This paper presents an UltraViolet-Visible (UV-Vis) spectral radiance simulation capability for Non-Local Thermodynamic Equilibrium (non-LTE) conditions, consisting of a full line-by-line (LBL) radiative transfer (RT) algorithm and a UV-Vis signatures library. Results are presented for two example scenarios where strong UV-Vis emissions arise, an atmospheric high altitude auroral event and a High Explosive (HE) detonation.
Optimal interpretation of remote sensing imagery requires characterizing the atmospheric composition between a sensor and the area it is observing. Timely estimates of atmospheric temperature, water vapor, and other constituents from the ground to the edge of the space environment are not always readily available. In those cases, we must supplement our knowledge of the atmosphere’s composition to fill in any gaps in knowledge and empirical models of the atmosphere are useful tools for this purpose. The Standardized Atmosphere Generator (SAG) was constructed is one such empirical. It has been designed to allow all the major known, systematic variability in the atmosphere and may be used to generate atmospheric profile from the ground to 300 km consistent with user-specified temporal, geophysical, and geographical information Output provides reasonable estimates for temperature, pressure, and densities of atmospheric constituents and can be directly incorporated into radiative transfer forward models or retrieval algorithms. SAG draws upon a number of existing empirical atmospheric models and ensures consistency of output between them. It can be used either as a stand-alone interactive program or scripted for batch execution and assist in determining atmospheric attenuation, refraction, scattering, chemical kinetic temperature profiles, and a host of other naturally occurring processes. Here, we will discuss the capabilities and performance of the SAG model for a variety of applications including its interactive and batch processing use. We will also demonstrate the physical realism of SAG through a small number of relevant use cases.
In this paper, we present examples of aerosol and Cirrus cloud altitude profiles over Hanoi, Vietnam, measured
with the ground LIDAR setup of the Institute of Physics. Comparisons are made to LIDAR data collected by the Calipso
satellite of the NASA A-Train during its orbits over the Hanoi area. The height distributions for both surface aerosols
and Cirrus clouds derived from ground and satellite observations are generally consistent, with distributions between
2km-3km, and 8km-15km respectively for aerosols and Cirrus clouds. Cirrus cloud locations inferred from an analysis of
limb spectral radiances obtained by the SCIAMACHY satellite are also consistent with the LIDAR data.
Singular value decomposition (SVD) and principal component analysis enjoy a broad range of applications, including,
rank estimation, noise reduction, classification and compression. The resulting singular vectors form orthogonal basis
sets for subspace projection techniques. The procedures are applicable to general data matrices. Spectral matrices
belong to a special class known as non-negative matrices. A key property of non-negative matrices is that their
columns/rows form non-negative cones, with any non-negative linear combination of the columns/rows belonging to the
cone. This special property has been implicitly used in popular rank estimation techniques know as virtual dimension
(VD) and hyperspectral signal identification by minimum error (HySime). Data sets of spectra reside in non-negative
orthants. The subspace spanned by a SVD of a set of spectra includes all orthants. However SVD projections can be
constrained to the non-negative orthants. In this paper two types of singular vector projection constraints are identified,
one that confines the projection to lie within the cone formed by the spectral data set, and a second that only restricts
projections to the non-negative orthant. The former is referred to here as the inner constraint set, the latter the outer
constraint set. The outer constraint set forms a broader cone since it includes projections outside the cone formed by the
data array. The two cones form boundaries for the cones formed by non-negative matrix factorizations (NNF).
Ambiguities in the NNF lead to a variety of possible sets of left and right non-negative vectors and their cones. The
paper presents the constraint set approach and illustrates it with applications to spectral classification.
This paper presents results that demonstrate the auroral modeling capabilities of the Air Force Research Laboratory
(AFRL) SAMM2 (SHARC And MODTRAN® Merged 2) radiance code. A scene generation capability is obtained by
coupling SAMM2 with a recently developed Clutter Region Atmosphere and Scene Module (CRASMO), which
provides an approach for rapid generation of time sequences and images of radiance clutter. Modeled results will be
compared to data collected by the Midcourse Space Experiment (MSX)1 in the IR and UV-visible spectral regions during
an auroral event on November 10, 1996.
The paper is organized as follows. We first present a brief history of the AFRL SHARC/SAMM codes, leading up to the
current version, SAMM2 v.2. The SAMM2 UV-visible auroral kinetic model will then be described, followed by a
comparison of modeled results to the MSX data.
A new correlated-k algorithm has recently been incorporated into SAMM-2, the Air Force Research Laboratory
background radiance and transmission code. SAMM-2 incorporates all of the major components necessary for
background scene generation at all altitudes: atmospheric characterization, solar irradiance, molecular chemical kinetics
and molecular spectroscopic data. The underlying physical models are applicable for both low-altitude local
thermodynamic equilibrium (LTE) conditions as well as high-altitude non-LTE (NLTE) conditions. Comprehensive
coverage in the .4 to 40 micron (250 to 25,000 wavenumber) wavelength region for arbitrary lines-of-sight (LOS) in the
0 to 300 kilometer altitude regime is provided. A novel 1 cm-1 resolution correlated-k algorithm has been developed in
order to provide the orders-of-magnitude increase in computational efficiency when compared to the existing SAMM-2
line-by-line (LBL) algorithm and applicable to both LTE and NLTE atmospheric conditions. The SAMM-2 correlated-k
algorithm processes molecular lines at runtime by reading line center information from the HITRAN 2000 database and
computing statistical cumulative probability distributions within a spectral interval under the presumption of a Voigt line
shape profile. This algorithm is useful for treating atmospheric phenomena at all altitudes requiring a spectrally
monochromatic treatment of the atmospheric transmission and/or radiance, including multiple scattering or atmospheric structure.
Assuming large signal-to-noise ratio and using the rotationally resolved fundamental vibration-rotation band emission from NO near 5.3 μm we propose a scheme for remotely sensing temperature above the altitudes where the 15 μm emission from CO2 becomes very weak. We also find that the rotationally resolved 5.3 μm emission can be used to remotely sense N(4S) atom, O2, and O densities in the terrestrial thermosphere -- this being the only method for remotely sensing the first two species.
MODTRAN4, version 2, will soon be released by the U.S. Air Force Geophysics Laboratory; it is an extension of the MODTRAN4, v1, atmospheric transmission, radiance and flux model developed jointly by the Air Force Research Laboratory / Space Vehicles Directorate (AFRL / VS) and Spectral Sciences, Inc. The primary accuracy improvements in MODTRAN4 remain those previously published: (1) the multiple scattering correlated-k approach to describe the statistically expected transmittance properties for each spectral bin and atmospheric layer, and (2) the Beer-Lambert formulation that improves the treatment of path inhomogeneities. Version 2 code enhancements are expected to include: *pressure-dependent atmospheric profile input, as an auxiliary where the hydrostatic equation is integrated explicitly to compute the altitudes, *CFC cross-sections with band model parameters derived from pseudo lines, *additional pressure-induced absorption features from O2, and *a new 5 cm-1 band model option. Prior code enhancements include the incorporation of solar azimuth dependence in the DISORT-based multiple scattering model, the introduction of surface BRDF (Bi-directional Radiance Distribution Functions) models and a 15 cm-1 band model for improved computational speed. Last year's changes to the HITRAN database, relevant to the 0.94 and 1.13 micrometers bands of water vapor, have been maintained in the MODTRAN4,v2 databases.
MODTRAN4, the newly released version of the U.S. Air Force atmospheric transmission, radiance and flux model is being developed jointly by the Air Force Research Laboratory / Space Vehicles Directorate (AFRL / VS) and Spectral Sciences, Inc. It is expected to provide the accuracy required for analyzing spectral data for both atmospheric and surface characterization. These two quantities are the subject of satellite and aircraft campaigns currently being developed and pursued by, for instance: NASA (Earth Observing System), NPOESS (National Polar Orbiting Environmental Satellite System), and the European Space Agency (GOME - Global Ozone Monitoring Experiment). Accuracy improvements in MODTRAN relate primarily to two major developments: (1) the multiple scattering algorithms have been made compatible with the spectroscopy by adopting a correlated-^ approach to describe the statistically expected transmittance properties for each spectral bin and atmospheric layer, and (2) radiative transfer calculations can be conducted with a Beer-Lambert formulation that improves the treatment of path inhomogeneities. Other code enhancements include the incorporation of solar azimuth dependence in the DISORT-based multiple scattering model, the introduction of surface BRDF (Bi-directional Radiance Distribution Functions) models and a 15 cm-1 band model for improved computational speed. Finally, recent changes to the HITRAN data base, relevant to the 0.94 and 1.13 um bands of water vapor, have been incorporated into the MODTRAN4 databases.
MODTRAN4, the newly released version of the U.S. Air Force atmospheric transmission, radiance and flux model is being developed jointly by the Air Force Research Laboratory/Space Vehicles Directorate and Spectral Sciences, Inc. It is expected to provide the accuracy required for analyzing spectral data for both atmospheric and surface characterization. These two quantities are the subject of satellite and aircraft campaigns currently being developed and pursued by, for instance: NASA (Earth Observing System), NPOESS (National Polar Orbiting Environmental Satellite System), and the European Space Agency (GOME--Global Ozone Monitoring Experiment). Accuracy improvements in MODTRAN relate primarily to two major developments: (1) the multiple scattering algorithms have been made compatible with the spectroscopy by adopting a corrected-k approach to describe the statistically expected transmittance properties for each spectral bin and atmospheric layer, and (2) radiative transfer calculations can be conducted with a Beer-Lambert formulation that improves the treatment of path inhomogeneities. Other code enhancements include the incorporation of solar azimuth dependence in the DISORT- based multiple scattering model, the introduction of surface BRDF (Bi-directional Radiance Distribution Functions) models and 15 cm-1 band model for improved computational speed.
MODTRAN4, the latest publicly released version of MODTRAN, provides many new and important options for modeling atmospheric radiation transport. A correlated-k algorithm improves multiple scattering, eliminates Curtis-Godson averaging, and introduces Beer's Law dependencies into the band model. An optimized 15 cm-1 band model provides over a 10-fold increase in speed over the standard MODTRAN 1 cm-1 band model with comparable accuracy when higher spectral resolution results are unnecessary. The MODTRAN ground surface has been upgraded to include the effects of Bidirectional Reflectance Distribution Functions (BRDFs) and Adjacency. The BRDFs are entered using standard parameterizations and are coupled into line-of-sight surface radiance calculations.
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