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Solar flare model atmospheres

Solar flare model atmospheres computed under the assumption of energetic equilibrium in the chromosphere are presented. The models use a static, one-dimensional plane-parallel geometry and are designed within a physically self-consistent coronal loop. Assumed flare heating mechanisms include collisions from a flux of nonthermal electrons and X-ray heating of the chromosphere by the corona. The heating by energetic electrons accounts explicitly for variations of the ionized fraction with depth in the atmosphere. X-ray heating of the chromosphere by the corona incorporates a flare loop geometry by approximating distant portions of the loop with a series of point sources, while treating the loop leg closest to the chromospheric footpoint in the plane-parallel approximation. Coronal flare heating leads to increased heat conduction, chromospheric evaporation and subsequent changes in coronal pressure; these effects are included self-consistently in the models. Cooling in the chromosphere is computed in detail for the important optically thick H I, Ca II and Mg II transitions using the non-local thermodynamic equilibrium (non-LTE) prescription in the program MULTI. Hydrogen ionization rates from X-ray photoionization and collisional ionization by nonthermal electrons are included explicitly in the rate equations. The models are computed in the 'impulsive' and 'equilibrium' limits, and in a set of intermediate 'evolving' states. The impulsive atmospheres have the density distribution frozen in the pre-flare configuration, while the equilibrium models assume the entire atmosphere is in hydrostatic and energetic equilibrium. The evolving atmospheres represent intermediate stages where hydrostatic equilibrium has been established in the chromosphere and corona, but the corona is not yet in energetic equilibrium with the flare heating source. Thus, for example, chromospheric evaporation is still in the process of occurring. We have computed the chromospheric radiation that results from a range of coronal heating rates, with particular emphasis on the widely observed diagnostic H(alpha). Our conclusion is that the H(alpha) fluxes and profiles actually observed in flares can only be produced under conditions of a low-pressure corona with strong beam heating. Therefore we suggest that H(alpha) in flares is produced primarily at the footprints of newly heated loops where significant evaporation has not yet occurred. As a single loop evolves in time, no matter how strong the heating rate may become, the H(alpha) flux will diminish as the corona becomes denser and hence more effective at stopping the beam. This prediction leads to several observable consequences regarding the spatial and temporal signatures of the X-ray and H(alpha) radiation during flares.

Hawley, Suzanne L.↗

Numerical coupling of aerosol emissions, dry removal, and turbulent mixing in the E3SM Atmosphere Model version 1 (EAMv1) – Part 1: Dust budget analyses and the impacts of a revised coupling scheme

Abstract. An earlier study evaluating dust life cycle in the Energy Exascale Earth System Model (E3SM) Atmosphere Model version 1 (EAMv1) has revealed that the simulated global mean dust lifetime is substantially shorter when higher vertical resolution is used, primarily due to significant strengthening of dust dry removal in source regions. This paper demonstrates that the sequential splitting of aerosol emissions, dry removal, and turbulent mixing in the model's time integration loop, especially the calculation of dry removal after surface emissions and before turbulent mixing, is the primary reason for the vertical resolution sensitivity reported in that earlier study. Based on this reasoning, we propose a revised numerical process coupling scheme that requires the least amount of code changes, in which the surface emissions are applied before turbulent mixing instead of before dry removal. The revised scheme allows newly emitted particles to be transported aloft by turbulence before being removed from the atmosphere, and hence better resembles the dust life cycle in the real world. Sensitivity experiments show that the revised process coupling substantially weakens dry removal and strengthens vertical mixing in dust source regions. It also strengthens the large-scale transport from source to non-source regions, strengthens dry removal outside the source regions, and strengthens wet removal and activation globally. In transient simulations of the years 2000–2009 conducted using 1∘ horizontal grid spacing, 72 vertical layers, and unchanged tuning parameters of emission strength, the revised process coupling leads to a 40 % increase in the global total dust burden and an increase of dust lifetime from 1.8 to 2.5 d in terms of 10-year averages. Weakened dry removal and increased mixing ratios are also seen for other aerosol species that have substantial surface emissions, although the changes in mixing ratio are considerably smaller for the submicron species than for dust and sea salt. Numerical experiments confirm that the revised coupling scheme significantly reduces the strong and non-physical sensitivities of model results to vertical resolution in the original EAMv1. This provides a motivation for adopting the revised scheme in EAM as well as for further improvements on the simple revision presented in this paper.

54 ENVIRONMENTAL SCIENCES↗

Simulating Hurricane Katrina in the Simple Cloud‐Resolving E3SM Atmosphere Model v1

Climate models are important tools for advancing understanding and prediction of tropical cyclones (TCs). Traditional global climate models, however, do not have the ability to properly simulate TC intensity due to their coarse horizontal resolution. Regional models can be run at convection‐permitting resolutions, but these models are often strongly influenced by the data used in the lateral boundary forcing, and domain choice can have a large impact on the simulation. Cloud‐resolving global climate models have demonstrated great potential for realism in TC simulations, and in this study we focus specifically on the Simple Cloud‐Resolving Energy Exascale Earth System Model (E3SM) Atmosphere Model (SCREAM) v1 configuration. We evaluate SCREAMv1 against the observational record and the Weather Research and Forecasting (WRF) model run at a convection‐permitting resolution with Hurricane Katrina as our case study. We found that both models produced realistic simulations of Hurricane Katrina. SCREAMv1 demonstrated skill in simulating TC track, size, and intensity, while the model produced an excessive amount of precipitation. In comparison, WRF more accurately simulated TC precipitation and intensity, although the TC wind extent was smaller than the observations.

54 ENVIRONMENTAL SCIENCES↗

Regionally refined test bed in E3SM atmosphere model version 1 (EAMv1) and applications for high-resolution modelling

Climate simulation with more accurate process-level representation at finer resolutions is a pressing necessity in order to provide actionable information to policy-makers regarding extreme events in a changing climate. Computational limitation is a major obstacle for building, and running high-resolution (HR, here 0.25° average grid spacing at the equator) models (HRM). A more affordable path to HRM is to use a global regionally refined model (RRM), which only simulates a portion of the globe at HR while the remaining is at low-resolution (LR, 1°). In this study, we compare the Energy Exascale Earth System Model (E3SM) atmosphere model version 1 (EAMv1) RRM with the HR mesh over the contiguous United States (CONUS) to its corresponding globally uniform LR and HR configurations, as well as to observations and reanalysis data. The RRM has a significantly reduced computational cost (roughly proportional to the HR mesh size) relative to the globally uniform HRM. Over the CONUS, we evaluate the simulation of important dynamical and physical quantities as well as various precipitation measures. Differences between the RRM and HRM over the HR region are predominantly small, demonstrating that the RRM reproduces both well- and poorly simulated behaviours of the HRM over the CONUS. Further analysis based on RRM simulations with the LR vs. HR model parameters reveals that RRM performance is greatly influenced by the different parameter choices used in the LR and HR EAMv1. This is a result of the poor scale-aware behaviour of physical parameterizations, especially for variables influencing sub-grid scale physical processes. RRM can serve as a useful framework to test physics schemes across a range of scales, leading to improved consistency in future E3SM versions. Applying nudging-to-observations techniques within the RRM framework also demonstrates significant advantages over a free-running configuration for use as a testbed, and as such represents an efficient and more robust physics testbed capability. Our conclusions provide additional confirmatory evidence that the RRM is an efficient and effective approach for HRM development and hydrologic research.

54 ENVIRONMENTAL SCIENCES↗

Venus Global Reference Atmospheric Model (Venus-GRAM) Upgrades

Introduction: The Venus Global Reference Atmospheric Model (Venus-GRAM) is one of the most widely used engineering models of Venus’ atmosphere. The Venus-GRAM upgrades are being developed by NASA Marshall Space Flight Center (MSFC) and NASA Langley Research Center (LaRC). This presentation will provide details regarding the upgrades that have been made to Venus-GRAM and the ongoing objectives, tasks, and milestones related to the GRAM upgrades funded by the NASA Science Mission Directorate (SMD). Venus-GRAM: Venus-GRAM is an engineering-oriented atmospheric model that estimates mean values and statistical variations of the atmospheric properties of Venus. Venus-GRAM provides mean values and variability for any point in the atmosphere as well as seasonal, geographic, and altitude variations. Venus-GRAM outputs include atmospheric density, temperature, pressure, winds, and chemical composition along a user-defined path. It is extensively used by the engineering community because of its ability to create realistic dispersions. GRAMs have been integrated into high fidelity flight dynamic simulations of launch, entry, descent and landing (EDL), aerobraking and aerocapture. GRAMs are currently available for Earth, Mars, Venus, Neptune, Titan, and Uranus. The lower atmosphere model in Venus-GRAM (up to 250 km) is based on the Venus International Reference Atmosphere (VIRA) [1]. The Venus-GRAM thermosphere (250 to 1000 km) is based on a MSFC-developed model [2] which assumes an isothermal temperature profile initialized using VIRA conditions at 250 km [3]. The VIRA version included in Venus-GRAM includes Pioneer Venus Orbiter and Probe data as well as Venera probe data, but it does not include a solid planet model or a high-resolution gravity model [4]. Venus-GRAM Upgrade Status: Code Modernization. Venus-GRAM has been rearchitected from Fortran to a common object-oriented C++ framework called the GRAM Suite. This new architecture creates a common GRAM library of data models and utilities. The first C++ release of the rearchitected Venus-GRAM is a straight conversion from the latest Fortran version. Model Upgrades. The focus of the model upgrade task is to improve the atmosphere models in the existing GRAMs and to establish a foundation for developing GRAMs for additional destinations. The GRAM ephemeris has been upgraded to the NASA Navigation and Ancillary Information Facility (NAIF) SPICE toolkit (version N0066). The calculation of the speed of sound has also been improved in the GRAMs. In FY20, the GRAM project established contracts to improve the model data within Venus-GRAM. Hampton University is developing an empirical global model for Venus. The University of Wisconsin is reanalyzing the Venus Express radio occultation observations and analyzing the Akatsuki thermal imaging data. Upgraded Venus-GRAM Release. GRAM Suite Version 1.3 will be released in September 2021 and will contain the rearchitected Venus-GRAM, including the common GRAM framework and planet–specific code. A User Guide and Programmer’s Manual are released with all GRAMs. Conclusions: GRAMs are frequently used toolsets and vital in assessing effects of atmospheres on interplanetary spacecraft during the program life cycle process. Releases of the GRAM Suite, upgrades of the existing planetary GRAMs, and development of new planetary GRAMs are ongoing. Venus-GRAM atmosphere model upgrades will be included in the next phase of GRAM tasks. References: [1] Kliore, A. J. et al. (1985) ASR, 5, 11, 1-304. [2] Justh, H. L. et al. (2006) AIAA/AAS Astrodynamics Specialist Conference & Exhibit, Abstract AIAA-2006-6394. [3] Guide to Reference and Standard Atmosphere Models, BSR/AIAA G-003-2010. [4] Limaye, S. S. (2012), LPSC VEXAG Townhall Meeting. Acknowledgments: The authors gratefully acknowledge support from the NASA SMD.

atmospheric models↗

Venus Global Reference Atmospheric Model

Venus Global Reference Atmospheric Model (Venus-GRAM) is an engineering-level atmospheric model developed by MSFC that is widely used for diverse mission applications including: Systems design; Performance analysis; Operations planning for aerobraking, Entry, Descent and Landing, and aerocapture; Is not a forecast model; Outputs include density, temperature, pressure, wind components, and chemical composition; Provides dispersions of thermodynamic parameters, winds, and density; Optional trajectory and auxiliary profile input files Has been used in multiple studies and proposals including NASA Engineering and Safety Center (NESC) Autonomous Aerobraking and various Discovery proposals; Released in 2005; Available at: https://software.nasa.gov/software/MFS-32314-1.

Justh, Hilary L.↗

Four-Dimensional Global Reference-Atmosphere Model

Four-Dimensional Global Reference Atmosphere Model (GRAM) computer program developed from empirical atmospheric model generating values for pressure, density, temperature, and winds, from ground to orbital altitudes. Is amalgamation of two empirical atmospheric models for low and high atmosphere with newly-developed latitude-and longitude-dependent model for middle atmosphere. UNIVAC version written in UNIVAC FORTRAN. DEC VAX version of GRAM written in FORTRAN 77. Applications include simulation of reentry trajectories of external tanks, studies of global circulation and diffusion and generation of plots or data for comparison.

Johnson, Dale↗

The NASA MSFC Earth Global Reference Atmospheric Model-2007 Version

Reference or standard atmospheric models have long been used for design and mission planning of various aerospace systems. The NASA/Marshall Space Flight Center (MSFC) Global Reference Atmospheric Model (GRAM) was developed in response to the need for a design reference atmosphere that provides complete global geographical variability, and complete altitude coverage (surface to orbital altitudes) as well as complete seasonal and monthly variability of the thermodynamic variables and wind components. A unique feature of GRAM is that, addition to providing the geographical, height, and monthly variation of the mean atmospheric state, it includes the ability to simulate spatial and temporal perturbations in these atmospheric parameters (e.g. fluctuations due to turbulence and other atmospheric perturbation phenomena). A summary comparing GRAM features to characteristics and features of other reference or standard atmospheric models, can be found Guide to Reference and Standard Atmosphere Models. The original GRAM has undergone a series of improvements over the years with recent additions and changes. The software program is called Earth-GRAM2007 to distinguish it from similar programs for other bodies (e.g. Mars, Venus, Neptune, and Titan). However, in order to make this Technical Memorandum (TM) more readable, the software will be referred to simply as GRAM07 or GRAM unless additional clarity is needed. Section 1 provides an overview of the basic features of GRAM07 including the newly added features. Section 2 provides a more detailed description of GRAM07 and how the model output generated. Section 3 presents sample results. Appendices A and B describe the Global Upper Air Climatic Atlas (GUACA) data and the Global Gridded Air Statistics (GGUAS) database. Appendix C provides instructions for compiling and running GRAM07. Appendix D gives a description of the required NAMELIST format input. Appendix E gives sample output. Appendix F provides a list of available parameters to enable the user to generate special output. Appendix G gives an example and guidance on incorporating GRAM07 as a subroutine in other programs such as trajectory codes or orbital propagation routines.

Leslie, F.W.↗

Modeling atmospheric data and identifying dynamics Temporal data-driven modeling of air pollutants

Atmospheric modelling has recently experienced a surge with the advent of deep learning. Most of these models, however, predict concentrations of pollutants following a data-driven approach in which the physical laws that govern their behaviors and relationships remain hidden. Furthermore, with the aid of real-world air quality data collected hourly in different stations throughout Madrid, we present a case study using a series of data-driven techniques with the following goals: (1) Find systems of ordinary differential equations that model the concentration of pollutants and their changes over time; (2) assess the performance and limitations of our model using stability analysis; (3) reconstruct the time series of chemical pollutants not measured in certain stations using delay coordinate embedding results.

54 ENVIRONMENTAL SCIENCES↗

Global Reference Atmospheric Model (GRAM) Advancements and Additions

Introduction:The Global Reference Atmospheric Model (GRAM) is one of the most widely used engineering models of the atmosphere. GRAM development and maintenance has been led by NASA Marshall Space Flight Center (MSFC). The NASA Science Mission Directorate (SMD) has provided funding support to upgrade the GRAMs since Fiscal Year 2018. NASA Langley Research Center has been working with MSFC on the upgrades.This presentation will provide details regarding the upgrades that have been made to the existing GRAMs, the development of new GRAMs, as well as the ongoing objectives, tasks, and milestones re-lated to the GRAM upgrades funded by NASA SMD. GRAM: The GRAMs are engineering-oriented atmospheric models that estimate mean values and statistical variations of the atmospheric properties for numerous planetary destinations.They provide mean values and variability for any point in the atmosphere as well as seasonal, geographic, and altitude variations. GRAM outputs include atmospheric density, temperature, pressure, winds, and chemical composition along a user-defined path.Theyhave been widely used by the engineering community because of their ability to create realistic dispersions. GRAMs have been integrated into high fidelity flight dynamic simulations of launch, entry, descent and landing (EDL), aerobraking and aerocapture. MSFC has been developing and updating GRAMs since 1974; GRAMs are currently available for Earth, Mars, Venus, Neptune, and Titan. GRAM Upgrade Status: Code Moderization.The planetary GRAMs are being rearchitected from Fortran to a common object-ori-entedC++ framework called the GRAM Suite. This new architecture creates a common GRAM library of data models and utilities. The first C++ releases of the existing planetary GRAMs (Mars, Venus, Neptune, and Titan-GRAM) in the GRAM Suite are straight conversions from the latest Fortran version. Model Upgrades.The focus of the model upgrade task is to improve the atmosphere models in the existing GRAMs and to establish a foundation for developing GRAMs for additional destinations. The GRAM ephemerishas been upgraded to the NASA Navigation and Ancillary Information Facility (NAIF) SPICE toolkit (version N0066). The calculation of the speed of sound has also been improved in the GRAMs. The GRAM team has received updated Mars General Circulation Model (MGCM) datasets from NASA Ames Research Center. Mars Global Ionosphere-Thermosphere Model (M-GITM) data is being obtained toreplace the Mars Thermospheric General Circulation Model (MTGCM) data in legacy Mars-GRAM. M-GITM and updated MGCM data will be incorporated into a future GRAM Suite release.Twoprojects that will improve the atmospheric model data in the GRAMs have been funded by the GRAM team since Fiscal Year 2020. Sanjay Limaye and Patrick Fry at the University of Wisconsin are reanalyzing the Venus Express radio occultation observations and analyzing the Akatsukiradio occultation observations.This will lead tothe calculation of number density, temperature, and pressure profiles for the 40-90 km altitude range. Kunio Sayanagi, Justin Garland, and Ryan McCabeat Hampton University are developing empirical global models for Venus,Jupiter, Saturn, Uranus, Neptune, and Titan that incorporates the latest data available for each of these planetary destinations. Upgraded GRAM Releases. GRAM Suite Version 1.0 was released in May 2020 and contains the rearchitected Neptune-GRAM, including the common GRAM framework and planet–specific code. GRAM Suite Version 1.1 was released in September 2020 and addedthe rearchitected Titan-GRAM to the GRAM Suite. A User Guide and Programmer’s Manualarereleased with all GRAMs. The rearchitected Mars and Venus-GRAMs will be released in upcomingversions of the GRAM Suite. New GRAM Releases. New GRAMs have been de-veloped for Uranus and Jupiter. Uranus-GRAM is based on an individual profile generated by Gary Allen (ARC) from Voyager 2 occultation data and will be released in GRAM Suite Version 1.2. Jupiter-GRAM is based on individual profile produced from Al Seiff’s Ju-piter model[1].Jupiter-GRAM will be released in GRAM Suite Version 1.3. Saturn-GRAM is currently under development and will be released in a future version of the GRAM Suite. Conclusions: GRAMs are vital and frequently used toolsets. Releases of the GRAM Suite, upgrades of the existing planetary GRAMs, and development of new planetary GRAMs are ongoing. NASA SMD funding has been essential to addressing current limitations and accomplishing GRAM developmental goals. Continua-tion ofSMD fundingwill ensure the development, up-grades, and maintenance of the GRAMs. References: [1] Seiff, A., et al. (1998) JGR, 103, 22,857-22,889. Acknowledgments: The authors gratefully acknowledge support from the NASA SMD

atmospheric models↗

Assessing Huygens Probe Entry, Descent, and Landing at Titan Simulation using Dragonfly Atmosphere Model

Dragonfly is a New Frontiers Program mission that will deliver a rotorcraft to Saturn's moon, Titan. This mission follows Huygens as the previous mission that successfully landed a vehicle on Titan. A flight mechanics simulation of Dragonfly's Entry, Descent, and Landing sequence has been developed using the Program to Optimize Simulated Trajectories II. The simulation incorporates several subsystem models, including aerodynamics, gravity, and mass properties, to fully capture the multi-body six degree of freedom dynamics. Among all the subsystem models that inform the Entry, Descent, and Landing dynamics, the atmosphere model of Titan is a critical component. The atmosphere model characterizes the density, temperature, pressure, and winds that the entry vehicle experiences during the descent. This impacts several aspects of the descent such as the peak heating, aerodynamics, parachute release conditions, the dynamics of the vehicle and parachutes, and the landing ellipse. In the course of developing Dragonfly, an updated model of the Titan atmosphere has been created corresponding to Dragonfly's arrival in the mid-2030s, approximately one Titan year after the Huygens mission successfully landed a probe on Titan. This work leverages previous work done to investigate Huygens EDL sequence to assess the atmosphere model developed for Dragonfly. This is done by utilizing the updated Titan atmosphere model, the Dragonfly atmosphere model, within the Huygens POST2-based flight simulation with the goal of characterizing the differences between the atmospheric models and assessing how the Dragonfly atmosphere model impacts Huygens entry dynamics.

Huygens↗

Assessing Huygens Probe Entry, Descent, and Landing at Titan Simulation using Dragonfly Atmosphere Model

Dragonfly is a New Frontiers Program mission that will deliver a rotorcraft to Saturn's moon, Titan. This mission follows Huygens as the previous mission that successfully landed a vehicle on Titan. A flight mechanics simulation of Dragonfly's Entry, Descent, and Landing sequence has been developed using the Program to Optimize Simulated Trajectories II. The simulation incorporates several subsystem models, including aerodynamics, gravity, and mass properties, to fully capture the multi-body six degree of freedom dynamics. Among all the subsystem models that inform the Entry, Descent, and Landing dynamics, the atmosphere model of Titan is a critical component. The atmosphere model characterizes the density, temperature, pressure, and winds that the entry vehicle experiences during the descent. This impacts several aspects of the descent such as the peak heating, aerodynamics, parachute release conditions, the dynamics of the vehicle and parachutes, and the landing ellipse. In the course of developing Dragonfly, an updated model of the Titan atmosphere has been created corresponding to Dragonfly's arrival in the mid-2030s, approximately one Titan year after the Huygens mission successfully landed a probe on Titan. This work leverages previous work done to investigate Huygens EDL sequence to assess the atmosphere model developed for Dragonfly. This is done by utilizing the updated Titan atmosphere model, the Dragonfly atmosphere model, within the Huygens POST2-based flight simulation with the goal of characterizing the differences between the atmospheric models and assessing how the Dragonfly atmosphere model impacts Huygens entry dynamics.

Entry Descent Landing↗

Model atmospheres for M (sub)dwarf stars. 1: The base model grid

We have calculated a grid of more than 700 model atmospheres valid for a wide range of parameters encompassing the coolest known M dwarfs, M subdwarfs, and brown dwarf candidates: 1500 less than or equal to T(sub eff) less than or equal to 4000 K, 3.5 less than or equal to log g less than or equal to 5.5, and -4.0 less than or equal to (M/H) less than or equal to +0.5. Our equation of state includes 105 molecules and up to 27 ionization stages of 39 elements. In the calculations of the base grid of model atmospheres presented here, we include over 300 molecular bands of four molecules (TiO, VO, CaH, FeH) in the JOLA approximation, the water opacity of Ludwig (1971), collision-induced opacities, b-f and f-f atomic processes, as well as about 2 million spectral lines selected from a list with more than 42 million atomic and 24 million molecular (H2, CH, NH, OH, MgH, SiH, C2, CN, CO, SiO) lines. High-resolution synthetic spectra are obtained using an opacity sampling method. The model atmospheres and spectra are calculated with the generalized stellar atmosphere code PHOENIX, assuming LTE, plane-parallel geometry, energy (radiative plus convective) conservation, and hydrostatic equilibrium. The model spectra give close agreement with observations of M dwarfs across a wide spectral range from the blue to the near-IR, with one notable exception: the fit to the water bands. We discuss several practical applications of our model grid, e.g., broadband colors derived from the synthetic spectra. In light of current efforts to identify genuine brown dwarfs, we also show how low-resolution spectra of cool dwarfs vary with surface gravity, and how the high-regulation line profile of the Li I resonance doublet depends on the Li abundance.

Allard, France↗

Upgrades to the Mars Global Reference Atmospheric Model (Mars-GRAM)

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 reference models of planetary atmospheres are the Global Reference Atmospheric Models (GRAMs). The NASA Science Mission Directorate (SMD) has provided funding support to upgrade the GRAMs since Fiscal Year 2018. The GRAM upgrades are being developed by NASA Marshall Space Flight Center and NASA Langley Research Center. This poster provides details regarding recent MarsGRAM upgrades.

atmospheric models↗

Atmospheric Modeling Using Accelerometer Data During Mars Atmosphere and Volatile Evolution (MAVEN) Flight Operations

The Mars Atmosphere and Volatile EvolutioN (MAVEN) spacecraft is a NASA orbiter designed to explore the Mars upper atmosphere, typically from 140 to 160 km altitude. In addition to the nominal science mission, MAVEN has performed several Deep Dip campaigns in which the orbit's closest point of approach, also called periapsis, was lowered to an altitude range of 115 to 135 km. MAVEN accelerometer data were used during mission operations to estimate atmospheric parameters such as density, scale height, along-track gradients, and wave structures. Density and scale height estimates were compared against those obtained from the Mars Global Reference Atmospheric Model and used to aid the MAVEN navigation team in planning maneuvers to raise and lower periapsis during Deep Dip operations. This paper describes the processes used to reconstruct atmosphere parameters from accelerometers data and presents the results of their comparison to model and navigation-derived values.

Tolson, Robert H.↗

Venus 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 Venus’ atmosphere is the Venus Global Reference Atmospheric Model (Venus-GRAM).The Venus-GRAM upgrades are being developed by NASA Marshall Space Flight Center and NASA Langley Research Center.

atmospheric models↗

Planned Improvements to the Venus Global Reference Atmospheric Model

The Venus Global Reference Atmospheric Model (Venus-GRAM) is an engineering-level atmospheric model applicable for engineering design analyses, mission planning, and operational decision making. Missions to Venus have generated a wealth of atmospheric data, however, Venus-GRAM has not been updated since its development and release in 2005. GRAM upgrades and maintenance have depended on inconsistent and waning project-specific support. The NASA Science Mission Directorate (SMD) has agreed to provide funding support in Fiscal Year 2018 and 2019 to upgrade the GRAMs. This presentation will provide an overview of Venus-GRAM and the objectives, tasks, and milestones related to the GRAM upgrades.

Justh, H. L.↗

Performance and Accuracy Implications of Parallel Split Physics-Dynamics Coupling in the Energy Exascale Earth System Atmosphere Model

Simultaneous calculation of atmospheric processes is faster than calculating processes one at a time. This type of parallelism is beneficial or perhaps even necessary to provide good performance on modern supercomputers, which achieve faster performance through increased processor count rather than improved clock speed. The scalability of the Energy Exascale Earth System Model (E3SM) Atmosphere Model (EAM) is limited by the fluid dynamics which scales up to the number of mesh cells in the global mesh. In contrast, the suite of physics parameterizations in EAM is scalable up to the total number of physics columns, which is an order of magnitude greater than the number of mesh cells. A proposed solution to unlocking the greater potential performance from the physics suite is to solve the physics and dynamics in parallel. This work represents a first attempt at parallel splitting of the grid-scale fluid dynamics model and the subgrid-scale physics parameterizations in a global atmosphere model. We will demonstrate that switching to parallel physics-dynamics coupling extends the scalability of the EAM to up to 3 times the previous peak scalability limit and is up to 20% faster than the sequentially split coupling at the highest core counts and the same time step. Decadal simulations of both coupling approaches show very little impact to the model climate. This improved performance does not come without drawbacks, however. Parallel splitting requires a shorter time step and other modifications which largely offset performance gains. A mass fixer is required for conservation. Techniques for mitigating these issues are also discussed.

97 MATHEMATICS AND COMPUTING↗