Extended Abstract (200K)2.7
Validation of a neural network based MODIS global cloud mask using ground-based instruments
Todd Berendes, Univ. of Alabama, Huntsville, AL; and D. A. Berendes, R. M. Welch, E. E. Clothiaux, E. G. Dutton, P. Minnett, and T. Uttal
A general purpose satellite cloud mask validation system is being developed. This system assimilates and extracts coincident data from multiple sources and generates intercomparisons between satellite and surface based measures of cloud cover. Currently, a neural network based MODIS cloud mask is being used for comparison. However, the system is general enough to accommodate virtually any kind of satellite data.
The Cloud Valdation and Database Retreival System (CVDRS) consists of a database of cloud instrument data and a set of programs which extract and process data. The cloud validation database is a compilation of instrument data at specific site locations for a limited time range. Three of the Atmospheric Radiation Measurement Program (ARM) sites are chosen for the initial database. Vaisala ceilometer, Whole Sky Imager and Micropulse Lidar are chosen as the initial cloud instruments. Surface observations at nearby airports are also included.
Results from the MODIS cloud mask are intercompared with the ground based methods. Strengths, weaknesses and limitations of the various instruments are discussed. The system may be expanded to inculde any instrument capable of deriving cloud cover. Improved algorithms for cloud determination from instruments may also be included.
Session 2, IIPS Applications in Satellites and Satellite Programs
Monday, 14 January 2002, 1:30 PM-5:15 PM
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