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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 55 records · Page 3
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Entry, Descent, and Landing Analysis of Low Mass Martian Probe for Surface Climate Network

Aeolus is a mission to provide the first direct measurements of Martian atmospheric wind speeds and correlate them with thermal and compositional data to bring together a complete systematic description for the global energy balance and climate cycles of Mars. Objective A of the Mars Exploration Program Analysis Group (MEPAG) Goal II cites a Science Investigation Area to develop a network of surface landers to provide global, diurnal and synoptic coverage of the near-surface environment to characterize present Mars climate [1]. Aeolus will characterize the present Martian global climate system via an orbiter element and a novel surface network element. A series of low mass, low power probes will be distributed across the Martian surface and measure pressure, sky opacity, temperature, wind speed, water vapor and other trace gases. Low mass and power electrical systems designed to operate in extreme cold and daily thermal cycling for one Martian year could facilitate lower cost, Class-D science probes. Aeolus is targeting a total per-probe mass of <5 kg. Recent advances in nanofabrication of chip-scale sensors that are highly robust to temperature and shock, combined with a novel packaging concept (the deployable sensor probe [2]) originally developed by the Aerospace Corp., for the first time enables a Mars surface climate sensor network. These probes are folded flat during transit to Mars and automatically deploy into the final reentry configuration once released from the orbiter. The capability to fold for stowage significantly increases the probe quantity carried by the orbiter.

EDL↗
NASA NTRS2018

Sea-Level Rise: Projections for Maryland 2018

In fulfillment of requirements of the Maryland Commission on Climate Change Act of 2015, this report provides updated projections of the amount of sea-level rise relative to Maryland coastal lands that is expected into the next century. These projections represent the consensus of an Expert Group drawn from the Mid-Atlantic region. The framework for these projections is explicitly tied to the projections of global sea-level rise included in the Intergovernmental Panel on Climate Change Fifth Assessment (2014) and incorporates regional factors such as subsidence, distance from melting glaciers and polar ice sheets, and ocean currents. The probability distribution of estimates of relative sea-level rise from the baseline year of 2000 are provided over time and, after 2050, for three different greenhouse gas emissions pathways: Growing Emissions (RCP8.5), Stabilized Emissions (RCP4.5), and meeting the Paris Agreement (RCP2.6). This framework has been recently used in developing relative sea-level rise projections for California, Oregon, Washington, New Jersey, and Delaware as well as several metropolitan areas. The Likely range (66% probability) of the relative rise of mean sea level expected in Maryland between 2000 and 2050 is 0.8 to 1.6 feet, with about a one-in-twenty chance it could exceed 2.0 feet and about a one-in-one hundred chance it could exceed 2.3 feet. Later this century, rates of sea-level rise increasingly depend on the future pathway of global emissions of greenhouse gases during the next sixty years. If emissions continue to grow well into the second half of the 21st century, the Likely range of sea-level rise experienced in Maryland is 2.0 to 4.2 feet over this century, two to four times the sea-level rise experienced during the 20th century. Moreover, there is a one-in-twenty chance that it could exceed 5.2 feet. If, on the other hand, global society were able to bring net greenhouse gas emissions to zero in time to meet the goals of the Paris Climate Agreement and reduce emissions sufficient to limit the increase in global mean temperature to less than 2°Celsius over pre-industrial levels, the Likely range for 2100 is 1.2 to 3.0 feet, with a one-in-twenty chance that it would exceed 3.7 feet. The difference in sea-level rise between these contrasting scenarios would diverge even more during the next century, with the failure to reduce emissions in the near term resulting in much greater sea-level rise 100 years from now. Moreover, recent research suggests that, without imminent and substantial reductions in greenhouse gas emissions, the loss of polar ice sheets-and thus the rate of sea-level rise-may be more rapid than assumed in these projections, particularly under the Growing Emissions scenario. These probabilistic sea-level rise projections can and should be used in planning and regulation, infrastructure siting and design, estimation of changes in tidal range and storm surge, developing inundation mapping tools, and adaptation strategies for high-tide flooding and saltwater intrusion.

Boesch, D. F.↗
DOE OSTI2024

When energy doesn’t add up: use of an energyshed framework in assessing progress towards renewable energy transitions

Global progress in energy transitions to support climate mitigation goals has been slower than anticipated; this has prompted shifts away from traditional paradigms of regulated energy ownership towards a model of energy democratization by local communities and individuals. For example, in the United States, local communities in over 250 cities, counties, and states have made pledges to reach 100% renewable electrification by target dates ranging from 2020 to 2050. However, the availability of infrastructure and the competition for renewable energy resources, as well as lack of awareness of these limitations, present significant barriers to overcome. In this study, we explored a subset of 31 of these cities to assess their current electricity generation and how much further they have to go to meet their goals. Through an energyshed framework, we estimated powerplant electricity allocation to each city assuming competition for power from various renewable and non-renewable resource types, as well as look at the ‘best case scenario’ assuming 100% allocation of renewable-sourced electricity for a handful of cities in order to understand the existing and planned energy mixes for 2021 and the following 20 years. It is likely most cities will meet 10% of their energy demand with renewable energy, with best cases scenarios reaching between 35% and 65% renewable penetration, within the next 20–30 years. This highlights the need for infrastructural development in the energy sector, as well as intentional planning efforts in order to make these energy goals a reality.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Transparency crucial to Paris climate scenarios—Response

King et al. raise important issues, several of which pertain to the broader policy discourse surrounding international climate negotiations and countries’ cli-mate pledges rather than the modeling conducted in our Policy Forum. We agree with King et al. that the updated Paris Agreement pledges could paint an overly optimistic picture of the future, especially if their success depends on postponing deeper reductions until after 2030. To illustrate a less-optimistic future, our Policy Forum includes scenarios showing what would happen if countries continued to implement current policies alone. Importantly, the “Current policy” scenarios in the Policy Forum result in less than a 10% chance of limiting global warming to below 2°C this century, whereas the “Updated pledges” scenarios result in at least a 33% chance of achieving the same temperature goal. Additional policy measures could help bridge emission gaps between current policies, updated pledges, and the global emission levels needed to cost-effectively achieve the Paris Agreement’s climate goals (1).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

The Global Climate Action Partnership

The Global Climate Action Partnership (GCAP; formerly the Low Emission Development Strategies Global Partnership) is a worldwide network that accelerates ambitious climate goals and advances implementation in Africa, Asia, and Latin America and the Caribbean (LAC). Our strategic approach emphasizes country-driven implementation actions to achieve resilient, just, and inclusive low-emission and net-zero economies. As an incubator for scalable knowledge and solutions, GCAP is leading the way to equitable, climate-resilient, low-emission development.

African Climate Action Partnership↗
DOE OSTI2025

Creating Accurate Methane Emission Inventories through Data-Driven Airborne Survey Strategies

Because natural gas emits less carbon than other fossil fuels, it holds promise as a green energy transition fuel. However, the overall carbon footprint of natural gas is significantly elevated by methane emissions that occur during its production and transmission (Cusworth et al. 2022). Methane “super-emitters,” while comprising only about 1% of sites, are responsible for the majority of oil- and gas-sourced methane emissions, making their detection and mitigation critical in reducing the climate impact of natural gas and in meeting national and global sustainability goals (Sherwin et al. 2024). Yet, despite advancements in detection, significant uncertainties remain regarding the size, frequency, and duration distributions of methane emissions (e.g., Frankenberg et al. 2016, Cusworth et al. 2022, Chen, Sherwin et al. 2022, Conrad et al. 2023, Johnson et al. 2023, Sherwin et al. 2024) underscoring the need for comprehensive emissions inventories segmented by basin across the US. Airborne surveys are well-suited for collecting data to build these comprehensive, basin-level inventories because they allow for extensive spatial coverage, and have the spatial resolution, and the sensitivity to pinpoint individual methane sources. As remote sensing technologies enable rapid basin-scale surveys, it is imperative to establish scientifically and statistically robust standards to generate reliable and actionable emissions inventories. Recent work has shown that differences in airborne sampling strategies, detection technologies, and analysis can lead to large differences between survey conclusions if not correctly accounted for (Chen et al. 2024). This elevates the importance of incorporating proper sampling and analysis techniques when designing a methane emissions monitoring campaign to produce accurate results and facilitate cross-study comparisons. In this paper, we describe a survey strategy designed using the latest conclusions from the literature to align results from different aerial surveys. We identify several sampling and analysis principles, including large sample sizes, balanced sampling across oil and gas production, careful survey area definition, and a unified protocol for analysis, to be vital to producing an unbiased estimate of basin-scale emissions. We present results from a Department of Energy-funded project that deployed this survey strategy in two understudied oil and gas- producing regions in the United States: the Haynesville Basin in Texas and Louisiana, and the Woodford Shale in the Anadarko Basin in Oklahoma.

03 NATURAL GAS↗
NASA NTRS2012

Workshop on the Development of an Experimental Global Drought Information System (GDIS): Overview of Workshop Goals

Among the key recommendations of a recent WCRP Workshop on Drought Predictability and Prediction in a Changing Climate is the development of an experimental global drought information system (GDIS). The timeliness of such an effort is evidenced by the wide aITay of relevant ongoing national and international (as well as regional and continental scale) efforts to provide drought information, including the US and North American drought monitors, and various integrating activities such as GEO and the Global Drought Portal. The workshop will review current capabilities and needs, and focus on the steps necessary to develop a GDIS that will build upon the extensive worldwide investments that have already been made in developing drought monitoring (including new space-based observations), drought risk management, and climate prediction capahilities.

Schubert, Siegfried↗
DOE OSTI2022

Land use for bioenergy: Synergies and trade-offs between sustainable development goals

Bioenergy aims to reduce greenhouse gas (GHG) emissions and contribute to meeting global climate change mitigation targets. Nevertheless, several sustainability concerns are associated with bioenergy, especially related to the impacts of using land for dedicated energy crop production. Cultivating energy crops can result in synergies or trade-offs between GHG emission reductions and other sustainability effects depending on context-specific conditions. Using the United Nations Sustainable Development Goals (SDGs) framework, the main synergies and trade-offs associated with land use for dedicated energy crop production were identified. Furthermore, the context-specific conditions (i.e., biomass feedstock, previous land use, climate, soil type and agricultural management) which affect those synergies and trade-offs were also identified. The most recent literature was reviewed and a pairwise comparison between GHG emission reduction (SDG 13) and other SDGs was carried out. A total of 427 observations were classified as either synergy (170), trade-off (176), or no effect (81). Most synergies with environmentally-related SDGs, such as water quality and biodiversity conservation, were observed when perennial crops were produced on arable land, pasture or marginal land in the ‘cool temperate moist’ climate zone and ‘high activity clay’ soils. Most trade-offs were related to food security and water availability. Previous land use and feedstock type are more impactful in determining synergies and trade-offs than climatic zone and soil type. This study highlights the importance of considering context-specific conditions in evaluating synergies and trade-offs and their relevance for developing appropriate policies and practices to meet worldwide demand for bioenergy in a sustainable manner.

09 BIOMASS FUELS↗
DOE OSTI2023

Large global variations in the carbon dioxide removal potential of seaweed farming due to biophysical constraints

Abstract Estimates suggest that over 4 gigatons per year of carbon dioxide (Gt-CO 2 year −1 ) be removed from the atmosphere by 2050 to meet international climate goals. One strategy for carbon dioxide removal is seaweed farming; however its global potential remains highly uncertain. Here, we apply a dynamic seaweed growth model that includes growth-limiting mechanisms, such as nitrate supply, to estimate the global potential yield of four types of seaweed. We estimate that harvesting 1 Gt year −1 of seaweed carbon would require farming over 1 million km 2 of the most productive exclusive economic zones, located in the equatorial Pacific; the cultivation area would need to be tripled to attain an additional 1 Gt year −1 of harvested carbon, indicating dramatic reductions in carbon harvest efficiency beyond the most productive waters. Improving the accuracy of annual harvest yield estimates requires better understanding of biophysical constraints such as seaweed loss rates (e.g., infestation, disease, grazing, wave erosion).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Resolution dependence of the turbulent atmospheric boundary layer in global storm-resolving climate simulations

The current generation of state-of-the-art global climate models are being run at increasingly higher horizontal resolutions, with the goal of resolving organised deep convection explicitly. How a kilometre-scale resolution impacts the representation of the atmospheric boundary layer is, however, not well known. Using statistical analysis on global fields as well as high-frequency data at selected locations, produced with the Integrated Forecasting System (IFS) model for the Next Generation Earth-system Models (nextGEMS) project, we investigate the horizontal resolution dependence of some boundary-layer processes. We find that a change in resolution from 9 to 2.8 km causes no substantial changes to boundary-layer properties and processes at most of the locations studied, although some global changes are detected that indicate circulation changes. Small changes to the boundary-layer depth and structure are found in the Tropics. The short simulation length and lack of data for optimal boundary-layer analysis limits the conclusions, especially in relation to the connection between the boundary layer and the atmosphere general circulation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A Machine Learning Assisted Development of a Model for the Populations of Convective and Stratiform Clouds

Abstract Traditional parameterizations of the interaction between convection and the environment have relied on an assumption that the slowly varying large‐scale environment is in statistical equilibrium with a large number of small and short‐lived convective clouds. They fail to capture nonequilibrium transitions such as the diurnal cycle and the formation of mesoscale convective systems as well as observed precipitation statistics and extremes. Informed by analysis of radar observations, cloud‐permitting model simulation, theory, and machine learning, this work presents a new stochastic cloud population dynamics model for characterizing the interactions between convective and stratiform clouds, with the goal of informing the representation of these interactions in global climate models. Fifteen wet seasons of precipitating cloud observations by a C‐band radar at Darwin, Australia are fed into a machine learning algorithm to obtain transition functions that close a set of coupled equations relating large‐scale forcing, mass flux, the convective cell size distribution, and the stratiform area. Under realistic large‐scale forcing, the derived transition functions show that, on the one hand, interactions with stratiform clouds act to dampen the variability in the size and number of convective cells and therefore in the convective mass flux. On the other, for a given convective area fraction, a larger number of smaller cells is more favorable for the growth of stratiform area than a smaller number of larger cells. The combination of these two factors gives rise to solutions with a few convective cells embedded in a large stratiform area, reminiscent of mesoscale convective systems.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1996

Line Coupling in Atmospheric Spectra

The theoretical modeling of atmospheric spectra is important for a number of different applications: for instance, in the determination of minor atmospheric constituents such as ozone, carbon dioxide, CFC's etc.; in monitoring the temperature profile for climate studies; and in measuring the incoming and outgoing radiation to input into global climate models. In order to accomplish the above mentioned goal, one needs to know the spectral parameters characterizing the individual spectral lines (frequency, width, strength, and shape) as well as the physical parameters of the atmosphere (temperature, abundances, and pressure). When all these parameters are known, it is usually assumed that the resultant spectra and concomitant absorption coefficient can then be calculated by a superposition of individual profiles of appropriate frequency, strength and shape. However, this is not true if the lines are 'coupled'. Line coupling is a subtle effect that takes place when lines of a particular molecule overlap in frequency. In this case when the initial states and the final states of two transitions are connected by collisions, there is a quantum interference resulting in perturbed shapes. In general, this results in the narrowing of Q-branches (those in which the rotational quantum number does not change), and vibration-rotational R- and P branches (those in which the rotational quantum number changes by +/- 1), and in the spectral region beyond band heads (regions where the spectral lines pile up due to centrifugal distortion). Because these features and spectral regions are often those of interest in the determination of the abundances and pressure-temperature profiles, one must take this effect into account in atmospheric models.

Tipping, R. H.↗
NASA NTRS2014

MISR Aerosol Typing

AeroCom is an open international initiative of scientists interested in the advancement of the understanding of global aerosol properties and aerosol impacts on climate. A central goal is to more strongly tie and constrain modeling efforts to observational data. A major element for exchanges between data and modeling groups are annual meetings. The meeting was held September 20 through October 2, 1014 and the organizers would like to post the presentations.

MISR↗
DOE OSTI2023

Microorganisms, climate change, and the Sustainable Development Goals: progress and challenges

The forthcoming UN summit marks the halfway point to 2030 and presents an important milestone in global efforts to address various challenges, including those related to climate change and environmental preservation. The UN SDGs include several related to microorganisms and climate change. Importantly, microbiology research is key to understanding and mitigating climate change, and in maintaining the health of terrestrial and aquatic ecosystems (SDGs 13, 14 and 15).

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2001

Responses of Precipitation and Hydrologic Processes to Tropical SST

The goal of the research is to identify the mechanisms in the response of tropical precipitation and atmospheric hydrologic cycle to sea surface temperature (SST) variability at seasonal-to-interannual time scales, and to utilize the knowledge for better understanding of climate feedback processes relevant to global change. As a first step to achieve the goal, we characterize the inter-relationship among convective/stratiform rain, ice/water clouds water vapor, and SST using TRMM satellite data and a cloud-resolving model. We examined the daily hydrologic variables [column water vapor (PW), cloud liquid water (CW), rainfall rates (RR)] as a function of SST using high-resolution data (0.25 x 0.25, daily) derived from TRMM satellite measurements. Comparing the winter of 97/98 (El Nino condition) against the winter of 99/00 (La Nina condition), area-mean values of all four hydrologic variables in cloudy areas within the tropical Pacific are higher in the El Nino winter than in the La Nina winter. This is consistent with previous observational analyses and SST warming experiments (idealized or ENSO-like) that showed the interaction between hydrologic cyclic and radiation at the seasonal to interannual time scales leads to intensified tropical circulation and hydrologic cycle. However, there is evidence that the enhanced hydrologic cycle over the warm pool is accompanied by an expansion of radiatively -driven subsidence in response to a stronger SST gradient between warm pool and surrounding cold pool. The expanding subsidence effectively reduces cloud amounts over the warm pool. Our analysis of daily variability further indicates a more vigorous water cycle characterized by higher PW, CW, and RR in response to overall warming. This is expected from the Clausius Clapeyron relation as a thermodynamic response to warming. However cloudy areas decrease in response to overall warming. This may be due to factors that are fundamentally different. One possibility is that in a warmer climate, there may be alteration in the microphysical processes in clouds, e.g., increased coalescence of cloud size droplets and increased entrainment of dry air from above due to the invigorated convective motions in response to overall warming. As a result, cloud amounts are less. Another interpretation is that, in colder air masses, more ice particles will be produced and, because of their lower densities, are less likely to precipitate, hence the higher cloud amount. This suggests that, when averaged over a sufficiently large area covering both the rising and sinking branches of the tropical circulation, there maybe an increase in the precipitation efficiency in stratiform clouds, in conjunction with increased subsidence in an enhanced water cycle. This is supported by the residence time at different rainrates.

Sui, C.-H.↗
DOE OSTI2020

Identifying geologic characteristics and operational decisions to meet global carbon sequestration goals

Geologic carbon sequestration is the process of injecting and storing CO 2 in subsurface reservoirs and is an essential technology for global environmental security (e.g., climate change mitigation) and economic security (e.g., CO 2 tax credits). To meet energy, economic, and environmental goals, society will have to identify vast volumes of high-capacity, low-cost, and viable storage reservoirs for sequestering CO 2 . In turn, this requires understanding how major geologic characteristics (such as reservoir depth, thickness, permeability, porosity, and temperature) and design and operational decisions (such as injection well spacing) impact CO 2 injection rates, storage capacity, and economics. Although many numerical simulation tools exist, they cannot repeat the required thousands or millions of simulations to identify ideal reservoir properties and the sensitivity and interaction between geologic parameters and operational decisions. Here, we use SCO 2 T—a fast-running, reduced-order modeling framework—to explore the sensitivity of major geologic parameters and operational decisions to engineering (CO 2 injection rates, plume dimensions, and storage capacities and effectiveness) and costs. Our results show, for the first time, benefits and impacts such as allowing CO 2 plumes to overlap, how different well spacing patterns affect CO 2 sequestration, the effects on costs of including brine treatment and disposal, and the effect of restricting injection rates to 1 MtCO 2 per y based on well limitations. We reveal multiple novel and unintuitive findings including: (i) deeper reservoirs have reduced carbon sequestration costs until injection rates reach 1 MtCO 2 per y, at which point deeper reservoirs become more expensive, (ii) thicker formations allow for increased injection rates and storage capacity, but thickness barely impacts plume areas, (iii) higher geothermal gradients result in reduced sequestration costs, unless brine treatment/disposal costs are included, at which point reservoirs having lower geothermal gradients are more economical because they produce less brine for each unit of injected CO 2 , and (iv) allowing plumes to overlap has a significantly positive impact of increasing storage capacities but has only a small influence on reducing sequestration costs. Altogether, our results illustrate new scientific conclusions to help identify suitable sites to inject and store CO 2 , to help understand the complex interaction between geology and resulting costs, and to help support the pursuit of meeting global sequestration targets.

58 GEOSCIENCES↗
DOE OSTI2020

CMIP5 model selection for ISMIP6 ice sheet model forcing: Greenland and Antarctica

Abstract. The ice sheet model intercomparison project for CMIP6 (ISMIP6) effort brings together the ice sheet and climate modeling communities to gain understanding of the ice sheet contribution to sea level rise. ISMIP6 conducts stand-alone ice sheet experiments that use space- and time-varying forcing derived from atmosphere–ocean coupled global climate models (AOGCMs) to reflect plausible trajectories for climate projections. The goal of this study is to recommend a subset of CMIP5 AOGCMs (three core and three targeted) to produce forcing for ISMIP6 stand-alone ice sheet simulations, based on (i) their representation of current climate near Antarctica and Greenland relative to observations and (ii) their ability to sample a diversity of projected atmosphere and ocean changes over the 21st century. The selection is performed separately for Greenland and Antarctica. Model evaluation over the historical period focuses on variables used to generate ice sheet forcing. For stage (i), we combine metrics of atmosphere and surface ocean state (annual- and seasonal-mean variables over large spatial domains) with metrics of time-mean subsurface ocean temperature biases averaged over sectors of the continental shelf. For stage (ii), we maximize the diversity of climate projections among the best-performing models. Model selection is also constrained by technical limitations, such as availability of required data from RCP2.6 and RCP8.5 projections. The selected top three CMIP5 climate models are CCSM4, MIROC-ESM-CHEM, and NorESM1-M for Antarctica and HadGEM2-ES, MIROC5, and NorESM1-M for Greenland. This model selection was designed specifically for ISMIP6 but can be adapted for other applications.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2010

Mixed Layer Sub-Mesoscale Parameterization - Part 1: Derivation and Assessment

Several studies have shown that sub-mesoscales (SM 1km horizontal scale) play an important role in mixed layer dynamics. In particular, high resolution simulations have shown that in the case of strong down-front wind, the re-stratification induced by the SM is of the same order of the de-stratification induced by small scale turbulence, as well as of that induced by the Ekman velocity. These studies have further concluded that it has become necessary to include SM in ocean global circulation models (OGCMs), especially those used in climate studies. The goal of our work is to derive and assess an analytic parameterization of the vertical tracer flux under baroclinic instabilities and wind of arbitrary directions and strength. To achieve this goal, we have divided the problem into two parts: first, in this work we derive and assess a parameterization of the SM vertical flux of an arbitrary tracer for ocean codes that resolve mesoscales, M, but not sub-mesoscales, SM. In Part 2, presented elsewhere, we have used the results of this work to derive a parameterization of SM fluxes for ocean codes that do not resolve either M or SM. To carry out the first part of our work, we solve the SM dynamic equations including the non-linear terms for which we employ a closure developed and assessed in previous work. We present a detailed analysis for down-front and up-front winds with the following results: (a) down-front wind (blowing in the direction of the surface geostrophic velocity) is the most favorable condition for generating vigorous SM eddies; the de-stratifying effect of the mean flow and re-stratifying effect of SM almost cancel each other out,

Canuto, V. M.↗