Dr. Graeme L. Stephens Profile

Dr. Graeme L. Stephens

Principal Investigator at Jet Propulsion Lab

SPIE Involvement:

Author

Proceedings Article | 23 October 2018 Paper

The challenges of representing vertical motion in numerical models

Susan van den Heever, Leah Grant, Graeme Stephens, Ziad Haddad, Rachel Storer, Ousmane Sy, Derek Posselt

Proceedings Volume 10782, 1078204 (2018) https://doi.org/10.1117/12.2501584

KEYWORDS: Motion models, Atmospheric modeling, Doppler effect, Convection, Thermodynamics, Radar, Diagnostics, Temperature metrology, Clouds, Liquids

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Proceedings Article | 22 October 2018 Paper

Atmospheric remote sensing with convoys of miniature radars

Ziad Haddad, Ousmane Sy, Graeme Stephens, Sue van den Heever, Derek Posselt

Proceedings Volume 10776, 107760I (2018) https://doi.org/10.1117/12.2500285

KEYWORDS: Reflectivity, Radar, Clouds, Convection, Satellites, Atmospheric sensing, Remote sensing, Motion estimation, Atmospheric sciences, Microwave radiation

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Proceedings Article | 5 May 2016 Paper

RaInCube: a proposed constellation of atmospheric profiling radars in cubesat

Ziad Haddad, Eva Peral, Simone Tanelli, Ousmane Sy, Graeme Stephens

Proceedings Volume 9876, 987606 (2016) https://doi.org/10.1117/12.2228188

KEYWORDS: Atmospheric modeling, Radar, Satellites, Profiling, Clouds, Climatology, Temporal resolution, Atmospheric modeling, Climatology, Antennas, Meteorological satellites, Radiometry

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Proceedings Article | 25 October 2013 Paper

Contemplating synergistic algorithms for the NASA ACE Mission

Gerald Mace, David Starr, Roger Marchand, Steven Ackerman, Steven Platnick, Ann Fridlind, Steven Cooper, Deborah Vane, Graeme Stephens

Proceedings Volume 8890, 88900I (2013) https://doi.org/10.1117/12.2030206

KEYWORDS: Clouds, Aerosols, Atmospheric particles, Climatology, Particles, Radar, Atmospheric modeling, Climate change, Liquids, Environmental sensing

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Proceedings Article | 29 October 2010 Paper

Cloud sciences using satellite remote sensing, cloud growth model, and radiative transfer

Takashi Nakajima, Takashi Matsui, Husi Letu, Kentaroh Suzuki, Haruma Ishida, Nobuyuki Kikuchi, Graeme Stephens, Teruyuki Nakajima, Haruhisa Shimoda

Proceedings Volume 7859, 785905 (2010) https://doi.org/10.1117/12.869436

KEYWORDS: Clouds, Satellites, Atmospheric modeling, Remote sensing, Radar, Imaging systems, Radiative transfer, Reflectivity, MODIS, Aerosols

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Proceedings Article | 8 December 2008 Paper

Advances in the remote sensing of clouds and precipitation from CloudSat and the A-Train

Graeme Stephens, Deborah Vane

Proceedings Volume 7152, 715206 (2008) https://doi.org/10.1117/12.812554

KEYWORDS: Clouds, Radar, Reflectivity, Atmospheric modeling, Satellites, Data modeling, Meteorology, LIDAR, Atmospheric particles, Multilayers

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Proceedings Article | 25 October 2007 Paper

Integrated cloud-aerosol-radiation product using CERES, MODIS, CALIPSO, and CloudSat data

Sunny Sun-Mack, Patrick Minnis, Yan Chen, Sharon Gibson, Yuhong Yi, Qing Trepte, Bruce Wielicki, Seiji Kato, Dave Winker, Graeme Stephens, Philip Partain

Proceedings Volume 6745, 674513 (2007) https://doi.org/10.1117/12.737903

KEYWORDS: Clouds, MODIS, Aerosols, LIDAR, Infrared radiation, Radar, Data centers, Data modeling, Calibration, Knowledge management

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SPIE Journal Paper | 1 January 2007

Cloud remote sensing from space in the era of the A-Train

Graeme Stephens, Deborah Vane

JARS, Vol. 1, Issue 01, 013507, (January 2007) https://doi.org/10.1117/12.10.1117/1.2709703

KEYWORDS: Clouds, Remote sensing, Satellites, Radar, Space operations, Microwave radiation, Reflectivity, Aerosols, Sensors, Particles

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Proceedings Article | 17 October 2006 Paper

Cloud remote sensing from space the era of the A-Train

Graeme Stephens, Deborah Vane

Proceedings Volume 6359, 635902 (2006) https://doi.org/10.1117/12.714423

KEYWORDS: Clouds, Remote sensing, Radar, Satellites, Microwave radiation, Sensors, Reflectivity, Aerosols, Space operations, Particles

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Proceedings Article | 1 November 2005 Paper

Sensitivity analysis and optimal estimation retrieval of aerosol optical properties over oceans utilizing simulated multi-angular and polarized radiances

Matthew Lebsock, Graeme Stephens

Proceedings Volume 5979, 59790Q (2005) https://doi.org/10.1117/12.638609

KEYWORDS: Aerosols, Signal to noise ratio, Atmospheric modeling, Error analysis, Statistical analysis, Optical properties, Radiative transfer, Atmospheric particles, Backscatter, Ocean optics

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Proceedings Article | 18 August 2005 Paper

Characterization and error analysis of an operational retrieval algorithm for estimating column ozone and aerosol properties from ground-based ultra-violet irradiance measurements

Thomas Taylor, Tristan L'Ecuyer, James Slusser, Graeme Stephens, Nick Krotkov, John Davis, Christian Goering

Proceedings Volume 5886, 58860Y (2005) https://doi.org/10.1117/12.628877

KEYWORDS: Atmospheric modeling, Error analysis, Aerosols, Ultraviolet radiation, Ozone, Radiative transfer, Climatology, Diagnostics, Algorithm development, Clouds

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Proceedings Article | 20 January 2005 Paper

On the information content of satellite radiance observations for cloud microphysical property retrievals

Tristan L'Ecuyer, Steven Cooper, Graeme Stephens, Philip Gabriel, Kyle Leesman

Proceedings Volume 5655, (2005) https://doi.org/10.1117/12.588321

KEYWORDS: Clouds, Liquids, MODIS, Atmospheric modeling, Shortwaves, Satellites, Error analysis, Crystals, Infrared radiation, Radiative transfer

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Clouds play an important role in the hydrologic cycle, influence global energy balance, and represent a significant yet poorly understood component of global climate change. As a result, quantitative global observations of liquid and ice cloud microphysical and radiative properties continue to be a focus of a growing number of satellite-based sensors each having an associated suite of retrieval algorithms. While a number of these algorithms have successfully been applied to map clouds, many can only be applied under specific conditions (eg. during the daytime) or over a limited dynamic range (eg. optically thin cirrus) often leading to unphysical discontinuities when one seeks to compile a complete picture of the global distribution of clouds. Furthermore, discrepancies exist between products of different algorithms when they are applied to the same scene by virtue of differences in the information provided by distinct combinations of measurements. This paper revisits the problem of cloud microphysical property retrievals from satellite radiance observations at solar and thermal wavelengths in an effort to quantify their information content with respect to single layer liquid and ice clouds over an oceanic background. Using the channels on the Moderate Resolution Imaging Spectroradiometer (MODIS) as an example, it will be demonstrated that an entropy-based definition of information content provides a useful metric for evaluating the utility of a set of observations in a retrieval problem. This approach is used to objectively determine the subset of wavelengths that provide the greatest amount of information for oceanic microphysical property retrievals from the MODIS instrument. The results show that the combination of a conservative and a non-conservative scattering shortwave channel in concert with a near-infrared channel, an infrared window channel, and one in the wings of the 15 m CO2 band provide the optimal channel combination for the wide variety of liquid and ice clouds examined. With an eye toward developing a coherent representation of the global distribution of cloud microphysical and radiative properties, this combination of channels may be integrated into a suitable multi-channel inversion methodology such as the optimal estimation or Bayesian techniques to provide a means of establishing a common framework for cloud retrievals under varying conditions. Under some circumstances, other channels may provide a small amount of additional information but in most cases the remaining channels only supply redundant information and do not justify the additional computation cost required to integrate them into an algorithm.

Proceedings Article | 12 January 2005 Paper

A combined lidar and radar retrieval of cloud optical properties

John Haynes, Cristian Mitrescu, Graeme Stephens

Proceedings Volume 5653, (2005) https://doi.org/10.1117/12.578929

KEYWORDS: LIDAR, Particles, Clouds, Radar, Crystals, Optical spheres, Solids, Mass attenuation coefficient, Signal attenuation, Backscatter

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Proceedings Article | 11 November 1991 Paper

Radiative transfer in the cloudy atmosphere: modeling radiative transport

Philip Gabriel, Graeme Stephens, Si Chee Tsay

Proceedings Volume 1558, (1991) https://doi.org/10.1117/12.49614

KEYWORDS: Clouds, Optical properties, Radiative transfer, Scattering, Atmospheric modeling, Absorption, Earth's atmosphere, Wave propagation, Solar radiation, Liquids

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Showing 5 of 14 publications

SPIE Conference Volume | 8 December 2008

Remote Sensing of the Atmosphere and Clouds II

Conference Committee Involvement (4)

Remote Sensing of the Atmosphere, Clouds, and Precipitation VII

24 September 2018 | Honolulu, Hawaii, United States

Remote Sensing of the Atmosphere, Clouds, and Precipitation V

13 October 2014 | Beijing, China

Remote Sensing of the Atmosphere, Clouds, and Precipitation IV

29 October 2012 | Kyoto, Japan

Remote Sensing of the Atmosphere and Clouds II

18 November 2008 | Noumea, New Caledonia

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