Methodology of Evaluating the Science Benefit of Various Satellite/Sensor Constellation Orbital Parameters to an Assimilative Data Forecast Model
Abstract
A methodology for evaluating the science benefit of adding space weather sensor data from a modest number of small satellites to the Utah State University Global Assimilation of Ionospheric MeasurementsFull Physics (GAIMFP) model is presented. Three orbital scenarios are presented, two focusing on improved coverage of narrowly specified regions of interest, and one on global coverage of the ionosphere as a whole. An Observing System Simulation Experiment is used to obtain qualitative and quantitative results of the impact of the various orbital scenarios on the ionospheric specifications. A simulated truth run of the ionosphere is obtained from a first principle model of the ionosphere/plasmasphere model and used to generate global simulated Global Positioning Satellite total electron content (GPSTEC) data as well as in situ plasma density observations. Initially, only GPS data were assimilated by GAIMFP, and the results of this limited run were compared to the truth run. Next, the simulated in situ plasma densities corresponding to our three orbital scenarios were assimilated together with the GPS data, and the results were compared to both the truth run and the limited GPSTEC only GAIMFP run. These model simulations have shown that adding a constellation of small satellites/sensors in addition to global TEC inputs does indeed converge the GAIMFP model closer to truth in the situations described.
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 06, 2015
- Accession Number
- AD1013465
Entities
People
- Brandon Mueller
- C L Enloe
- David J. Barnhart
- Lance T. Wilhelm
- Ludger Scherliess
- Matthew. G. Mcharg
- Richard L. Balthazor
- Robert M. Brown
- Zachary W. Hoeffner
Organizations
- United States Air Force Academy