An Enhanced Geostationary Satellite–Based Convective Initiation Algorithm for 0–2-h Nowcasting with Object Tracking

Abstract

AbstractThis paper describes an enhanced 0–2-h convective initiation (CI) nowcasting algorithm known as Satellite Convection Analysis and Tracking, version 2 (SATCASTv2). Tracking of developing cumulus cloud “objects” in advance of CI was developed as a means of reducing errors caused by tracking single satellite pixels of cumulus clouds, as identified in Geostationary Operational Environmental Satellite (GOES) output. The method rests on the idea that cloud objects at one time, when extrapolated forward in space and time using mesoscale atmospheric motion vectors, will overlap with the same actual cloud objects at a later time. Significant overlapping confirms that a coherent cumulus cloud is present and trackable in GOES data and that it is persistent enough that various infrared threshold–based tests may be performed to assess cloud growth. Validation of the new object-tracking approach to nowcasting CI was performed over four regions in the United States: 1) Melbourne, Florida; 2) Memphis, Tennessee; 3) the central United States/Great Plains; and 4) the northeastern United States as a means of evaluating algorithm performance in various convective environments. In this study, 9943 CI nowcasts and 804 CI events were analyzed. Optimal results occurred in the central U.S./Great Plains domain, where the probability of detection (POD) and false-alarm ratio (FAR) reached 85% and 55%, respectively, for tracked cloud objects. The FARs were partially attributed to difficulties inherent to the CI nowcasting problem. PODs were seen to decrease for CI events in Florida. Discussion is provided on how SATCASTv2 performed, as well as on how certain problems may be mitigated, especially in light of enhanced geostationary-satellite systems.