Atmospheric Remote Sensing

ars_thumbCPI provides critical scientific and technical support for many successful atmospheric remote sensing programs, and has significant in-house expertise in the key areas of algorithm development, data processing and analysis and product validation. CPI's capabilities contribute to all critical phases of the geophysical remote sensing problem including: detailed sensor simulations; satellite/sensor characterization and mission design optimization; development of ground data processing systems; development of forward models for atmospheric radiative transfer and particle precipitation; retrieval algorithm development; retrieval characterization and error analysis; data product validation; and scientific analysis.

Taking advantage of the synergy provided by its experience in developing data analysis algorithms for a variety of platforms and instruments, CPI has developed a number of useful models and core software packages that are widely applicable to atmospheric remote sensing. One such package is a suite of generic, highly modular algorithms for remote sensing retrievals. These algorithms implement a rigorous theoretical framework for geophysical retrieval algorithms that can be readily tailored to specific experimental situations utilizing different measurement techniques, spectral bandwidths, and viewing geometries. The theoretical basis for this general retrieval algorithm is the optimal estimation technique which has been implemented in both FORTRAN and IDL in an optimal estimation code (named OPT) developed at CPI. A key attribute of the OPT algorithms is the highly generic form of the code, which allows it to be readily adapted to a wide range of retrieval problems. This package has been used as the core of operational retrieval algorithms for a number of satellite and ground-based remote sensing missions.

In addition to the generalized retrieval algorithms, CPI has significant capabilities in first-principles modeling of atmospheric phenomena, including photochemistry and optical emission from the ultraviolet (UV) to the near infrared (near-IR). CPI also has state of the art algorithms for calculating satellite orbits and simulating arbitrary instrument viewing geometries (for example, limb, nadir, or zenith viewing, scanning mode or fixed line-of-sight, etc.). Other CPI models are used to calculate key atmospheric emissions or scattering/extinction along a given line of sight through the atmosphere. All of these capabilities can be utilized to construct the detailed forward models necessary for realistic satellite measurement simulations, or to construct the forward model component to be used in the OPT retrieval algorithms.

Upper Atmosphere
CPI, since its inception, has been conducting research to better understand the connection between upper atmosphere spectral radiances (dayglow and aurora) and their energy inputs (solar EUV and auroral precipitation). Key to a long list of successful investigations has been detailed modeling using CPI's first-principles models AURIC and B3C that link the above inputs to a variety of outputs (e.g., spectral radiances and chemistry-dependent densities). These models have allowed us to develop remote sensing algorithms for converting satellite and ground-based optical measurements to some key data products. From far ultraviolet (FUV) dayglow disk observations, these include the energy flux of solar EUV shortward of 45 nm (designated as QEUV), associated spectral properties, and the O to N2 column density ratio referenced to a fixed N2 column density (designated as O/N2). Specifications of QEUV and O/N2 from TIMED/GUVI data have made important contributions since 2002 to better understanding thermospheric and solar EUV variability. From auroral FUV disk observations, products include particle precipitation parameters Q (energy flux) and Eavg (average energy) for electron and proton aurora, auroral O/N2, and auroral E-region parameters NmE (peak electron density) and HmE (height of the peak). From coincident DMSP/SSUSI FUV and DMSP/SSJ/5 particle data, we now have a better understanding of FUV emission efficiencies for proton aurora and how they compare to those for electron aurora. Such understanding is needed when developing FUV auroral remote sensing algorithms. CPI has an extensive list of peer-reviewed papers addressing model development, algorithm development, and use of models and algorithms on satellite, rocket, and ground-based data.

Projects that CPI has contributed to include:

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SSUSI F16 auroral images for two of the three spectral channels used to specify precipitation characteristics (the third channel is LBHS, shortward of the LBHL channel). Contours of constant solar zenith angle at 90° and 100° are displayed to identify nightside versus dayside observations.

Middle Atmosphere
CPI has supported numerous successful programs in middle atmospheric remote sensing, and has significant in-house expertise in the key areas of algorithm development, data analysis and product validation, and scientific analysis. Taking advantage of the synergy provided by its experience in developing data analysis algorithms for a variety of platforms and instruments, CPI has developed a suite of generic, highly modular algorithms for remote sensing applications. These algorithms implement a rigorous theoretical framework for geophysical retrieval algorithms that can be readily tailored to specific experimental situations utilizing different measurement techniques, spectral bandwidths, and viewing geometries.

In addition to the generalized retrieval algorithms, CPI has significant capabilities in first-principles modeling of atmospheric phenomena, including photochemistry and optical emission from the UV to the near-infrared (NIR). CPI also has state of the art algorithms for calculating satellite orbits and simulating arbitrary instrument viewing geometries (for example, limb, nadir, or zenith viewing, scanning mode or fixed line-of-sight, etc.). Other CPI models are used to calculate key atmospheric emissions or extinction (scattering and absorption) along a given line of sight through the atmosphere.

These core capabilities allow CPI to address all aspects of atmospheric remote sensing missions through the design, development and operational stages, including: detailed simulations of sensor performance and measurement scenarios for current and future satellite-borne sensors; development and implementation of operational retrieval algorithms; as well as data processing, validation and analysis.

Projects that CPI has contributed to include:

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Sample CIPS PMC albedio image for a single orbit on July 3, 2010.

Lower Atmosphere
CPI's core capabilities in algorithm development, data processing and software development for middle- and upper-atmospheric remote sensing are directly applicable to lower-atmospheric remote sensing. CPI provides critical technical support in multiple key areas to several current and future missions focused on remote sensing of the lower atmosphere (troposphere) and Earth's surface.

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