations exhibit approximately two times more tropical tropospheric warming than satellite observations since 1979. The causes of this difference are not fully understood and are poorly quantified. Here, we apply machine learning to relate the patterns of surface-temperature change to the forced and unforced components of tropical tropospheric warming. This approach allows us to disentangle the forced and unforced change in the model-simulated temperature of the midtroposphere (TMT). In applying the climate-model-trained machine-learning framework to observations, we estimate that external forcing has produced a tropical TMT trend of 0.25 ± 0.08 K⋅decade −1 between 1979 and 2014, but internal variability has offset this warming by 0.07 ± 0.07 K⋅decade −1 . Using the Community Earth System Model version 2 (CESM2) large ensemble, we also find that a discontinuity in the variability of prescribed biomass-burning aerosol emissions artificially enhances simulated tropical TMT change by 0.04 K⋅decade −1 . The magnitude of this aerosol-forcing bias will vary across climate models, but since the latest generation of climate models all use the same emissions dataset, the bias may systematically enhance climate-model trends over the satellite era. Our results indicate that internal variability and forcing uncertainties largely explain differences in satellite-versus-model warming and are important considerations when evaluating climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Anticipating water distribution service outages from increasing temperatures

With projected temperature increases and extreme events due to climate change for many regions of the world, characterizing the impacts of these emerging hazards on water distribution systems is necessary to identify and prioritize adaptation strategies for ensuring reliability. To aid decision-making, new insights are needed into how water distribution system reliability to climate-driven heat will change, and the proactive maintenance strategies available to combat failures. To this end, we present the model Perses, a framework that joins a water distribution network hydraulic solver with reliability models of physical assets or components to estimate temperature increase-driven failures and resulting service outages in the long term. A theoretical case study is developed using Phoenix, Arizona temperature profiles, a city with extreme temperatures and a rapidly expanding infrastructure. By end-of-century under hotter futures there are projected to be 1%–5% more pump failures, 2%–5% more PVC pipe failures, and 3%–7% more iron pipe failures (RCP 4.5–8.5) than a baseline historical temperature profile. Service outages, which constitute inadequate pressure for domestic and commercial use are projected to increase by 16%–26% above the baseline under maximum temperature conditions. The exceedance of baseline failures, when compounded across a large metro region, reveals potential challenges for budgeting, management, and maintenance. An exploration of the mitigation potential of adaptation strategies shows that expedited repair times are capable of offsetting the additional outages from climate change, but will come with a cost.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Climate-Driven Legacies in Simulated Microbial Communities Alter Litter Decomposition Rates

The mechanisms underlying diversity-functioning relationships have been a consistent area of inquiry in biogeochemistry since the 1950s. Though these mechanisms remain unresolved in soil microbiomes, many approaches at varying scales have pointed to the same notion—composition matters. Confronting the methodological challenge arising from the complexity of microbiomes, this study used the model DEMENTpy, a trait-based modeling framework, to explore trait-based drivers of microbiome-dependent litter decomposition. We parameterized DEMENTpy for five sites along a climate gradient in Southern California, United States, and conducted reciprocal transplant simulations analogous to a prior empirical study. The simulations demonstrated climate-dependent legacy effects of microbial communities on plant litter decomposition across the gradient. This result is consistent with the previous empirical study across the same gradient. An analysis of community-level traits further suggests that a 3-way tradeoff among resource acquisition, stress tolerance, and yield strategies influences community assembly. Simulated litter decomposition was predictable with two community traits (indicative of two of the three strategies) plus local environment, regardless of the system state (transient vs. equilibrium). Although more empirical confirmation is still needed, community traits plus local environmental factors (e.g., environment and litter chemistry) may robustly predict litter decomposition across spatial-temporal scales. In conclusion, this study offers a potential trait-based explanation for climate-dependent community effects on litter decomposition with implications for improved understanding of whole-ecosystem functioning across scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Climate change alters slug abundance but not herbivory in a temperate grassland

Climate change will significantly impact the world’s ecosystems, in part by altering species interactions and ecological processes, such as herbivory and plant community dynamics, which may impact forage quality and ecosystem production. Yet relatively few field experimental manipulations assessing all of these parameters have been performed to date. To help fill this knowledge gap, we evaluated the effects of increased temperature (+3°C day and night, year-round) and precipitation (+30% of mean annual rainfall) on slug herbivory and abundance and plant community dynamics biweekly in a pasture located in central Kentucky, U.S.A. Warming increased slug abundance once during the winter, likely due to improving conditions for foraging, whereas warming reduced slug abundance at times in late spring, mid-summer, and early fall (from 62–95% reduction depending on month). We found that warming and increased precipitation did not significantly modify slug herbivory at our site, despite altering slug abundance and affecting plant community composition and forage quality. Climate change will alter seasonal patterns of slug abundance through both direct effects on slug biology and indirect effects mediated by changes in the plant community, suggesting that pasture management practices may have to adapt.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Biogeophysical Effects of Land-Use and Land-Cover Change Not Detectable in Warmest Month

Land-use and land-cover changes (hereafter simply “land use”) alter climates biogeophysically by affecting surface fluxes of energy and water. Yet, near-surface temperature responses to land use across observational versus model-based studies and spatial-temporal scales can be inconsistent. Here we assess the prevalence of the historical land use signal of daily maximum temperatures averaged over the warmest month of the year (t LU ) using regularized optimal fingerprinting for detection and attribution. We use observations from the Climatic Research Unit and Berkeley Earth alongside historical simulations with and without land use from phase 6 of the Coupled Model Intercomparison Project to reconstruct an experiment representing the effects of land use on climate. To assess the signal of land use at spatially resolved continental and global scales, we aggregate all input data across reference regions and continents, respectively. At both scales, land use does not comprise a significantly detectable set of forcings for two of four Earth system models and their multimodel mean. Furthermore, using a principal component analysis, we find that t LU is mostly composed of the nonlocal effects of land use rather than its local effects. These findings show that, at scales relevant for climate attribution, uncertainties in Earth system model representations of land use are too high relative to the effects of internal variability to confidently assess land use.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Sensitivity evaluation of the Kudryavtsev permafrost model

Modeling is an important way to assess current and future permafrost spatial distribution and dynamics, especially in data poor areas like the Arctic region. Here, we evaluate a physics-based analytical model, Kudryavtsev's active layer model, which is widely used because it has relatively few data requirements. This model was recently incorporated into a component modeling toolbox, allowing for coupled modeling of permafrost and geomorphic processes over geological timescales. However, systematic quantitative assessment of the influence of its controlling parameters on permafrost temperature and active layer thickness predictions has not been undertaken before. In this work, we investigate the sensitivity of the Kudryavtsev's active layer model by Monte Carlo simulations to generate probability distributions for input parameters and compare predictions with a comprehensive benchmark dataset of in-situ permafrost observations over entire Alaska. Predicted permafrost surface temperature is highly dependent on mean annual air temperature (r = 0.78 on average), annual temperature amplitude (–0.41), and winter-averaged snow thickness (0.30). Uncertainty of predicted permafrost temperature is relatively small (RMSE = 1 °C), when air temperature and snow depth are well constrained. Similarly, RMSE between simulated and observed ALT at stations is ~0.08 m. However, under given air temperature and snow conditions, soil water content bias can significantly affect modeled active layer thickness (RMSE = 0.1 m or 40% of the observed active layer thickness). If soil water content has a large bias, improvements in other parameters may not significantly improve the active layer predictions of the Kudryavtsev's model.

54 ENVIRONMENTAL SCIENCES↗