Ionospheric Ensemble Forecasting System

The main objective of this proposal is to provide a modeling, assimilation, forecasting, and data analysis platform to support the Communication / Navigation Outage Forecasting System (C/NOFS) mission of the AFRL. The system will combine several components developed by Fusion Numerics Inc. along with new specialized modules. The goal of the C/NOFS mission is to understand the physics of the ionosphere in equatorial regions and to forecast accurately the subsequent scintillation-producing irregularities. To meet this goal, we propose a system based on the synthesis of several unique techniques developed during prior SBIR funded projects: (1) an artificial intelligence algorithm known as Support Vector Machine for predicting changes in solar wind from solar images; (2) an empirical model of electric field potentials; (3) a physics-based assimilative ionospheric model for forecasting ionospheric dynamics; and (4) a model and forecast uncertainty evolution scheme based on ensemble Kalman filter. Additionally, we propose a novel infrastructure for a modular unified forecast system. Such an infrastructure will allow practitioners to easily replace models of ionospheric components as they become available. The infrastructure will rely on ESML (Earth Science Markup Language) and SOAP (Simple Object Access Protocol) based web-services for model interfacing, data stream integration and data distribution.