A Real-time Cloud Seeding Guidance System based on the WRF Model: System refinements and new results

A prototype real-time cloud seeding modeling framework has been created, tested, and evaluated. This system utilizes a silver iodide (AgI) cloud seeding parameterization implemented in a real-time forecast version of the Weather Research and Forecasting (WRF) model. As part of this system, a seeding case calling algorithm was developed in order to automatically identify seeding opportunities based on the model forecast, and then simulate those seeding events to generate a real-time seeding forecast. This system has been run for two winter seasons over Idaho. An evaluation of the model's performance during each season has been conducted and has led to improvements to the system. The evaluation utilizes observations from precipitation gauges, radiometers, and soundings in the region to assess the forecast model performance, as well as compares seeding cases called by the model's case calling algorithm against seeding decisions made by Idaho Power forecasters. This paper presents the real-time model set up, analysis done to evaluate the performance of the modeling system, and preliminary results of the newly refined system.