SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Comparison of FPS-16 and GMD-1 radar tracking and radiosonde measurements and methods for processing wind data - time variability of atmospheric parameters
Global climate models (GCMs) disagree with other lines of evidence on the rapid adjustments of cloud cover and liquid water path to anthropogenic aerosols. Attempts to use observations to constrain the parameterizations of cloud processes in GCMs have failed to reduce the disagreement. We propose using observations sensitive to the relevant cloud processes rather than only to the atmospheric state and focusing on process realism in the absence of aerosol perturbations in addition to the process susceptibility to aerosols. We show that process-sensitive observations of precipitation can reduce the uncertainty on GCM estimates of rapid cloud adjustments to aerosols. The feasibility of an observational constraint depends on understanding the precipitation intensity spectrum in both observations and models and also on improving methods to compare the two.
Research projects for the period ending September 15, 1973 are reported as follows: (1) the abundances of carbon dioxide in the atmosphere, and the processes by which it is released from carbonate deposits in the earth and then transferred to organic material by photosynthesis; the pathways for movement of carbon and oxygen through the atmosphere; (2) space science computation assistance by PDP computer; the performance characteristics and user instances; (3) OGO-6 data analysis studies of the variations of nighttime ion temperature in the upper atmosphere.
The seasonal variability of Saturn's clouds and weather layer, currently displaying a variety of phenomena (convective storms, planetary waves, giant storms and lightning-induced events, etc.) is not yet fully understood. Variations of Saturn's radiance at 5.2 microns, a spectral region dominated by thermal emission in an atmospheric window containing weak gaseous absorption, contain a strong axisymmetric component as well as large discrete features at low and mid-latitudes that are several degrees colder than the planetary average and uncorrelated with features at shorter wavelengths that are dominated by reflected sunlight (Yanamandra-Fisher et al., 2001. Icarus, Vol. 150). The characterization of several fundamental atmospheric properties and processes, however, remains incomplete, namely: How do seasons affect (a) the global distribution of gaseous constituents and aerosols; and (b) temperatures and the stability against convection and large scale-atmospheric transport? Do 5-micron clouds have counterparts at other altitude levels? What changes occur during the emergence of Great White Storms? Data acquired at the NASA/IRTF and NAOJ/Subaru from 1995 - 2011; since 2004, high-resolution multi-spectral and high-spatial imaging data acquired by the NASA/ESA Cassini mission, represents half a Saturnian year or two seasons. With the addition of detailed multi-spectral data sets acquired by amateur observers, we study these dramatic phenomena to better understand the timeline of the evolution of these events. Seasonal (or temporal) trends in the observables such as albedo of the clouds, thermal fields of the atmosphere as function of altitude, development of clouds, hazes and global abundances of various hydrocarbons in the atmosphere can now be modeled. We will present results of our ongoing investigation for the search and characterization of periodicities over half a Saturnian year, based on a non-biased a priori approach and time series techniques (such as Principal Component Analysis, PCA and Lomb-Scargle periodograms, LSP).
The Sample Analysis at Mars (SAM) instrument onboard the Mars Science Laboratory Curiosity rover measures the chemical composition of major atmospheric species (CO2, N2, 40Ar,O2, and CO) through a dedicated atmospheric inlet. We report here measurements of volume mixing ratios in Gale Crater using the SAM quadrupole mass spectrometer, obtained over a period of nearly 5 years (3 Mars years) from landing. The observation period spans the northern summer of MY31 and solar longitude (L(sub S)) of 175° through spring of MY 34, L(sub S) = 12°. This work expands upon prior reports of the mixing ratios measured by SAM QMS in the first 105 sols of the mission. The SAM QMS atmospheric measurements were taken periodically, with a cumulative coverage of four or five experiments per season on Mars. Major observations include the seasonal cycle of CO2, N2, and Ar, which lags approximately 20–40° of L(sub S) behind the pressure cycle driven by CO2 condensation and sublimation from the winter poles. This seasonal cycle indicates that transport occurs on faster timescales than mixing. The mixing ratio of O2 shows significant seasonal and interannual variability, suggesting an unknown atmospheric or surface process at work. The O2 measurements are compared to several parameters, including dust optical depth and trace CH4 measurements by Curiosity. We derive annual mean volume mixing ratios for the atmosphere in Gale Crater: CO2 = 0.951 (±0.003), N2 = 0.0259 (±0.0006), 40Ar = 0.0194 (±0.0004), O2 = 1.61 (±0.09) x 10(exp ‐3), and CO = 5.8 (±0.8) x 10(exp ‐4).
Organic aerosols (OA) are an important but poorly characterized component of the earth’s climate system. Enormous complexities commonly associated with OA composition and life cycle processes have significantly complicated the simulation and quantification of aerosol effects. To unravel these complexities and improve understanding of the properties, sources, formation, evolution processes, and radiative properties of atmospheric OA, we propose to perform advanced and integrated analyses of multiple DOE aerosol mass spectrometry datasets, including two high-resolution time-of-flight aerosol mass spectrometer (HR-AMS) datasets from intensive field campaigns on the aerosol life cycle and the Aerosol Chemical Speciation Monitor (ACSM) datasets from long-term routine measurement programs at ACRF sites. In this project, we will focus on 1) characterizing the chemical (i.e., composition, organic elemental ratios), physical (i.e., size distribution and volatility), and radiative (i.e., sub- and super-saturated growth) properties of organic aerosols, 2) examining the correlations of these properties with different source and process regimes (e.g., primary, secondary, urban, biogenic, biomass burning, marine, or mixtures), 3) quantifying the evolutions of these properties as a function of photochemical processing, 4) identifying and characterizing special cases for important processes such as SOA formation and new particle formation and growth, and 5) correlating size-resolved aerosol chemistry with measurements of radiative properties of aerosols to determine the climatically relevant properties of OA and characterize the relationship between these properties and processes of atmospheric aerosol organics. Our primary goal is to improve a process-level understanding of the life cycle of organic aerosols in the Earth’s atmosphere. We will also aim at bridging between observations and models via synthesizing and translating the results and insights generated from this research into data products and formulations that may be directly used to inform, improve, and evaluate regional and global models. In addition, we will continue our current very active collaborations with several modeling groups to enhance the use and interpretation of our data products. Overall, this research will contribute new data to improve quantification of the aerosol’s effects on climate and thus the achievement of ASR’s science goal of – “improving the fidelity and predictive capability of global climate models”.
An international field campaign aiming at atmospheric and oceanic processes associated with the Madden-Julian Oscillation (MJO) was conducted in and around the tropical Indian Ocean (IO) during October 2011 - March 2012. The objective of the field campaign was to collect observations urgently needed to expedite the progress of understanding the key processes of the MJO, focusing on its initiation but also including propagation and maturation, and ultimately to improve skills of numerical simulation and prediction of the MJO. Primary targets of the field campaign include interaction of atmospheric deep convection with its environmental moisture, evolution of cloud populations, and air-sea interaction. Several MJO events were captured by ground-based, airborne, and oceanic instruments with advanced observing technology. Numerical simulations and real-time forecasts were integrated components of the field campaign in its design and operation. Observations collected during the campaign provide unprecedented opportunities to reveal detailed processes of the MJO and to assist evaluation, improvement and development of weather and climate models. The data policy of the campaign encourages the broad research community to use the field observations to advance the MJO study.
Abstract Because of the pervasive role of water in the Earth system, the relative abundances of stable isotopologues of water are valuable for understanding atmospheric, oceanic, and biospheric processes, and for interpreting paleoclimate proxy reconstructions. Isotopologues are transported by both large‐scale and turbulent flows, and the ratio of heavy to light isotopologues changes due to fractionation that can accompany condensation and evaporation processes. Correctly predicting the isotopic distributions requires resolving the relationships between large‐scale ocean and atmospheric circulation and smaller‐scale hydrological processes, which can be accomplished within a coupled climate modeling framework. Here we present the water isotope‐enabled version of the Community Earth System Model version 1 (iCESM1), which simulates global variations in water isotopic ratios in the atmosphere, land, ocean, and sea ice. In a transient Last Millennium simulation covering the 850–2005 period, iCESM1 correctly captures the late‐twentieth‐century structure of δ 18 O and δD over the global oceans, with more limited accuracy over land. The relationship between salinity and seawater δ 18 O is also well represented over the observational period, including interbasin variations. We illustrate the utility of coupled, isotope‐enabled simulations using both Last Millennium simulations and freshwater hosing experiments with iCESM1. Closing the isotopic mass balance between all components of the coupled model provides new confidence in the underlying depiction of the water cycle in CESM, while also highlighting areas where the underlying hydrologic balance can be improved. The iCESM1 is poised to be a vital community resource for ongoing model development with both modern and paleoclimate applications.
The coherent Doppler laser radar (lidar), when operated from an airborne platform, is a unique tool for the study of atmospheric and surface processes and features. This is especially true for scientific objectives requiring measurements in optically-clear air, where other remote sensing technologies such as Doppler radar are typically at a disadvantage. The atmospheric lidar remote sensing groups of several US institutions, led by Marshall Space Flight Center, have developed an airborne coherent Doppler lidar capable of mapping the wind field and aerosol structure in three dimensions. The instrument consists of an eye-safe approx. 1 Joule/pulse lidar transceiver, telescope, scanner, inertial measurement unit, and flight computer system to orchestrate all subsystem functions and tasks. The scanner is capable of directing the expanded lidar beam in a variety of ways, in order to extract vertically-resolved wind fields. Horizontal resolution is approx. 1 km; vertical resolution is even finer. Winds are obtained by measuring backscattered, Doppler-shifted laser radiation from naturally-occurring aerosol particles (of order 1 micron diameter). Measurement coverage depends on aerosol spatial distribution and composition. Velocity accuracy has been verified to be approx. 1 meter per second. A variety of applications have been demonstrated during the three flight campaigns conducted during 1995-1998. Examples will be shown during the presentation. In 1995, boundary layer winds over the ocean were mapped with unprecedented resolution. In 1996, unique measurements were made of. flow over the complex terrain of the Aleutian Islands; interaction of the marine boundary layer jet with the California coastal mountain range; a weak dry line in Texas - New Mexico; the angular dependence of sea surface scattering; and in-flight radiometric calibration using the surface of White Sands National Monument. In 1998, the first measurements of eyewall and boundary layer winds within a hurricane were made with the airborne Doppler lidar. Potential applications and plans for improvement will also be described.
Large-scale deployment of negative emissions technologies (NETs) that permanently remove CO 2 from the atmosphere is now considered essential for limiting the global temperature increase to less than 2°C by the end of this century. One promising NET is direct air capture (DAC), a technology that employs engineered chemical processes to remove atmospheric carbon dioxide, potentially at the scale of billions of metric tons per year. This review highlights one of the two main approaches to DAC based on aqueous solvents. The discussion focuses on different aspects of DAC with solvents, starting with the fundamental chemistry that includes the chemical species and reactions involved and the thermodynamics and kinetics of CO 2 binding and release. Chemical engineering aspects are also discussed, including air–liquid contactor design, process development, and technoeconomic assessments to estimate the cost of the DAC technologies. Various solvents employed in DAC are reviewed, from aqueous alkaline solutions (NaOH, KOH) to aqueous amines, amino acids, and peptides, along with different solvent regeneration methods, from the traditional thermal swinging to the more exploratory carbonate crystallization with guanidines or electrochemical methods.
Two field experiments to study atmospheric and land surface processes and their interactions are summarized. The Hydrologic-Atmospheric Pilot Experiment, which tested techniques for measuring evaporation, soil moisture storage, and runoff at scales of about 100 km, was conducted over a 100 X 100 km area in France from mid-1985 to early 1987. The first International Satellite Land Surface Climatology Program field experiment was conducted in 1987 to develop and use relationships between current satellite measurements and hydrologic, climatic, and biophysical variables at the earth's surface and to validate these relationships with ground truth. This experiment also validated surface parameterization methods for simulation models that describe surface processes from the scale of vegetation leaves up to scales appropriate to satellite remote sensing.
Sampling a continuous radiance spectrum in many narrow contiguous spectral bands results in a high covariance between the bands. Hence, the true dimensionality of imaging spectrometer data is not determined by the number of spectral bands, but by the number of spectrally unique signatures whose mixtures reproduce the spectral variance observed in an image. Methods to unmix high dimensional multispectral data use principal components analysis to reduce the dimensionality. The variance of the spectral data is modeled as a linear combination of a finite set of endmembers in the space of the eigen-vectors that account for most of the variance. The number and characteristics of these endmembers are determined not only by the number and characteristics of the spectrally unique materials on the surface but also by processes (e.g., illumination, atmospheric scattering and absorption) affecting the signal received by the sensor. Selection of endmember spectra has typically been from a library. However, since most libraries are incomplete and do not account for the processes mentioned above, we have devised a computer display that allows researchers to explore interactively the eigenvector space of a representative and mean-corrected subset of the image data in search of extreme spectra to designate as endmembers. This display, which is based on parallel coordinates, is unique in the area of multidimensional visualization in that it includes not only a passive view of higher dimensional data but also the capability to interact and move geometrical objects in higher dimensional spaces.
The Claridge-Culp-Liu Dehumidification Process is a novel and efficient approach to removing water vapor from air using a combination of membrane separation, vacuum compression and sub-atmospheric condensation. The basic theory of this process is to separate water vapor from moist air flowing across one side of a membrane by applying a partial vacuum to the opposite side of the membrane and then compressing the water vapor to its saturation pressure at the wet-bulb temperature of the ambient air so as to facilitate condensation. We report this process has a fundamental efficiency limit that approximates the Carnot limit, but for eight different ideal dehumidification-only cases examined herein, the process requires only 26–56% the energy required by a Carnot vapor-compression system. Furthermore, the limiting energy required by an ideal 5-stage membrane system is 16–31% that of a Carnot system for the same cases. Of special importance, the ideal Claridge-Culp-Liu Dehumidification Process requires less than 5% of the energy required by an ideal desiccant process for all cases treated. The Claridge-Culp-Liu Dehumidification Process can also be combined with evaporative cooling to provide dehumidification and sensible cooling with the temperature and humidity controlled independently. Of special importance, this system uses no HFC refrigerants, and it generates pure water as a by-product.
To explore the interactions among column processes in the Community Atmosphere Model (CAM), the single-column version of CAM (SCAM) is integrated for 1000 days in radiative-convective equilibrium (RCE) with tropical values of boundary conditions, spanning a parameter or configuration space of model physics versions (v5 vs. v6), vertical resolution (standard and 60 levels), sea surface temperature (SST), and some interpretation-driven experiments. The simulated time-mean climate is reasonable, near observations and RCE of a cyclic cloud-resolving model. Updraft detrainment in the deep convection scheme produces distinctive grid-scale structures in humidity and cloud, which also interact with radiative transfer processes. These grid artifacts average out in multi-column RCE results reported elsewhere, illustrating the nuts-and-bolts interpretability that SCAM adds to the hierarchy of model configurations. Multi-day oscillations of precipitation arise from descent of warm convection-capping layers starting near the tropopause, eventually reset by a burst of convective deepening. Experiments reveal how these oscillations depend critically on an internal parameter that controls the number of neutral buoyancy levels allowed for determining cloud top and computing dilute convective available potential energy in the deep convection scheme, and merely modified a little by disabling cloud-base radiation (heating of cloud base). This strong dependence of transient behavior in 1D on this parameter will be tested in the second part of this work, in which SCAM is coupled to a parameterized dynamics of two-dimensional, linearized gravity wave, and in the 3D simulations in future study.
Soil water content is a function of inputs from precipitation and outputs via evaporation, transpiration, lateral flow, and vertical percolation, and is sensitive to biogeochemical processes. As such, soils serve as an ideal integrator of atmospheric, hydrological, and biogeochemical processes affecting the water cycle. In addition, soil water retention capacity, infiltration rates, and hydraulic conductivity can buffer or exacerbate the effects of extreme precipitation events (e.g., flooding, runoff, subsurface transport, erosion, greenhouse gas emissions) and mitigate the impact of droughts and heat waves on land systems (e.g., fire, crop failure). However, integrating water cycle measurements spanning different land atmosphere compartments across scales is a fundamental barrier for numerical model predictability. A significant challenge is that each domain (soil, hydrology, biology, and atmosphere) typically collects different sets of data at different temporal and spatial frequencies/scales, and even different dimensionalities (2D vs 3D). To implement soil as an integrator of the water cycle in land models, we suggest that novel machine learning (ML) tools can be developed to effectively simulate complex landscapes across various domains and scales, extended to regions with sparse or no data. The ultimate goals are to improve predictive understanding of land-atmosphere interactions and to extend the predictability of current Earth System Models (ESMs) through better integration of hydrological and biogeochemical data. We envision a framework in which: (1) ML-aided data reconstructions enable the merger of data sources into a unified geospatial product; (2) automated detection techniques are used to improve the knowledge of complex soil processes and interactions; and (3) this knowledge is leveraged and incorporated into models through AI-based emulators to distinctly connect the land and atmospheric compartments of the water cycle in models.
The areas of emphasis are: (1) develop theoretical models of the transient release of magnetic energy in the solar atmosphere, e.g., in solar flares, eruptive prominences, coronal mass ejections, etc.; (2) investigate the role of the Sun's magnetic field in the structuring of solar corona by the development of three-dimensional numerical models that describe the field configuration at various heights in the solar atmosphere by extrapolating the field at the photospheric level; (3) develop numerical models to investigate the physical parameters obtained by the ULYSSES mission; (4) develop numerical and theoretical models to investigate solar activity effects on the solar wind characteristics for the establishment of the solar-interplanetary transmission line; and (5) develop new instruments to measure solar magnetic fields and other features in the photosphere, chromosphere transition region and corona. We focused our investigation on the fundamental physical processes in solar atmosphere which directly effect our Planet Earth. The overall goal is to establish the physical process for the Sun-Earth connections.
The exospheres that surround airless bodies such as the Moon are tenuous, atmosphere-like layers whose constituent particles rarely collide with one another. Some particles contained within such exospheres are the product of direct interactions between airless bodies and the space environment, and offer insights into space weathering processes. NASAs Lunar Atmosphere and Dust Environment Explorer (LADEE) mission studied the Moons exospheric constituents in situ and detected a permanent dust exosphere1 of particles with radii as small as 300 nm. Here we present evidence from LADEE spectral data for an additional fluctuating nanodust exosphere at the Moon containing a population of particles sufficiently dense to be detectable via scattered sunlight. We compare two anti-Sun spectral observations: one near the peak of the Quadrantidmeteoroid stream, the other during a period of comparativelyweak stream activity. The former shows a negative spectralslope consistent with backscattering of sunlight by nanodustgrains with radii less than 20 to 30 nm; the latter has a flatterspectral slope. We hypothesize that a spatially and temporallyvariable nanodust exosphere may exist at the Moon, and thatit is modulated by changes in meteoroid impact rates, suchas during encounters with meteoroid streams. The findingssuggest that similar nanodust exospheresand the particle ejection and transport processes that form themmay occurat other airless bodies.
The PACE mission represents NASA’s next investment in ocean color, cloud, and aerosol data records to enable continued and advanced insight into oceanographic and atmospheric responses to Earth’s changing climate. The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission represents NASA’s next investment in satellite ocean color and the study of Earth’s ocean-atmosphere system, enabling new insights into oceanographic and atmospheric responses to Earth's changing climate. PACE objectives include extending systematic cloud, aerosol, and ocean biological and biogeochemical data records, making essential ocean color measurements to further understand marine carbon cycles, food web processes, and ecosystem responses to a changing climate, and improving knowledge of how aerosols influence ocean ecosystems and, conversely, how ocean ecosystems and photochemical processes affect the atmosphere. PACE objectives also encompass management of fisheries, large freshwater bodies, and air and water quality and reducing uncertainties in climate and radiative forcing models of the Earth system. PACE observations will provide information on radiative properties of land surfaces and characterization of the vegetation and soils that dominate their reflectance. The primary PACE instrument is a spectrometer that spans the ultraviolet to shortwave infrared, with a ground sample distance of 1-km at nadir. This payload is complemented by two multi-angle polarimeters with spectral ranges that span the visible to near-infrared region. Scheduled for launch in late 2022-to-early 2023, the PACE observatory will enable significant advances in the study of Earth’s biogeochemistry, carbon cycle, clouds, hydrosols, and aerosols in the ocean-atmosphere-land system. Here, we present an overview of the PACE mission, including its developmental history, science objectives, instrument payload, observatory characteristics, and data products.