Convection Initiation Forecasting Using Synthetic Satellite Imagery from the Warn-on-Forecast System

Abstract

Forecasting convection initiation (CI) has advanced greatly during the past decade through the use of high-resolution satellite observations and model output. One of the primary CI products used in forecast operations is based on GOES-16 visible and infrared imagery along with GLM lightning flash detections to determine the location of growing ice-containing cumulus clouds that are the precursor to developing thunderstorms. Another approach to CI forecasting that has recently become available is high frequency output from numerical weather prediction (NWP) models such as the Warn-on-Forecast System (WoFS). NWP model simulated composite reflectivity forecasts are one method used to determine when and where severe thunderstorms might develop. However, waiting for high reflectivity (> 40 dBZ) to be created within the NWP model limits the potential lead time available to forecasters when using WoFS output to anticipate areas where convection might form.Also, forecast reflectivity alone does not always give an indication of whether or not the precipitation developed by the NWP model is convective in nature. To address these limitations, this work applies a CI forecasting methodology developed for GOES satellite data on synthetic satellite imagery produced from WoFS output. Forecast cloud objects are tracked over a 10-min interval and CI forecasting parameters are applied to determine whether or not these cloud objects will continue to develop into organized thunderstorms.