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At least 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Where is the Best Site on Earth? Domes A, B, C, and F, and Ridges A and B

The Antarctic plateau contains the best sites on earth for many forms of astronomy, but none of the existing bases were selected with astronomy as the primary motivation. In this paper, we try to systematically compare the merits of potential observatory sites. We include South Pole, Domes A, C and F, and also Ridge B (running NE from Dome A), and what we call Ridge A (running SW from Dome A). Our analysis combines satellite data, published results and atmospheric models, to compare the boundary layer, weather, free atmosphere, sky brightness, pecipitable water vapour, and surface temperature at each site. We find that all Antarctic sites are likely compromised for optical work by airglow and aurorae. Of the sites with existing bases, Dome A is the best overall; but we find that Ridge A offers an even better site. We also find that Dome F is a remarkably good site. Dome C is less good as a thermal infrared or terahertz site, but would be able to take advantage of a predicted OH hole over Antarctica during Spring.

Suanders, Will↗
NASA NTRS2011

Trajectory-Based Loads for the Ares I-X Test Flight Vehicle

In trajectory-based loads, the structural engineer treats each point on the trajectory as a load case. Distributed aero, inertial, and propulsion forces are developed for the structural model which are equivalent to the integrated values of the trajectory model. Free-body diagrams are then used to solve for the internal forces, or loads, that keep the applied aero, inertial, and propulsion forces in dynamic equilibrium. There are several advantages to using trajectory-based loads. First, consistency is maintained between the integrated equilibrium equations of the trajectory analysis and the distributed equilibrium equations of the structural analysis. Second, the structural loads equations are tied to the uncertainty model for the trajectory systems analysis model. Atmosphere, aero, propulsion, mass property, and controls uncertainty models all feed into the dispersions that are generated for the trajectory systems analysis model. Changes in any of these input models will affect structural loads response. The trajectory systems model manages these inputs as well as the output from the structural model over thousands of dispersed cases. Large structural models with hundreds of thousands of degrees of freedom would execute too slowly to be an efficient part of several thousand system analyses. Trajectory-based loads provide a means for the structures discipline to be included in the integrated systems analysis. Successful applications of trajectory-based loads methods for the Ares I-X vehicle are covered in this paper. Preliminary design loads were based on 2000 trajectories using Monte Carlo dispersions. Range safety loads were tied to 8423 malfunction turn trajectories. In addition, active control system loads were based on 2000 preflight trajectories using Monte Carlo dispersions.

Vause, Roland F.↗
NASA NTRS2014

The Sensitivity of WRF Daily Summertime Simulations over West Africa to Alternative Parameterizations. Part 1: African Wave Circulation

The performance of the NCAR Weather Research and Forecasting Model (WRF) as a West African regional-atmospheric model is evaluated. The study tests the sensitivity of WRF-simulated vorticity maxima associated with African easterly waves to 64 combinations of alternative parameterizations in a series of simulations in September. In all, 104 simulations of 12-day duration during 11 consecutive years are examined. The 64 combinations combine WRF parameterizations of cumulus convection, radiation transfer, surface hydrology, and PBL physics. Simulated daily and mean circulation results are validated against NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) and NCEP/Department of Energy Global Reanalysis 2. Precipitation is considered in a second part of this two-part paper. A wide range of 700-hPa vorticity validation scores demonstrates the influence of alternative parameterizations. The best WRF performers achieve correlations against reanalysis of 0.40-0.60 and realistic amplitudes of spatiotemporal variability for the 2006 focus year while a parallel-benchmark simulation by the NASA Regional Model-3 (RM3) achieves higher correlations, but less realistic spatiotemporal variability. The largest favorable impact on WRF-vorticity validation is achieved by selecting the Grell-Devenyi cumulus convection scheme, resulting in higher correlations against reanalysis than simulations using the Kain-Fritch convection. Other parameterizations have less-obvious impact, although WRF configurations incorporating one surface model and PBL scheme consistently performed poorly. A comparison of reanalysis circulation against two NASA radiosonde stations confirms that both reanalyses represent observations well enough to validate the WRF results. Validation statistics for optimized WRF configurations simulating the parallel period during 10 additional years are less favorable than for 2006.

variability↗
NASA NTRS2017

A Theory of Immersion Freezing

Immersion freezing is likely involved in the initiation of precipitation and determines to large extent the phase partitioning in convective clouds. Theoretical models commonly used to describe immersion freezing in atmospheric models are based on the classical nucleation theory which however neglects important interactions near the immersed particle that may affect nucleation rates. This work introduces a new theory of immersion freezing based on two premises. First, immersion ice nucleation is mediated by the modification of the properties of water near the particle-liquid interface, rather than by the geometry of the ice germ. Second, the same mechanism that leads to the decrease in the work of germ formation also decreases the mobility of water molecules near the immersed particle. These two premises allow establishing general thermodynamic constraints to the ice nucleation rate. Analysis of the new theory shows that active sites likely trigger ice nucleation, but they do not control the overall nucleation rate nor the probability of freezing. It also suggests that materials with different ice nucleation efficiency may exhibit similar freezing temperatures under similar conditions but differ in their sensitivity to particle surface area and cooling rate. Predicted nucleation rates show good agreement with observations for a diverse set of materials including dust, black carbon and bacterial ice nucleating particles. The application of the new theory within the NASA Global Earth System Model (GEOS-5) is also discussed.

Ice Nucleating particle↗
NASA NTRS2022

Assimilation of NASA’s Airborne Snow Observatory Snow Measurements for Improved Hydrological Modeling: A Case Study Enabled by the Coupled LIS/WRF-Hydro System

he NASA LIS/WRF-Hydro system is a coupled modeling framework that combines the modeling and data assimilation (DA) capabilities of the NASA Land Information System (LIS) with the multi-scale surface hydrological modeling capabilities of the WRF-Hydro model, both of which are widely used in both operations and research. This coupled modeling framework builds on the linkage between land surface models (LSMs), which simulate surface boundary conditions in atmospheric models, and distributed hydrologic models, which simulate horizontal surface and sub-surface flow, adding new land DA capabilities. In the present study, we employ this modeling framework in the Tuolumne River basin in central California. We demonstrate the added value of the assimilation of NASA Airborne Snow Observatory (ASO) snow water equivalent (SWE) estimates in the Tuolumne basin. This analysis is performed in both LIS as an LSM column model and LIS/WRF-Hydro, with hydrologic routing. Results demonstrate that ASO DA in the basin reduced snow bias by as much as 30% from an open-loop (OL) simulation compared to three independent datasets. It also reduces downstream streamflow runoff biases by as much as 40%, and improves streamflow skill scores in both wet and dry years. Analysis of soil moisture and evapotranspiration (ET) also reveals the impacts of hydrologic routing from WRF-Hydro in the simulations, which would otherwise not be resolved in an LSM column model. By demonstrating the beneficial impact of SWE DA on the improving streamflow forecasts, the article outlines the importance of such observational inputs for reservoir operations and related water management applications.

Hydrologic modeling↗
NASA NTRS2022

Assimilation of NASA's Airborne Snow Observatory Snow Measurements for Improved Hydrological Modeling: A Case Study Enabled by the Coupled LIS/WRF-Hydro System

The NASA LIS/WRF-Hydro system is a coupled modeling framework that combines the modeling and data assimilation (DA) capabilities of the NASA Land Information System (LIS) with the multi-scale surface hydrological modeling capabilities of the WRF-Hydro model, both of which are widely used in both operations and research. This coupled modeling framework builds on the linkage between land surface models (LSMs), which simulate surface boundary conditions in atmospheric models, and distributed hydrologic models, which simulate horizontal surface and sub-surface flow, adding new land DA capabilities. In the present study, we employ this modeling framework in the Tuolumne River basin in central California. We demonstrate the added value of the assimilation of NASA Airborne Snow Observatory (ASO) snow water equivalent (SWE) estimates in the Tuolumne basin. This analysis is performed in both LIS as an LSM column model and LIS/WRF-Hydro, with hydrologic routing. Results demonstrate that ASO DA in the basin reduced snow bias by as much as 30% from an open-loop (OL) simulation compared to three independent datasets. It also reduces downstream streamflow runoff biases by as much as 40%, and improves streamflow skill scores in both wet and dry years. Analysis of soil moisture and evapotranspiration (ET) also reveals the impacts of hydrologic routing from WRF-Hydro in the simulations, which would otherwise not be resolved in an LSM column model. By demonstrating the beneficial impact of SWE DA on the improving streamflow forecasts, the article outlines the importance of such observational inputs for reservoir operations and related water management applications.

Timothy M. Lahmers↗
NASA NTRS2022

Camera Simulation for the Perseverance Rover’s Lander Vision System

On February 18, 2021, the Perseverance Rover safely landed on Mars at Jezero Crater. Part of the successful landing was due to the Lander Vision System (LVS), which takes descent images from the LVS Camera (LCAM) and IMU measurements and estimates the lander position relative to a map of the Jezero landing site. The LVS Simulation LCAM (LVSS LCAM) model is an image rendering program developed to test the LVS in a variety of scenarios to ensure performance amid uncertainty. The LVSS LCAM model includes a pointing misalignment model, an exposure timing model, shadowing, a terrain reflectance model, atmospheric attenuation from dust, and sensor effects. This model was used for performance analysis, verification, and validation of the LVS algorithms in a Mars-like simulation prior to landing. This paper describes the LVSS LCAM rendering algorithm and compares flight images from LVS operation during the Perseverance landing with their rendered counterparts.

Zheng, Jason↗
NASA NTRSDate not supplied

Impact of Canadian Wildfires on Mid Atlantic’s Region Air Quality: An Analysis Using ASDC Data

Wildfires pose a growing concern in North America due to their harmful impacts on air quality and public health, with increased wildfire activity in recent years leading to widespread smoke plumes that can transcend borders. The exposure of New York City (NYC), the most populous city in North America, to Canadian wildfire smoke highlights the substantial implications for public health and urban environments. To better understand the impact of Canadian wildfires on air quality in NYC, satellite data from the NASA Atmospheric Science Data Center (ASDC) at Langley Research Center, along with ground-based measurements and atmospheric modeling results, are analyzed. We examine concentrations of atmospheric aerosols—particularly PM2.5 particulate matter originating from Canadian wildfires—their dispersion patterns, and the duration and intensity of smoke events impacting NYC. Data from multiple satellites, such as those from the Earth Polychromatic Imaging Camera (EPIC), are synergistically used to identify regions affected by wildfires and estimate aerosol loading. Ground-based measurements, including data from air quality monitoring stations, provide localized information for validation and calibration purposes. The findings of this study contribute to our understanding of the impact of Canadian wildfires on NYC's air quality and emphasize the importance of monitoring and prediction of transboundary smoke events using data synthesized from multiple sources, such as those provided by the ASDC. This information is crucial for policymakers, public health officials, and residents in affected areas to develop effective strategies for mitigating the health risks associated with wildfire smoke and improving air quality during wildfire seasons. The utilization of ASDC data in this research highlights the critical role of atmospheric remote sensing in addressing the challenges posed by wildfires and their consequences on regional scales.

Ingrid Garcia-Solera↗
NASA NTRSDate not supplied

Analyzing the Impact of Canadian Wildfires on Air Quality in the U.S. Mid-Atlantic: with Data and Tools from NASA’s Atmospheric Sciences Data Center

Wildfires pose a growing concern in North America due to their harmful impacts on air quality and public health, with increased wildfire activity in recent years leading to widespread smoke plumes that can transcend borders. The exposure of New York City (NYC), the most populous city in North America, to Canadian wildfire smoke highlights the substantial implications for public health and urban environments. To better understand the impact of Canadian wildfires on air quality in NYC, satellite data from the NASA Atmospheric Science Data Center (ASDC) at Langley Research Center, along with ground-based measurements and atmospheric modeling results, are analyzed. We examine concentrations of atmospheric aerosols—particularly PM2.5 particulate matter originating from Canadian wildfires—their dispersion patterns, and the duration and intensity of smoke events impacting NYC. Data from multiple satellites, such as those from the Earth Polychromatic Imaging Camera (EPIC), are synergistically used to identify regions affected by wildfires and estimate aerosol loading. Ground-based measurements, including data from air quality monitoring stations, provide localized information for validation and calibration purposes. The findings of this study contribute to our understanding of the impact of Canadian wildfires on NYC's air quality and emphasize the importance of monitoring and prediction of transboundary smoke events using data synthesized from multiple sources, such as those provided by the ASDC. This information is crucial for policymakers, public health officials, and residents in affected areas to develop effective strategies for mitigating the health risks associated with wildfire smoke and improving air quality during wildfire seasons. The utilization of ASDC data in this research highlights the critical role of atmospheric remote sensing in addressing the challenges posed by wildfires and their consequences on regional scales.

Ingrid Garcia-Solera↗
NASA NTRS1973

The Development of a Stochastic Model of the Atmosphere Between 30 and 90 Km to Be Used in Determining the Effect of Atmospheric Variability on Space Shuttle Entry Parameters

A stochasitc model of the atmosphere between 30 and 90 km was developed for use in Monte Carlo space shuttle entry studies. The model is actually a family of models, one for each latitude-season category as defined in the 1966 U.S. Standard Atmosphere Supplements. Each latitude-season model generates a pseudo-random temperature profile whose mean is the appropriate temperature profile from the Standard Atmosphere Supplements. The standard deviation of temperature at each altitude for a given latitude-season model was estimated from sounding-rocket data. Departures from the mean temperature at each altitude were produced by assuming a linear regression of temperature on the solar heating rate of ozone. A profile of random ozone concentrations was first generated using an auxiliary stochastic ozone model, also developed as part of this study, and then solar heating rates were computed for the random ozone concentrations.

Campbell, J. W.↗
DOE OSTI2023

Modeling Land-Atmosphere Coupling at Cloud-Resolving Scale Within the Multiple Atmosphere Multiple Land (MAML) Framework in SP-E3SM

Representing subgrid variabilities of land surface processes and their upscaled effects is crucial for global climate modeling. Here, we implement a Multiple Atmosphere Multiple Land (MAML) framework in the superparamaterized version of E3SM (SP32 E3SM) to explicitly simulate the subgrid variabilities of land states and fluxes at cloud-resolving scale and their interactions with atmosphere. Comparing to the standard SP-E3SM in which all the atmospheric columns of the cloud resolving model embedded within the global atmospheric model grid interact with the same land surface (i.e., Multiple Atmosphere Single Land (MASL)), the impact of MAML on the strength of land-atmosphere coupling is limited, partly because the current implementation mainly facilitates one-way coupling between the cloud-resolving model and the land surface model. Despite such limitation, MAML increases the surface latent heat flux at the expense of sensible heat flux, and increases precipitation in India, Amazon, and Central Africa, reducing the model dry bias compared to the standard SP-E3SM. By employing a normalized gross moist stability (NGMS) diagnostic framework, we find that the increase in precipitation minus evaporation (PE) is primarily driven by the change in large-scale moisture convergence, particularly by the increase of water vapor in the lower atmosphere, while the local effect of total surface energy flux plays a minor role in the P-E change. More specifically, MAML changes the surface energy partitioning (evaporative fraction), increases the atmosphere water vapor, and further increases P-E by decreasing the NGMS. Finally, future development in the MAML framework is discussed.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1993

The NASA/GISS Mars general circulation model: Preliminary experiments

The NASA/GISS Mars General Circulation Model (GCM) is an adapted version of the GISS Global Climate/Middle Atmosphere Model, specifically developed for the diagnostic validation and objective analysis of measured atmospheric temperatures from the Mars Observer Pressure Modulator Infrared Radiometer (PMIRR) experiment. The GISS Mars GCM has 23 vertical layers extending from the surface to approximately 80 km altitude, representing a vertical resolution of about 0.3 scale heights. The primitive (vertically hydrostatic) equations are solved in finite difference form on the Krakawa B grid, with a horizontal resolution of 8 deg x 10 deg (latitude-longitude). The model includes a diurnal solar cycle, heat transport within a two-layer ground, and a high-order 'slopes-scheme' for the advection of heat in the upper atmosphere. The radiative transfer scheme is based on the correlated k distribution method for the treatment of nongray gaseous absorption thermal emission, and multiple scattering, including options for suspended dust. A special feature of the model of particular importance for Mars is a parameterization of gravity-wave-induced drag incorporating orographic forcing, wind shear, convection, and radiative damping. The implementation of the GISS Mars model includes global maps of topography, roughness, and albedo.

Allison, Michael↗
NASA NTRS1973

A radiation model for calculating atmospheric corrections to remotely sensed infrared measurements, version 2

A numerical model is developed which calculates the atmospheric corrections to infrared radiometric measurements due to absorption and emission by water vapor, carbon dioxide, and ozone. The corrections due to aerosols are not accounted for. The transmissions functions for water vapor, carbon dioxide, and water are given. The model requires as input the vertical distribution of temperature and water vapor as determined by a standard radiosonde. The vertical distribution of carbon dioxide is assumed to be constant. The vertical distribution of ozone is an average of observed values. The model also requires as input the spectral response function of the radiometer and the nadir angle at which the measurements were made. A listing of the FORTRAN program is given with details for its use and examples of input and output listings. Calculations for four model atmospheres are presented.

Boudreau, R. D.↗
NASA NTRS1978

The clouds of Venus - An anisotropic scattering model

The phase function for anisotropic scattering is applied to a homogeneous atmospheric model to ascertain the effects of anisotropy on the near-infrared spectrum of Venus. Young's (1971) equivalent widths for the 7820-A CO2 band are analyzed to derive allowed combinations of CO2 specific abundance, continuum albedo, pressure, and degree of anisotropy. From these combinations, values are derived for the photon mean free path and total optical thickness of the clouds. The Venera 10 measurement of the transmitted flux at 7200 A is then used in conjunction with spherical-albedo requirements to reduce the range of possible solutions to the equivalent-width analysis. Through the application of approximate similarity relations, the 'true' (i.e., anisotropic) atmospheric parameters are derived from the isotropic values. For an assumed Mie scatterer with an average anisotropy factor of 0.7, the results indicate a total optical thickness of about 55 with a single-scattering albedo of 0.9992 to 0.9995.

Lestrade, J. P.↗
DOE OSTI2014

Precise atmospheric parameters for the shortest-period binary white dwarfs: gravitational waves, metals, and pulsations

We present a detailed spectroscopic analysis of 61 low-mass white dwarfs and provide precise atmospheric parameters, masses, and updated binary system parameters based on our new model atmosphere grids and the most recent evolutionary model calculations. For the first time, we measure systematic abundances of He, Ca, and Mg for metal-rich, extremely low mass white dwarfs and examine the distribution of these abundances as a function of effective temperature and mass. Based on our preliminary results, we discuss the possibility that shell flashes may be responsible for the presence of the observed He and metals. We compare stellar radii derived from our spectroscopic analysis to model-independent measurements and find good agreement except for white dwarfs with T {sub eff} ≲ 10,000 K. We also calculate the expected gravitational wave strain for each system and discuss their significance to the eLISA space-borne gravitational wave observatory. Finally, we provide an update on the instability strip of extremely low mass white dwarf pulsators.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2001

Wind-Related Modification of Some Small Impact Craters on Mars

Inferred wind-related modifications of impact craters are observed in the vicinity of the Mare Pathfinder (MPF) site and in other regions of Mars. Mars Orbiter Camera (MOC) images show three types of inferred wind-modified morphologies for craters 0.3-1 km in diameter Such modifications could be related to seasonal variations of the strongest winds and a possible paleowind regime. Geomorphic mapping of Big Crater at the MPF shows evidence of former aeolian modification of the crater rim and interiors similar to smaller craters in the area. The morphologic patterns are in good agreement with the results from the Mars Regional Atmospheric Modeling Simulation (MRAMS) of topographically forced wind circulation and atmosphere surface interactions generated by flow over small craters. Simulations show that the maximum surface stress is on the downwind crater rim, consistent with inferred wind modification of the crater rim seen in MOC images. The trend of the Inferred paleowind regime at the MPF site cannot be explained by a change In the global atmospheric circulation resulting ~ from changes in Mars obliquity. We suggest that this wind regime could be associated with a regional meteorological pattern that is not modeled by global scale circulation, An alternative explanation is that Mars spin axis was in a different geographic position than it is at present.

Kuzmin, Ruslan O.↗
NASA NTRS2006

Data Needs for Stellar Atmosphere and Spectrum Modeling

The main data need for stellar atmosphere and spectrum modeling remains atomic and molecular transition data, particularly energy levels and transition cross-sections. We emphasize that data is needed for bound-free (b - f) as well as bound-bound (b - b), and collisional as well as radiative transitions. Data is now needed for polyatomic molecules as well as atoms, ions, and diatomic molecules. In addition, data for the formation of, and extinction due to, liquid and solid phase dust grains is needed. A prioritization of species and data types is presented, and gives emphasis to Fe group elements, and elements important for the investigation of nucleosynthesis and Galactic chemical evolution, such as the -elements and n-capture elements. Special data needs for topical problems in the modeling of cool stars and brown dwarfs are described.

Short, C. I.↗
NASA NTRS2022

The Turning Point of the Aerosol Era

Over the CMIP6 historical period (1850–2014), aerosols provided the largest negative forcing compared to all other climate forcings via their ability to absorb or scatter solar radiation and alter clouds. Aerosols played an important role in counterbalancing warming by greenhouse gases (GHGs). Here we study aerosol forcing trends in the CMIP6 simulations of the NASA Goddard Institute for Space Studies (GISS) ocean-atmosphere ModelE version 2.1 (GISS-E2.1-G) using a fully coupled atmospheric composition configuration, including interactive gas-phase chemistry, and either an aerosol microphysical (MATRIX) or a mass-based aerosol (OMA) module. Simulations of the CMIP6 historical period are analyzed as well as four Shared Socioeconomic Pathway (SSP) future scenarios for 2015–2100: SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. The main conclusion of this study is that aerosol forcing in the GISS model has reached its turning point, switching from globally increasing to a decreasing trend in the first decade of the 21st century. This result is robust, independent of which aerosol module or SSP scenario is used. Non-linear aerosol-cloud interactions dominate as a forcing agent over aerosol-radiation interactions. Aerosols' ability to counterbalance GHG forcing on the global scale is today at a level comparable to that at the beginning of the last century. In the 1980s, the decade of largest global aerosol loads, aerosols balanced up to 80% of GHG forcing. As a consequence, global warming of the last decades, which is primarily driven by greenhouse gases, has been augmented by the effect of decreasing aerosol cooling in our model. By the end of this century, following the SSP scenarios, aerosols will only counterbalance 0%–20% of GHG forcing, depending on model and on scenario.

Aerosol forcing↗