Improving Aerosol and Visibility Forecasting Capabilities Using Current and Future Generations of Satellite Observations

Accurate visibility forecasts, being necessary for military operations and field applications of optically-sensitive equipment such as advanced electro-optical (EO) systems, remain as a challenging scientific problem. One reason is because large spatial and temporal variations exist, not only with a...

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Bibliographic Details
Main Author: Zhang, Jianglong
Other Authors: NORTH DAKOTA UNIV GRAND FORKS DEPT OF ATMOSPHERIC SCIENCES
Format: Text
Language:English
Published: 2012
Subjects:
Atmospheric Physics
*FORECASTING
*SATELLITE IMAGERY
AEROSOLS
MULTISENSORS
OZONE
RADIATIVE TRANSFER
SPECTRORADIOMETERS
VISIBILITY
MODIS(MODERATE RESOLUTION IMAGING SPECTRORADIOMETER)
MISR(MULTIANGLE IMAGING SPECTRORADIOMETER)
OMI(OZONE MONITORING INSTRUMENT)
GOES(GEOSTATIONARY OPERATIONAL ENVIRONMENTAL SATELLITE)
AERONET(AEROSOL ROBOTIC NETWORK)
MPLNET(MICROPULSE LIDAR NETWORK)
DATA ASSIMILATION
OPTICAL DEPTH
PARAMETERIZATION
Aerosol Robotic Network
Online Access:http://www.dtic.mil/docs/citations/ADA574587
http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA574587
Description
Summary:Accurate visibility forecasts, being necessary for military operations and field applications of optically-sensitive equipment such as advanced electro-optical (EO) systems, remain as a challenging scientific problem. One reason is because large spatial and temporal variations exist, not only with aerosol physical and optical properties, but with emission sources. Clearly, to further advance aerosol forecasts and aerosol modeling studies, it is necessary to combine modeling and observational based studies through the use of space-borne observations from current and future aerosol-sensitive sensors. The long-term goal of this study is to improve the Navy s electro-optical propagation forecast capability through the use of multi-channel and multi-sensor aerosol data assimilation. The original document contains color images.

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