Dr. Joseph William Snow Profile

Dr. Joseph William Snow

Technical Staff at MIT Lincoln Lab

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Publications (8)

Proceedings Article | 4 May 2006 Paper

Satellite hyperspectral IR sensing: investigating water vapor variability using AIRS data

Hsiao-hua Burke, J. William Snow, Fred Chen, Kris Farrar

Proceedings Volume 6233, 62331C (2006) https://doi.org/10.1117/12.666572

KEYWORDS: Satellites, Atmospheric sensing, Clouds, Sensors, Data modeling, Ultrasound-modulated optical tomography, Atmospheric monitoring, Temperature metrology, Spectral resolution, Troposphere

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Proceedings Article | 4 November 2005 Paper

Polarimetric bio-aerosol detection: numerical simulation

J. William Snow, W. Ed Bicknell, Hsiao-hua Burke

Proceedings Volume 5995, 59950Z (2005) https://doi.org/10.1117/12.631337

KEYWORDS: Aerosols, Scattering, Laser scattering, Signal to noise ratio, Atmospheric particles, Light scattering, Polarization, Polarimetry, Particles, LIDAR

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Proceedings Article | 1 June 2005 Paper

Potential roles of satellite hyperspectral IR sensors in monitoring greenhouse effects

Hsiao-hua Burke, Bill Snow, Kris Farrar

Proceedings Volume 5806, (2005) https://doi.org/10.1117/12.604905

KEYWORDS: Clouds, Satellites, Gases, Climate change, Infrared sensors, Atmospheric modeling, Climatology, Methane, Carbon monoxide, Infrared radiation

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Proceedings Article | 2 August 2002 Paper

Analysis of MTI data over coastal Massachusetts

Hsiao-hua Burke, J. William Snow, Michael Griffin, Carolyn Upham

Proceedings Volume 4725, (2002) https://doi.org/10.1117/12.478773

KEYWORDS: Clouds, Aerosols, Reflectivity, Scattering, Atmospheric particles, Satellites, Vegetation, Short wave infrared radiation, Optical properties, Particles

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VNIR-SWIR data from DOE MTI satellite are used to demonstrate the retrieval of aerosol and cloud properties. MTI data offer high spatial resolution and high SNR data. Furthermore, collection from both nadir and off-nadir views offer a unique opportunity to assess atmospheric path length effects both through clear and cloud conditions. Data sets were acquired to investigate cloud and aerosol properties: 29 July and 22 August 2000 over the coastal region of Massachusetts near Plymouth. Two topics are investigated: (1) retrieval of aerosol optical properties, and (2) characterization of water and ice clouds at nadir and off-nadir views. Data collection on 22 August 2000 represents a relatively clear atmospheric condition in the vicinity of Pilgrim Power Plant, Plymouth. Data over both vegetated land and ocean are analyzed. Two algorithms for aerosol retrieval over land are compared: the conventional dense-dark vegetation (DDV) algorithm and a generalized VIS-SWIR reflectance correlation and scatter-plot analysis (VSP) algorithm. Optical depths at multiple wavelengths and aerosol type were derived and compared with ground based AERONET data. It is demonstrated that the VSP algorithm captures the spectral variability in aerosol extinction, and thus performs better. Data collection from 29 July 2000 over the same area was investigated for cloud characteristics at different viewing geometries. Top-of-the-Atmosphere (TOA) reflectance statistics is computed for a common cloudy region. It is observed that in cloud free regions, nadir TOA reflectance is lower than that from off-nadir observations. This is due to the increased atmospheric scattering effect from the longer paths. On the other hand, TOA reflectance over cloud area depends on the scattering phase function and the look angle. Here we use simple expressions to illustrate that the effects for water and ice particles can be quite different resulting in very different viewing geometry effects between cumulus and cirrus clouds.

Proceedings Article | 20 August 2001 Paper

Examples of atmospheric characterization using hyperspectral data in the VNIR, SWIR and MWIR

Hsiao-hua Burke, Michael Griffin, J. William Snow, Carolyn Upham, Craig Richard

Proceedings Volume 4381, (2001) https://doi.org/10.1117/12.437023

KEYWORDS: Atmospheric particles, Aerosols, Clouds, Sensors, Absorption, Short wave infrared radiation, Mid-IR, Atmospheric physics, Atmospheric sensing, Transmittance

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Proceedings Article | 23 August 2000 Paper

Mitigation of atmospheric effects in hyperspectral data analysis

Hsiao-hua Burke, Michael Griffin, J. William Snow

Proceedings Volume 4049, (2000) https://doi.org/10.1117/12.410367

KEYWORDS: Atmospheric modeling, Aerosols, Reflectivity, Atmospheric particles, Absorption, Atmospheric physics, Visibility, Atmospheric sensing, Scattering, Sensors

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Proceedings Article | 23 August 2000 Paper

Characterization and delineation of plumes, clouds, and fires in hyperspectral images

Michael Griffin, Su Hsu, Hsiao-hua Burke, J. William Snow

Proceedings Volume 4049, (2000) https://doi.org/10.1117/12.410349

KEYWORDS: Clouds, Principal component analysis, Reflectivity, Particles, Vegetation, Feature extraction, Combustion, Hyperspectral imaging, Visible radiation, Short wave infrared radiation

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Proceedings Article | 23 December 1994 Paper

Improved cloud analysis for CDFS II through the SERCAA research and development program

Ronald Isaacs, Gary Gustafson, Thomas Neu, J. William Snow

Proceedings Volume 2309, (1994) https://doi.org/10.1117/12.196689

KEYWORDS: Clouds, Satellites, Analytical research, Algorithm development, Data modeling, Sensors, Meteorological satellites, Data processing, Climate change, Computing systems

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Showing 5 of 8 publications

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