The application of infrared flux models to atmospheric data.
Upward and downward IR flux expressions for nontransparent and semitransparent computational models applied to atmospheric measurements
SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Upward and downward IR flux expressions for nontransparent and semitransparent computational models applied to atmospheric measurements
Performance of deep space optical communications is impacted by atmospheric outages. By monitoring known stellar objects with calibrated telescopes, atmospheric attenuation statistics can be recorded. This paper describes a program to develop an atmospheric transmission model for optical communications by making automous visibility measurements of known stellar objects from three locations in the southwestern US. The data will be correlated and infused with weather data to establish the atmospheric transmission model. This model will be sent in link margin analysis for optical communications channels. The statistics will be updated on a quarterly basis and calibrated using data taken over a long period of time. This calibration is expected to allow extrapolation to other ground-based locations through use of global weather databases.
Atmospheric aerosols are a significant public health hazard and have substantial impacts on the climate. Secondary organic aerosols (SOAs) have been shown to phase separate into a highly viscous organic outer layer surrounding an aqueous core. This phase separation can decrease the partitioning of semi-volatile and low-volatile species to the organic phase and alter the extent of acid-catalyzed reactions in the aqueous core. A new algorithm that can determine SOA phase separation based on their glass transition temperature (T g ), oxygen to carbon (O:C) ratio and organic mass to sulfate ratio, and meteorological conditions was implemented into the Community Multiscale Air Quality Modeling (CMAQ) system version 5.2.1 and was used to simulate the conditions in the continental United States for the summer of 2013. SOA formed at the ground/surface level was predicted to be phase separated with core–shell morphology, i.e., aqueous inorganic core surrounded by organic coating 65.4 % of the time during the 2013 Southern Oxidant and Aerosol Study (SOAS) on average in the isoprene-rich southeastern United States. Our estimate is in proximity to the previously reported ~70 % in literature. The phase states of organic coatings switched between semi-solid and liquid states, depending on the environmental conditions. The semi-solid shell occurring with lower aerosol liquid water content (western United States and at higher altitudes) has a viscosity that was predicted to be 10 2 –10 12 Pa s, which resulted in organic mass being decreased due to diffusion limitation. Organic aerosol was primarily liquid where aerosol liquid water was dominant (eastern United States and at the surface), with a viscosity <10 2 Pa s. Phase separation while in a liquid phase state, i.e., liquid–liquid phase separation (LLPS), also reduces reactive uptake rates relative to homogeneous internally mixed liquid morphology but was lower than aerosols with a thick viscous organic shell. The sensitivity cases performed with different phase-separation parameterization and dissolution rate of isoprene epoxydiol (IEPOX) into the particle phase in CMAQ can have varying impact on fine particulate matter (PM 2.5 ) organic mass, in terms of bias and error compared to field data collected during the 2013 SOAS. This highlights the need to better constrain the parameters that govern phase state and morphology of SOA, as well as expand mechanistic representation of multiphase chemistry for non-IEPOX SOA formation in models aided by novel experimental insights.
Atmospheric rivers (ARs) play a crucial role in the poleward transport of water vapor, and the AR-associated precipitation is a critical component of global water supplies, making it critical that we understand how ARs may change in the future. To approach this issue, integrations of the NASA Goddard Institute for Space Studies global climate model ModelE version 2.1 (GISSE2.1) are employed. Multiple configurations of the model simulating different climates are analyzed: (1) the last-glacial maximum; (2) present day; (3) the end of the 21st century. The thermodynamic and dynamic components of changes to AR frequency are analyzed using a decomposition method. This method utilizes differences in distinct AR seasonal climatology frequencies derived from various vertically integrated water vapor transport (IVT) thresholds to resolve AR frequency into its components. Global mean state changes in poleward AR frequency for different climates are dominated by precipitable water vapor (PWV) changes. A set of idealized cold and warm climates in which present day sea surface temperatures are uniformly changed are considered for a targeted analysis of the south Pacific Ocean basin. For this analysis, frequency and distribution of AR events in the model runs are analyzed by comparing them to changes in the jet stream as well as the Eulerian storm tracks and low-level baroclinicity. Latitudinal shifts in the ARs in the south Pacific Ocean basin using our integrations are not as tightly coupled to these two storm-related climatological metrics in the midlatitudes but fare better on the poleward side of the storm tracks.
An atmospheric density model is developed and the implications of the model on the analytical drag theory are discussed. The ballistic number and coefficient of drag are assumed constant.
Several independent measurements of warm-season soil moisture and surface atmospheric variables recorded at the ARM Southern Great Plains (SGP) research facility are used to estimate the terrestrial component of land-atmosphere coupling (LAC) strength and its regional uncertainty. The observations reveal substantial variation in coupling strength, as estimated from three soil moisture measurements at a single site, as well as across six other sites having varied soil and land cover types. The observational estimates then serve as references for evaluating SGP terrestrial coupling strength in the Community Atmospheric Model coupled to the Community Land Model. These coupled model components are operated in both a free-running mode and in a controlled configuration, where the atmospheric and land states are reinitialized daily, so that they do not drift very far from observations. Although the controlled simulation deviates less from the observed surface climate than its free-running counterpart, the terrestrial LAC in both configurations is much stronger and displays less spatial variability than the SGP observational estimates. Preliminary investigation of vegetation leaf area index (LAI) substituted for soil moisture suggests that the overly strong coupling between model soil moisture and surface atmospheric variables is associated with too much evaporation from bare ground and too little from the vegetation cover. Lastly, these results imply that model surface characteristics such as LAI, as well as the physical parameterizations involved in the coupling of the land and atmospheric components, are likely to be important sources of the problematical LAC behaviors.
Numerical models and numerical analyses of observations were used to improve the understanding of the physical processes important in global weather and climate. Results from a study of the effect of baroclinic waves on mid-latitude vertical temperature structure show that the waves' vertical eddy heat flux tend to eliminate the potential vorticity gradient near the steering level by causing the static stability to decrease rapidly with height in the lower troposphere above the boundary layer. An empirical study of the relationship between eddy heat fluxes and the meridional temperature gradient has been completed. The results indicate that the feedback in the flux-gradient system is comparable to dissipation on all time scales between the synoptic and the seasonal. The definition of the Eliassen-Palm flux and the Eliassen-Palm and non-acceleration theorems has been generalized to include eddy forcing of condensation. Calculations based on the generalized diagnostics showed that the annual mean eddy forcing of the zonal mean zonal wind is two and one half times stronger when the condensation effects are included.
Knowledge of the directional reflectance properties of natural surfaces such as soils and vegetation canopies is essential for classification studies and canopy model inversion. Atmospheric correction schemes, using various levels of approximation, are described to retrieve surface bidirectional reflectance factors (BRFs) and directional-hemispherical reftectances (albedos)from multiangle radiance measurements taken at ground level. The retrieval schemes are tested on simulated data incorporating realistic surface BRFs and atmospheric models containing aerosols. Sensitivity of the atmospherically corrected BRFs and associated directional-hemispherical reflectances to various aerosol properties and the sun-view geometry is illustrated. A measurement strategy for obtaining highly accurate surface reflectance properties also is examined in the context of instrument radiametric calibration, knowledge of the atmospheric properties, and sun-view angular coverage.
In the event of an accidental or intentional hazardous material release in the atmosphere, researchers often run physics-based atmospheric transport and dispersion models to predict the extent and variation of the contaminant spread. These predictions are imperfect due to propagated uncertainty from atmospheric model physics (or parameterizations) and weather data initial conditions. Ensembles of simulations can be used to estimate uncertainty, but running large ensembles is often very time consuming and resource intensive, even using large supercomputers. In this paper, we present a machine-learning-based method which can be used to quickly emulate spatial deposition patterns from a multi-physics ensemble of dispersion simulations. We use a hybrid linear and logistic regression method that can predict deposition in more than 100,000 grid cells with as few as fifty training examples. Logistic regression provides probabilistic predictions of the presence or absence of hazardous materials, while linear regression predicts the quantity of hazardous materials. The coefficients of the linear regressions also open avenues of exploration regarding interpretability—the presented model can be used to find which physics schemes are most important over different spatial areas. A single regression prediction is on the order of 10,000 times faster than running a weather and dispersion simulation. However, considering the number of weather and dispersion simulations needed to train the regressions, the speed-up achieved when considering the whole ensemble is about 24 times. Ultimately, this work will allow atmospheric researchers to produce potential contamination scenarios with uncertainty estimates faster than previously possible, aiding public servants and first responders.
Active galactic nuclei (AGN) accretion disk spectra were calculated using non-LTE stellar atmosphere models for Kerr and Schwarzschild geometries. It is found that the Lyman limit absorption edge, probably the most conclusive observational evidence for the accretion disk, would be drastically distorted and displaced by the relativistic effects from the large gravitational field of the central black hole and strong Doppler motion of emitting material on the disk surface. These effects are especially pronounced in the Kerr geometry. The strength of the Lyman limit absorption is very sensitive to the surface gravity in the stellar atmosphere models used. For models at the same temperature but different surface gravities, the strength of the Lyman edge exhibits an almost exponential decrease as the surface gravity approach the Eddington limit, which should approximate the thin disk atmosphere. The relativistic effects as well as the vanishing of the Lyman edge at the Eddington gravity may be the reasons that not many Lyman edges in the rest frames of AGNs and quasars are found.
We present spectrophotometry spanning 1–5 μm of 51 Eridani b, a 2–10 M{sub Jup} planet discovered by the Gemini Planet Imager Exoplanet Survey. In this study, we present new K1 (1.90–2.19 μm) and K2 (2.10–2.40 μm) spectra taken with the Gemini Planet Imager as well as an updated L {sub P} (3.76 μm) and new M {sub S} (4.67 μm) photometry from the NIRC2 Narrow camera. The new data were combined with J (1.13–1.35 μm) and H (1.50–1.80 μm) spectra from the discovery epoch with the goal of better characterizing the planet properties. The 51 Eri b photometry is redder than field brown dwarfs as well as known young T-dwarfs with similar spectral type (between T4 and T8), and we propose that 51 Eri b might be in the process of undergoing the transition from L-type to T-type. We used two complementary atmosphere model grids including either deep iron/silicate clouds or sulfide/salt clouds in the photosphere, spanning a range of cloud properties, including fully cloudy, cloud-free, and patchy/intermediate-opacity clouds. The model fits suggest that 51 Eri b has an effective temperature ranging between 605 and 737 K, a solar metallicity, and a surface gravity of log(g) = 3.5–4.0 dex, and the atmosphere requires a patchy cloud atmosphere to model the spectral energy distribution (SED). From the model atmospheres, we infer a luminosity for the planet of −5.83 to −5.93 (logL/L{sub ⊙}), leaving 51 Eri b in the unique position of being one of the only directly imaged planets consistent with having formed via a cold-start scenario. Comparisons of the planet SED against warm-start models indicate that the planet luminosity is best reproduced by a planet formed via core accretion with a core mass between 15 and 127 M{sub ⊕}.
We present an overview and description of the atmospheric transport model (ATM) component of the Defense Land Fallout Interpretative Code (DELFIC) and its revision history. In particular, we discuss the hybrid Eulerian-Lagrangian model of the DELFIC diffusive transport module (DTM), its assumptions and constraints, and assess its capability for modeling the transport, dispersion, and deposition of nuclear fallout debris. This hybrid model is an efficient transport model for the wide range of particle sizes found in nuclear fallout debris. Furthermore, we validate the 1979 version of DELFIC using the 1979 test case input and output presented in its documentation. Except for some rounding differences and exposure rate differences from the OPM, the DTM output is in very good agreement with the 1979 results. Overall, the DELFIC DTM provides a reasonable and rapid approximation to the transport and deposition of local nuclear fallout debris.
Monte Carlo relaxation method for physically self consistent model stellar atmospheres, discussing stability, accuracy and convergence of solution
An atmospheric corrosion model and corrosion monitoring system has been developed for low cost solar arrays (LSA). The corrosion model predicts that corrosion rate is the product of the surface condensation probability of water vapor and the diffusion controlled corrosion current. This corrosion model is verified by simultaneous monitoring of weather conditions and corrosion rates at the solar array test site at Mead, Nebraska.
This project was targeting the development of a computational approach that would allow resolving cloud processes on small-scales within the framework of the most recent version of the NASA/NCAR Finite-Volume Community Atmospheric Model (FVCAM). The FVCAM is based on the multidimensional Flux-Form Semi-Lagrangian (FFSL) dynamical core and uses a “vertically Lagrangian” finite-volume (FV) representation of the model equations with a mass-conserving re-mapping algorithm. The Lagrangian coordinate requires a remapping of the Lagrangian volume back to Eulerian coordinates to restore the original resolution and keep the mesh from developing distortions such as layers with overlapping interfaces. The main objectives of the project were, first, to develop the 3D library which allows refinement and coarsening of the model domain in spherical coordinates, and second, to develop a non-hydrostatic code for calculation of the model variables within the refined areas that could be seamlessly incorporated with the hydrostatic finite volume dynamical core when higher resolution is wanted. We also updated the aerosol simulation model in CAM in order to ready the model for the treatment of aerosol/cloud interactions.
Surface flow and subsurface flow constitute a naturally linked hydrologic continuum that has not traditionally been simulated in an integrated fashion. Recognizing the interactions between these systems has encouraged the development of integrated hydrologic models (IHMs) capable of treating surface and subsurface systems as a single integrated resource. IHMs are dynamically evolving with improvements in technology, and the extent of their current capabilities are often only known to the developers and not general users. This article provides an overview of the core functionality, capability, applications, and ongoing development of one open-source IHM, ParFlow. ParFlow is a parallel, integrated, hydrologic model that simulates surface and subsurface flows. ParFlow solves the Richards equation for three-dimensional variably saturated groundwater flow and the two-dimensional kinematic wave approximation of the shallow water equations for overland flow. The model employs a conservative centered finite-difference scheme and a conservative finite-volume method for subsurface flow and transport, respectively. ParFlow uses multigrid-preconditioned Krylov and Newton–Krylov methods to solve the linear and nonlinear systems within each time step of the flow simulations. The code has demonstrated very efficient parallel solution capabilities. ParFlow has been coupled to geochemical reaction, land surface (e.g., the Common Land Model), and atmospheric models to study the interactions among the subsurface, land surface, and atmosphere systems across different spatial scales. This overview focuses on the current capabilities of the code, the core simulation engine, and the primary couplings of the subsurface model to other codes, taking a high-level perspective.
Recent ROSAT and EUVE detections of spin-powered neutron stars suggest that many emit 'thermal' radiation, peaking in the EUV/soft X-ray band. These data constrain the neutron stars' thermal history, but interpretation requires comparison with model atmosphere computations, since emergent spectra depend strongly on the surface composition and magnetic field. As recent opacity computations show substantial change to absorption cross sections at neutron star photospheric conditions, we report here on new model atmosphere computations employing such data. The results are compared with magnetic atmosphere models and applied to PSR J0437-4715, a low field neutron star.
Models of Jupiter's formation and interior predict that its atmosphere is enriched in oxygen relative to the Sun and that consequently, a water cloud is present globally near the 5-bar pressure level.