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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Characterizing Young Giant Planets with the Gemini Planet Imager: An Iterative Approach to Planet Characterization

After discovery, the first task of exoplanet science is characterization. However experience has shown that the limited spectral range and resolution of most directly imaged exoplanet data requires an iterative approach to spectral modeling. Simple, brown dwarf-like models, must first be tested to ascertain if they are both adequate to reproduce the available data and consistent with additional constraints, including the age of the system and available limits on the planet's mass and luminosity, if any. When agreement is lacking, progressively more complex solutions must be considered, including non-solar composition, partial cloudiness, and disequilibrium chemistry. Such additional complexity must be balanced against an understanding of the limitations of the atmospheric models themselves. For example while great strides have been made in improving the opacities of important molecules, particularly NH3 and CH4, at high temperatures, much more work is needed to understand the opacity of atomic Na and K. The highly pressure broadened fundamental band of Na and K in the optical stretches into the near-infrared, strongly influencing the spectral shape of Y and J spectral bands. Discerning gravity and atmospheric composition is difficult, if not impossible, without both good atomic opacities as well as an excellent understanding of the relevant atmospheric chemistry. I will present examples of the iterative process of directly imaged exoplanet characterization as applied to both known and potentially newly discovered exoplanets with a focus on constraints provided by GPI spectra. If a new GPI planet is lacking, as a case study I will discuss HR 8799 c and d will explain why some solutions, such as spatially inhomogeneous cloudiness, introduce their own additional layers of complexity. If spectra of new planets from GPI are available I will explain the modeling process in the context of understanding these new worlds.

exoplanets↗
NASA NTRS2017

Ground-Based High Spectral Resolution Lidar Observation of Aerosol Vertical Distribution in the Summertime Southeast United States

As part of the Southeast United States-based Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS), and collinear with part of the Southeast Atmosphere Study, the University of Wisconsin High Spectral Resolution Lidar system was deployed to the University of Alabama from 19 June to 4 November 2013. With a collocated Aerosol Robotic Network (AERONET) sun photometer, a nearby Chemical Speciation Network (PM2.5) measurement station, and near daily ozonesonde releases for the August-September SEAC4RS campaign, the site allowed the regions first comprehensive diurnal monitoring of aerosol particle vertical structure. A 532nm lidar ratio of 55 sr provided good closure between aerosol backscatter and AERONET (aerosol optical thickness, AOT). A principle component analysis was performed to identify key modes of variability in aerosol backscatter. ''Fair weather'' days exhibited classic planetary boundary layer structure of a mixed layer accounting for approx. 50% of AOT and an entrainment zone providing another 25%. An additional 5-15% of variance is gained from the lower free troposphere from either convective detrainment or frequent intrusions of western United States biomass burning smoke. Generally, aerosol particles were contained below the 0 C level, a common level of stability in convective regimes. However, occasional strong injections of smoke to the upper troposphere were also observed, accounting for the remaining 10-15% variability in AOT. Examples of these common modes of variability in frontal and convective regimes are presented, demonstrating why AOT often has only a weak relationship to surface PM2.5 concentration.

HSRL↗
NASA NTRS2015

Detecting and Constraining N2 Abundances in Planetary Atmospheres Using Collisional Pairs

Characterizing the bulk atmosphere of a terrestrial planet is important for determining surface pressure and potential habitability. Molecular nitrogen (N2) constitutes the largest fraction of Earth's atmosphere and is likely to be a major constituent of many terrestrial exoplanet atmospheres. Due to its lack of significant absorption features, N2 is extremely difficult to remotely detect. However, N2 produces an N2-N2 collisional pair, (N2)2, which is spectrally active. Here we report the detection of (N2)2 in Earth's disk-integrated spectrum. By comparing spectra from NASA's EPOXI mission to synthetic spectra from the NASA Astrobiology Institute's Virtual Planetary Laboratory three-dimensional spectral Earth model, we find that (N2)2 absorption produces a ~35% decrease in flux at 4.15 μm. Quantifying N2 could provide a means of determining bulk atmospheric composition for terrestrial exoplanets and could rule out abiotic O2 generation, which is possible in rarefied atmospheres. To explore the potential effects of (N2)2 in exoplanet spectra, we used radiative transfer models to generate synthetic emission and transit transmission spectra of self-consistent N2-CO2-H2O atmospheres, and analytic N2-H2 and N2-H2-CO2 atmospheres. We show that (N2)2 absorption in the wings of the 4.3 μm CO2 band is strongly dependent on N2 partial pressures above 0.5 bar and can significantly widen this band in thick N2 atmospheres. The (N2)2 transit transmission signal is up to 10 ppm for an Earth-size planet with an N2-dominated atmosphere orbiting within the habitable zone of an M5V star and could be substantially larger for planets with significant H2 mixing ratios.

Schwieterman, Edward W.↗
NASA NTRS2009

Uncertain Representations of Sub-Grid Pollutant Transport in Chemistry-Transport Models and Impacts on Long-Range Transport and Global Composition

Sub-grid transport, by convection and turbulence, is known to play an important role in lofting pollutants from their source regions. Consequently, the long-range transport and climatology of simulated atmospheric composition are impacted. This study uses the Goddard Earth Observing System, Version 5 (GEOS-5) atmospheric model to study pollutant transport. The baseline model uses a Relaxed Arakawa-Schubert (RAS) scheme that represents convection through a sequence of linearly entraining cloud plumes characterized by unique detrainment levels. Thermodynamics, moisture and trace gases are transported in the same manner. Various approximate forms of trace-gas transport are implemented, in which the box-averaged cloud mass fluxes from RAS are used with different numerical approaches. Substantial impacts on forward-model simulations of CO (using a linearized chemistry) are evident. In particular, some aspects of simulations using a diffusive form of sub-grid transport bear more resemblance to space-biased CO observations than do the baseline simulations with RAS transport. Implications for transport in the real atmosphere will be discussed. Another issue of importance is that many adjoint/inversion computations use simplified representations of sub-grid transport that may be inconsistent with the forward models: implications will be discussed. Finally, simulations using a complex chemistry model in GEOS-5 (in place of the linearized CO model) are underway: noteworthy results from this simulation will be mentioned.

Pawson, Steven↗
NASA NTRS1974

The atmosphere of Titan

Review of the currently available knowledge on Titan's atmosphere, based on the report of the 1973 Titan Atmosphere Workshop. The atmosphere composition, clouds, haze, and thermal structure are discussed, along with the photochemistry, escape, and recycling of the atmosphere.

Hunten, D. M.↗
NASA NTRS1981

Plasma density features associated with strong convection in the winter high-latitude F region

A single plasma convection model was combined with an ionospheric-atmospheric composition model to study plasma density features associated with string convection in the winter high-latitude F region. Time dependent, three-dimensional, ion density distributions for NO(+), O2(+), N2(+), O(+) and He(+) were produced, and the ionosphere above 42 deg N magnetic latitude was covered for 24 hours. The study found that for strong and weak convection, electron density exhibited a variation with altitude, latitude, longitude and universal time. Ionospheric features were evident for strong convection, but modified in comparison with those found for slow convection. Also found for strong convection was a more pronounced tongue of ionization, the appearance of a new polar hole in the polar cap, and a midlatitude electron density trough that was not as deep as found for a weak convection. In addition, good agreement was found between predictions and Atmosphere Explorer measurements of ion composition variation with latitude and local time.

Sojka, J. J.↗
NASA NTRS2022

Chapter 7: Sun Photometers

Sun photometry is an extended technique for monitoring the atmospheric composition and support satellite product validation. By measuring the direct solar irradiance, the amount and characteristics of the atmospheric aerosol particles, precipitable water vapor column, and ozone columns can be derived. Global operational networks such as the Aerosol Robotic Network (AERONET), Global Atmosphere Watch-Precision Filter Radiometer Network (GAW-PFR), Maritime Aerosol Network (MAN), or the Brewer spectrophotometer networks constitute sustained efforts for long-term monitoring of the atmosphere, with invaluable data production using cost-effective and relatively simple instrumentation. The data quality relies on the standardization of these networks, with special emphasis on the calibration as the key element in Sun photometry.

Sun photometry↗
DOE OSTI2025

TRACER-MAP: Mapping Aerosol Processes Across Houston During Convective Cell Events

The Houston, TX Metropolitan area was selected for the 2022 Tracking Aerosol Convection Interactions Experiment (TRACER) due to its high convective storm activity and broad range of polluted aerosol conditions. With the overall TRACER project in mind, we planned TRACER-MAP, a related investigation of the impacts of convective storms on atmospheric composition, chemistry and aerosol processing in Houston. Because the Houston metroplex is large and has a wide range of atmospheric conditions, this project has “MAP-ped” the air chemistry conditions across Houston while atmospheric scientists working in the TRACER project monitor convective storm activity overhead. Specifically, we conducted a series of aerosol, gas, and meteorological measurements in the summer of 2022 that matches measurements from the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Mobile Facilities. The TRACER-MAP campaign extended from Jul 1 – Sept 3, 2022. TRACER-MAP included two urban sites: Aldine and University of Houston (UH); two industrial sites: San Jacinto Battleground and the main DOE TRACER site at the La Porte Municipal Airport (ARM/La Porte AMF); and one background site in WG Jones State Forest north of Houston.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1975

Interior structure of Uranus

Critical measurements relative to interior structure which can be made during a spacecraft mission to Uranus are discussed. Models of atmospheric composition, possible magnetic moment, and gravitational harmonics are described, and it is shown that high quality imaging of the atmospheric rotation and determination of the possible magnetic field rotation will facilitate construction of an accurate model of the interior structure of the planet.

Hubbard, W. B.↗
NASA NTRS1991

Future chlorine-bromine loading and ozone depletion

The prediction of future ozone requires three elements: (1) a scenario for the net emissions of chemically and radiatively active trace gases from the land and oceans; (2) a global atmospheric model that projects the accumulation of these gases; and (3) a chemical transport model that describes the distribution of ozone for a prescribed atmospheric composition and climate. This chapter, of necessity, presents models for all three elements and focuses on the following: (1) atmospheric abundance of chlorine and bromine in the form of halocarbons; and (2) the associated perturbations to stratospheric ozone.

Prather, Michael J.↗
NASA NTRS2013

Quantifying the Impact of BOReal Forest Fires on Tropospheric Oxidants Over the Atlantic Using Aircraft and Satellites (BORTAS) Experiment: Design, Execution, and Science Overview

We describe the design and execution of the BORTAS (Quantifying the impact of BOReal forest fires on Tropospheric oxidants using Aircraft and Satellites) experiment, which has the overarching objective of understanding the chemical aging of airmasses that contain the emission products from seasonal boreal wildfires and how these airmasses subsequently impact downwind atmospheric composition. The central focus of the experiment was a two-week deployment of the UK BAe-146-301 Atmospheric Research Aircraft (ARA) over eastern Canada. The planned July 2010 deployment of the ARA was postponed by 12 months because of activities related to the dispersal of material emitted by the Eyjafjallaj¨okull volcano. However, most other planned model and measurement activities, including ground-based measurements at the Dalhousie University Ground Station (DGS), enhanced ozonesonde launches, and measurements at the Pico Atmospheric Observatory in the Azores, went ahead and constituted phase A of the experiment. Phase B of BORTAS in July 2011 included the same measurements, but included the ARA, special satellite observations and a more comprehensive measurement suite at the DGS. Integrating these data helped us to describe pyrogenic plumes from wildfires on a wide spectrum of temporal and spatial scales. We interpret these data using a range of chemistry models, from a near-explicit gas-phase chemical mechanism to regional and global models of atmospheric transport and lumped chemistry. We also present an overview of some of the new science that has originated from this project.

BORTAS↗
NASA NTRS2017

Optimal A-Train Data Utilization: A Use Case of Aura OMI L2G and MERRA-2 Aerosol Products

Ozone Monitoring Instrument (OMI) aboard NASA's Aura mission measures ozone column and profile, aerosols, clouds, surface UV irradiance, and the trace gases including NO2, SO2, HCHO, BrO, and OClO using UltraViolet electromagnetic spectrum (280 - 400 nm) with a daily global coverage and a pixel spatial resolution of 13 km × 24 km at nadir, and it's been one of the key instruments to study the Earth's atmospheric composition and chemistry. The second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) is NASA's atmospheric reanalysis using an upgraded version of Goddard Earth Observing System Model, version 5 (GEOS-5) data assimilation system. Compared to its predecessor MERRA, MERRA-2 is enhanced with more aspects of the Earth system among which is aerosol assimilation. When comparing between satellite pixel measurements and modeled grid data, how to properly handle counterpart pairing is critical considering their spatial and temporal variations. The comparison between satellite and model data by simply using Level 3 (L3) products may result biases due to lack of detailed temporal information. It has been preferred to inter-compare or implement satellite derived physical quantity (i.e., Level 2 (L2) Swath type) directly with/to model measurements with higher temporal and spatial resolution as possible. However, this has posed a challenge in the community to handle. Rather than directly handling the L2 or L3 data, there is a Level 2G (L2G) product conserving L2 pixel scientific data quality but in Grid type with the global coverage. In this presentation, we would like to demonstrate the optimal utilization of OMI L2G daily aerosol products by comparing with MERRA-2 hourly aerosol simulations matched well in both space and time.

MERRA-2 reanalysis↗
NASA NTRS2018

GEOS-CF Model Assessment of PM2.5 During Wildfires: Inferring the Impact of PM2.5 Exposure on Adverse Respiratory & Cardiovascular Conditions

Exposure to fine particulate matter (PM2.5) can aggravate pre-existing respiratory and cardiovascular conditions. When PM2.5 is inhaled it can cause damage to the lungs such as reduced lung function and shortness of breath. After being inhaled PM2.5 can enter the bloodstream and cause harm to the heart. One major natural source of PM2.5 exposure is from wildfire smoke. The particulates within the smoke from the wildfires can spread from the initial source region, potentially impacting communities both near and far. During and after wildfire events, PM2.5 levels can exceed the WHO air quality guidelines (10 gm^3 annual mean; 25 gm^3 daily mean), becoming hazardous to an individual's health. Global models can be used to simulate the emission and transport of these particulates and subsequently they can be valuable to air quality forecasting in highly polluted areas. The NASA Goddard Earth Observing System (GEOS) version 5 Composition Forecast (GEOS-CF) system has been used to produce near-real time air quality forecasts of atmospheric composition at a high global resolution of 25 km. The GEOS-CF system utilizes the GEOS weather forecast model coupled with GEOS-Chem (version 11) chemistry module to provide analyses and forecasts of various toxic air pollutants, including PM2.5. The GEOS-CF simulated high levels of PM2.5 (40 gm^3 to 250 gm^3 ), exceeding the WHO guidelines, during multiple recent regional and global wildfire seasons, including the 2017 Seattle, WA and Los Angeles, CA wildfire seasons, and biomass burning events in India. Furthermore, the GEOS-CF simulated PM2.5 applied to a human health assessment model, BenMAP (The Environmental Benefits Mapping and Analysis Program, version 1.3), estimates the impact on adverse respiratory health conditions due to PM2.5 exposure from wildfires. The GEOS-CF predicted PM2.5 during the wildfire season with the corresponding BenMAP results provides an assessment of the human health impact of PM2.5 exposure.

Saunders, Emily↗
NASA NTRS2018

NASA's GEOS Composition Model Assessment of PM2.5 During Wildfires: Inferring the Impact of PM2.5 Exposure on Adverse Respiratory & Cardiovascular Conditions

Particulate matter pollution is a mixture of solid and liquid droplets floating in the air that can lead to reduced air quality and increased adverse health impact. Fine particulate matter (PM2.5) can be emitted into the air from anthropogenic sources such as the burning of fossil fuels, motor vehicles, and powerplant emissions. Exposure to PM2.5 can aggravate pre-existing respiratory and cardiovascular conditions. When PM2.5 is inhaled it can cause damage to the lungs such as reduced lung function and shortness of breath. After being inhaled PM2.5 can enter the bloodstream and cause harm to the heart. One major natural source of PM2.5 exposure is from wildfire smoke. The particulates within the smoke from the wildfires can spread from the initial source region, potentially impacting communities both near and far. During and after wildfire events, PM2.5 levels can exceed the WHO air quality guidelines (10 m.g/m^3 annual mean; 25 m.g/m^3 daily mean), becoming hazardous to an individual's health. Global models can be used to simulate the emission and transport of these particulates and subsequently they can be valuable to air quality forecasting in highly polluted areas. The NASA Goddard Earth Observing System (GEOS) Composition Forecast (GEOS-CF) system has been used to produce near-real time air quality forecasts of atmospheric composition at a high global resolution of 25x25 km2. The GEOS-CF system utilizes the GEOS weather forecast model coupled with GEOS-Chem (version 11) chemistry module to provide analyses and forecasts of various toxic air pollutants, including PM2.5. The GEOS-CF simulated high levels of PM2.5 (40 m.g/m^3 to 250 m.g/m^3 ), exceeding the WHO guidelines, during multiple recent regional and global wildfire seasons, including the 2017 Washington State and Northern and Southern California wildfire seasons. Furthermore, the GEOS-CF simulated PM2.5 applied to a human health assessment model, BenMAP (The Environmental Benefits Mapping and Analysis Program, version 1.3), estimates the impact on adverse respiratory health conditions due to PM2.5 exposure from wildfires. The GEOS-CF predicted PM2.5 during the wildfire season with the corresponding BenMAP results provides an assessment of the human health impact of PM2.5 exposure.

Saunders, Emily↗
NASA NTRS2017

Evaluation of HZETRN on the Martian Surface: Sensitivity Tests and Model Results

The Mars Science Laboratory Radiation Assessment Detector (MSLRAD) is providing continuous measurements of dose, dose equivalent, and particle flux on the surface of Mars. These measurements have been highly useful in validating environmental and radiation transport models that will be heavily relied upon for future deep space missions. In this work, the HZETRN code is utilized to estimate radiation quantities of interest on the Martian surface. A description of the modeling approach used with HZETRN is given along with the various input models and parameters used to define the galactic cosmic ray (GCR) environment and Martian geometry. Sensitivity tests are performed to gauge the impact of varying several input factors on quantities being compared to MSLRAD data. Results from these tests provide context for inter-code comparisons presented in a companion paper within this issue. It is found that details of the regolith and atmospheric composition have a minimal impact on surface flux, dose, and dose equivalent. Details of the density variation within the atmosphere and uncertainties associated with specifying the vertical atmospheric thickness are also found to have minimal impact. Two widely used GCR models are used as input into HZETRN and it is found that the associated surface quantities are within several percent of each other.

Tony C Slaba↗
NASA NTRSDate not supplied

Global-to-local air quality forecasts using the NASA GEOS Composition Forecast System

Since 2019, the NASA Global Earth Observing System (GEOS) model has been used to generate global, near-real-time estimates and daily five-day forecasts of atmospheric composition at a horizontal resolution of 0.25 degrees (~25 km) from the surface up to the lower mesosphere. This composition forecast system (“GEOS-CF”) combines the GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module to deliver detailed analysis of a wide range of air pollutants, including the policy-relevant species such as ozone, carbon monoxide, nitrogen oxides, sulfur dioxide and fine particulate matter (PM2.5). Because GEOS-CF includes atmospheric levels up through the stratosphere, this system has been leveraged to support the Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite mission and provide stratospheric intrusion alerts to ground-based monitoring stations. We will present recent advances to GEOS-CF which target increased computational efficiency and accuracy. These include the incorporation of simplified chemistry mechanisms to accelerate model forecasts, use of model-observation data fusion techniques to provide highly localized forecasts, and assimilation of satellite observations to produce more accurate model analyses. We further discuss our attempts to make these tools publicly available on platforms outside the NASA domain, such as Google Earth Engine and Amazon Web Services with the goal to facilitate the integration of state-of-the-science air quality information onto platforms used by stakeholders, air quality managers, and the public.

Emma Knowland↗