Abstract
Infrared (IR) data from the Meteosat Second Generation (MSG) satellite are used to understand cloud-top signatures for growing cumulus clouds prior to known convective initiation (CI) events, or the first occurrence of a ≥35-dBZ echo from a new convective cloud. In the process, this study proposes how MSG IR fields may be used to infer three physical attributes of growing cumuli, cloud depth, cloud-top glaciation, and updraft strength, with limited information redundancy. These three aspects are observed as unique signatures within MSG IR data, for which this study seeks to relate to previous research, as well as develop a new understanding on which subset of IR information best identifies these attributes. Data from 123 subjectively identified CI events observed during the 2007 Convection and Orograpically Induced Precipitation Study (COPS) field experiment conducted over southern Germany and northeastern France are processed, per convective cell, to meet this study’s objectives. A total of 67 IR “interest fields” are initially assessed for growing cumulus clouds, with correlation and principal component analyses used to highlight the top 21 fields that are considered the best candidates for describing the three attributes. Using between 6 and 8 fields per category, a method is then proposed on how growing convective clouds may be quantified per 3-km2 pixel (or per cumulus cloud object) toward inferring each attribute. No independent CI-nowcasting analysis is performed, which instead is the subject of ongoing research.
Corresponding author address: John R. Mecikalski, Atmospheric Science Dept., University of Alabama in Huntsville, NSSTC, 320 Sparkman Dr., Huntsville, AL 35805-1912. Email: john.mecikalski@nsstc.uah.edu
