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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Lunar Topography: Results from the Lunar Orbiter Laser Altimeter

The Lunar Orbiter Laser Altimeter (LOLA) onboard the Lunar Reconnaissance Orbiter (LRO) has been operating nearly continuously since July 2009, accumulating over 6 billion measurements from more than 2 billion in-orbit laser shots. LRO's near-polar orbit results in very high data density in the immediate vicinity of the lunar poles, with full coverage at the equator from more than 12000 orbital tracks averaging less than 1 km in spacing at the equator. LRO has obtained a global geodetic model of the lunar topography with 50-meter horizontal and 1-m radial accuracy in a lunar center-of-mass coordinate system, with profiles of topography at 20-m horizontal resolution, and 0.1-m vertical precision. LOLA also provides measurements of reflectivity and surface roughness down to its 5-m laser spot size. With these data LOLA has measured the shape of all lunar craters 20 km and larger. In the proposed extended mission commencing late in 2012, LOLA will concentrate observations in the Southern Hemisphere, improving the density of the polar coverage to nearly 10-m pixel resolution and accuracy to better than 20 m total position error. Uses for these data include mission planning and targeting, illumination studies, geodetic control of images, as well as lunar geology and geophysics. Further improvements in geodetic accuracy are anticipated from the use of re ned gravity fields after the successful completion of the Gravity Recovery and Interior Laboratory (GRAIL) mission in 2012.

Neumann, Gregory↗
NASA NTRS2015

Use of North American and European Air Quality Networks to Evaluate Global Chemistry-Climate Modeling of Surface Ozone

We test the current generation of global chemistry-climate models in their ability to simulate observed, present-day surface ozone. Models are evaluated against hourly surface ozone from 4217 stations in North America and Europe that are averaged over 1 degree by 1 degree grid cells, allowing commensurate model-measurement comparison. Models are generally biased high during all hours of the day and in all regions. Most models simulate the shape of regional summertime diurnal and annual cycles well, correctly matching the timing of hourly (approximately 15:00 local time (LT)) and monthly (mid-June) peak surface ozone abundance. The amplitude of these cycles is less successfully matched. The observed summertime diurnal range (25 ppb) is underestimated in all regions by about 7 parts per billion, and the observed seasonal range (approximately 21 parts per billion) is underestimated by about 5 parts per billion except in the most polluted regions, where it is overestimated by about 5 parts per billion. The models generally match the pattern of the observed summertime ozone enhancement, but they overestimate its magnitude in most regions. Most models capture the observed distribution of extreme episode sizes, correctly showing that about 80 percent of individual extreme events occur in large-scale, multi-day episodes of more than 100 grid cells. The models also match the observed linear relationship between episode size and a measure of episode intensity, which shows increases in ozone abundance by up to 6 parts per billion for larger-sized episodes. We conclude that the skill of the models evaluated here provides confidence in their projections of future surface ozone.

diurnal variations↗
DOE OSTI2024

Terrestrial photosynthesis inferred from plant carbonyl sulfide uptake

Terrestrial photosynthesis, or gross primary production (GPP), is the largest carbon flux in the biosphere, but its global magnitude and spatiotemporal dynamics remain uncertain. The global annual mean GPP is historically thought to be around 120 PgC yr −1 , which is about 30–50 PgC yr −1 lower than GPP inferred from the oxygen-18 ( 18 O) isotope and soil respiration. This disparity is a source of uncertainty in predicting climate–carbon cycle feedbacks. Here, in this study, we infer GPP from carbonyl sulfide, an innovative tracer for CO 2 diffusion from ambient air to leaf chloroplasts through stomata and mesophyll layers. We demonstrate that explicitly representing mesophyll diffusion is important for accurately quantifying the spatiotemporal dynamics of carbonyl sulfide uptake by plants. From the estimate of carbonyl sulfide uptake by plants, we infer a global contemporary GPP of 157 (±8.5) PgC yr −1 , which is consistent with estimates from 18 O (150–175 PgC yr −1 ) and soil respiration ($149^{+29}_{-23}$) PgC yr −1 ), but with an improved confidence level. Our global GPP is higher than satellite optical observation-driven estimates (120–140 PgC yr –1 ) that are used for Earth system model benchmarking. This difference predominantly occurs in the pan-tropical rainforests and is corroborated by ground measurements, suggesting a more productive tropics than satellite-based GPP products indicated. As GPP is a primary determinant of terrestrial carbon sinks and may shape climate trajectories, our findings lay a physiological foundation on which the understanding and prediction of carbon–climate feedbacks can be advanced.

Lai, Jiameng↗
DOE OSTI2024

Locally narrow droplet size distributions are ubiquitous in stratocumulus clouds

Marine stratocumulus clouds are the “global reflectors,” sharply contrasting with the underlying dark ocean surface and exerting a net cooling on Earth’s climate. The magnitude of this cooling remains uncertain in part owing to the averaged representation of microphysical processes, such as the droplet-to-drizzle transition in global climate models (GCMs). Current GCMs parameterize cloud droplet size distributions as broad, cloud-averaged gammas. Here, using digital holographic measurements of discrete stratocumulus cloud volumes, we found cloud droplet size distributions to be narrower at the centimeter scale, never resembling the cloud average. These local distributions tended to form pockets of similar-looking cloud regions, each characterized by a size distribution shape that is diluted to varying degrees. These observations open the way for new modeling representations of microphysical processes.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1981

Experimental modal analysis of the fuselage panels of an Aero Commander aircraft

The reduction of interior noise in light aircraft was investigated with emphasis the thin fuselage sidewall. The approach used is theoretical and involves modeling of the sidewall panels and stiffeners. Experimental data obtained from tests investigating the effects of mass and stiffness treatments to the sidewalls are presented. The dynamic characteristics of treated panels are contrasted with the untreated sidewall panels using experimental modal analysis techniques. The results include the natural frequencies, modal dampling, and mode shapes of selected panels. Frequency response functions, data relating to the global fuselage response, and acoustic response are also presented.

Geisler, D.↗
NASA NTRS2021

Retrieving Rain Drop Size Distribution Moments from GPM Dual-Frequency Precipitation Radar

A novel method for retrieving the moments of rain drop size distribution (DSD) from the dual-frequency precipitation radar (DPR) onboard the global precipitation mission satellite (GPM)is presented. The method involves the estimation of two chosen reference moments from two specific DPR products, namely the attenuation-corrected Ku-band radar reflectivity and (if made available) the specific attenuation at Ka-band. The reference moments are then combined with a function representing the underlying shape of the DSD based on the generalized gamma model. Simulations are performed to quantify the algorithm errors. The performance of methodology is assessed with two GPM-DPR overpass cases over disdrometer sites, one in Huntsville, Alabama and one in Delmarva peninsula, Virginia, both in the US. Results are promising and indicate that it is feasible to estimate DSD moments directly from DPR-based quantities.

Merhala Thurai↗
NASA NTRS1985

MHD modelling of the earth's magnetosphere

Attention is given to the shock capturing technique, nonuniform grid system, and multiple time scale problem aspects of a global MHD model of the earth's magnetosphere that uses numerical methods. Because of the fast Alfven waves near the earth, the model is more difficult to solve than problems of hydrodynamic flow past bodies. The Rusanov (1962) scheme, which is a variant of the Lax (1954) method that maintains viscosity at a minimum value except where a large one is required, is used. The magnetosphere shape obtained by these means is noted.

Wu, C. C.↗
NASA NTRS2016

Do We Know the Actual Magnetopause Position for Typical Solar Wind Conditions?

We compare predicted magnetopause positions at the subsolar point and four reference points in the terminator plane obtained from several empirical and numerical MHD (magnetohydrodynamics) models. Empirical models using various sets of magnetopause crossings and making different assumptions about the magnetopause shape predict significantly different magnetopause positions (with a scatter greater than 1 Earth radius (R (sub E)) even at the subsolar point. Axisymmetric magnetopause models cannot reproduce the cusp indentations or the changes related to the dipole tilt effect, and most of them predict the magnetopause closer to the Earth than non axisymmetric models for typical solar wind conditions and zero tilt angle. Predictions of two global non axisymmetric models do not match each other, and the models need additional verification. MHD models often predict the magnetopause closer to the Earth than the non axisymmetric empirical models, but the predictions of MHD simulations may need corrections for the ring current effect and decreases of the solar wind pressure that occur in the foreshock. Comparing MHD models in which the ring current magnetic field is taken into account with the empirical Lin et al. model, we find that the differences in the reference point positions predicted by these models are relatively small for B (sub z) equals 0 (note: B (sub z) is when the Earth's magnetic field points north versus Sun's magnetic field pointing south). Therefore, we assume that these predictions indicate the actual magnetopause position, but future investigations are still needed.

Samsonov, A. A.↗
DOE OSTI2023

Modeling dust mineralogical composition: sensitivity to soil mineralogy atlases and their expected climate impacts

Soil dust aerosols are a key component of the climate system, as they interact with short- and long-wave radiation, alter cloud formation processes, affect atmospheric chemistry and play a role in biogeochemical cycles by providing nutrient inputs such as iron and phosphorus. The influence of dust on these processes depends on its physicochemical properties, which, far from being homogeneous, are shaped by its regionally varying mineral composition. The relative amount of minerals in dust depends on the source region and shows a large geographical variability. However, many state-of-the-art Earth system models (ESMs), upon which climate analyses and projections rely, still consider dust mineralogy to be invariant. The explicit representation of minerals in ESMs is more hindered by our limited knowledge of the global soil composition along with the resulting size-resolved airborne mineralogy than by computational constraints. In this work we introduce an explicit mineralogy representation within the state-of-the-art Multiscale Online Nonhydrostatic AtmospheRe CHemistry (MONARCH) model. We review and compare two existing soil mineralogy datasets, which remain a source of uncertainty for dust mineralogy modeling and provide an evaluation of multiannual simulations against available mineralogy observations. Soil mineralogy datasets are based on measurements performed after wet sieving, which breaks the aggregates found in the parent soil. Our model predicts the emitted particle size distribution (PSD) in terms of its constituent minerals based on brittle fragmentation theory (BFT), which reconstructs the emitted mineral aggregates destroyed by wet sieving. Our simulations broadly reproduce the most abundant mineral fractions independently of the soil composition data used. Feldspars and calcite are highly sensitive to the soil mineralogy map, mainly due to the different assumptions made in each soil dataset to extrapolate a handful of soil measurements to arid and semi-arid regions worldwide. For the least abundant or more difficult-to-determine minerals, such as iron oxides, uncertainties in soil mineralogy yield differences in annual mean aerosol mass fractions of up to ~ 100 %. Although BFT restores coarse aggregates including phyllosilicates that usually break during soil analysis, we still identify an overestimation of coarse quartz mass fractions (above 2 µm in diameter). In a dedicated experiment, we estimate the fraction of dust with undetermined composition as given by a soil map, which makes up ~ 10 % of the emitted dust mass at the global scale and can be regionally larger. Changes in the underlying soil mineralogy impact our estimates of climate-relevant variables, particularly affecting the regional variability of the single-scattering albedo at solar wavelengths or the total iron deposited over oceans. All in all, this assessment represents a baseline for future model experiments including new mineralogical maps constrained by high-quality spaceborne hyperspectral measurements, such as those arising from the NASA Earth Surface Mineral Dust Source Investigation (EMIT) mission.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

Multiobjective Aerodynamic Shape Optimization Using Pareto Differential Evolution and Generalized Response Surface Metamodels

Differential Evolution (DE) is a simple, fast, and robust evolutionary algorithm that has proven effective in determining the global optimum for several difficult single-objective optimization problems. The DE algorithm has been recently extended to multiobjective optimization problem by using a Pareto-based approach. In this paper, a Pareto DE algorithm is applied to multiobjective aerodynamic shape optimization problems that are characterized by computationally expensive objective function evaluations. To improve computational expensive the algorithm is coupled with generalized response surface meta-models based on artificial neural networks. Results are presented for some test optimization problems from the literature to demonstrate the capabilities of the method.

Madavan, Nateri K.↗
NASA NTRS2023

Modeling Dust Mineralogical Composition: Sensitivity to Soil Mineralogy Atlases and Their Expected Climate Impacts

Soil dust aerosols are a key component of the climate system, as they interact with short- and long-wave radiation, alter cloud formation processes, affect atmospheric chemistry and play a role in biogeochemical cycles by providing nutrient inputs such as iron and phosphorus. The influence of dust on these processes depends on its physicochemical properties, which, far from being homogeneous, are shaped by its regionally varying mineral composition. The relative amount of minerals in dust depends on the source region and shows a large geographical variability. However, many state-of-the-art Earth system models (ESMs), upon which climate analyses and projections rely, still consider dust mineralogy to be invariant. The explicit representation of minerals in ESMs is more hindered by our limited knowledge of the global soil composition along with the resulting size-resolved airborne mineralogy than by computational constraints. In this work we introduce an explicit mineralogy representation within the state-of-the-art Multiscale Online Nonhydrostatic AtmospheRe CHemistry (MONARCH) model. We review and compare two existing soil mineralogy datasets, which remain a source of uncertainty for dust mineralogy modeling and provide an evaluation of multiannual simulations against available mineralogy observations. Soil mineralogy datasets are based on measurements performed after wet sieving, which breaks the aggregates found in the parent soil. Our model predicts the emitted particle size distribution (PSD) in terms of its constituent minerals based on brittle fragmentation theory (BFT), which reconstructs the emitted mineral aggregates destroyed by wet sieving. Our simulations broadly reproduce the most abundant mineral fractions independently of the soil composition data used. Feldspars and calcite are highly sensitive to the soil mineralogy map, mainly due to the different assumptions made in each soil dataset to extrapolate a handful of soil measurements to arid and semi-arid regions worldwide. For the least abundant or more difficult-to-determine minerals, such as iron oxides, uncertainties in soil mineralogy yield differences in annual mean aerosol mass fractions of up to ∼ 100 %. Although BFT restores coarse aggregates including phyllosilicates that usually break during soil analysis, we still identify an overestimation of coarse quartz mass fractions (above 2 µm in diameter). In a dedicated experiment, we estimate the fraction of dust with undetermined composition as given by a soil map, which makes up ∼ 10 % of the emitted dust mass at the global scale and can be regionally larger. Changes in the underlying soil mineralogy impact our estimates of climate-relevant variables, particularly affecting the regional variability of the single-scattering albedo at solar wavelengths or the total iron deposited over oceans. All in all, this assessment represents a baseline for future model experiments including new mineralogical maps constrained by high-quality spaceborne hyperspectral measurements, such as those arising from the NASA Earth Surface Mineral Dust Source Investigation (EMIT) mission.

Soil dust↗
NASA NTRS1991

Uranus atmospheric dynamics and circulation

The observations, models, and theories relevant to the atmospheric dynamics and meteorology of Uranus are discussed. The available models for the large-scale heat transport and atmospheric dynamics as well as diagnostic interpretations of the Voyager data are reviewed. Some pertinent ideas and questions regarding the global circulation balance are considered, partly in comparison with other planetary atmospheres. The available data indicate atmospheric rotation at midlatitudes nearly 200 m/s faster than that of the planetary magnetic field. Analysis of the dynamical deformation of the shape and size of isobaric surfaces measured by the Voyager radio-occultation experiment suggests a subrotating equator at comparable altitudes. Infrared temperature retrievals above the cloud deck indicate a smaller equator-to-pole contrast than expected for purely radiative-convective equilibrium, but show local variations implying a latitudinally correlated decrease with altitude in the cloud-tracked wind.

Allison, Michael↗
NASA NTRS2012

Detecting Falling Snow from Space

There is an increased interest in detecting and estimating the amount of falling snow reaching the Earth's surface in order to fully capture the atmospheric water cycle. An initial step toward global spaceborne falling snow algorithms includes determining the thresholds of detection for various active and passive sensor channel configurations, snow event cloud structures and microphysics, snowflake particle electromagnetic properties, and surface types. In this work, cloud resolving model simulations of a lake effect and synoptic snow event were used to determine the minimum amount of snow (threshold) that could be detected by the following instruments: the W -band radar of CloudSat, Global Precipitation Measurement (GPM) Dual-frequency Precipitation Radar (DPR) Ku and Ka band, and the GPM Microwave Imager (GMI) channels from 10 to 183 plus or minus 7 GHz. Eleven different snowflake shapes were used to compute radar reflectivities and passive brightness temperatures. Notable results include: (1) the W-Band radar has detection thresholds more than an order of magnitude lower than the future GPM sensors, (2) the cloud structure macrophysics influences the thresholds of detection for passive channels, (3) the snowflake microphysics plays a large role in the detection threshold for active and passive instruments, (4) with reasonable assumptions, "the passive 166 GHz channel has detection threshold values comparable to the GPM DPR Ku and Ka band radars with approximately 0.05 g per cubic meter detected at the surface, or an approximately 0.5-1 millimeter per hr. melted snow rate (equivalent to 0.5-2 centimeters per hr. solid fluffy snowflake rate). With detection levels of falling snow known, we can focus current and future retrieval efforts on detectable storms and concentrate advances on achievable results. We will also have an understanding of the light snowfall events missed by the sensors and not captured in the global estimates.

Gail Skofronick-Jackson↗
NASA NTRS2013

Determination of Liquid/Gas Interface and Liquid Center of Gravity for GPM Tank with PMD Using Surface Evolver

Many spacecraft, such as the Global Precipitation Mission (GPM) spacecraft, use propellant management devices (PMDs) to control liquid propellant within propellant tanks. Surface Evolver, an energy minimization routine, is used to find liquid-gas interface shapes due to surface tension and propellant center of mass locations for varying initial liquid positions, contact angles, and fill fractions for the GPM tank with a PMD. This study shows that Surface Evolver can accurately model the liquid-gas interface and liquid center of mass location for a complicated tank and PMD. The Surface Evolver results show that the initial position of the propellant, the contact angle between the propellant and solid surfaces, and the fill fraction of the propellant can drastically affect the liquid-gas interface in the tank and thus the center of mass of the propellant.

Benson, David J.↗
NASA NTRS2015

Multi-Angle Polarimetry: The Once and Future King of Aerosol Remote Sensing

Although aerosols (and their interactions with clouds) are widely known to be one of the most uncertain components of the climate, they remain largely unconstrained in climate simulations. This is because global observations of all the parameters relevant to such simulations - quantity, size, shape, optical properties and chemical composition - are very difficult to simultaneously retrieve from existing remote sensing instruments. The problem can be addressed by maximizing the scene information gathered by a remote sensing instrument, by the use of (passive) multi-spectral, multi-angle and polarimetrically sensitive sensors. These observations, coupled with a radiative transfer model, can be inverted to solve for aerosol parameters. However, the choices to be made when designing an such an observing system and retrieval algorithm are complex, and a variety of approaches have been undertaken by the scientific community. I will review the various multi-spectral, multi-angle, polarimetric observation systems employed for aerosol remote sensing and their corresponding retrieval algorithms. This includes the French Polarization and Directionality of Earth Reflectance (POLDER) instrument, which has been the only such instrument successfully deployed in orbit thus far (most recently from 2004-2013), the NASA Aerosol Polarimetry Sensor (APS) on the ill-fated NASA Glory Mission (launch failure in 2011), potential or planned polarimeters on the NASA Aerosol-Cloud-Ecosystem (ACE) and Pre-Aerosol, Clouds and ocean Ecosystems (PACE) missions, and airborne prototypes from around the world.

Knobelspiesse, Kirk↗
NASA NTRS1991

Thermal models for icy satellites

The solid state greenhouse models were constrained for water ice surfaces using thermal eclipse data. As a result, it was determined that at depths of 3 cm or more Europa can have about a 30 K temperature enhancement over the diurnal mean surface temperature of about 97 K at the equator. It was also determined that the unusual shape of Europa's thermal flux curves during eclipses can be explained by the solid state greenhouse effect. The solid state greenhouse models were applied to the problem of the origin and energy sources of Triton's geyser-like plumes. Two classes of models are examined which may explain the driving energy for Triton's plumes. Triton's internal heatflow is recognized as a major contributor to its global energy balance. Internal heat flow from radioactive decay in Triton's interior along with absorbed thermal energy from Neptune total 5 to 20 pct. of the insolation absorbed by Triton, thus comprising a significant fraction of Triton's surface energy balance.

Brown, Robert H.↗
NASA NTRS2019

The Cumulus and Stratocumulus CloudSat-CALIPSO Dataset (CASCCAD)

Low clouds continue to contribute greatly to the uncertainty in cloud feedback estimates. Depending on whether a region is dominated by cumulus (Cu) or stratocumulus (Sc) clouds, the interannual low-cloud feedback is somewhat different in both spaceborne and large-eddy simulation studies. Therefore, simulating the correct amount and variation of the Cu and Sc cloud distributions could be crucial to predict future cloud feedbacks. Here we document spatial distributions and profiles of Sc and Cu clouds derived from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and CloudSat measurements. For this purpose, we create a new dataset called the Cumulus And Stratocumulus CloudSat-CALIPSO Dataset (CASCCAD), which identifies Sc, broken Sc, Cu under Sc, Cu with stratiform outflow and Cu. To separate the Cu from Sc, we design an original method based on the cloud height, horizontal extent, vertical variability and horizontal continuity, which is separately applied to both CALIPSO and combined CloudSat–CALIPSO observations. First, the choice of parameters used in the discrimination algorithm is investigated and validated in selected Cu, Sc and Sc–Cu transition case studies. Then, the global statistics are compared against those from existing passive- and active-sensor satellite observations. Our results indicate that the cloud optical thickness – as used in passive-sensor observations – is not a sufficient parameter to discriminate Cu from Sc clouds, in agreement with previous literature. Using clustering-derived datasets shows better results although one cannot completely separate cloud types with such an approach. On the contrary, classifying Cu and Sc clouds and the transition between them based on their geometrical shape and spatial heterogeneity leads to spatial distributions consistent with prior knowledge of these clouds, from ground-based, ship-based and field campaigns. Furthermore, we show that our method improves existing Sc–Cu classifications by using additional information on cloud height and vertical cloud fraction variation. Finally, the CASCCAD datasets provide a basis to evaluate shallow convection and stratocumulus clouds on a global scale in climate models and potentially improve our understanding of low-level cloud feedbacks. The CASCCAD dataset (Cesana, 2019, https://doi.org/10.5281/zenodo.2667637) is available on the Goddard Institute for Space Studies (GISS) website at https://data.giss.nasa.gov/clouds/casccad/ (last access: 5 November 2019) and on the zenodo website at https://zenodo.org/record/2667637 (last access: 5 November 2019).

Cesana, Gregory V.↗
DOE OSTI2021

Quantifying microbial control of soil organic matter dynamics at macrosystem scales

Soil organic matter (SOM) stocks, decomposition and persistence are largely the product of controls that act locally. Yet the controls are shaped and interact at multiple spatiotemporal scales, from which macrosystem patterns in SOM emerge. Theory on SOM turnover recognizes the resulting spatial and temporal conditionality in the effect sizes of controls that play out across macrosystems, and couples them through evolutionary and community assembly processes. For example, climate history shapes plant functional traits, which in turn interact with contemporary climate to influence SOM dynamics. Selection and assembly also shape the functional traits of soil decomposer communities, but it is less clear how in turn these traits influence temporal macrosystem patterns in SOM turnover. Here, we review evidence that establishes the expectation that selection and assembly should generate decomposer communities across macrosystems that have distinct functional effects on SOM dynamics. Representation of this knowledge in soil biogeochemical models affects the magnitude and direction of projected SOM responses under global change. Yet there is high uncertainty and low confidence in these projections. To address these issues, we make the case that a coordinated set of empirical practices are required which necessitate (1) greater use of statistical approaches in biogeochemistry that are suited to causative inference; (2) long-term, macrosystem-scale, observational and experimental networks to reveal conditionality in effect sizes, and embedded correlation, in controls on SOM turnover; and (3) use of multiple measurement grains to capture local- and macroscale variation in controls and outcomes, to avoid obscuring causative understanding through data aggregation. Here, when employed together, along with process-based models to synthesize knowledge and guide further empirical work, we believe these practices will rapidly advance understanding of microbial controls on SOM and improve carbon cycle projections that guide policies on climate adaptation and mitigation.

59 BASIC BIOLOGICAL SCIENCES↗