Rainfall Area Identification Using GOES Satellite Data
Journal
Journal of Irrigation and Drainage Engineering
Journal Volume
118
Journal Issue
1
Pages
179--190
Date Issued
1992-01
Author(s)
Sun F. Shih
Abstract
Geostationary operational environmental satellite (GOES) infrared (IR) images and rain gauge measurements are used to study five convective storm events in Florida. The study region is divided into a training area and a test area. An approach is initiated in this study to identify rainfall areas within GOES images using the coldest cloud-top temperature (CCTT) and the standard deviation of cloud-top temperatures (STD-DEV) within a group of pixels. A threshold value of satellite-derived cloud-top temperature is used to define the cloud-covered areas. GOES IR images are then divided into two categories: Expanding cloud images and contracting cloud images. The Bayesian optimal classifier using CCTT and STD-DEV is implemented to further classify the cloud pixels in each category into precipitation-free cloud pixels and precipitating cloud pixels. Cutoff rain rates from the gauge measurements are used to define the actual precipitation-free and precipitating pixels. The results show that the classification accuracies are about 73% in the training area, and 63% in test area. ? ASCE.
Other Subjects
Imaging Techniques; Remote Sensing--Agricultural Applications; Satellites--Geostationary; Coldest Cloud Top temperatures; Geostationary Operational Environmental Satellite (GOES); Infrared Images; Rainfall Area Identification; Rain and Rainfall
Type
journal article