Record Display for the EPA National Library Catalog


Main Title Estimating cloud paramters [i.e. parameters] for NEROS I /
Author Vukovich, Fred M.
Other Authors
Author Title of a Work
Erlich, D. P.
Publisher U.S. Environmental Protection Agency, Environmental Sciences Research Laboratory ; Center for Environmental Research Information [distributor],
Year Published 1982
Report Number EPA/600-S3-82-011
OCLC Number 09472111
Subjects Cloud physics ; Atmospheric ozone--United States
Internet Access
Description Access URL
Library Call Number Additional Info Location Last
EJBD ARCHIVE EPA 600-S3-82-011 In Binder Headquarters Library/Washington,DC 04/11/2018
EJBD  EPA 600-S3-82-011 In Binder Headquarters Library/Washington,DC 11/14/2018
Collation 3 pages ; 28 cm
Caption title. At head of title: Project summary. "Sept. 1982." "EPA/600-S3-82-011."
Contents Notes
Geosynchronous Orbiting Earth Satellite infrared and visible imagery were combined with surface and upper-air meteorological observations to determine cloud amounts and cloud-top heights over the Northeast Regional Oxidant Study grid for 1200, 1500, and 1800 EOT, on August 3,4, and 13, 1979. Cloud amounts were determined for cumulus clouds alone and for all clouds. Cloud-top heights were determined specifically for cumulus clouds. A study was begun to develop a model that could be used to estimate the parameters of the cloud ozone flux. Several models were developed to estimate the average maximum cloud vertical velocity; the best model developed was a multiple linear regression model. The model input parameters were the cloud-top height and the cloud amount, which were derived from satellite imagery. This model yielded an average correlation coefficient of -0.78 and a root mean square difference of «0.8 m/s~1. On the average, with the use of the multiple linear regression model, there was a 24% error in the estimated average cloud vertical velocity. However, the modeling results were not statistically significant because of the limited data available for developing the model. The total number of data points was nine, but only seven were useful.