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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

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↗
NASA NTRSDate not supplied

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↗
NASA NTRSDate not supplied

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↗
NASA NTRSDate not supplied

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↗
NASA NTRS1995

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↗
DOE OSTI2015

Modeling dust as component minerals in the Community Atmosphere Model: development of framework and impact on radiative forcing

The mineralogy of desert dust is important due to its effect on radiation, clouds and biogeochemical cycling of trace nutrients. This study presents the simulation of dust radiative forcing as a function of both mineral composition and size at the global scale, using mineral soil maps for estimating emissions. Externally mixed mineral aerosols in the bulk aerosol module in the Community Atmosphere Model version 4 (CAM4) and internally mixed mineral aerosols in the modal aerosol module in the Community Atmosphere Model version 5.1 (CAM5) embedded in the Community Earth System Model version 1.0.5 (CESM) are speciated into common mineral components in place of total dust. The simulations with mineralogy are compared to available observations of mineral atmospheric distribution and deposition along with observations of clear-sky radiative forcing efficiency. Based on these simulations, we estimate the all-sky direct radiative forcing at the top of the atmosphere as + 0.05 Wm −2 for both CAM4 and CAM5 simulations with mineralogy. We compare this to the radiative forcing from simulations of dust in release versions of CAM4 and CAM5 (+0.08 and +0.17 Wm −2 ) and of dust with optimized optical properties, wet scavenging and particle size distribution in CAM4 and CAM5, −0.05 and −0.17 Wm −2 , respectively. The ability to correctly include the mineralogy of dust in climate models is hindered by its spatial and temporal variability as well as insufficient global in situ observations, incomplete and uncertain source mineralogies and the uncertainties associated with data retrieved from remote sensing methods.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

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↗
NASA NTRS2017

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.↗
NASA NTRSDate not supplied

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↗
NASA NTRS2018

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.↗
DOE OSTI2016

Charter for the ARM Atmospheric Modeling Advisory Group

The Atmospheric Modeling Advisory Group of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility is guided by the following: 1. The group will provide feedback on the overall project plan including input on how to address priorities and trade-offs in the modeling and analysis workflow, making sure the modeling follows general best practices, and reviewing the recommendations provided to ARM for the workflow implementation. 2. The group will consist of approximately 6 members plus the PI and co-PI of the Large-Eddy Simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) pilot project. The ARM Technical Director, or his designee, serves as an ex-officio member. This size is chosen based on the ability to efficiently conduct teleconferences and to span the general needs for input to the LASSO pilot project.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

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↗
DOE OSTI2014

Detecting and Testing for Structural Error in Computer Models with Application to the Community Atmospheric Model

Bayesian calibration/inversion methods for uncertain input parameters to simulation codes have generated an increasing amount of interest in the climate community in the recent years. This approach uses multiple disparate observational datasets related to the output of the simulator of interest to yield a probabilistic constraint on the uncertain inputs (i.e. probability distribution). A major challenge in applying Bayesian calibration methods to simulation codes is related to the possible presence of a large structural error in the output fields of interest; that is, the presence of discrepancy between the observed and the simulated output that is neither explained by the uncertainty in the inputs nor the observations. We present here methods to test for and visualize structural error in an ensemble of input-perturbed simulations. The methods are based on bootstrap (resmpling) test statistics and well-known metrics to quantify the difference between two probability distributions. The proposed methods are demonstrated using selected precipitation output fields of the Community Atmospheric Model (CAM), which are compared to observations provided by the Global Precipitation Climatology Project (GPCP). The methods are found to be useful in identifying regions and seasons with a large structural error. The proposed structural error detection methodology can be used to screen multiple observational datasets of interest for structural error, making it possible to retain only the datasets with a small structural error for use in Bayesian calibration. In addition, information about the amount of structural error can be valuable to model developers.

58 GEOSCIENCES↗
NASA NTRS1973

Use of 4-D atmospheric models in the simulation of radiometric measurements

Atmospheric moisture data contained in the Global 4-D Atmospheric Models developed in previous studies were analyzed to establish regional differences. The regional values of precipitable water along latitudinal belts were compared with values derived from the corresponding atmospheric models defined in the U.S Standard Atmosphere Supplement. The effects of the differences between the 4-D Models and the Standard Atmosphere Models on radiometric computations in the infrared window and water vapor absorption band regions were evaluated using a standard computation model of radiation transfer through a cloudless atmosphere. The significance of these differences in simulation is discussed.

Chang, D. T.↗
NASA NTRS1982

Development of mathematical techniques for the assimilation of remote sensing data into atmospheric models

The problem of the assimilation of remote sensing data into mathematical models of atmospheric pollutant species was investigated. The data assimilation problem is posed in terms of the matching of spatially integrated species burden measurements to the predicted three-dimensional concentration fields from atmospheric diffusion models. General conditions were derived for the reconstructability of atmospheric concentration distributions from data typical of remote sensing applications, and a computational algorithm (filter) for the processing of remote sensing data was developed.

Seinfeld, J. H.↗
NASA NTRS1982

Development of mathematical techniques for the assimilation of remote sensing data into atmospheric models

The problem of the assimilation of remote sensing data into mathematical models of atmospheric pollutant species was investigated. The problem is posed in terms of the matching of spatially integrated species burden measurements to the predicted three dimensional concentration fields from atmospheric diffusion models. General conditions are derived for the "reconstructability' of atmospheric concentration distributions from data typical of remote sensing applications, and a computational algorithm (filter) for the processing of remote sensing data is developed.

Seinfeld, J. H.↗
DOE OSTI2021

Convection-Permitting Simulations With the E3SM Global Atmosphere Model

This paper describes the first implementation of the Δx = 3.25 km version of the Energy Exascale Earth System Model (E3SM) global atmosphere model and its behavior in a 40-day prescribed-sea-surface-temperature simulation (January 20 through February 28, 2020). This simulation was performed as part of the DYnamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains (DYAMOND) Phase 2 model intercomparison. Effective resolution is found to be ~ 6x the horizontal dynamics grid resolution despite using a coarser grid for physical parameterizations. Despite this new model being in an immature and untuned state, moving to 3.25 km grid spacing solves several long-standing problems with the E3SM model. In particular, Amazon precipitation is much more realistic, the frequency of light and heavy precipitation is improved, agreement between the simulated and observed diurnal cycle of tropical precipitation is excellent, and the vertical structure of tropical convection and coastal stratocumulus look good. In addition, the new model is able to capture the frequency and structure of important weather events (e.g., tropical cyclones, extratropical cyclones including atmospheric rivers, and cold air outbreaks). Interestingly, this model does not get rid of the erroneous southern branch of the intertropical convergence zone nor the tendency for strongest convection to occur over the Maritime Continent rather than the West Pacific, both of which are classic climate model biases. Several other problems with the simulation are identified, underscoring the fact that this model is a work in progress.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1976

The global reference atmospheric model, mod 2 (with two scale perturbation model)

The Global Reference Atmospheric Model was improved to produce more realistic simulations of vertical profiles of atmospheric parameters. A revised two scale random perturbation model using perturbation magnitudes which are adjusted to conform to constraints imposed by the perfect gas law and the hydrostatic condition is described. The two scale perturbation model produces appropriately correlated (horizontally and vertically) small scale and large scale perturbations. These stochastically simulated perturbations are representative of the magnitudes and wavelengths of perturbations produced by tides and planetary scale waves (large scale) and turbulence and gravity waves (small scale). Other new features of the model are: (1) a second order geostrophic wind relation for use at low latitudes which does not "blow up" at low latitudes as the ordinary geostrophic relation does; and (2) revised quasi-biennial amplitudes and phases and revised stationary perturbations, based on data through 1972.

Justus, C. G.↗