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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

Trident: The Path to Triton on a Discovery Budget

This paper describes Trident, a proposed Discovery mission to Neptune’s moon Triton, 30 AU from the Sun. Triton formed in the Kuiper Belt but was captured by Neptune into a highly-inclined retrograde orbit, where tidal forces thawed its interior, forming an ocean that likely persists to the present day. Recent outer solar system missions like Cassini and New Horizons have yielded completely new models for processes on ocean worlds, active worlds, and KBOs. Triton isn’t just a key to solar system science, it’s a whole keyring: a singular captured KBO and evolved ocean world, with active plumes, an energetic ionosphere, and a young unique surface. The NASA OPAG Roadmap to Ocean Worlds identifies Triton as the highest priority candidate ocean world [1], ripe for investigation. The Trident mission concept is an excellent case study in “design to cost”: we show how exploration of Triton under Discovery is made possible by radioisotope power combined with a rare, extremely efficient Jupiter gravity assist, enabling a simple, lowmass spacecraft design on a ballistic trajectory. The Triton encounter sequence probes for an ocean, measures the ionosphere, and views nearly the whole of Triton as it traverses a single orbit around Neptune, mapping the >60% of the surface that is as yet unseen. The Triton encounter concludes with fullframe imaging illuminated by “Neptune-shine” when Trident is in Neptune eclipse, for direct comparison with Voyager 2’s observations nearly 50 years prior. Trident carries a mature complement of instruments: a Magnetometer, IR Spectrometer & Narrow Angle Camera, Wide-Angle Camera, Plasma Spectrometer, and telecom hardware-enabled Radio Science. The flight system design integrates heritage components from Ball with JPL leadership and expertise in key specialty areas to provide a Voyager-like, robust spacecraft commensurate with a Discovery cost and risk tolerance. Cost avoidance features include: use of existing instrument designs, small blowdown monopropellant propulsion system, a contributed X-band telecommunications system that also performs radio science, and a simple power system. Additionally, the passive thermal design accommodates the large solar dynamic range from Venus to Neptune by using the HGA for shade when close to the sun, and MMRTG excess heat, modulated by louvers.

Frazier, William↗
DOE OSTI2024

Modification of CO2/H2O Selectivity of Polymer Through Graphene Coating for Carbon Capture Materials

A harmful issue that needs attention and solution is the rising carbon dioxide (CO2) in our atmosphere. Carbon dioxide in our atmosphere is at an all time high and has continuously increased since the industrial revolution. It has increased tremendously going from 315 parts per million (ppm) in the 1960s up to 419.3 ppm in 2023 as shown in Figure 1. Moreover, CO2 emissions have increased from 11 billion tons/year in the 1960s to 38.6 billion tons/year in 2023. The increase in CO2 found in our atmosphere has a number of detrimental effects such as increase in global temperatures and an increase in the ocean’s acidity. Human activities are greatly involved in the cause of CO2 emissions. At Lawrence Livermore National Lab (LLNL) the Microencapsulated CO2 sorbents (MECS) division has been doing research and investigating formulations for their microcapsules. MECS are core-shell microcapsules consisted of a highly permeable polymer shell and a fluid (sodium carbonate solution) that reacts and absorbs carbon dioxide. An example of the microcapsules are shown in Figure 2. Equation 1 shows the chemical reaction of the fluid (sodium carbonate) contained in the polymer shell that acts as the carbon dioxide sorbent and becomes sodium bicarbonate. The LLNL MECS team is in the process of scaling up their microcapsules for potential applications in “carbon capture from flue gas streams generated by fossil fuel combustion in industrial plants and operations, carbon capture in breweries and soft drink manufacture, carbon capture directly from indoor air to improve its quality”. The microcapsule’s possibility for commercial applications was discovered in 2017.

36 MATERIALS SCIENCE↗
NASA NTRS2019

A Large Source of Cloud Condensation Nuclei from New Particle Formation in the Tropics

Cloud condensation nuclei (CCN) can affect cloud properties and therefore the Earth’s radiative balance. New particle formation (NPF) from condensable vapours in the free troposphere has been suggested to contribute to CCN, especially in remote, pristine atmospheric regions, but direct evidence is sparse, and the magnitude of this contribution is uncertain. Here we use in-situ aircraft measurements of vertical profiles of aerosol size distributions to present a global-scale survey of NPF occurrence. We observed intense NPF occurring at high altitude in tropical convective regions over both the Pacific and Atlantic Oceans. Together with the results of chemical-transport models, our findings indicate that NPF persists at all longitudes as a global-scale band in the tropical upper troposphere, covering about 40% of the Earth’s surface. Furthermore, we find that this NPF in the tropical upper troposphere is a globally important source of CCN in the lower troposphere, where they can affect cloud properties. Our findings suggest that the production of CCN, as these new particles descend towards the surface, is currently not adequately captured in global models, because they tend to underestimate both the magnitude of tropical upper tropospheric NPF and the subsequent growth to CCN sizes. This has potential implications for cloud albedo and the global radiative balance.

Atmospheric chemistry↗
DOE OSTI2025

Real-Time Sea State Estimation for Wave Energy Converter Control via Machine Learning

Wave energy converters (WECs) harness the untapped power of ocean waves to generate renewable energy, offering a promising solution to sustainable energy. An optimal WEC control strategy is essential to maximize power capture that dynamically adjusts system parameters in response to rapidly changing sea states. This study presents a novel control approach that leverages neural networks to estimate sea states from onboard WEC measurements such as position, velocity, and force. Using a point absorber WEC device as a test platform, our proposed approach estimates sea states in real-time and subsequently adjusts PID controller gains to maximize energy extraction. Simulation results across diverse sea conditions demonstrate that our strategy eliminates the need for external wave monitoring equipment while maintaining power capture efficiency. The results show that our neural network-based control technique can improve power capture by 25.6% while significantly reducing system complexity. This approach offers a practical alternative for WEC deployments where direct wave measurements are either infeasible or cost prohibitive.

PIDcontrol↗
DOE OSTI2020

Electrochemical carbon dioxide capture to close the carbon cycle

Electrochemical CO 2 capture technologies are gaining attention due to their flexibility, their ability to address decentralized emissions (e.g., ocean and atmosphere) and their fit in an electrified industry. In the present work, recent progress made in electrochemical CO 2 capture is reviewed. The majority of these methods rely on the concept of “pH-swing” and the effect it has on the CO 2 hydration/dehydration equilibrium. Through a pH-swing, CO 2 can be captured and recovered by shifting the pH of a working fluid between acidic and basic pH. Such swing can be applied electrochemically through electrolysis, bipolar membrane electrodialysis, reversible redox reactions and capacitive deionization. In this review, we summarize main parameters governing these electrochemical pH-swing processes and put the concept in the framework of available worldwide capture technologies. We analyse the energy efficiency and consumption of such systems, and provide recommendations for further improvements. Although electrochemical CO 2 capture technologies are rather costly compared to the amine based capture, they can be particularly interesting if more affordable renewable electricity and materials (e.g., electrode and membranes) become widely available. Furthermore, electrochemical methods have the ability to (directly) convert the captured CO 2 to value added chemicals and fuels, and hence prepare for a fully electrified circular carbon economy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Outcomes of the DOE Workshop on Atmospheric Challenges for the Wind Energy Industry

The U.S. Department of Energy-funded Mesoscale-to-Microscale Coupling (MMC) project team planned and conducted a virtual Workshop on Atmospheric Challenges for the Wind Energy Industry on October 19 and 20, 2020. The goal of the workshop was to forge a dialog with the community, including industry representatives, on how modeling tools are currently being used, the present active atmospheric modeling research in support of wind energy, and required advancements in capabilities and technology to continue to advance wind energy deployment. The workshop was planned in collaboration with an industry advisory panel that included representatives from wind power plant developers, turbine manufacturers, and companies that provide resource assessment and forecasting services. The format of the workshop included panels from government research sponsors, visionaries from industry, and mixed panels of researchers discussing research status and needs. A shared keynote presentation from the Technical University of Denmark experts anchored the second day of the workshop. An emphasis was placed on understanding the research needs in the offshore environment. In addition, breakout opportunities were provided each day. On the first day, the breakout discussions addressed predesigned questions configured to elicit participants’ thoughts on needed research directions. The second-day breakouts treated three important technical topics through a combination of presentations and group conversations. Each workshop participant chose their breakout preference from among downscaling details, modeling for turbines, and using artificial intelligence for atmospheric modeling. The discussions were robust and productive. The outcomes of the workshop include archiving a series of recommendations from industry and the research community on research directions required to further advance wind energy deployment. Discussions confirmed the need for high-fidelity modeling but that there are specific areas of applicability and other areas where the time and cost of computation is prohibitive. In those cases, the high-fidelity models can inform low-order models that are more practical for real-time or widely deployed applications. Industry must consider the financial cost of performing more expensive modeling approaches, but industry engineers and researchers are using these approaches where there appears to be a return on investment. An emerging type of low-order model is based on machine learning (ML). Participants confirmed that there are many atmospheric phenomena that need to be modeled better, including low-level jets, cold air outbreaks, land-sea induced circulations, diurnal variability, thin stable boundary layers, dynamic changes such as from frontal passage, interaction of wakes and blockage, and more. For the offshore environment, there is wide agreement that some level of ocean-wave-atmospheric coupling is necessary to capture variations in rotor-level winds needed to plan and operate offshore wind plants. Another recurring recommendation is that more observations are needed, particularly for the offshore environment. Those observations should consider the needs for model improvement, both for physically based models and for ML models. Observations must capture atmospheric profiles of variables that are important to understanding and modeling atmospheric and oceanic phenomena that impact boundary layer winds. Models must be validated with data and the uncertainty quantified, particularly those that are sensitive to initial and boundary conditions. Finally, a repeated request was to consider the holistic needs of hybrid plants of wind, solar, and storage resources because those types of plants are likely to be the wave of the future. In addition, industry wishes to understand impacts of the resource under a changing climate for long-term planning.

17 WIND ENERGY↗
DOE OSTI2024

Advocating Feedback Control for Human-Earth System Applications

This paper proposes a feedback control perspective for Human-Earth Systems (HESs) which essentially are complex systems that capture the interactions between humans and nature. Recent attention in HES research has been directed towards devising strategies for climate change mitigation and adaptation, aimed at achieving environmental and societal objectives. However, existing approaches heavily rely on HES models, which inherently suffer from inaccuracies due to the complexity of the system. Moreover, overly detailed models often prove impractical for optimization tasks. We propose a framework inheriting from feedback control strategies the robustness against model errors, because inaccuracies are mitigated using measurements retrieved from the field. The framework comprises two nested control loops. The outer loop computes the optimal inputs to the HES, which are then implemented by actuators controlled in the inner loop. Potential fields of applications are also identified and a numerical example is provided.

biological system modeling↗
DOE OSTI2022

Exploring dimethyl sulfide (DMS) oxidation and implications for global aerosol radiative forcing

Abstract. Aerosol indirect radiative forcing (IRF), which characterizes how aerosols alter cloud formation and properties, is very sensitive to the preindustrial (PI) aerosol burden. Dimethyl sulfide (DMS), emitted from the ocean, is a dominant natural precursor of non-sea-salt sulfate in the PI and pristine present-day (PD) atmospheres. Here we revisit the atmospheric oxidation chemistry of DMS, particularly under pristine conditions, and its impact on aerosol IRF. Based on previous laboratory studies, we expand the simplified DMS oxidation scheme used in the Community Atmospheric Model version 6 with chemistry (CAM6-chem) to capture the OH-addition pathway and the H-abstraction pathway and the associated isomerization branch. These additional oxidation channels of DMS produce several stable intermediate compounds, e.g., methanesulfonic acid (MSA) and hydroperoxymethyl thioformate (HPMTF), delay the formation of sulfate, and, hence, alter the spatial distribution of sulfate aerosol and radiative impacts. The expanded scheme improves the agreement between modeled and observed concentrations of DMS, MSA, HPMTF, and sulfate over most marine regions, based on the NASA Atmospheric Tomography (ATom), the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA), and the Variability of the American Monsoon Systems (VAMOS) Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx) measurements. We find that the global HPMTF burden and the burden of sulfate produced from DMS oxidation are relatively insensitive to the assumed isomerization rate, but the burden of HPMTF is very sensitive to a potential additional cloud loss. We find that global sulfate burden under PI and PD emissions increase to 412 Gg S (+29 %) and 582 Gg S (+8.8 %), respectively, compared to the standard simplified DMS oxidation scheme. The resulting annual mean global PD direct radiative effect of DMS-derived sulfate alone is −0.11 W m−2. The enhanced PI sulfate produced via the gas-phase chemistry updates alone dampens the aerosol IRF as anticipated (−2.2 W m−2 in standard versus −1.7 W m−2, with updated gas-phase chemistry). However, high clouds in the tropics and low clouds in the Southern Ocean appear particularly sensitive to the additional aqueous-phase pathways, counteracting this change (−2.3 W m−2). This study confirms the sensitivity of aerosol IRF to the PI aerosol loading and the need to better understand the processes controlling aerosol formation in the PI atmosphere and the cloud response to these changes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Machine-learned closure of URANS for stably stratified turbulence: connecting physical timescales & data hyperparameters of deep time-series models

Stably stratified turbulence (SST), a model that is representative of the turbulence found in the oceans and atmosphere, is strongly affected by fine balances between forces and becomes more anisotropic in time for decaying scenarios. Moreover, there is a limited understanding of the physical phenomena described by some of the terms in the Unsteady Reynolds-Averaged Navier–Stokes (URANS) equations—used to numerically simulate approximate solutions for such turbulent flows. Rather than attempting to model each term in URANS separately, it is attractive to explore the capability of machine learning (ML) to model groups of terms, i.e. to directly model the force balances. We develop deep time-series ML for closure modeling of the URANS equations applied to SST. We consider decaying SST which are homogeneous and stably stratified by a uniform density gradient, enabling dimensionality reduction. We consider two time-series ML models: long short-term memory and neural ordinary differential equation. Both models perform accurately and are numerically stable in a posteriori (online) tests. Furthermore, we explore the data requirements of the time-series ML models by extracting physically relevant timescales of the complex system. We find that the ratio of the timescales of the minimum information required by the ML models to accurately capture the dynamics of the SST corresponds to the Reynolds number of the flow. The current framework provides the backbone to explore the capability of such models to capture the dynamics of high-dimensional complex dynamical system like SST flows.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2016

A Fly-Through Mission Strategy Targeting Peptide as a Signature of Chemical Evolution and Possible Life in Enceladus Plumes

In situ detection of organic molecules in the extraterrestrial environment provides a key step towards better understanding the variety and the distribution of building blocks of life and it may ultimately lead to finding extraterrestrial life within the Solar System. Here we present combined results of two separate experiments that enable us to realize such in situ life signature detection from the deep habitats of the "Ocean World": a hydrothermal reactor experiment simulating complex organic synthesis and a simulated fly-through capture experiment of organic-bearing microparticles using silica aerogels, followed by subsequent analysis. Both experiments employ peptide as a plausible organics existing in Encleadus plume particles produced in its subsurface ocean. Recent laboratory hydrothermal experiments and a theoretical model on silica saturation indicated an on going hydrothermal reactions in subsurface Enceladus ocean. Given the porous chondritic origin of the core, it is likely that organic compounds originated by radiation chemistry such as amino acid precursors could have been provided, leached, and altered through widespread water-rock interactions. By using the same laboratory experimental setup from the latest water-rock interaction study, we performed amino acid polymerization experiments for 144 days and monitored the organic complexity changing over time. So far over 3,000 peaks up to the size of greater than 600 MW were observed through the analysis of capillary electrophoresis time-of-flight mass spectrometry (CE-TOF-MS) with an indication of amino acid derivatives and short peptides. Generally abiotic polymerization of enantiomeric amino acids results in forming stereoisomeric peptides with identical molecular weight and formula as opposed to homochiral biopolymers. Assuming Enceladus plume particles may contain a mixture of stereoisomeric peptides, we were able to distinguish 16 of the 17 stereoisomeric tripeptides as a test sample using capillary electrophoresis (CE) under optimized conditions. We further conducted Enceladus plume fly-through capture experiment by accelerating peptides soaked in rock particles up to a speed of 5.7 km/s and capturing with originally developed hydrophobic silica aerogels. Direct peptide extraction with acetonitrile-water followed by CE analysis led to detection of only but two stereoisomeric acidic peptide peaks, presenting the first run-through hypervelocuty impact sample analysis targeting peptides as key molecule to to understand the ongoing astrobiology on Enceladus.

organic molecules↗
DOE OSTI2020

General Analysis of Data Collected from DOE Lidar Buoy Deployments Off Virginia and New Jersey

Pacific Northwest National Laboratory (PNNL) operates two AXYS WindSentinel lidar buoys for the U.S. Department of Energy’s Wind Energy Technologies. The purpose of these buoys is to collect hub-height winds and supporting meteorological and oceanographic information to facilitate the development of offshore wind energy in the U.S. In general, each buoy is deployed for a year or more at a given location in order to capture at least a full annual cycle of weather conditions. The initial deployment for one buoy was off the coast of Virginia beginning in 2015, and the other buoy was first deployed off the coast of New Jersey beginning in 2016. Over the last two years, PNNL has had an opportunity to analyze the data collected during these first two deployments. This report describes a substantial analysis of data collected by the two lidar buoys operated off the coasts of Virginia and New Jersey. The centerpiece instrument for each buoy as deployed off Virginia and New Jersey is a lidar system, which is designed to measure the horizontal wind vector from approximately 40 m to 200 m above the sea surface with vertical resolution of 40 m. Since the initial deployments, the original lidars have been replaced with more powerful Leosphere 866 v2 systems. The analyses in this report will apply to the original Vindicator systems. In addition to the wind profiles from the lidars, the buoys collect near-surface measurements of wind speed and direction, air temperature, relative humidity, barometric pressure, and solar irradiance. Oceanographic variables measured include the two-dimensional wave spectrum, water temperature and conductivity, and ocean current vectors to a depth of 90 m. An assessment of overall data recovery and a basic analysis of the data collected was provided in a previous report This report substantially extends that analysis. The various sections describe the development and application of an inertial measurement unit (IMU) data recovery scheme for the New Jersey deployment; a climatological analysis of winds at hub height and at the surface together with thermodynamic variables measured at the surface for the full deployment periods; an analysis of oceanographic observations describe sea state; the development of a refinement for NOAA’s WaveWatch III model to allow its application to near-shore areas; a basic climatology of ocean currents observed from the buoys; an analysis of observed winds in the framework of Monin-Obukhov Similarity Theory; and the development and evaluation of techniques to extract turbulence intensity and turbulence kinetic energy from the lidars. The analyses contained in this report provide a great deal of new information about offshore conditions on the U.S. East Coast. In addition, the experience gained will inform both configurations and analysis of data from future deployments of these lidar buoy systems.

17 WIND ENERGY↗
NASA NTRS2005

Pre-Launch GOES-R Risk Reduction Activities for the Geostationary Lightning Mapper

The GOES-R Geostationary Lightning Mapper (GLM) is a new instrument planned for GOES-R that will greatly improve storm hazard nowcasting and increase warning lead time day and night. Daytime detection of lightning is a particularly significant technological advance given the fact that the solar illuminated cloud-top signal can exceed the intensity of the lightning signal by a factor of one hundred. Our approach is detailed across three broad themes which include: Data Processing Algorithm Readiness, Forecast Applications, and Radiance Data Mining. These themes address how the data will be processed and distributed, and the algorithms and models for developing, producing, and using the data products. These pre-launch risk reduction activities will accelerate the operational and research use of the GLM data once GOES-R begins on-orbit operations. The GLM will provide unprecedented capabilities for tracking thunderstorms and earlier warning of impending severe and hazardous weather threats. By providing direct information on lightning initiation, propagation, extent, and rate, the GLM will also capture the updraft dynamics and life cycle of convective storms, as well as internal ice precipitation processes. The GLM provides information directly from the heart of the thunderstorm as opposed to cloud-top only. Nowcasting applications enabled by the GLM data will expedite the warning and response time of emergency management systems, improve the dispatch of electric power utility repair crews, and improve airline routing around thunderstorms thereby improving safety and efficiency, saving fuel and reducing delays. The use of GLM data will assist the Bureau of Land Management (BLM) and the Forest Service in quickly detecting lightning ground strikes that have a high probability of causing fires. Finally, GLM data will help assess the role of thunderstorms and deep convection in global climate, and will improve regional air quality and global chemistry/climate modeling. The GLM has a robust design that benefits and improves upon its strong heritage of NASA-developed LEO predecessors, the Optical Transient Detector (OTD) and the Lightning Imaging Sensor (LIS). GLM will have a substantially larger number of pixels within the focal plane, two lens systems, and multiple Real-Time Event Processors REPS for on-board event detection and data compression to provide continuous observations of the Americas and adjacent oceans.

Goodman, S. J.↗
DOE OSTI2026

Nanoscale elemental mapping reveals the effect of light and temperature on Gephyrocapsa huxleyi coccoliths

Coccolithophores produce vast quantities of stable calcium carbonate coccoliths, occupying the distinctive position as one of the most productive calcifying organisms on Earth. Gephyrocapsa huxleyi, the most abundant species of coccolithophores across modern oceans, plays an important role in the biological carbon pump and may serve as inspiration for nature-based carbon capture and sequestration technologies. Despite intensive study into G. huxleyi, the biological mechanisms of coccolith synthesis remain unclear. Here, we employ synchrotron X-ray fluorescence to quantitatively map elemental incorporation (calcium, Ca; strontium, Sr; sulfur, S; iron, Fe; and silicon, Si) into G. huxleyi coccoliths at 40-nanometer resolution. Trace elements play a role in determining the thermodynamic stability of coccolith carbonate sequestration and may provide insight into unknown mechanisms of coccolithogenesis. Although the coccolith Sr/Ca ratio has been widely applied as a paleoceanographic proxy, understanding of the Sr/Ca phenomena is limited. Our results confirm that Sr/Ca is temperature dependent but challenge the hypothesis that growth rate is a primary determinant. We find that increased light irradiance led to an ~30% decrease in calcium incorporated into the coccoliths. Surprisingly, X-ray fluorescence spectra and mapping revealed evidence of sulfur, at approximately three times the concentration of Sr, embedded in and around the calcite matrix, suggesting that G. huxleyi coccoliths may play an expanded role in the global sulfur cycle. Here, based on our elemental maps, we postulate that sulfur is active in the intracellular coccolith vesicle and plays a direct role in formation of G. huxleyi coccoliths.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Offshore low-level jet observations and model representation using lidar buoy data off the California coast

Abstract. Low-level jets (LLJs) occur under a variety of atmospheric conditions and influence the available wind resource for wind energy projects. In 2020, lidar-mounted buoys owned by the US Department of Energy (DOE) were deployed off the California coast in two wind energy lease areas administered by the Bureau of Ocean Energy Management: Humboldt and Morro Bay. The wind profile observations from the lidars and collocated near-surface meteorological stations (4–240 m) provide valuable year-long analyses of offshore LLJ characteristics at heights relevant to wind turbines. At Humboldt, LLJs were associated with flow reversals and north-northeasterly winds, directions that are more aligned with terrain influences than the predominant northerly flow. At Morro Bay, coastal LLJs were observed primarily during northerly flow as opposed to the predominant north-northwesterly flow. LLJs were observed more frequently in colder seasons within the lowest 250 m a.s.l. (above sea level), in contrast with the summertime occurrence of the higher-altitude California coastal jet influenced by the North Pacific High, which typically occurs at heights of 300–400 m. The lidar buoy observations also validate LLJ representation in atmospheric models that estimate potential energy yield of offshore wind farms. The European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5) was unsuccessful at identifying all observed LLJs at both buoy locations within the lowest 200 m. An extension of the National Renewable Energy Laboratory (NREL) 20-year wind resource dataset for the Outer Continental Shelf off the coast of California (CA20-Ext) yielded marginally greater captures of observed LLJs using the Mellor–Yamada–Nakanishi–Niino (MYNN) planetary boundary layer (PBL) scheme than the 2023 National Offshore Wind dataset (NOW-23), which uses the Yonsei University (YSU) scheme. However, CA20-Ext also produced the most LLJ false alarms, which are instances when a model identified an LLJ but no LLJ was observed. CA20-Ext and NOW-23 exhibited a tendency to overestimate the duration of LLJ events and underestimate LLJ core heights.

17 WIND ENERGY↗
NASA NTRS2024

Assessing Acetone for the GISS ModelE2.1 Earth System Model

Acetone is an abundant volatile organic compound (VOC) in the atmosphere, with important influences on ozone and oxidation capacity. Direct sources include chemical production from other VOCs and anthropogenic emissions, terrestrial vegetation, biomass-burning emissions, and ocean production. Sinks include chemical loss, deposition onto the land surface, and ocean uptake. Acetone also has a lifetime that is long enough to allow transport and reactions with other compounds remote from its sources. The NASA Goddard Institute for Space Studies (GISS) Earth system model ModelE2.1 simulates a variety of Earth system interactions. Previously, acetone had a very simplistic representation in the ModelE chemical scheme. This study assesses a more sophisticated acetone scheme in which acetone is a full 3-dimensional tracer with explicit sources, sinks, and atmospheric transport. We first evaluate the new global acetone budget in the context of past literature. Estimated source and sink fluxes fall within the range of previous models, although total atmospheric burden and lifetime are at the lower end of the published literature. Acetone's new representation in ModelE2.1 also results in more realistic spatial and vertical distributions, which we compare against previous models and field observations. The seasonality of acetone-related processes was also studied in conjunction with field measurements, and these comparisons show promising agreement but also shortcomings at high-emission urban locations, where the model's resolution is too coarse to capture the true behavior. Finally, we conduct a variety of sensitivity studies that explore the influence of key parameters on the acetone budget and its global distribution. An impactful finding is that the production of acetone from precursor hydrocarbon oxidation has strong leverage on the overall chemical source, indicating the importance of accurate molar yields. Overall, our implementation is one that corroborates with previous studies and marks a significant improvement in the development of the acetone tracer in GISS ModelE2.1.

Acetone↗
DOE OSTI2024

Characterizing Ice Nucleating Particles Over the Southern Ocean Using Simultaneous Aircraft and Ship Observations

Abstract Supercooled liquid clouds are ubiquitous over the Southern Ocean (SO), even to temperatures below −20°C, and comprise a large fraction of the marine boundary layer (MBL) clouds. Earth system models and reanalysis products have struggled to reproduce the observed cloud phase distribution and occurrence of cloud ice in the region. Recent simulations found the microphysical representation of ice nucleation and growth has a large impact on these properties, however, measurements of SO ice nucleating particles (INPs) to validate simulations are sparse. This study presents measurements of INPs from simultaneous aircraft and ship campaigns conducted over the SO in austral summer 2018, which include the first in situ observations in and above cloud in the region. Our results confirm recent observations that INP concentrations are uniformly lower than measurements made in the late 1960s. While INP concentrations below and above cloud are similar, higher ice nucleation efficiency above cloud supports model simulations that the dominant INP composition varies with height. Model parameterizations based solely on aerosol properties capture the mean relationship between INP concentration and temperature but not the observed variability, which is likely related to the only modest correlations observed between INPs and environmental or aerosol metrics. Including wind speed in addition to activation temperature in a marine INP parameterization reduces bias but does not explain the large range of observed INP concentrations. Direct and indirect inference of marine INP size suggests MBL INPs, at least during Austral summer, are dominated by particles with diameters smaller than 500 nm.

Meteorology & Atmospheric Sciences↗
NASA NTRS2001

Diagnosing Tropical Divergent Circulations From Satellite-Derived Diabatic Forcing and Variational Integral Constraints

Large-scale divergent circulations are part of the atmospheric dynamic response to diabatic heating from condensation, radiative processes, and surface energy fluxes. Vertical motion and the associated divergent wind is thus intimately tied to the hydrologic cycle and the global beat balance. Despite its importance, the divergent circulation is too small in comparison to the rotational flow to measure directly with any accuracy. Vertical motions are recovered diagnostically from reanalyses and, as such, are subject to shortcomings in model physics, numerics, and data availability. While reanalysis estimates of tropical divergent circulations are much improved over those from the Global Weather Experiment, there are still substantial differences between products from operational centers. This is because these circulations are still forced largely by model physics and only secondarily by observations. In order to produce a refined estimate of tropical divergence and its interannual variability we have used a number of remotely-sensed data sets along with variational constraints to improve upon reanalysis estimates. Among these are: precipitation from SSM/I and GPCP, TOVS Path-A vertical cloud distributions; ISCCP radiative cooling rates; TOA radiative fluxes from ERBS, surface radiative fluxes from the SRB project, and surface latent and sensible flux estimates from SSM/I. The TOVS Path-A data constrain the divergent outflow in precipitating regions to have the same vertical structure as observed cloudiness. Using integral constraints for moisture, heat, and mass balance, we retrieve consistent divergent wind flows. We examine the ability of this type analysis to capture regional details of ENSO related perturbations to the divergent wind and associated tropical energy balance. Precipitation from satellite is found to be the major constraint in supplying this horizontal structure. We also consider the ability of this analysis to quantify integrated (land vs. ocean) fluctuations in the global monsoonal flow and energy balance. This depends, of course, on the error characteristics of the data constraints. Some estimate of these properties and their relative importance is provided.

Robertson, Franklin R.↗
DOE OSTI2025

Signatures of aerosol-cloud interactions in GiOcean: a coupled global reanalysis with two-moment cloud microphysics

Aerosols influence the Earth's radiative balance through direct interactions with radiation and by affecting cloud properties. Anthropogenic aerosols have led to cooling during the industrial era through aerosol–cloud interactions (ACI), including aerosol effects on cloud microphysical properties and the subsequent adjustments. However, large uncertainties remain in Earth system models (ESMs) regarding the magnitude of this cooling. In part, ESMs substantially disagree on cloud properties, thermodynamics, the hydrological cycle, and general circulation. Reanalysis provides a useful avenue for exploring the impact of ACI on clouds and radiation because its atmosphere is forced to match realistic conditions through the assimilation of observations. Here, we explore the impact of ACI on clouds in the GiOcean reanalysis – the first to incorporate aerosol-cloud interactions. We contrast variables important for ACI between GiOcean and satellite observations and develop 2-dimensional lookup tables of ACI for both using a source-sink budget perspective to attribute the changes in cloud droplet number (Nd) and liquid water path (LWP) to aerosol and meteorology. A compositing analysis using lookup tables shows that GiOcean captures key aspects of aerosol–cloud–precipitation interactions, including (1) activation of aerosol into cloud droplets, (2) effective precipitation scavenging of Nd, (3) suppression of precipitation by high Nd in regions with heavy aerosol emissions. In contrast, satellite observations do not exhibit clear patterns for processes (2) and (3). Random Forest analysis shows that interannual variability in Nd and LWP over the Northern Hemisphere ocean in GiOcean is primarily driven by precipitation, consistent with satellite observations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗