Model atmospheres for RR Lyrae stars.
RR Lyrae gap stellar model atmospheres including radiation spectra, temperature radiation and convection, etc
Strom, S. E.↗
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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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Earth Global Reference Atmospheric Model (GRAM) Overview and Future Improvements
Earth Global Reference Atmospheric Model (GRAM) Overview and Future Improvements
Patrick Wayne White↗
An Extensible Perturbed Parameter Ensemble for the Community Atmosphere Model Version 6
This paper documents the methodology and preliminary results from a Perturbed Parameter Ensemble (PPE) technique, where multiple parameters are varied simultaneously and the parameter values are determined with Latin hypercube sampling. This is done with the Community Atmosphere Model version 6 (CAM6), the atmospheric component of the Community Earth System Model version 2 (CESM2). We apply the PPE method to CESM2-CAM6 to understand climate sensitivity to atmospheric physics parameters. The initial simulations vary 45 parameters in the microphysics, convection, turbulence and aerosol schemes with 263 ensemble members. These atmospheric parameters are typically the most uncertain in many climate models. Control simulations are analyzed and targeted simulations to understand climate forcing due to aerosols and fast climate feedbacks. The use of various emulators is explored in the multi- dimensional space mapping input parameters to output metrics. Parameter impacts on various model outputs, such as radiation, cloud and aerosol properties are evaluated. Machine learning is also used to probe optimal parameter values against observations. Our findings show that using PPE is a valuable tool for climate uncertainty analysis. Furthermore, by varying many parameters simultaneously, we find that many different combinations of parameter values can produce results consistent with observations, and thus careful analysis of tuning is important. The CESM2-CAM6 PPE is publicly available, and extensible to other configurations to address questions of other model processes in the atmosphere and other model components (e.g. coupling to the land surface).
Machine learning↗
CIRA 1972, recent atmospheric models, and improvements in progress
The paper reviews current progress in the development of atmospheric models. Consideration is given to CIRA 1972 (COSPAR International Reference Atmosphere), the OGO 6 model (1974), the ESRO 4 model (1977), the global Doppler-temperature model of Thuillier et al. (1977), the Jacchia 1977 model (based on a synthesis of temperature, mass-spectrometer, and total-density data from many sources), and the MSIS model (1977), based on incoherent-scatter temperatures and mass-spectrometer data from various sources. New models of the disturbed thermosphere, developed by the author, are compared with recent mass-spectrometer measurements at 170 km.
Jacchia, L. G.↗
Use of the 4D-Global Reference Atmosphere Model (GRAM) for space shuttle descent design
The method of using the Global Reference Atmosphere Model (GRAM) mean and dispersed atmospheres to study skipout/overshoot requirements, to characterize mean and worst case vehicle temperatures, study control requirements, and verify design was discussed. Landing sites in these analyses range from 65 N to 30 S, while orbit inclinations vary from 20 deg to 98 deg. The primary concern was that they cannot use as small vertical steps in the reentry calculation as desired because the model predicts anomalously large density shear rates for very small vertical step sizes. The winds predicted by the model are not satisfactory. This is probably because they are geostrophic winds and because the model has an error in the computation of winds in the equatorial regions.
Mccarty, S. M.↗
Users of middle atmosphere models remarks
The procedure followed for shuttle operations is to calculate descent trajectories for each potential shuttle landing site using the Global Reference Atmosphere Model (GRAM) to interactively compute density along the flight path 100 times to bound the statistics. The purpose is to analyze the flight dynamics, along with calculations of heat loads during reentry. The analysis program makes use of the modified version of the Jacchia-70 atmosphere, which includes He bulges over the poles and seasonal latitude variations at lower altitudes. For the troposphere, the 4-D Model is used up to 20 km, Groves from 30 km up to 90 km. It is extrapolated over the globe and faired into the Jacchia atmosphere between 90 and 115 km. Since data on the Southern Hemisphere was lacking, what was done was that the data was flipped over and lagged 6 months. Sometimes when winds are calculated from pressure data in the model there appear to be discontinuities. Modelers indicated that the GRAM was not designed to produce winds, but good wind data is needed for the landing phase of shuttle operations. Use of atmospheric models during reentry is one application where it is obvious that a single integrated atmosphere model is required.
Gamble, Joe↗
Atmosphere Modeling and Performance Sensitivity for the Mars Sample Return Earth Entry System
The Capture, Containment, and Return System (CCRS) mission is a key element of the joint NASA-European Space Agency (ESA) planned Mars Sample Return (MSR) Campaign. The CCRS assembled Earth Entry System (EES) will enter the mission’s final segment in its Approach, Entry, Descent, and Landing (AEDL) Phase. The EES AEDL aims to deliver a highly reliable, safe, and accurate return while maintaining strict containment assurance targets established by the campaign. As currently designed, the EES would be the first fully passive sample return capsule with no parachute or onboard control system, prompting a significant effort in Earth atmosphere characterization and modeling. Earth’s atmosphere, specifically winds, have a strong influence on EES flight mechanics and landing footprint during its free fall landing. This paper describes Earth atmosphere modeling, atmosphere characterization, and performance sensitivities incorporated into the teams’s efforts to ensure AEDL success. By utilizing high resolution balloon radiosondes, analyzing wind structural and distributional compositions, and investigating flight mechanics sensitivities, the AEDL atmosphere team has been able to better understand and simulate local wind conditions at the Utah Test and Training Range (UTTR). Utilizing tools such as horizontal turbulent kinetic energy, vertical wind shear, or integrated wind, the team have been able to reveal valuable information about wind profiles in a deeper context than previously conducted, ultimately improving understanding of AEDL flight mechanics sensitivity and EES design.
Kaustubh Ray↗
Earth Global Reference Atmospheric Model (GRAM) Overview and Updates: DOLWG Meeting
What is Earth-GRAM (Global Reference Atmospheric Model): Provides monthly mean and standard deviation for any point in atmosphere - Monthly, Geographic, and Altitude Variation; Earth-GRAM is a C++ software package - Currently distributed as Earth-GRAM 2016; Atmospheric variables included: pressure, density, temperature, horizontal and vertical winds, speed of sound, and atmospheric constituents; Used by engineering community because of ability to create dispersions in atmosphere at a rapid runtime - Often embedded in trajectory simulation software; Not a forecast model; Does not readily capture localized atmospheric effects.
White, Patrick↗
Daily and Hourly Variability in Global Fire Emissions and Consequences for Atmospheric Model Predictions of Carbon Monoxide
Attribution of the causes of atmospheric trace gas and aerosol variability often requires the use of high resolution time series of anthropogenic and natural emissions inventories. Here we developed an approach for representing synoptic- and diurnal-scale temporal variability in fire emissions for the Global Fire Emissions Database version 3 (GFED3). We distributed monthly GFED3 emissions during 2003-2009 on a daily time step using Moderate Resolution Imaging Spectroradiometer (MODIS)-derived measurements of active fires from Terra and Aqua satellites. In parallel, mean diurnal cycles were constructed from Geostationary Operational Environmental Satellite (GOES) active fire observations. We found that patterns of daily variability in fires varied considerably across different biomes, with short but intense periods of daily emissions in boreal ecosystems and lower intensity (but more continuous) periods of bunting in savannas. On diurnal timescales, our analysis of the GOES active fires indicated that fires in savannas, grasslands, and croplands occurred earlier in the day as compared to fires in nearby forests. Comparison with Total Carbon Column Observing Network (TCCON) and Measurements of Pollution in the Troposphere (MOPITT) column CO observations provided evidence that including daily variability in emissions moderately improved atmospheric model simulations, particularly during the fire season and near regions with high levels of biomass burning. The high temporal resolution estimates of fire emissions developed here may ultimately reduce uncertainties related to fire contributions to atmospheric trace gases and aerosols. Important future directions include reconciling top-down and bottom up estimates of fire radiative power and integrating burned area and active fire time series from multiple satellite sensors to improve daily emissions estimates.
Mu, M.↗
The NASA/MSFC Global Reference Atmospheric Model: 1999 Version (GRAM-99)
The latest version of Global Reference Atmospheric Model (GRAM-99) is presented and discussed. GRAM-99 uses either (binary) Global Upper Air Climatic Atlas (GUACA) or (ASCII) Global Gridded Upper Air Statistics (GGUAS) CD-ROM data sets, for 0-27 km altitudes. As with earlier versions, GRAM-99 provides complete geographical and altitude coverage for each month of the year. GRAM-99 uses a specially-developed data set, based on Middle Atmosphere Program (MAP) data, for 20-120 km altitudes, and NASA's 1999 version Marshall Engineering Thermosphere (MET-99) model for heights above 90 km. Fairing techniques assure smooth transition in overlap height ranges (20-27 km and 90-120 km). GRAM-99 includes water vapor and 11 other atmospheric constituents (O3, N2O, CO, CH4, CO2, N2, O2, O, A, He and H). A variable-scale perturbation model provides both large-scale (wave) and small-scale (stochastic) deviations from mean values for thermodynamic variables and horizontal and vertical wind components. The small-scale perturbation model includes improvements in representing intermittency ("patchiness"). A major new feature is an option to substitute Range Reference Atmosphere (RRA) data for conventional GRAM climatology when a trajectory passes sufficiently near any RRA site. A complete user's guide for running the program, plus sample input and output, is provided. An example is provided for how to incorporate GRAM-99 as subroutines in other programs (e.g., trajectory codes).
Justus, C. G.↗
A Numerical Method for Calculating Stellar Occultation Light Curves from an Arbitrary Atmospheric Model
We present a method for speeding up numerical calculations of a light curve for a stellar occultation by a planetary atmosphere with an arbitrary atmospheric model that has spherical symmetry. This improved speed makes least-squares fitting for model parameters practical. Our method takes as input several sets of values for the first two radial derivatives of the refractivity at different values of model parameters, and interpolates to obtain the light curve at intermediate values of one or more model parameters. It was developed for small occulting bodies such as Pluto and Triton, but is applicable to planets of all sizes. We also present the results of a series of tests showing that our method calculates light curves that are correct to an accuracy of 10(exp -4) of the unocculted stellar flux. The test benchmarks are (i) an atmosphere with a l/r dependence of temperature, which yields an analytic solution for the light curve, (ii) an atmosphere that produces an exponential refraction angle, and (iii) a small-planet isothermal model. With our method, least-squares fits to noiseless data also converge to values of parameters with fractional errors of no more than 10(exp -4), with the largest errors occurring in small planets. These errors are well below the precision of the best stellar occultation data available. Fits to noisy data had formal errors consistent with the level of synthetic noise added to the light curve. We conclude: (i) one should interpolate refractivity derivatives and then form light curves from the interpolated values, rather than interpolating the light curves themselves; (ii) for the most accuracy, one must specify the atmospheric model for radii many scale heights above half light; and (iii) for atmospheres with smoothly varying refractivity with altitude, light curves can be sampled as coarsely as two points per scale height.
Chamberlain, D. M.↗
Evaluation of Tropospheric Water Vapor Simulations from the Atmospheric Model Intercomparison Project
Simulations of humidity from 28 general circulation models for the period 1979-88 from the Atmospheric Model Intercomparison Project are compared with observations from radiosondes over North America and the globe and with satellite microwave observations over the Pacific basin. The simulations of decadal mean values of precipitable water (W) integrated over each of these regions tend to be less moist than the real atmosphere in all three cases; the median model values are approximately 5% less than the observed values. The spread among the simulations is larger over regions of high terrain, which suggests that differences in methods of resolving topographic features are important. The mean elevation of the North American continent is substantially higher in the models than is observed, which may contribute to the overall dry bias of the models over that area. The authors do not find a clear association between the mean topography of a model and its mean W simulation, however, which suggests that the bias over land is not purely a matter of orography. The seasonal cycle of W is reasonably well simulated by the models, although over North America they have a tendency to become moister more quickly in the spring than is observed. The interannual component of the variability of W is not well captured by the models over North America. Globally, the simulated W values show a signal correlated with the Southern Oscillation index but the observations do not. This discrepancy may be related to deficiencies in the radiosonde network, which does not sample the tropical ocean regions well. Overall, the interannual variability of W, as well as its climatology and mean seasonal cycle, are better described by the median of the 28 simulations than by individual members of the ensemble. Tests to learn whether simulated precipitable water, evaporation, and precipitation values may be related to aspects of model formulation yield few clear signals, although the authors find, for example, a tendency for the few models that predict boundary layer depth to have large values of evaporation and precipitation. Controlled experiments, in which aspects of model architecture are systematically varied within individual models, may be necessary to elucidate whether and how model characteristics influence simulations.
Gaffen, Dian J.↗
All Recent Mars Landers Have Landed Downrange - Are Mars Atmosphere Models Mis-Predicting Density?
All recent Mars landers (Mars Pathfinder, the two Mars Exploration Rovers Spirit and Opportunity, and the Mars Phoenix Lander) have landed further downrange than their pre-entry predictions. Mars Pathfinder landed 27 km downrange of its prediction [1], Spirit and Opportunity landed 13.4 km and 14.9 km, respectively, downrange from their predictions [2], and Phoenix landed 21 km downrange from its prediction [3]. Reconstruction of their entries revealed a lower density profile than the best a priori atmospheric model predictions. Do these results suggest that there is a systemic issue in present Mars atmosphere models that predict a higher density than observed on landing day? Spirit Landing: The landing location for Spirit was 13.4 km downrange of the prediction as shown in Fig. 1. The navigation errors upon Mars arrival were very small [2]. As such, the entry interface conditions were not responsible for this downrange landing. Consequently, experiencing a lower density during the entry was the underlying cause. The reconstructed density profile that Spirit experienced is shown in Fig. 2, which is plotted as a fraction of the pre-entry baseline prediction that was used for all the entry, descent, and landing (EDL) design analyses. The reconstructed density is observed to be less dense throughout the descent reaching a maximum reduction of 15% at 21 km. This lower density corresponded to approximately a 1- low profile relative to the dispersions predicted. Nearly all the deceleration during the entry occurs within 10- 50 km. As such, prediction of density within this altitude band is most critical for entry flight dynamics analyses and design (e.g., aerodynamic and aerothermodynamic predictions, landing location, etc.).
Desai, Prasun N.↗
Spectral Irradiance Calibration in the Infrared: New Composite Spectra, Comparison with Model Atmospheres, and Far-Infrared Extrapolations - Part 7
We present five new absolutely calibrated continuous stellar spectra constructed as far as possible from spectral fragments observed from the ground, the Kuiper Airborne Observatory (KAO), and the IRAS Low Resolution Spectrometer. These stars-alpha Boo, gamma Dra, alpha Cet, gamma Cru, and mu UMa-augment our six, published, absolutely calibrated spectra of K and early-M giants. All spectra have a common calibration pedigree. A revised composite for alpha Boo has been constructed from higher quality spectral fragments than our previously published one. The spectrum of gamma Dra was created in direct response to the needs of instruments aboard the Infrared Space Observatory (ISO); this star's location near the north ecliptic pole renders it highly visible throughout the mission. We compare all our low-resolution composite spectra with Kurucz model atmospheres and find good agreement in shape, with the obvious exception of the SiO fundamental, still lacking in current grids of model atmospheres. The CO fundamental seems slightly too deep in these models, but this could reflect our use of generic models with solar metal abundances rather than models specific to the metallicities of the individual stars. Angular diameters derived from these spectra and models are in excellent agreement with the best observed diameters. The ratio of our adopted Sirius and Vega models is vindicated by spectral observations. We compare IRAS fluxes predicted from our cool stellar spectra with those observed and conclude that, at 12 and 25 microns, flux densities measured by IRAS should be revised downwards by about 4.1% and 5.7%, respectively, for consistency with our absolute calibration. We have provided extrapolated continuum versions of these spectra to 300 microns, in direct support of ISO (PHT and LWS instruments). These spectra are consistent with IRAS flux densities at 60 and 100 microns.
Cohen, Martin↗
Proposed Changes in the Mission Control Jacchia Atmospheric Model
The space shuttle orbit prediction program uses the Jacchia Atmospheric model. The errors in the shuttle orbit prediction are investigated by not considering variations in solar flux or geomagnetic activity.
Solis, A. J.↗
A Revised Thermosphere for the Mars Global Reference Atmospheric Model (Mars-GRAM Version 3.4)
This report describes the newly-revised model thermosphere for the Mars Global Reference Atmospheric Model (Mars-GRAM, Version 3.4). It also provides descriptions of other changes made to the program since publication of the programmer's guide for Mars-GRAM Version 3.34. The original Mars-GRAM model thermosphere was based on the global-mean model of Stewart. The revised thermosphere is based largely on parameterizations derived from output data from the three-dimensional Mars Thermospheric Global Circulation Model (MTGCM). The new thermospheric model includes revised dependence on the 10.7 cm solar flux for the global means of exospheric temperature, temperature of the base of the thermosphere, and scale height for the thermospheric temperature variations, as well as revised dependence on orbital position for global mean height of the base of the thermosphere. Other features of the new thermospheric model are: (1) realistic variations of temperature and density with latitude and time of day, (2) more realistic wind magnitudes, based on improved estimates of horizontal pressure gradients, and (3) allowance for user-input adjustments to the model values for mean exospheric temperature and for height and temperature at the base of the thermosphere. Other new features of Mars-GRAM 3.4 include: (1) allowance for user-input values of climatic adjustment factors for temperature profiles from the surface to 75 km, and (2) a revised method for computing the sub-solar longitude position in the 'ORBIT' subroutine.
Justus, C. G.↗
Simulations of X-59 Sonic Thumps and Traditional Sonic Booms Propagated Around the World for Three Atmospheric Models
Propagation simulations of sonic booms from supersonic aircraft through atmospheric data over time at fixed locations provides the opportunity to assess noise exposure statistics for different climate regions. Knowledge of climate-based differences in sonic boom noise exposure statistics is important to ensure that future civil supersonic aircraft noise certification standards are globally applicable and effective. In this presentation, simulated sonic booms from the NASA X-59 Quesst quiet supersonic aircraft and conventional supersonic aircraft were propagated through atmospheric data at 100 locations across the world using PCBoom. Noise exposure statistics are compared for propagation results from three different atmospheric databases (NOAA Global Forecast System, NOAA Climate Forecast System Version 2, and the ECMWF Reanalysis Version 5). These atmospheric models were chosen due to their global coverage, popularity, and database availability. Preliminary statistical models are fit to assess the impact of several factors including flight direction, season, ground elevation, and climate on noise exposure size and loudness. Areas with prevalence of higher noise due to their climate are identified, which could help inform future supersonic aircraft noise standards.
X-59↗
Comparison and Analysis of the Venus Global Reference Atmospheric Model (GRAM)
Comparison and analysis of the Venus Global Reference Atmospheric Model (GRAM).
Libby Cutler↗