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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Regional MJO Modulation of Northwest Pacific Tropical Cyclones Driven by Multiple Transient Controls

The Madden–Julian Oscillation (MJO) is widely acknowledged for its ability to modulate Northwest Pacific tropical cyclones (TCs), but a complete understanding of the underlying mechanisms remains uncertain. Beyond established effects of the MJO's relative humidity envelope, other dynamical factors have recently been invoked via new genesis potential indices and high-resolution modeling studies. Here we revisit the ability of the MJO to modulate West Pacific TCs through a quasi-explicit cyclone downscaling strategy driven by composited observations, paired later with a genesis index to investigate regional drivers of modulation. In this work, we reveal two distinct spatial modes of TC modulation in which the MJO's dynamic and thermodynamic effects act in tandem to increase TCs. In the South China Sea, for instance, shear reductions associated with the MJO's circulation lead to increasing potential intensity ahead of the arrival of a positive humidity anomaly, all of which combine for an extended period of cyclogenesis favorability.

58 GEOSCIENCES↗
DOE OSTI2020

Wintertime particulate matter decrease buffered by unfavorable chemical processes despite emissions reductions in China

Extreme and persistent haze events frequently occur during wintertime China. While recent emissions reductions reduced annual mean fine particulate matter (PM2.5) concentrations over eastern China, their effectiveness on wintertime PM2.5 trend remains uncertain. We use observations and model simulations to quantify seasonal differences in PM2.5 trends and investigate the underlying chemical mechanisms driving such differences. We find a much slower decrease in observed wintertime PM2.5 (–3.2% yr-1) since 2014, in contrast to a drastic summertime decrease (–10.3% yr-1). Simulations show two previously underappreciated mechanisms buffering wintertime PM2.5 decrease, including an increase in oxidation capacity due to nitrogen oxides (NOx) reductions under wintertime volatile organic compound (VOC)- limited chemistry, and an enhanced conversion of nitric acid to nitrate by ammonia due to sulfur dioxide reductions. Our findings suggest that control policies targeting VOC and deep NOx reductions are needed to improve wintertime PM2.5 air quality over China.

Leung, Danny M.↗
DOE OSTI2020

Assessing Global and Local Radiative Feedbacks Based on AGCM Simulations for 1980–2014/2017

In order to avoid contamination of unobservable and uncertain effective radiative forcing (ERF) on the diagnosis of radiative feedbacks based on short-term climate variability, we verify the Kernel-Gregory feedback calculation method using atmospheric model experiments with prescribed ERF. We show that both clear-sky radiative fluxes and all-sky radiative feedbacks have a closure between model simulations and kernel derivations. A near-zero global mean net cloud feedback is found in the simulation with prescribed ERF, which results in a more negative global net climate feedback, -2 W m -2 K -1 . Consistent with AMIP6 ensemble mean results, the lapse rate feedback is the largest contributor among all feedbacks to temperature amplification over the three poles (Arctic, Antarctic and Tibetan Plateau), followed by surface albedo feedback and Planck feedback deviation from its global mean. Except for the higher surface albedo feedback in the Antarctic, other feedbacks are almost same between the Arctic and Antarctic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Projected Future Changes in Tropical Cyclones Using the CMIP6 HighResMIP Multimodel Ensemble

Future changes in tropical cyclone properties are an important component of climate change impacts and risk for many tropical and midlatitude countries. In this study we assess the performance of a multimodel ensemble of climate models, at resolutions ranging from 250 to 25 km. We use a common experimental design including both atmosphere-only and coupled simulations run over the period 1950–2050, with two tracking algorithms applied uniformly across the models. There are overall improvements in tropical cyclone frequency, spatial distribution, and intensity in models at 25 km resolution, with several of them able to represent very intense storms. Projected tropical cyclone activity by 2050 generally declines in the South Indian Ocean, while changes in other ocean basins are more uncertain and sensitive to both tracking algorithm and imposed forcings. Coupled models with smaller biases suggest a slight increase in average TC 10 m wind speeds by 2050.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Aquifer Monitoring Using Ambient Seismic Noise Recorded With Distributed Acoustic Sensing (DAS) Deployed on Dark Fiber

Abstract Groundwater is a critical resource for human activities worldwide, and a vital component of many natural ecosystems. However, the state and dynamics of water‐bearing aquifers remain uncertain, mostly due to the paucity of subsurface data at high spatial and temporal resolution. Here, we show that analysis of infrastructure‐generated ambient seismic noise acquired on distributed acoustic sensing (DAS) arrays has potential as a tool to track variations in seismic velocities (d v / v ) caused by groundwater level fluctuations. We analyze 5 months of ambient noise acquired along an unused, 23 km‐long telecommunication fiber‐optic cable in the Sacramento Valley, CA, a so‐called “dark fiber." Three array subsections, ∼6 km apart, are processed and the stretching technique is applied to retrieve daily d v / v beneath each location. Near the Sacramento river, d v / v variations in the order of 2%–3% correlate with precipitation events and fluctuations in river stage of ∼1.5 m. In contrast, regions away (2.5 km) from the river do not experience large d v / v variations. These observations reveal short‐scale spatial variability in aquifer dynamics captured by this approach. Dispersion analysis and surface wave inversion of noise gathers reveal that seismic velocity perturbations occur at depths of 10–30 m. Rock physics modeling confirms that observed d v / v are linked to pore pressure changes at these depths, caused by groundwater table fluctuations. Our results suggest that DAS combined with ambient noise interferometry provides a means of tracking aquifer dynamics at high spatial and temporal resolutions at local to regional scales, relevant for effective groundwater resource management.

58 GEOSCIENCES↗
DOE OSTI2021

Geochemical, Biological, and Clumped Isotopologue Evidence for Substantial Microbial Methane Production Under Carbon Limitation in Serpentinites of the Samail Ophiolite, Oman

In hyperalkaline (pH > 10) fluids that have participated in low-temperature (<150°C) serpentinization reactions, the dominant form of C is often methane (CH 4 ), but the origin of this CH 4 is uncertain. To assess CH 4 origin in serpentinite aquifers within the Samail Ophiolite, Oman, we determined fluid chemical compositions, analyzed taxonomic profiles of fluid-hosted microbial communities, and measured isotopic compositions of hydrocarbon gases. We found that 16S rRNA gene sequences affiliated with methanogens were widespread in the aquifer. We measured clumped isotopologue ( 13 CH 3 D and 12 CH 2 D 2 ) relative abundances less than equilibrium, consistent with substantial microbial CH 4 production. Furthermore, we observed an inverse relationship between dissolved inorganic C concentrations and δ 13 C CH 4 across fluids bearing microbiological evidence of methanogenic activity, suggesting that the apparent C isotope effect of microbial methanogenesis is modulated by C availability. An additional source of CH 4 is evidenced by the presence of CH 4 -bearing fluid inclusions in the Samail Ophiolite and our measurement of high δ 13 C values of ethane and propane, which are similar to those reported in studies of CH 4 -rich inclusions in rocks from the oceanic lithosphere. In addition, we observed 16S rRNA gene sequences affiliated with aerobic methanotrophs and, in lower abundance, anaerobic methanotrophs, indicating that microbial consumption of CH 4 in the ophiolite may further enrich CH 4 in 13 C. We conclude that substantial microbial CH 4 is produced under varying degrees of C limitation and mixes with abiotic CH 4 released from fluid inclusions. This study lends insight into the functioning of microbial ecosystems supported by water/rock reactions.

58 GEOSCIENCES↗
DOE OSTI2020

Evaluation of Methods for Causal Discovery in Hydrometeorological Systems

Understanding causal relations is of utmost importance in hydrology and climate research for systems identification, prediction, and understanding systems behavior in a changing climate. Traditionally, researchers in hydrometeorology attempted to study causal questions by conducting controlled experiments using numerical models. This approach, however, in most cases of interest provides uncertain results because the models are approximate representation of the natural system. An alternative approach that has recently drawn significant attention in several fields is to infer causal relations from purely observational data. It possesses several traits to its utility particularly in hydrometeorology due to the rapid accumulation of in situ and remotely sensed data records. The first objective of this study is to present a brief description of four causal discovery methods (Granger causality, Transfer Entropy, graph-based algorithms, and Convergent Cross Mapping) with special emphasis on the assumptions on which they are built. Second, using synthetic data generated from a hydrological model, we assess their performance in retrieving causal information taking into account sensitivity to sample size and presence of noise. Last, we use causal analysis to examine and formulate hypotheses on causal drivers of evapotranspiration in a shrubland region during summer and winter seasons. An interpretation of the hypotheses based on canopy seasonal dynamics and evapotranspiration processes is presented. It is hoped that the results presented here can be useful in guiding researchers studying hydrometeorological systems as to which causal method is most appropriate to the characteristics of the system under study.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Assessing Adaptive Irrigation Impacts on Water Scarcity in Nonstationary Environments—A Multi‐Agent Reinforcement Learning Approach

Abstract One major challenge in water resource management is to balance the uncertain and nonstationary water demands and supplies caused by the changing anthropogenic and hydroclimate conditions. To address this issue, we developed a reinforcement learning agent‐based modeling (RL‐ABM) framework where agents (agriculture water users) are able to learn and adjust water demands based on their interactions with the water systems. The intelligent agents are created by a reinforcement learning algorithm adapted from the Q‐learning algorithm. We illustrated this framework in a case study where the RL‐ABM is two‐way coupled with the Colorado River Simulation System (CRSS), a long‐term planning model used for the administration of the Colorado River Basin, for assessing agriculture water uses impacts on water scarcity. Seventy‐eight intelligent agents are simulated, which can be grouped into three categories based on their parameter values: the “aggressive” (swift actions; low regrets), the “forward‐looking conservative” (mild actions; high regrets; fast learning), and the “myopic conservative” (mild actions; median regrets; slow learning). The ABM‐CRSS results showed that the major reservoirs in the Upper Colorado Basin might experience more frequent water shortages due to the increasing water uses compared to the original CRSS results. If the drought continues, the case study also demonstrates that agents can learn and adjust their demands.

Hung, Fengwei↗
DOE OSTI2022

Modeling the Economic and Environmental Impacts of Land Scarcity Under Deep Uncertainty

Abstract Land scarcity is increasing over time, driven by complex multisector dynamics. The impacts of land scarcity on the economy and environment are multi‐faceted and regional, so any action to convert land will contain inherent tradeoffs. These impacts are complicated by the deeply uncertain evolution of the various sectors influencing land scarcity. A need therefore exists to provide multi‐metric and multi‐sector assessments that are robust to myriad uncertainties. Land conservation effectively limits the supply of productive land, while biofuel consumption increases the demand and competition for that land, and how these dynamics individually and jointly propagate to economic and environmental impacts is an important open question. To address this, we adopt the Global Change Analysis Model (GCAM) that has representations of various important systems including the climate, macroeconomic, energy, agriculture and land, and water resources systems. Various scenarios of increased land demand (from biofuels) and decreased land supply (from conservation) under various socioeconomic scenarios drawn from the SSPs were simulated using GCAM. We find that while biofuel consumption and land conservation reduce carbon emissions, this comes at the cost of higher food prices, reduced crop production, and increased water withdrawals. Additionally, some regions experience these tradeoffs more severely than others and are more heavily impacted from the same biofuel mandate or by an additional percent of protected land. These and other findings highlight the importance of multisector modeling frameworks that capture many cross‐sector linkages, and acknowledge the important uncertainties confronting the human‐Earth system when making any analysis of land scarcity impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Quantifying Northern High Latitude Gross Primary Productivity (GPP) Using Carbonyl Sulfide (OCS)

The northern high latitude (NHL, 40°N to 90°N) is where the second peak region of gross primary productivity (GPP) other than the tropics. The summer NHL GPP is about 80% of the tropical peak, but both regions are still highly uncertain. Carbonyl sulfide (OCS) provides an important proxy for photosynthetic carbon uptake. Here we optimize the OCS plant uptake fluxes across the NHL by fitting atmospheric concentration simulation with the GEOS-CHEM global transport model to the aircraft profiles acquired over Alaska during NASA's Carbon in Arctic Reservoirs Vulnerability Experiment (2012–2015). We use the empirical biome-specific linear relationship between OCS plant uptake flux and GPP to derive the six plant uptake OCS fluxes from different GPP data. Such GPP-based fluxes are used to drive the concentration simulations. We evaluate the simulations against the independent observations at two ground sites of Alaska. The optimized OCS fluxes suggest the NHL plant uptake OCS flux of -247 Gg S year -1 , about 25% stronger than the ensemble mean of the six GPP-based OCS fluxes. GPP-based OCS fluxes systematically underestimate the peak growing season across the NHL, while a subset of models predict early start of season in Alaska, consistent with previous studies of net ecosystem exchange. The OCS optimized GPP of 34 PgC yr -1 for NHL is also about 25% more than the ensembles mean from six GPP data. Further work is needed to fully understand the environmental and biotic drivers and quantify their rate of photosynthetic carbon uptake in Arctic ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Vegetation Response to Rising CO 2 Amplifies Contrasts in Water Resources Between Global Wet and Dry Land Areas

Rising atmospheric CO 2 impacts on vegetation physiological processes can alter land feedbacks on precipitation and water resources, but understanding of regional differences in these changes is uncertain. We investigate the impact of rising CO 2 on land water resources for different wetness levels using four Earth system models. We find an overall tendency of runoff to increase across all wetness levels. However, runoff increases in wet regions are much larger than those in dry regions, especially in wet seasons. This substantial amplification of contrasts between wet and dry regions increases at 3% per 100 ppm increase in CO 2 relative to the historical period, reaching 18% for a quadrupling of CO 2 , quantified by a new wetting contrast index (WCI). Physiological effects suppress evapotranspiration more in wet than dry regions, which has a larger contribution than radiative forcing to the amplification of runoff contrast, reshaping the spatial distribution of future land water resources.

58 GEOSCIENCES↗
DOE OSTI2021

The NPF Effect on CCN Number Concentrations: A Review and Re-Evaluation of Observations From 35 Sites Worldwide

The new particle formation (NPF) effect on cloud condensation nuclei (CCN) differs from region to region and remains highly uncertain. In this work, we re-evaluate the NPF-initiated enhancements in CCN number concentrations (E_N CCN ) by compiling results from 35 field sites worldwide and five global models. We show the E_N CCN at sites close to the anthropogenic sources are more than 2-fold as large as that at remote sites with supersaturations of 0.1%–1.0%. The enhancements anti-correlate with the time scales for the new particles to grow to CCN size, which are 5–10 and 20–30 hr at polluted and remote sites, respectively. We further reveal that under polluted environments the condensational growth of new particles may be accelerated, leading to larger E_N CCN . The models fail to simulate the E_NCCN in polluted regions. Our study highlights the importance of parameterizing the time scale of NPF to affect CCN differently for remote and polluted regions in models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Earth System Model Overestimation of Cropland Temperatures Scales With Agricultural Intensity

Intensive crop growth can modify regional climate by partitioning energy to latent heating through transpiration, cooling growing season temperatures. Recent work shows that cooling associated with agriculture can dampen anthropogenic warming over breadbasket regions. However, it is unknown whether climate models reproduce crop influences on regional climate, and thus the future risk of extreme climate events over global breadbasket regions. Here, we show that models overestimate growing season temperatures and underestimate evapotranspiration (ET) over global croplands, and that these differences increase with cropped area. We trace this warm and dry difference through each model's representation of the surface energy budget, showing that model differences in transpiration, leaf area index, and the ratio of transpiration to total ET drive the overall effect. While the implications of these model deficiencies for future projections are uncertain, they point to the importance of improving representations of crop-climate processes to better assess breadbasket vulnerability to climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Probabilistic Evaluation of Geoscientific Hypotheses with Geophysical Data: Application to Electrical Resistivity Imaging of a Fractured Bedrock Zone

As climate changes and populations grow, groundwater sustainability is becoming increasingly important. Groundwater models, based on a conceptual understanding of the subsurface structure, are crucial tools for making sustainable management decisions. Conceptual models of the subsurface are based on knowledge of geological processes, and, frequently, observations from geophysical data. A frequent problem in groundwater model development occurs when multiple geological phenomena could explain a single subsurface observation. Uncertainty in geophysical data makes it even more difficult to discern which explanations are consistent with the geophysics. Here, we present a framework for testing geological when a geological feature is observed in geophysical data, but its physical characteristics are uncertain. The framework builds on Popper-Bayes methods developed in previous work, and is applied to study a fractured bedrock zone in a mountainous watershed in southwest Colorado. First, we outline six hypotheses based on the geological history of the watershed. Then, using the proposed Popper-Bayes approach, we demonstrate that three of the six hypotheses are inconsistent with measured electrical resistivity data, even after accounting for uncertainty. Finally, we discuss the importance of the prior model, and how this framework for handling geophysical uncertainty can be applied in other settings.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Investigating the Impacts of Daytime Boundary Layer Clouds on Surface Energy Fluxes and Boundary Layer Structure During CHEESEHEAD19

Studies of land-atmosphere interactions under a clear sky and low cumulus cloud conditions are common from long-term observatories like at the southern great plains. How well the relationships and responses of surface radiative and turbulent heat fluxes determined from these investigations hold for more heterogeneous surfaces in other climate regimes, however, is uncertain. In this study, detailed observations of the surface energy budget and daytime boundary layer properties are analyzed using measurements from the Chequamegon Heterogenous Ecosystem Energy-Balance Study Enabled by a High-Density Extensive Array of Detectors 2019 (CHEESEHEAD19) field campaign, July-October 2019, across a heterogeneous forested landscape of northern Wisconsin. A cloud regime framework is employed to classify consecutive periods of clear skies from lower atmosphere stratiform and cumulus clouds. A seasonal transition from low cumulus to low stratiform periods occurred, together with a diurnal pattern in cloudy or clear sky period dominance. Radiative forcing was highly dependent on sky conditions, leading to changes in the redistribution efficiency of radiative energy by the surface turbulent heat fluxes. During CHEESEHEAD19, small Bowen ratios dominated with daytime latent heat fluxes three times as large as sensible heat fluxes for all sky conditions studied; the forested region, therefore, falls within an energy-limited regime. The depth of the daytime mixed layer depended upon the sky condition and thermodynamic setting; deeper mixed layers occurred during periods of low cumulus and not clear skies. Profiles of vertical velocity were found to have enhanced variance under low cumulus compared to clear sky periods, suggesting potential for cloud feedbacks on boundary layer structure and surface energy fluxes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Experimental Soil Warming and Permafrost Thaw Increase CH 4 Emissions in an Upland Tundra Ecosystem

Rapid Arctic warming is causing permafrost to thaw and exposing large quantities of soil organic carbon (C) to potential decomposition. In dry upland tundra systems, subsidence from thawing permafrost can increase surface soil moisture resulting in higher methane (CH 4 ) emissions from newly waterlogged soils. The proportion of C released as carbon dioxide (CO 2 ) and CH 4 remains uncertain as previously dry landscapes transition to a thawed state, resulting in both wetter and drier microsites. To address how thaw and moisture interact to affect total C emissions, here we measured CH 4 and CO 2 emissions from paired chambers across thaw and moisture gradients created by nine years of experimental soil warming in interior Alaska. Cumulative growing season (May–September) CH 4 emissions were elevated at both wetter (216.1–1,099.4 mg CH 4 -C m –2 ) and drier (129.7–392.3 mg CH 4 -C m –2 ) deeply thawed microsites relative to shallow thaw (55.6–215.7 mg CH 4 -C m –2 ) and increased with higher deep soil temperatures and permafrost thaw depth. Interannual variability in CH4 emissions was driven by wet conditions in graminoid-dominated plots that generated >70% of emissions in a wet year. Shoulder season emissions were equivalent to growing season CH 4 emissions rates in the deeply thawed, warmed soils, highlighting the importance of non-growing season CH 4 emissions. Net C sink potential was reduced in deeply thawed wet plots by 4%–42%, and by 3.5%–8% in deeply thawed drier plots due to anaerobic respiration, suggesting that some dry upland tundra landscapes may transition into stronger CH 4 sources in a warming Arctic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Climate Drives Modeled Forest Carbon Cycling Resistance and Resilience in the Upper Great Lakes Region, USA

Forests dominate the global terrestrial carbon budget, but their ability to continue doing so in the face of a changing climate is uncertain. A key uncertainty is how forests will respond (resistance) and recover from (resilience) to rising levels of disturbance of varying intensities. This knowledge gap can optimally be addressed by integrating manipulative field experiments with ecophysiological modeling. We used the ED-2.2 model to project carbon fluxes for a northern temperate deciduous forest subjected to a real-world disturbance severity manipulation experiment. ED-2.2 was run for 150 years, starting from near bare ground in 1900, and subjected to three disturbance treatments under an ensemble of climate conditions. Both disturbance severity and climate strongly affected carbon fluxes, and interacted with one another. We then calculated metrics of functional ecosystem stability. Modeled gross primary production exhibited a mean resistance of -0.13, -0.23, and -0.42 (unitless) in response to increasing disturbance severity of 45%, 65%, and 85% mortality, respectively; and resilience of 0.002, 0.004, 0.008 (yr-1) respectively. This pattern held true for other carbon fluxes, meaning that in general simulated GPP declined more initially but recovered more quickly from higher mortality. Notably, however, heterotrophic respiration responded more slowly to disturbance, and its highly variable response was affected by different drivers. This work provides insight into how future conditions might affect the functional stability of mature forests in this region under ongoing climate change and changing disturbance regimes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Conceptualizing Biogeochemical Reactions With an Ohm's Law Analogy

Abstract In studying problems like plant‐soil‐microbe interactions in environmental biogeochemistry and ecology, one usually has to quantify and model how substrates control the growth of, and interaction among, biological organisms (and abiotic factors, e.g., adsorptive mineral soil surfaces). To address these substrate‐consumer relationships, many substrate kinetics and growth rules have been developed, including the famous Monod kinetics for single‐substrate‐based growth and Liebig's law of the minimum for multiple‐nutrient‐colimited growth. However, the mechanistic basis that leads to these various concepts and mathematical formulations and the implications of their parameters are often quite uncertain. Here, we show that an analogy based on Ohm's law in electric circuit theory is able to unify many of these different concepts and mathematical formulations. In this Ohm's law analogy, a resistor is defined by a combination of consumers’ and substrates’ kinetic traits. In particular, the resistance is equal to the mean first passage time that has been used to derive the Michaelis‐Menten kinetics under substrate replete conditions for a single substrate as well as the predation rate of individual organisms. We further show that this analogy leads to important insights on various biogeochemical problems, such as (a) multiple‐nutrient‐colimited biological growth, (b) denitrification, (c) fermentation under aerobic conditions, (d) metabolic temperature sensitivity, and (e) the legitimacy of Monod kinetics for describing bacterial growth. We expect that our approach will help both modelers and nonmodelers to better understand and formulate hypotheses when studying certain aspects of environmental biogeochemistry and ecology.

54 ENVIRONMENTAL SCIENCES↗