Developing an Algorithm to Investigate Cloud Lifetime using GOES Thermal Channel Information

Clouds continually change shape and position over time, so it is difficult to track them. This work presents the performance of an algorithm investigating cloud lifetime employed cloud top brightness temperature. Our approach to cloud investigation involves use of GOES satellite channel-4 to track clouds, locate clouds, determine cloud sizes, etc. GOES satellite data files in AREA format were ordered from the Comprehensive Large Array-data Stewardship System (CLASS) website. To be able to read GOES data in MATLAB, we used NOAA's Weather and Climate Toolkit to convert AREA format to NETCDF. A MATLAB code has generated to read NETCDF data files and produce cloud top images that tell a story of cloud formation and dissipation from June 1st to September 1st in 2003.

For tracking clouds, only two days of June 1st and June 2nd were used as study time. There was a big cloud mass over the study area in the early morning, June 1st, 2003. Most region of the cloud had very cold cloud-top temperature. Eventually, this cloud mass floated to the east, and finally moved away from the study area at midnight. June 2nd had a clear sky and no major clouds. Therefore, the temperature of ground surface in study area was viewed. This algorithm gives an idea on how cloud-top brightness temperature can be used for computing cloud lifetime. It may help many people with their researches.