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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Review of quantitative methods to assess impacts of changing climate and socioeconomic conditions on Arctic transportation systems

Rapid climate and socioeconomic changes are transforming Arctic human- Earth systems. An integral part of these systems is mobility, which encompasses the transport of humans and goods into, out of, and between Arctic regions. Impacts of climate and socioeconomic drivers on Arctic mobility are heterogenous. Methodologies are needed to quantify these impacts in measures that can be linked with broader socioeconomic systems. This article reviews existing such methods and organizes them into a conceptual framework to understand trends and gaps in the literature. We found methods quantifying impacts of a range of climate drivers on most transportation modes present in the Arctic, but few methods focused on socioeconomic drivers. Also underrepresented were methods explicitly considering adaptive capacity of transportation systems. In conclusion, we provide insight into the data and relationships relevant to understanding impacts of Arctic change on transportation systems and how these impacts fit into broader human- Earth systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

MSD CoP Webinar: Representing Climate Impacts in Scenaros

Context: This webinar was hosted by the MultiSector Dynamics Community of Practice (MSD CoP; https://multisectordynamics.org). Abstract: Scenarios of future emissions and land use have been most commonly produced without accounting for the effects that climate impacts linked to those emissions and land use changes may have. The questions of how important such impacts could be, at the regional or global scale, has become an increasingly cogent one. Using the Global Change Analysis Model (GCAM), we implement climate impacts on water supply, agricultural productivity, and energy demand driven by climatic impact drivers whose evolution over the 21st century is representative of a climate consistent with GCAM's reference scenario and compare the output to the reference at both regional and global scales. We show that the impacts from the version of GCAM that uses GDP as an exogenous input are not sufficient to bend emission pathways at the global scale. However, we see effects emerge at the regional scale in terms of emissions, among other metrics linked to water, land and energy. We expect the impacts to become more significant at an aggregate, global scale in a forthcoming version of the model with endogenous GDP. Meanwhile, we document the mechanisms that drive the difference at regional scales which could still be significant in their impacts for individual economies and populations. Presenters: Dr. Claudia Tebaldi (Joint Global Change Research Institute, Pacific Northwest National Laboratory) Moderator(s): Jennifer Morris (MSD CoP SSG member), Patrick Reed (MSD CoP Facilitation Team Member, Moderator and Organizer) This webinar was held on: November 5, 2024 from 1 PM - 2:15 PM ET

Climate Scenarios↗
DOE OSTI2021

Joint effects of climate, tree size, and year on annual tree growth derived from tree–ring records of ten globally distributed forests

Tree rings provide an invaluable long-term record for understanding how climate and other drivers shape tree growth and forest productivity. However, conventional tree-ring analysis methods were not designed to simultaneously test effects of climate, tree size, and other drivers on individual growth. This has limited the potential to test ecologically relevant hypotheses on tree growth sensitivity to environmental drivers and their interactions with tree size. Here, we develop and apply a new method to simultaneously model nonlinear effects of primary climate drivers, reconstructed tree diameter at breast height (DBH), and calendar year in generalized least squares models that account for the temporal autocorrelation inherent to each individual tree's growth. We analyze data from 3811 trees representing 40 species at 10 globally distributed sites, showing that precipitation, temperature, DBH, and calendar year have additively, and often interactively, influenced annual growth over the past 120 years. Growth responses were predominantly positive to precipitation (usually over ≥3-month seasonal windows) and negative to temperature (usually maximum temperature, over ≤3-month seasonal windows), with concave-down responses in 63% of relationships. Climate sensitivity commonly varied with DBH (45% of cases tested), with larger trees usually more sensitive. Trends in ring width at small DBH were linked to the light environment under which trees established, but basal area or biomass increments consistently reached maxima at intermediate DBH. Accounting for climate and DBH, growth rate declined over time for 92% of species in secondary or disturbed stands, whereas growth trends were mixed in older forests. These trends were largely attributable to stand dynamics as cohorts and stands age, which remain challenging to disentangle from global change drivers. By providing a parsimonious approach for characterizing multiple interacting drivers of tree growth, our method reveals a more complete picture of the factors influencing growth than has previously been possible.

generalized least squares (GLS)↗
DOE OSTI2024

Estimating the CO 2 Fertilization Effect on Extratropical Forest Productivity From Flux‐Tower Observations

Abstract The land sink of anthropogenic carbon emissions, a crucial component of mitigating climate change, is primarily attributed to the CO 2 fertilization effect on global gross primary productivity (GPP). However, direct observational evidence of this effect remains scarce, hampered by challenges in disentangling the CO 2 fertilization effect from other long‐term confounding drivers, particularly climatic changes. Here, we introduce a novel statistical approach to separate the CO 2 fertilization effect on photosynthetic carbon uptake using eddy covariance (EC) records across 38 extratropical forest sites. We find the median stimulation rate of GPP to be 3.2 ± 0.9 gC m −2 yr −1 ppm −1 (or 16.4 ± 4.2% per 100 ppm) under increasing atmospheric CO 2 across these sites, respectively. To validate the robustness of our findings, we test our statistical method using factorial simulations of an ensemble of process‐based land surface models. We address additional factors, including nitrogen deposition and land management, that may impact plant productivity, potentially confounding the attribution to the CO 2 fertilization effect. Assuming these site‐specific effects offset to some extent across sites as random factors, the estimated median value still reflects the strength of the CO 2 fertilization effect. However, disentanglement of these long‐term effects, often inseparable by timescale, requires further causal research. Our study provides direct evidence that the photosynthetic stimulation is maintained under long‐term CO 2 fertilization across multiple EC sites. Such observation‐based quantification is key to constraining the long‐standing uncertainties in the land carbon cycle under rising CO 2 concentrations.

Environmental Sciences & Ecology↗
DOE OSTI2022

Vegetation type is an important predictor of the arctic summer land surface energy budget

Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994–2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm –2 ) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

The Largely Ignored but Important Role of Non‐Rooted, Submersed Vegetation and Small Waterbodies on Greenhouse Gas Emissions

Abstract Small, shallow waterbodies are abundant globally and are associated with greenhouse gas (GHG) emissions disproportionate to their size. One reason for this is the prevalence of non‐rooted, submersed (NRS) macrophytes that often dominate these systems. Despite these plants' significant role in the carbon ecology of their ecosystems, they are often excluded from climate change models due, in part, to the lack of clarity of their effects. Theus et al. (2023, https://doi.org/10.1029/2023JG007758 ) provides new insights into the role that NRS macrophytes have on GHG emissions, demonstrating that increasing densities of these macrophytes lead to increases in both CO 2 and CH 4 gas fluxes. Here, we highlight the importance of both shallow waterbodies and NRS vegetation within the context of the field of aquatic ecosystem biogeochemistry. We identify a need for the inclusion of these drivers into climate change models based partly on the findings of Theus et al. (2023, https://doi.org/10.1029/2023JG007758 ).

Hassett, Erin↗
DOE OSTI2025

Northern peatland microbial communities exhibit resistance to warming and acquire electron acceptors from soil organic matter

The response of microbial communities that regulate belowground carbon turnover to climate change drivers in peatlands is poorly understood. Here, we leverage a whole ecosystem warming experiment to elucidate the key processes of terminal carbon decomposition and community responses to temperature rise. Our dataset of 697 metagenome-assembled genomes (MAGs) represents the microbial community from the surface (10 cm) to 2 m deep into the peat column, with only 3.7% of genomes overlapping with other well-studied peatlands. Community composition has yet to show a significant response to warming after 3 years, suggesting that metabolically diverse soil microbial communities are resistant to climate change. Surprisingly, abundant and active methanogens in the genus Candidatus Methanoflorens, Methanobacterium , and Methanoregula show the potential for both acetoclastic and hydrogenotrophic methanogenesis. Nonetheless, the predominant pathways for anaerobic carbon decomposition include sulfate/sulfite reduction, denitrification, and acetogenesis, rather than methanogenesis based on gene abundances. Multi-omics data suggest that organic matter cleavage provides terminal electron acceptors, which together with methanogen metabolic flexibility, may explain peat microbiome composition resistance to warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Elevated temperature alters microbial communities, but not decomposition rates, during 3 years of in situ peat decomposition

ABSTRACT Peatlands are large carbon sinks with primary production outpacing decomposition of organic matter. Results from the S pruce and P eatland R esponses U nder C hanging E nvironments (SPRUCE) study show net losses of organic matter and increased greenhouse gas production from peatlands in response to whole-ecosystem warming. Here, we investigated how warming and elevated CO 2 impact peat microbial communities and peat soil decomposition rates and characterized microbial communities through amplicon sequencing and compositional changes across four depth increments. Microbial diversity and community composition were significantly impacted by soil depth, temperature, and CO 2 treatment. Bacterial/archaeal α-diversity increased significantly with increasing temperature, and fungal α-diversity was lower under elevated CO 2 treatments. Trans domain microbial networks showed higher complexity of microbial communities in decomposition ladder depths from the warmed enclosures, and the number of highly connected hub taxa within the networks was positively correlated with temperature. Methanogenic hubs were identified in the networks constructed from the warmest enclosures, indicating increased importance of methanogenesis in response to warming. Microbial community responses were not however reflected in measures of peat soil decomposition, as warming and elevated CO 2 had no significant short-term effects on soil mass loss or composition. Regardless of treatment, on average only 4.5% of the original soil mass was lost after 3 years and variation between replicates was high, potentially masking treatment effects. Previous results at the SPRUCE experiment have shown warming is accelerating organic-matter decomposition and CO 2 and CH 4 production, and our results suggest these changes may be driven by warming-induced shifts in microbial communities. IMPORTANCE Microbial community changes in response to climate change drivers have the potential to alter the trajectory of important ecosystem functions. In this paper, we show that while microbial communities in peatland systems responded to manipulations of temperature and CO 2 concentrations, these changes were not associated with similar responses in peat decomposition rates over 3 years. It is unclear however from our current studies whether this functional resiliency over 3 years will continue over the longer time scales relevant to peatland ecosystem functions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Urban Scaling as Validation for Predictions of Imperviousness From Population

Abstract Strategies for creating quantitative projections for human systems, especially impervious surfaces, are necessary to consider the human drivers of climate and ecosystem change. There are models that generate predictions of how impervious surfaces may change in response to different potential futures, but few tools exist for validating those predictions. We seek to fill that gap. We demonstrate a statistically robust sublinear scaling relationship between population and urban imperviousness across a 15 year history. We show that Integrated Climate and Land‐Use Scenarios (ICLUS) urbanization projections are also consistent with theory. These results demonstrate a theory that can be used to validate other models' predictions of urban growth and land cover change, analogous to the ways in which allometric scaling laws in biology have been used to validate process‐based models of ecosystem composition under different climate scenarios.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Trends in Downwelling Longwave Radiance Over the Southern Great Plains

Downwelling longwave radiation is an important part of the surface energy budget. Spectral trends in the downwelling longwave radiance (DLR) provide insight into the radiative drivers of climate change. In this research, we process and analyze a 23-year DLR record measured by the Atmospheric Emitted Radiance Interferometer (AERI) at the U.S. Department of Energy Atmospheric Radiation Program Southern Great Plains (SGP) site. Two AERIs were deployed at SGP with an overlapping observation period of about 10 years, which allows us to examine the consistency and accuracy of the measurements and to account for discrepancies between them due to errors associated with the instruments themselves. We then analyzed the all-sky radiance trends in DLR, which are associated with the surface warming trend at SGP during this same period and also the complex changes in meteorological conditions. For instance, the observed radiance in the CO2 absorption band follows closely the near-surface air temperature variations. The significant positive radiance trends in weak absorption channels, such as in the wings of the CO 2 band and in the weak absorption channels in the H 2 O vibration-rotational band, show earlier detectability of climate change. The magnitude of the radiance trend uncertainty in the DLR record mainly results from internal climate variability rather than from measurement error, which highlights the importance of continuing the DLR spectral measurements to unambiguously detect and attribute climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Scaling of Floods With Geomorphologic Characteristics and Precipitation Variability Across the Conterminous United States

Abstract Accurate flood risk assessment requires a comprehensive understanding of flood sensitivity to regional drivers and climate factors. This paper presents the scaling of floods (duration, peak, volume) with geomorphologic characteristics of the basin (i.e., drainage area, slope, elevation) and precipitation patterns (rainfall accumulation, variability). Long‐term daily streamflow observations over the 20th and early 21st centuries from Hydro‐Climatic Data Network streamgages across the conterminous United States are used to create a flood event database based on their flood stage information. Antecedent daily rainfall accumulation and variability corresponding to these floods are computed using Global Historical Climatology Network daily data set. Two Bayesian scaling models are developed, and the spatial organization of scaling exponents is investigated. The baseline model quantifies the scaling of floods to geomorphologic characteristics. The dynamic model quantifies the scaling of floods to antecedent precipitation distribution which is further conditioned on geomorphologic characteristics. Results show that small and low‐elevation basins have a stronger response to antecedent rainfall distribution in amplifying flood peaks, while high‐elevation steeper basins have a lower response for flood duration and volume. The dynamic models demonstrate that there are significant variations in the flood scaling rates, with the largest rates up to 40% and 4.5% for flood duration, 64% and 44% for peak, and 98% and 40% for volume found across the Northeast, Coastal Southeast, and Northwest with intensifying rainfall accumulation and variability, respectively. This study advances flood predictions by better informing the flood attributes in the context of dynamical land‐atmosphere perturbations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Aerosol effective radiative forcing increases Earth’s energy imbalance in recent decades

Earth’s energy imbalance (EEI), a key driver of climate change, has risen markedly over the last two decades. Greenhouse gas forcing, aerosol forcing, and cloud feedback all contribute to this increase. However, the role of aerosol forcing, particularly effective radiative forcing through aerosol-cloud interactions (ERF ACI ), remains highly uncertain and closely intertwined with cloud feedback. Here, we estimate shortwave ERF ACI using satellite observations and show its importance as a contributor to the EEI increase between 2003 and 2023. ERF ACI exhibits a significant increasing trend of 0.33 Wm −2 /decade averaged over oceans between 60°S and 60°N. The increasing trend of ERF ACI stems from a global decline in cloud droplet number concentration driven by decreasing anthropogenic aerosol emissions. It is of similar magnitude as the combined instantaneous forcing trend from greenhouse gases and aerosol-radiation interactions. Our results may reduce the gap between the simulated and observed shortwave contribution to EEI trends while implying a weak shortwave cloud feedback. They also suggest a stronger aerosol forcing than the multi-model mean.

Yuan, Tianle [NASA Goddard Space Flight Center (GS↗
DOE OSTI2023

Pantropical Indo-Atlantic temperature gradient modulates multi-decadal AMOC variability in models and observations

Abstract Interconnections between ocean basins are recognized as an important driver of climate variability. Recent modeling evidence suggests that the North Atlantic climate can respond to persistent warming of the tropical Indian Ocean sea surface temperature (SST) relative to the rest of the tropics (rTIO). Here, we use observational data to demonstrate that multi-decadal changes in pantropical ocean temperature gradients lead to variations of an SST-based proxy of the Atlantic Meridional Overturning Circulation (AMOC). The largest contribution to this temperature gradient-AMOCconnection comes from gradients between the Indian and Atlantic Oceans. TherTIOindex yields the strongest connection of this tropical temperature gradient to theAMOC. Focusing on the internally generated signal in three observational products reveals that an SST-basedAMOCproxy index has closely followed low-frequency changes ofrTIOtemperature with about 26-year lag since 1870. Analyzing the pre-industrial control simulations of 44 CMIP6 climate models shows that theAMOCproxy index lags simulated mid-latitudeAMOCvariations by 4 ± 4 years. These model simulations reveal the mechanism connectingAMOCvariations to pantropical ocean temperature gradients at a 27 ± 2 years lag, matching the observed time lag in 28 out of the 44 analyzed models. rTIO temperature changes affect the North Atlantic climate through atmospheric planetary waves, impacting temperature and salinity in the subpolar North Atlantic, which modifies deep convection and ultimately the AMOC. Through this mechanism, observed internalrTIOvariations can serve as a multi-decadal precursor ofAMOCchanges with important implications forAMOCdynamics and predictability.

Meteorology & Atmospheric Sciences↗
DOE OSTI2022

Monitoring Methane Emissions from Oil and Gas Operations

The atmospheric concentration of methane has more than doubled since the start of the Industrial Revolution. Methane is the second-most-abundant greenhouse gas created by human activities and a major driver of climate change. This APS-Optica report provides a technical assessment of the current state of monitoring U.S. methane emissions from oil and gas operations, which accounts for roughly 30% of U.S. anthropogenic methane emissions. The report identifies current technological and policy gaps and makes recommendations for the federal government in three key areas: methane emissions detection, reliable and systematized data and models to support mitigation measures, and effective regulation.

02 PETROLEUM↗
DOE OSTI2024

Priorities, opportunities, and challenges for integrating microorganisms into Earth system models for climate change prediction

ABSTRACT Climate change jeopardizes human health, global biodiversity, and sustainability of the biosphere. To make reliable predictions about climate change, scientists use Earth system models (ESMs) that integrate physical, chemical, and biological processes occurring on land, the oceans, and the atmosphere. Although critical for catalyzing coupled biogeochemical processes, microorganisms have traditionally been left out of ESMs. Here, we generate a “top 10” list of priorities, opportunities, and challenges for the explicit integration of microorganisms into ESMs. We discuss the need for coarse-graining microbial information into functionally relevant categories, as well as the capacity for microorganisms to rapidly evolve in response to climate-change drivers. Microbiologists are uniquely positioned to collect novel and valuable information necessary for next-generation ESMs, but this requires data harmonization and transdisciplinary collaboration to effectively guide adaptation strategies and mitigation policy.

Microbiology↗
DOE OSTI2025

Genetic and biochemical characterization of a radical SAM enzyme required for post-translational glutamine methylation of methyl-coenzyme M reductase

ABSTRACT Methyl-coenzyme M reductase (MCR), the key catalyst in the anoxic production and consumption of methane, contains an unusual 2-methylglutamine residue within its active site. In vitro data show that a B12-dependent radical SAM (rSAM) enzyme, designated MgmA, is responsible for this post-translational modification (PTM). Here, we show that two different MgmA homologs are able to methylate MCR in vivo when expressed in Methanosarcina acetivorans , an organism that does not normally possess this PTM. M. acetivorans strains expressing MgmA showed small, but significant, reductions in growth rates and yields on methylotrophic substrates. Structural characterization of the Ni(II) form of Gln-methylated M. acetivorans MCR revealed no significant differences in the protein fold between the modified and unmodified enzyme; however, the purified enzyme contained the heterodisulfide reaction product, as opposed to the free cofactors found in eight prior M. acetivorans MCR structures, suggesting that substrate/product binding is altered in the modified enzyme. Structural characterization of MgmA revealed a fold similar to other B12-dependent rSAMs, with a wide active site cleft capable of binding an McrA peptide in an extended, linear conformation. IMPORTANCE Methane plays a key role in the global carbon cycle and is an important driver of climate change. Because MCR is responsible for nearly all biological methane production and most anoxic methane consumption, it plays a major role in setting the atmospheric levels of this important greenhouse gas. Thus, a detailed understanding of this enzyme is critical for the development of methane mitigation strategies.

Rodriguez Carrero, Roy J. (ORCID:0000000184475641)↗
DOE OSTI2020

Impact of Model Resolution on Tropical Cyclone Simulation Using the HighResMIP–PRIMAVERA Multimodel Ensemble

A multimodel, multiresolution set of simulations over the period 1950–2014 using a common forcing protocol from CMIP6 HighResMIP have been completed by six modeling groups. Analysis of tropical cyclone performance using two different tracking algorithms suggests that enhanced resolution toward 25 km typically leads to more frequent and stronger tropical cyclones, together with improvements in spatial distribution and storm structure. Both of these factors reduce typical GCM biases seen at lower resolution. Using single ensemble members of each model, there is little evidence of systematic improvement in interannual variability in either storm frequency or accumulated cyclone energy as compared with observations when resolution is increased. Changes in the relationships between large-scale drivers of climate variability and tropical cyclone variability in the Atlantic Ocean are also not robust to model resolution. However, using a larger ensemble of simulations (of up to 14 members) with one model at different resolutions does show evidence of increased skill at higher resolution. The ensemble mean correlation of Atlantic interannual tropical cyclone variability increases from ~0.5 to ~0.65 when resolution increases from 250 to 100 km. In the northwestern Pacific Ocean the skill keeps increasing with 50-km resolution to 0.7. These calculations also suggest that more than six members are required to adequately distinguish the impact of resolution within the forced signal from the weather noise.

54 ENVIRONMENTAL SCIENCES↗