Hydrogen line blanketed model stellar atmospheres
Hydrogen line blanketed stellar model atmospheres
Klinglesmith, D. A.↗
SEARCH · Engineering Papers
Results for “Atmospheric Models”
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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A comparison of two Greenhouse models for the Cytherean atmosphere
Surface temperature calculations for Venus based on two Greenhouse atmospheric model comparisons
ATMOSPHERE MODEL↗
Models of the upper atmosphere for a wide range of boundary conditions.
Upper atmosphere model giving composition, density and temperature of neutral atmosphere as function of altitude correlated with satellite drag data
UPPER ATMOSPHERE↗
Constraints on the Profiles of Total Water PDF in AGCMs from AIRS and a High-Resolution Model
Atmospheric general circulation model (AGCM) cloud parameterizations generally include an assumption about the subgrid-scale probability distribution function (PDF) of total water and its vertical profile. In the present study, the Atmospheric Infrared Sounder (AIRS) monthly-mean cloud amount and relative humidity fields are used to compute a proxy for the second moment of an AGCM total water PDF called the RH01 diagnostic, which is the AIRS mean relative humidity for cloud fractions of 0.1 or less. The dependence of the second moment on horizontal grid resolution is analyzed using results from a high-resolution global model simulation.The AIRS-derived RH01 diagnostic is generally larger near the surface than aloft, indicating a narrower PDF near the surface, and varies with the type of underlying surface. High-resolution model results show that the vertical structure of profiles of the AGCM PDF second moment is unchanged as the grid resolution changes from 200 to 100 to 50 km, and that the second-moment profiles shift toward higher values with decreasing grid spacing.Several Goddard Earth Observing System, version 5 (GEOS-5), AGCM simulations were performed with several choices for the profile of the PDF second moment. The resulting cloud and relative humidity fields were shown to be quite sensitive to the prescribed profile, and the use of a profile based on the AIRS-derived proxy results in improvements relative to observational estimates. The AIRS-guided total water PDF profiles, including their dependence on underlying surface type and on horizontal resolution, have been implemented in the version of the GEOS-5 AGCM used for publicly released simulations.
Molod, Andrea↗
The use of atmospheric prediction models to invert infrasound for linear-equivalent time domain moment tensors: Source Physics Experiment, Phase 1
We invert far field infrasound data for the equivalent seismo-acoustic time domain moment tensor to assess the effects of variable atmospheric models as well as to quantify the relative contributions of two presumed source phenomena. The infrasound data was produced by a series of underground chemical explosions that were conducted during the Source Physics Experiment, (SPE) which was originally designed to study explosion-generated seismo-acoustic signal phenomena. The goal of the work presented herein is two-fold: the first goal is to investigate the sensitivity of the estimated time domain moment tensors to variability of the estimated atmospheric model. The second goal is to determine the relative contribution of two possible source mechanisms to the observed infrasonic wave field. Rather than using actual atmospheric observations to estimate the necessary atmospheric Green's functions, we build a series of atmospheric models that rely on publicly available, regional atmospheric observations and the assumption that the acoustic energy results from a linear combination of an underground isotropic explosion and surface spall. The atmospheric observations are summarized and interpolated onto a 3D grid to produce a model of sound speed at the time of the experiment. For each of four SPE acoustic datasets that we invert, we produced a suite of three atmospheric models, based on ten years of regional meteorological observations: an average model, which averages the atmospheric conditions for ten years prior to each SPE event, as well as two extrema models. We find that the inversion yields relatively repeatable results for the estimated spall source. Conversely, the estimated isotropic explosion source is highly variable. This suggests that the majority of the observed acoustic energy is produced by the spall source and/or our modeling of the elastic energy propagation, and it's subsequent conversion to acoustic energy via linear elastic-to-acoustic coupling at the free surface, is too simplistic.
58 GEOSCIENCES↗
Engineering models of the Martian atmosphere and surface
Mars surface and atmosphere models for landing module design
LANDING MODULE↗
The problem of using Mariner IV IONOSPHERIC densities to deduce a model of the Martian atmospheric structure
Martian atmosphere model deduced from Mariner IV IONOSPHERE electron density measurements
MARINER IV SPACE PROBE↗
Technical Report Series on Global Modeling and Data Assimilation: A Coupled Ocean-Atmosphere Radiative Model for Global Ocean Biogeochemical Models - Volume 22
An ocean-atmosphere radiative model (OARM) evaluates irradiance availability and quality in the water column to support phytoplankton growth and drive ocean thermodynamics. An atmospheric component incorporates spectral and directional effects of clear and cloudy skies as a function of atmospheric optical constituents, and spectral reflectance across the air-sea interface. An oceanic component evaluates the propagation of spectral and directional irradiance through the water column as a function of water, five phytoplankton groups, and chromophoric dissolved organic matter. It tracks the direct and diffuse streams from the atmospheric component, and a third stream, upwelling diffuse irradiance. The atmospheric component of OARM was compared to data sources at the ocean surface with a coefficient of determination (r2) of 0.97 and a root mean square of 12.1%.
Gregg, Watson W.↗
Preserving Tracer Correlations in Moment-Based Atmospheric Transport Models
A linear non-diffusive algorithm for advective transport is developed that greatly improves the detail at which aerosols and clouds can be represented in atmospheric models. Linear advection schemes preserve tracer correlations but the most basic linear scheme is rarely used by atmospheric modelers on account of its excessive numerical diffusion. Higher-order schemes are in widespread use, but these present new problems as nonlinear adjustments are required to avoid occurrences of negative concentrations, spurious oscillations, and other non-physical effects. Generally successful at reducing numerical diffusion during the advection of individual tracers, for example, particle number or mass, the higher-order schemes fail to preserve even the simplest of correlations between interrelated tracers. As a result, important attributes of aerosol and cloud populations including radial moments of particle size distributions, molecular precursors related through chemical equilibria, aerosol mixing state, and distribution of cloud phase are poorly represented. We introduce a new transport scheme, minVAR, that is both non-diffusive and preservative of tracer correlations, thereby combining the best features of the basic and higher-order schemes while enabling new features such as the tracking of sub-grid information at arbitrarily fine scales with high computational efficiency.
54 ENVIRONMENTAL SCIENCES↗
Integration of Dust Prediction Systems and Vegetation Phenology to Track Pollen for Asthma Alerts in Public Health
Pollen can be transported great distances. Van de Water et. al., 2003 reported Juniperus pollen, a significant aeroallergen was transported 200-600 km. Hence local observations of plant phenology may not be consistent with the timing and source of pollen collected by pollen sampling instruments. The DREAM (Dust REgional Atmospheric Model, Yin 2007) is a verified model for atmospheric dust transport modeling using MODIS data products to identify source regions and quantities of dust (Yin 2007). The use of satellite data products for studying phenology is well documented (White and Nemani 2006). We are modifying the DREAM model to incorporate pollen transport. The linkages already exist with DREAM through PHAiRS (Public Health Applications in remote Sensing) to the public health community. This linkage has the potential to fill this data gap so that health effects of pollen can better be tracked for linkage with health outcome data including asthma, respiratory effects, myocardial infarction, and lost work days. DREAM is based on the SKIRON/Eta modeling system and the Eta/NCEP regional atmospheric model. The dust modules of the entire system incorporate the state of the art parameterizations of all the major phases of the atmospheric dust life such as production, diffusion, advection, and removal. These modules also include effects of the particle size distribution on aerosol dispersion. The dust production mechanism is based on the viscous/turbulent mixing, shear-free convection diffusion, and soil moisture. In addition to these sophisticated mechanisms, very high resolution databases, including elevation, soil properties, and vegetation cover are utilized. The DREAM model was modified to use pollen sources instead of dust (PREAM). Pollen release will be estimated based on satellite-derived phenology of Juniperus spp. communities. The MODIS surface reflectance product (MOD09) will provide information on the start of the plant growing season, growth stage, peak greenness, dry-down and pollen release. Ground based observational records of pollen release timing and quantities will be used as verification. Techniques developed using MOD09 surface reflectance products will be directly applicable to the next generation sensors such as VIIRS. The resulting deterministic model for predicting and simulating pollen emission and downwind concentration to study details of phenology and meteorology and their dependencies. This information will be used to support the Centers for Disease Control and Prevention (CDC)'s National Environmental Public Health Tracking Program (EPHT) and the State of New Mexico environmental public health decision support for asthma and allergies alerts
Luvall, Jeffrey C.↗
DCMIP2016: a review of non-hydrostatic dynamical core design and intercomparison of participating models
Abstract. Atmospheric dynamical cores are a fundamental component of global atmospheric modeling systems and are responsible for capturing the dynamical behavior of the Earth's atmosphere via numerical integration of the Navier–Stokes equations. These systems have existed in one form or another for over half of a century, with the earliest discretizations having now evolved into a complex ecosystem of algorithms and computational strategies. In essence, no two dynamical cores are alike, and their individual successes suggest that no perfect model exists. To better understand modern dynamical cores, this paper aims to provide a comprehensive review of 11 non-hydrostatic dynamical cores, drawn from modeling centers and groups that participated in the 2016 Dynamical Core Model Intercomparison Project (DCMIP) workshop and summer school. This review includes a choice of model grid, variable placement, vertical coordinate, prognostic equations, temporal discretization, and the diffusion, stabilization, filters, and fixers employed by each system.
54 ENVIRONMENTAL SCIENCES↗
Selecting a model of the neutral atmosphere
The characteristics and applicability of some of the more frequently used atmospheric models covering the thermosphere are discussed from the point of view of selecting the most appropriate model for an engineering or scientific problem. Models based on satellite atmospheric drag are the earliest examples of global models and are still widely used for engineering studies. Later models based on satellite instrumentation and ground based measurements were originally aimed at scientific studies of the atmosphere, but their absolute accuracies for total densities are now similar to those of drag based models while providing better thermospheric temperature, composition, and winds. Theoretical models are now approaching the accuracy of climatological empirical models and may surpass them in the near future. Each new model generation, however, is more complicated and costly to run on a computer.
Hedin, A. E.↗
Three dimensional global modeling of atmospheric CO2
A model was developed to study the prospects of extracting information on carbon dioxide sources and sinks from observed CO2 variations. The approach uses a three dimensional global transport model, based on winds from a 3-D general circulation model (GCM), to advect CO2 noninteractively, i.e., as a tracer, with specified sources and sinks of CO2 at the surface. The 3-D model employed is identified and biosphere, ocean and fossil fuel sources and sinks are discussed. Some preliminary model results are presented.
Fung, I.↗
Quantitative evaluation of an air-monitoring network using atmospheric transport modeling and frequency of detection methods
A methodology to quantify the performance of an air monitoring network in terms of frequency of detection has been developed. The methodology utilizes an atmospheric transport model to predict air concentrations of radionuclides at the samplers for a given release time and duration. Frequency of detection is defined as the fraction of “events” that result in a detection at either a single sampler or network of samplers. An “event” is defined as a release of finite duration that begins on a given day and hour of the year from a facility with the potential to emit airborne radionuclides. Another metric of interest is the network intensity, which is defined as the fraction of samplers in the network that have a positive detection for a given event. The frequency of detection methodology allows for evaluation of short-term releases that include effects of short-term variability in meteorological conditions. The methodology was tested using the U.S. Department of Energy Idaho National Laboratory (INL) Site ambient air monitoring network consisting of 37 low-volume air samplers in 31 different locations covering a 17,630 km 2 region. Releases from six major INL facilities distributed over an area of 1,435 km 2 were modeled and included three stack sources and eight ground-level sources. A Lagrangian Puff air dispersion model (CALPUFF) was used to model atmospheric transport. The model was validated using historical 125 Sb releases and measurements. Relevant one-week release quantities from each emission source were calculated based on a dose of 1.9 × 10 –4 mSv at a public receptor (0.01 mSv assuming release persists over a year). Important radionuclides considered include 241 Am, 137 Cs, 238 Pu, 239 Pu, 90 Sr, and tritium. Results show the detection frequency is over 97.5% for the entire network considering all sources and radionuclides. Network intensities ranged from 3.75% to 62.7%. Evaluation of individual samplers indicated some samplers were poorly situated and add little to the overall effectiveness of the network. As a result, using the frequency of detection methods, optimum sampler placements were simulated that could substantially improve the performance and efficiency of the network.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Composition Changes After the "Halloween" Solar Proton Event: The High-Energy Particle Precipitation in the Atmosphere (HEPPA) Model Versus MIPAS Data Intercomparison Study
We have compared composition changes of NO, NO2, H2O2,O3, N2O, HNO3 , N2O5, HNO4, ClO, HOCl, and ClONO2 as observed by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on Envisat in the aftermath of the "Halloween" solar proton event (SPE) in October/November 2003 at 25-0.01 hPa in the Northern hemisphere (40-90 N) and simulations performed by the following atmospheric models: the Bremen 2D model (B2dM) and Bremen 3D Chemical Transport Model (B3dCTM), the Central Aerological Observatory (CAO) model, FinROSE, the Hamburg Model of the Neutral and Ionized Atmosphere (HAMMONIA), the Karlsruhe Simulation Model of the Middle Atmosphere (KASIMA), the ECHAM5/MESSY Atmospheric Chemistry (EMAC) model, the modeling tool for SO1ar Climate Ozone Links studies (SOCOL and SOCOLi), and the Whole Atmosphere Community Climate Model (WACCM4). The large number of participating models allowed for an evaluation of the overall ability of atmospheric models to reproduce observed atmospheric perturbations generated by SPEs, particularly with respect to NOS, and ozone changes. We have further assessed the meteorological conditions and their implications on the chemical response to the SPE in both the models and observations by comparing temperature and tracer (CH4 and CO) fields. Simulated SPE-induced ozone losses agree on average within 5% with the observations. Simulated NO(y) enhancements around 1 hPa, however, are typically 30% higher than indicated by the observations which can be partly attributed to an overestimation of simulated electron-induced ionization. The analysis of the observed and modeled NO(y) partitioning in the aftermath of the SPE has demonstrated the need to implement additional ion chemistry (HNO3 formation via ion-ion recombination and water cluster ions) into the chemical schemes. An overestimation of observed H2O2 enhancements by all models hints at an underestimation of the OH/HO2 ratio in the upper polar stratosphere during the SPE. The analysis of chlorine species perturbations has shown that the encountered differences between models and observations, particularly the underestimation of observed ClONO2 enhancements, are related to a smaller availability of ClO in the polar night region already before the SPE. In general, the intercomparison has demonstrated that differences in the meteorology and/or initial state of the atmosphere in the simulations causes a relevant variability of the model results, even on a short timescale of only a few days.
Funke, B.↗
Application of a Reduced Order Kalman Filter to Initialize a Coupled Atmosphere-Ocean Model: Impact on the Prediction of El Nino
A reduced order Kalman Filter, based on a simplification of the Singular Evolutive Extended Kalman (SEEK) filter equations, is used to assimilate observed fields of the surface wind stress, sea surface temperature and sea level into the nonlinear coupled ocean-atmosphere model. The SEEK filter projects the Kalman Filter equations onto a subspace defined by the eigenvalue decomposition of the error forecast matrix, allowing its application to high dimensional systems. The Zebiak and Cane model couples a linear reduced gravity ocean model with a single vertical mode atmospheric model of Zebiak. The compatibility between the simplified physics of the model and each observed variable is studied separately and together. The results show the ability of the model to represent the simultaneous value of the wind stress, SST and sea level, when the fields are limited to the latitude band 10 deg S - 10 deg N. In this first application of the Kalman Filter to a coupled ocean-atmosphere prediction model, the sea level fields are assimilated in terms of the Kelvin and Rossby modes of the thermocline depth anomaly. An estimation of the error of these modes is derived from the projection of an estimation of the sea level error over such modes. This method gives a value of 12 for the error of the Kelvin amplitude, and 6 m of error for the Rossby component of the thermocline depth. The ability of the method to reconstruct the state of the equatorial Pacific and predict its time evolution is demonstrated. The method is shown to be quite robust for predictions I up to six months, and able to predict the onset of the 1997 warm event fifteen months before its occurrence.
Ballabrera-Poy, Joaquim↗
Application of a Reduced Order Kalman Filter to Initialize a Coupled Atmosphere-Ocean Model: Impact on the Prediction of El Nino
A reduced order Kalman Filter, based on a simplification of the Singular Evolutive Extended Kalman (SEEK) filter equations, is used to assimilate observed fields of the surface wind stress, sea surface temperature and sea level into the nonlinear coupled ocean-atmosphere model of Zebiak and Cane. The SEEK filter projects the Kalman Filter equations onto a subspace defined by the eigenvalue decomposition of the error forecast matrix, allowing its application to high dimensional systems. The Zebiak and Cane model couples a linear reduced gravity ocean model with a single vertical mode atmospheric model of Zebiak. The compatibility between the simplified physics of the model and each observed variable is studied separately and together. The results show the ability of the model to represent the simultaneous value of the wind stress, SST and sea level, when the fields are limited to the latitude band 10 deg S - 10 deg N In this first application of the Kalman Filter to a coupled ocean-atmosphere prediction model, the sea level fields are assimilated in terms of the Kelvin and Rossby modes of the thermocline depth anomaly. An estimation of the error of these modes is derived from the projection of an estimation of the sea level error over such modes. This method gives a value of 12 for the error of the Kelvin amplitude, and 6 m of error for the Rossby component of the thermocline depth. The ability of the method to reconstruct the state of the equatorial Pacific and predict its time evolution is demonstrated. The method is shown to be quite robust for predictions up to six months, and able to predict the onset of the 1997 warm event fifteen months before its occurrence.
Ballabrera-Poy, J.↗
Methods for Incorporating Model Uncertainty into Exoplanet Atmospheric Analysis
A key goal of exoplanet spectroscopy is to measure atmospheric properties, such as abundances of chemical species, in order to connect them to our understanding of atmospheric physics and planet formation. In this new era of high-quality JWST data, it is paramount that these measurement methods are robust. When comparing atmospheric models to observations, multiple candidate models may produce reasonable fits to the data. Typically, conclusions are reached by selecting the best-performing model according to some metric. This ignores model uncertainty in favor of specific model assumptions, potentially leading to measured atmospheric properties that are overconfident and/or incorrect. In this paper, we compare three ensemble methods for addressing model uncertainty by combining posterior distributions from multiple analyses: Bayesian model averaging, a variant of Bayesian model averaging using leave-one-out predictive densities, and stacking of predictive distributions. We demonstrate these methods by fitting the Hubble Space Telescope (HST) + Spitzer transmission spectrum of the hot Jupiter HD 209458b using models with different cloud and haze prescriptions. All of our ensemble methods lead to uncertainties on retrieved parameters that are larger but more realistic and consistent with physical and chemical expectations. Since they have not typically accounted for model uncertainty, uncertainties of retrieved parameters from HST spectra have likely been underreported. We recommend stacking as the most robust model combination method. Our methods can be used to combine results from independent retrieval codes and from different models within one code. They are also widely applicable to other exoplanet analysis processes, such as combining results from different data reductions.
79 ASTRONOMY AND ASTROPHYSICS↗