The goal of this project is to determine the operational usefulness of the GOES-R Proving Ground convection initiation (CI) products developed and distributed by the Cooperative Institute for Meteorological Satellite Studies (CIMSS). Previous research has shown that the CI products do a reasonably good job of indicating convection and can even provide positive lead times of the convection for the forecaster. However, the products can also have a significant false alarm rate. This research will investigate conditions when the convection initiation products worked or did not work through an evaluation of the products related to the atmospheric conditions. The research will provide information to the forecaster regarding confidence levels and situations when the products will be beneficial to operations. In addition, the concept of “data fusion” of satellite data with other environmental data sources will be explored. The analysis will be able to use either or both the CIMSS or University of Alabama algorithms.
The positive detection and false alarm situations will be obtained through a collection of convection initiation events. For positive detection cases, lead times will be analyzed. The events will be collected on a daily basis and then summarized on monthly and seasonal scales. Observed and modeled environmental data will also be collected to correlate positive and negative cases with various environmental characteristics. At the conclusion of the research, a thorough statistical analysis will be performed on the convection initiation products’ POD, FAR, and lead times. Of primary importance to operational forecasters will be an assessment of atmospheric conditions in which the products performed well and conditions in which they performed poorly.