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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Testing model atmospheres for young very-low-mass stars and brown dwarfs in the infrared: Evidence for significantly underestimated dust opacities

We test state-of-the-art model atmospheres for young very-low-mass stars and brown dwarfs in the infrared, by comparing the predicted synthetic photometry over 1.2–24 μm to the observed photometry of M-type spectral templates in star-forming regions. We find that (1) in both early and late young M types, the model atmospheres imply effective temperatures (T{sub eff}) several hundred Kelvin lower than predicted by the standard pre-main sequence (PMS) spectral type–T{sub eff} conversion scale (based on theoretical evolutionary models). It is only in the mid-M types that the two temperature estimates agree. (2) The T{sub eff} discrepancy in the early M types (corresponding to stellar masses ≳0.4 M{sub ⊙} at ages of a few Myr) probably arises from remaining uncertainties in the treatment of atmospheric convection within the atmospheric models, whereas in the late M types it is likely due to an underestimation of dust opacity. (3) The empirical and model-atmosphere J-band bolometric corrections are both roughly flat, and similar to each other, over the M-type T{sub eff} range. Thus the model atmospheres yield reasonably accurate bolometric luminosities (L{sub bol}), but lead to underestimations of mass and age relative to evolutionary expectations (especially in the late M types) due to lower T{sub eff}. We demonstrate this for a large sample of young Cha I and Taurus sources. (4) The trends in the atmospheric model J−K{sub s} colors, and their deviations from the data, are similar at PMS and main sequence ages, suggesting that the model dust opacity errors we postulate here for young ages also apply at field ages.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2018

New Efforts to Update NASA's Global Reference Atmospheric Models (GRAM)

NASA is at the forefront of planetary exploration. The inability to test planetary spacecraft in the flight environment prior to a mission requires engineers to rely on ground-based testing and models of the vehicle and expected environments. One of the most widely used engineering models of the atmosphere for many NASA projects is the Global Reference Atmospheric Model (GRAM) developed by the NASA Marshall Space Flight Center (MSFC). Over the past decade GRAM upgrades and maintenance have depended on inconsistent and waning project-specific support. Recently, the NASA Science Mission Directorate agreed to provide funding support in Fiscal Year 2018 and 2019 to upgrade the GRAMs. This poster summarizes the objectives, tasks and milestones of this effort.

Justh, Hilary↗
NASA NTRS2018

New Efforts to Update NASA's Global Reference Atmospheric Models (GRAM)

NASA is at the forefront of planetary exploration. The inability to test planetary space-craft in the flight environment prior to a mission requires engineers to rely on ground-based testing and models of the vehicle and expected environments. One of the most widely used engineering models of the atmosphere for many NASA projects is the Global Reference Atmospheric Model (GRAM) developed by the NASA Marshall Space Flight Center (MSFC). Over the past decade GRAM upgrades and maintenance have depended on inconsistent and waning project-specific support. Recently, the NASA Science Mission Directorate (SMD) has agreed to provide funding support in Fiscal Year 2018 and 2019 to upgrade the GRAMs.

Justh, H. L.↗
NASA NTRS2018

New Efforts to Update NASA's Global Reference Atmospheric Models (GRAM)

NASA is at the forefront of planetary exploration. The inability to test planetary spacecraft in the flight environment prior to a mission requires engineers to rely on ground-based testing and models of the vehicle and expected environments. One of the most widely used engineering models of the atmosphere for many NASA projects is the Global Reference Atmospheric Model (GRAM) developed by the NASA Marshall Space Flight Center (MSFC). Over the past decade GRAM upgrades and maintenance have depended on inconsistent and waning project-specific support. Recently, the NASA Science Mission Directorate agreed to provide funding support in Fiscal Year 2018 and 2019 to upgrade the GRAMs. This poster summarizes the objectives, tasks and milestones of this effort.

Dwyer Cianciolo, Alicia↗
NASA NTRS2020

Status of Outer Planet Global Reference Atmospheric Model (GRAM) Upgrades

The inability to test planetary spacecraft in the flight environment prior to a mission requires engineers to rely on ground-based testing and models of the vehicle and expected environments. One of the most widely used engineering models of the atmosphere is the Global Reference Atmospheric Model (GRAM) developed and maintained by the NASA Marshall Space Flight Center (MSFC). The NASA Science Mission Directorate (SMD) has provided funding support to upgrade the GRAMs.

Justh, H. L.↗
DOE OSTI2025

Applying Corrective Machine Learning in the E3SM Atmosphere Model in C++ (EAMxx)

The Simplified Cloud-Resolving E3SM Atmosphere Model (SCREAM) is the newest addition to the family of Earth System Models capable of explicitly resolving convective systems. SCREAM is a kilometer-scale configuration of the advanced E3SM Atmosphere Model (EAMxx), designed for heterogeneous systems. While the enhanced accuracy of kilometer-scale modeling offers significant benefits, it comes with a substantial computational cost, limiting feasible simulation durations to only a few years, even on the fastest supercomputers. Machine learning presents an opportunity for scientists to achieve the high accuracy of storm-resolving models at a significantly reduced cost. Building on the previous success of applying corrective machine learning (ML) to the FV3 model, this study explores the effects of implementing corrective ML in EAMxx-SCREAM. We also address the computational challenges of integrating the corrective ML, which is written in Python, with the C++/Kokkos EAMxx driver, as well as the potential pitfalls of generalizing an approach that was effective with one atmosphere model to another.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2024

Mars Global Reference Atmospheric Model (Mars-GRAM) 2024: User Guide

This Technical Memorandum (TM) presents the Mars Global Reference Atmospheric Model (Mars-GRAM) 2024 and its updated features. Mars-GRAM is an engineering-oriented atmospheric model that estimates mean values and statistical variations of atmospheric properties for Mars. This TM summarizes the atmospheric data model in Mars-GRAM and provides a guide for the user to obtain, set up, and run the code in various configurations. Additional details regarding the Mars-GRAM input and output files and how to interpret Mars-GRAM results are also provided.

atmospheric density↗
NASA NTRS1992

Meridionally propagating interannual-to-interdecadal variability in a linear ocean-atmosphere model

Meridional oscillation modes in a global, primitive-equation coupled ocean-atmosphere model have been analyzed in order to determine whether they contain such meridionally propagating modes as surface-pressure perturbations with years-to-decades oscillation periods. A two-layer global ocean model and a two-level global atmosphere model were then formulated. For realistic parameter values and basic states, meridional modes oscillating at periods of several years to several decades are noted to be present in the coupled ocean-atmosphere model; the oscillation periods, travel times, and meridional structures of surface pressure perturbations in one of the modes are found to be comparable to the corresponding characteristics of observed sea-level pressure perturbations.

Mehta, Vikram M.↗
NASA NTRS1999

Model Atmospheres for Novae in Outburst: Summary of Research

This paper presents a final report and summary of research on Model Atmospheres for Novae in Outburst. Some of the topics include: 1) Detailed NLTE (non-local thermodynamic equilibrium) Model Atmospheres for Novae during Outburst: II. Modeling optical and ultraviolet observations of Nova LMC 1988 #1; 2) A Non-LTE Line-Blanketed Stellar Atmosphere Model of the Early B Giant epsilon CMa; 3) Spectroscopy of Low Metallicity Stellar atmospheres; 4) Infrared Colors at the Stellar/Substellar Boundary; 5) On the abundance of Lithium in T CrB; 6) Numerical Solution of the Expanding Stellar Atmosphere Problem; and 7) The NextGen Model Atmosphere grid for 3000 less than or equal to T (sub eff) less than or equal to 10000K.

Hauschildt, Peter H.↗
NASA NTRS2021

Jupiter Global Reference Atmospheric Model (Jupiter-GRAM): User Guide

This Technical Memorandum (TM) presents the Jupiter Global Reference Atmospheric Model (Jupiter-GRAM) and the updated features of the GRAMs. Jupiter-GRAM is an engineering-oriented atmospheric model that estimates mean values of atmospheric properties for Jupiter. This TM summarizes the atmospheric data model in Jupiter-GRAM and provides a guide for the user to obtain, set up, and run the code in various configurations. Additional details regarding the Jupiter-GRAM input and output files and how to interpret Jupiter-GRAM results are also provided.

atmospheric models↗
DOE OSTI2020

Improving Time Step Convergence in an Atmosphere Model With Simplified Physics: The Impacts of Closure Assumption and Process Coupling

Convergence testing is a common practice in the development of dynamical cores of atmospheric models but is not as often exercised for the parameterization of sub-grid physics. An earlier study revealed that the stratiform cloud parameterizations in several predecessors of the Energy Exascale Earth System Model (E3SM) showed strong time-step sensitivity and slower-than-expected convergence when the model's time step was systematically refined. In this work, a simplified atmosphere model is configured that consists of the spectral-element dynamical core of the E3SM atmosphere model coupled with a large-scale condensation parameterization based on commonly used assumptions. This simplified model also resembles E3SM and its predecessors in the numerical implementation of process coupling and shows poor time-step convergence in short ensemble tests. We present a formal error analysis to reveal the expected time-step convergence rate and the conditions for obtaining such convergence. Numerical experiments are conducted to investigate the root causes of convergence problems. We show that revisions in the process coupling and closure assumption help to improve convergence in short simulations using the simplified model; the same revisions applied to a full atmosphere model lead to significant changes in the simulated long-term climate. This work demonstrates that causes of convergence issues in atmospheric simulations can be understood by combining analyses from physical and mathematical perspectives. Addressing convergence issues can help to obtain a discrete model that is more consistent with the intended representation of the physical phenomena.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1993

Development and analysis of prognostic equations for mesoscale kinetic energy and mesoscale (subgrid scale) fluxes for large-scale atmospheric models

Generated by landscape discontinuities (e.g., sea breezes) mesoscale circulation processes are not represented in large-scale atmospheric models (e.g., general circulation models), which have an inappropiate grid-scale resolution. With the assumption that atmospheric variables can be separated into large scale, mesoscale, and turbulent scale, a set of prognostic equations applicable in large-scale atmospheric models for momentum, temperature, moisture, and any other gaseous or aerosol material, which includes both mesoscale and turbulent fluxes is developed. Prognostic equations are also developed for these mesoscale fluxes, which indicate a closure problem and, therefore, require a parameterization. For this purpose, the mean mesoscale kinetic energy (MKE) per unit of mass is used, defined as E-tilde = 0.5 (the mean value of u'(sub i exp 2), where u'(sub i) represents the three Cartesian components of a mesoscale circulation (the angle bracket symbol is the grid-scale, horizontal averaging operator in the large-scale model, and a tilde indicates a corresponding large-scale mean value). A prognostic equation is developed for E-tilde, and an analysis of the different terms of this equation indicates that the mesoscale vertical heat flux, the mesoscale pressure correlation, and the interaction between turbulence and mesoscale perturbations are the major terms that affect the time tendency of E-tilde. A-state-of-the-art mesoscale atmospheric model is used to investigate the relationship between MKE, landscape discontinuities (as characterized by the spatial distribution of heat fluxes at the earth's surface), and mesoscale sensible and latent heat fluxes in the atmosphere. MKE is compared with turbulence kinetic energy to illustrate the importance of mesoscale processes as compared to turbulent processes. This analysis emphasizes the potential use of MKE to bridge between landscape discontinuities and mesoscale fluxes and, therefore, to parameterize mesoscale fluxes generated by such subgrid-scale landscape discontinuities in large-scale atmospheric models.

Avissar, Roni↗
NASA NTRS2021

Earth Global Reference Atmospheric Model (Earth-GRAM): User Guide

This Technical Memorandum (TM) presents the Earth Global Reference Atmospheric Model (Earth-GRAM) and the updated features of the GRAMs. Earth-GRAM is an engineering-oriented atmospheric model that estimates mean values and statistical variations of atmospheric properties for Earth. This TM summarizes the atmospheric data model in Earth-GRAM and provides a guide for the user to obtain, set up, and run the code in various configurations. Additional details regarding the Earth-GRAM input and output files and how to interpret Earth-GRAM results are also provided.

Atmospheric Models↗
NASA NTRS2021

Venus Global Reference Atmospheric Model (Venus-GRAM): User Guide

This Technical Memorandum (TM) presents the Venus Global Reference Atmospheric Model (Venus-GRAM) and the updated features of the GRAMs. Venus-GRAM is an engineering-oriented atmospheric model that estimates mean values and statistical variations of atmospheric properties for Venus. This TM summarizes the atmospheric data model in Venus-GRAM and provides a guide for the user to obtain, set up, and run the code in various configurations. Additional details regarding the Venus-GRAM input and output files and how to interpret Venus-GRAM results are also provided.

atmospheric models↗
NASA NTRS2021

Mars Global Reference Atmospheric Model (Mars-GRAM): User Guide

This Technical Memorandum (TM) presents the Mars Global Reference Atmospheric Model (Mars-GRAM) and the updated features of the GRAMs. Mars-GRAM is an engineering-oriented atmospheric model that estimates mean values and statistical variations of atmospheric properties for Mars. This TM summarizes the atmospheric data model in Mars-GRAM and provides a guide for the user to obtain, set up, and run the code in various configurations. Additional details regarding the Mars-GRAM input and output files and how to interpret Mars-GRAM results are also provided.

atmospheric models↗
DOE OSTI2023

Region and cloud regime dependence of parametric sensitivity in E3SM atmosphere model

Abstract The Department of Energy (DOE)’s Energy Exascale Earth System Model (E3SM), including its atmosphere model (EAM), has many relatively new features. In a previous study we conducted a systematic parametric sensitivity analysis for EAM based on short, perturbed parameter ensemble (PPE) simulations, mainly focusing on global mean climate features and metrics. While parameter values in global climate models are generally invariant in space and time, model response to parameters perturbation may vary by regions and climate regimes, which motivates the need to better understand the EAM model behaviors and physics at regional scale and process level. In this study, using the same set of PPE simulations and a similar sensitivity analysis framework, we identify parameters that cause largest sensitivities over different regions and compare model responses in fast atmospheric processes to the parameters across different cloud regimes for several important cloud-related fidelity metrics. We find that cloud forcing has opposite response to some parameters over mid-latitude vs. tropical land. We also analyze how the parametric sensitivity varies as stratocumulus transitions to shallow convection and to deep convection over ocean. Low cloud forcing and shortwave cloud forcing in the subtropical eastern Pacific are most sensitive to the parameters controlling the width of the probability density function (PDF) of the subgrid vertical velocity ( w’ ) ( gamma ) and the damping of the w’ skewness ( c8 ) near the coast but become more sensitive to the parameter affecting the damping of the w’ variance ( c1 ) further offshore. Detailed interpretation of the spatial dependence of parametric sensitivity is provided. We also investigate how the parametric sensitivity evolves with prediction duration. This study improves our process-level understanding of cloud physics and parameterization and provides insights for developing more advanced regime-aware parameterization schemes in global climate model.

54 ENVIRONMENTAL SCIENCES↗