Long-term Ionospheric Forecasting System

Period of Performance: 07/03/2003 - 04/30/2004


Phase 1 SBIR

Recipient Firm

Environmental Research Technologies
3291 Cripple Creek Trail
Boulder, CO 80305
Principal Investigator


The objective of the proposed effort is to investigate the feasibility of an end-to-end global long-term ionospheric forecast model based on a fusion of several diverse technologies and to develop the related probability density function evolution formalism to characterize the forecast quality. In order to meet the stated goal of a 3-day forecast one has to address the complete chain of events starting from highly unpredictable changes in solar conditions to changes in the ionosphere. Ideally, the system would consist of several physics-based models, a sufficient number of observational data streams and a data assimilation system that provides for computing error covariance evolution. Presently, an end-to-end first-principles based assimilative system is impossible. We propose a practical system based on a synthesis of several different technologies: (1) an artificial intelligence algorithm known as Support Vector Machines for predicting changes in solar wind from time sequences of solar images; (2) an empirical model of the high-latitude electric field potentials; and (3) a physics-based ionospheric model coupled with efficient Kalman filter for forecasting the final ionospheric parameters of interest. Additionally, we propose a prototype error propagation scheme for computing evolution of forecast probability density functions starting from errors of representativeness in the synoptic solar images to uncertainties in the final forecast. Improvements in space weather modeling and forecasting will be of immediate use for a number of practical military and civilian applications, particularly in satellite-based communications and navigation. Our commercialization strategy is based on the fact that contemporary space weather models are not capable of generating precise forecasts for use by those industries where solar and Ionospheric affects disrupt operations in a costly manner. At the same time, given our reliance and dependency on satellite and wireless communications such forecasts are of considerable interest to the private sector and the military to allow for operational planning instead of emergency reaction. In the private sector potential clients include: companies in satellite-based navigation (GPS industry); satellite-based communications, including high band width requirements and mission critical applications; cellular communications companies; power distribution concerns; and research institutions. Development of a physics-based ionospheric forecast system will address these needs and open up radically new commercial and military applications. To further substantiate commercial application of this technology we have established relationships in the commercial sector with major GPS service companies, confirmed by the enclosed letters of interest.