The goal of this presentation is to describe a new evaluation project that is designed to determine the usefulness of the GOES-R Proving Ground convection initiation (CI) products. The project will investigate products developed and distributed by the Cooperative Institute for Meteorological Satellite Studies (CIMSS) and the University of Alabama-Huntsville (UAH) and used by the NWS forecaster. These products are designed to provide valuable information on a cloud field that has the potential to evolve upscale into convection. Two primary products are generated: a filtered cloud top cooling (CTC) rate, and from the CTC product, a CI nowcast is produced. The CI nowcast has three CI categories: pre-CI Cloud Growth, CI Likely, and CI Occurring. 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. An assessment of atmospheric conditions during both positive and negative situations from the use of these products has not been thoroughly completed. Therefore, the 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 proposed 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.

In order to determine the usefulness of the CI parameters for NWS forecasters, several specific research tasks are proposed. The major task will be to determine the POD, FAR, and lead times of the CI products and determine the atmospheric conditions during the CI events. The thought is to collect all CI pixels, Pre-CI cloud growth, CI likely, and CI occurring when a parameter is calculated and follow the event through time to determine if convection occurred or not. Convection will be determined by using the radar reflectivity returns greater than a 35 dBZ value on the 0.5 degree elevation angle. Pixels will be grouped together where feasible and followed as a group. Once a CI parameter is identified, a data report will be made for the event and recorded for further analysis. 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. We expect to learn when the products will be the most beneficial to forecasters, as well as how to best incorporate environmental data into the use of the products to accurately predict where and when convection initiation will occur. This knowledge will also improve the forecaster's ability to maintain and improve situational awareness of the convective environment.