Joint Session J1.4 Forecasting Convective Initiation by Monitoring the Evolution of Moving Cumulus in Daytime GOES Imagery

Tuesday, 5 October 2004: 2:15 PM
Kristopher M. Bedka, CIMSS/Univ. of Wisconsin, Madison, WI; and J. R. Mecikalski, S. J. Paech, T. Berendes, and U. S. Nair

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This study identifies the precursor signals of convective initiation from sequences of 15-minute time resolution 1 km visible (VIS) and 4-8 km infrared (IR) imagery from Geostationary Operational Environmental Satellite (GOES) instrument data. Convective initiation (CI) is defined for this study as the first detection of Weather Surveillance Radar(1988 Doppler (WSR-88D) reflectivities >= 30 dBz produced by convective clouds. Results indicate that CI may be forecasted up to 45 minutes in advance through the monitoring of key IR fields for convective clouds. This is made possible by the development and coincident use of three components of GOES data: 1) a cumulus cloud "mask" at 1 km resolution using VIS and IR data, 2) satellite-derived winds for tracking individual cumulus clouds in sequential imagery, and 3) IR brightness temperature and multi-spectral band differencing time trends. In effect, these techniques isolate only the cumulus convection in satellite imagery, track moving cumulus convection, and evaluate various IR cloud properties in time. CI is predicted by accumulating information within a satellite pixel that is attributed to the first occurrence of a >= 30 dBz radar echo. Through the incorporation of satellite tracking of moving cumulus clouds, this work represents a significant advance in the use of routinely available GOES data for monitoring several aspects of cumulus found important for nowcasting CI (0-1 hour forecasts). This presentation will highlight the development and performance of this CI nowcasting system for several convective events, each representing a unique thermodynamic environment and mesoscale forcing regime. In addition, current and future algorithm development will be discussed including validation efforts, the incorporation of lightning data for CI nowcasting, and nocturnal CI assessment methods.

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