Dr. Jules R. Dim Profile

Dr. Jules R. Dim

Manager at Denka

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Publications (8)

SPIE Journal Paper | 25 September 2013

Performance of the GCOM-C/SGLI satellite prelaunch phase cloud properties’ algorithm

Jules Dim, Takahashi Nakajima, Tamio Takamura

JRS Vol. 7 Issue 01

KEYWORDS: Clouds, Satellites, Commercial off the shelf technology, MODIS, Detection and tracking algorithms, Sensors, Atmospheric corrections, Absorption, Water, Reflectivity

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Proceedings Article | 19 February 2013 Paper

Decomposition of satellite-derived images for the distinction of cloud types' features

Jules Dim, Hiroshi Murakami

Proc. SPIE. 8655, Image Processing: Algorithms and Systems XI

KEYWORDS: Clouds, Satellites, Thermography, Image segmentation, Image classification, Satellite imaging, Earth observing sensors, Climatology, Convection, Optical properties

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Proceedings Article | 2 February 2012 Paper

Application of spatial contrast techniques on satellite imagery for cloud shape differentiation

Jules Dim, Hiroshi Murakami

Proc. SPIE. 8295, Image Processing: Algorithms and Systems X; and Parallel Processing for Imaging Applications II

KEYWORDS: Clouds, Satellites, Satellite imaging, Earth observing sensors, Optical properties, Shape analysis, Climatology, Atmospheric physics, Radiometry, Thermography

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Proceedings Article | 4 February 2011 Paper

Signal filtering of daily cloud types' trends as derived from satellite images

Jules Dim, Hiroshi Murakami

Proc. SPIE. 7870, Image Processing: Algorithms and Systems IX

KEYWORDS: Clouds, Satellites, Satellite imaging, Earth observing sensors, Thermography, Image filtering, Electronic filtering, Image classification, Infrared imaging, Infrared radiation

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Proceedings Article | 8 February 2010 Paper

Use of satellite image enhancement procedures for global cloud identification

J. Dim, H. Murakami, M. Hori

Proc. SPIE. 7532, Image Processing: Algorithms and Systems VIII

KEYWORDS: Clouds, Satellites, Climatology, Satellite imaging, Image enhancement, Earth observing sensors, Convection, Climate change, Carbon dioxide, Infrared imaging

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Proceedings Article | 29 September 2009 Paper

Sensitivity of atmospheric circulation models to upper tropospheric relative humidity derived from satellite observed radiances

J. Dim, H. Murakami, T. Nakajima, T. Takamura, M. Hori

Proc. SPIE. 7475, Remote Sensing of Clouds and the Atmosphere XIV

KEYWORDS: Clouds, Atmospheric modeling, Data modeling, Satellites, Atmospheric sensing, Troposphere, Humidity, Convection, Earth observing sensors, Atmospheric particles

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Meso-scale atmospheric models outputs are valuable data for cloud and aerosols retrievals. In view of the launch the Global Change Observation Mission-Climate/Second generation Global Imager (GCOM-C/SGLI) satellite, atmospheric models products are tested against satellite observations data in order to evaluate the degree of reliability and the sensitivity of these models outputs to variations of atmospheric conditions. The analyses presented in this study are based on two models outputs: the Nonhydrostatic Icosahedral Atmospheric Model (NICAM) and the National Center for Environmental Protection/Department Of Energy (NCEP/DOE) re-analysis-2 data. Terra/Moderate Resolution Imaging Spectrometer (Terra/MODIS) satellite sensor observations of water vapor radiances are used as the verification data set for the tests conducted. These tests are based on the comparison between upper tropospheric water vapor properties (clear sky and above-low clouds) observed by satellite and radiative transfer forward calculations (using models' predicted atmospheric profiles, the satellite sensor spectral response and geometrical characteristics) derived from NICAM and NCEP/DOE. The parameters measured are the upper tropospheric brightness temperature (UTBT) and relative humidity (UTRH). Discrepancies between simulated data and observations are analyzed in terms of atmospheric instability, cloud convection movements and, effective emissivity. The results obtained show that both NICAM and NCEP/DOE simulated UTBT and UTRH outputs have a relatively comparable distribution pattern. However, simulations performed with the NCEP/DOE outputs present generally fewer discrepancies with satellite observations. For the interpretation of these results, the stability index study shows that differences between models and observation data tend to be high in unstable atmospheres. This atmospheric instability can be attributed to cloud convection processes affecting areas adjacent to convective clouds. As the amount of convective clouds increases, the errors in the water vapour depiction by the models increase also. Analyses of heat movements studied through the variation of the cloud effective emissivity suggest that the discrepancies between the observations and the models increase with the decrease of the clouds' effective emissivity. Adjustments of some of the models parameters, notably the microphysical parameterization of the clouds resolving scheme, are suggested in order to improve the accuracy of the models' results.

Proceedings Article | 9 October 2007 Paper

Vegetation canopy optical and structural variability based on radiometric and laser analysis

Jules Dim, Koji Kajiwara, Yoshiaki Honda

Proc. SPIE. 6742, Remote Sensing for Agriculture, Ecosystems, and Hydrology IX

KEYWORDS: Vegetation, Reflectivity, Near infrared, Laser scanners, Solar radiation, Remote sensing, Solar radiation models, Data modeling, Radio optics, Airborne laser technology

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Proceedings Article | 29 October 2005 Paper

Three-dimensional radiative effects on cloud variability and structural inhomogeneity as observed by satellites

J. Dim, T. Takamura, I. Okada, T. Nakajima, H. Takenaka

Proc. SPIE. 5979, Remote Sensing of Clouds and the Atmosphere X

KEYWORDS: Clouds, MODIS, Satellites, Reflectivity, Earth observing sensors, Sensors, Spatial resolution, Solar radiation, Optical properties, Infrared radiation

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Showing 5 of 8 publications

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