SA42A-01:
Multimodel Ensemble Prediction System (MEPS) for the Ionosphere-Thermosphere-Electrodynamics System
Thursday, 18 December 2014: 10:20 AM
Robert Walter Schunk1, Ludger Scherliess2, Vincent Eccles1, Larry C Gardner1, Jan Josef Sojka1, Lie Zhu1, Xiaoqing Pi3, Anthony J Mannucci3, Mark Butala4, Brian D Wilson3, Attila Komjathy3, Chunming Wang5 and Gary Rosen5, (1)Utah State University, Logan, UT, United States, (2)Utah State Univ, Logan, UT, United States, (3)Jet Propulsion Laboratory, Pasadena, CA, United States, (4)NASA Jet Propulsion Laboratory, Pasadena, CA, United States, (5)University of Southern California, Los Angeles, CA, United States
Abstract:
As part of the NASA-NSF Space Weather Modeling Collaboration, we created a Multimodel Ensemble Prediction System (MEPS) for the Ionosphere-Thermosphere-Electrodynamics (I-T-E) system that is based on data assimilation models. MEPS is composed of 7 first-principles-based data assimilation models for the ionosphere, ionosphere-plasmasphere, thermosphere, high-latitude ionosphere-electrodynamics, and mid-low latitude ionosphere-electrodynamics. The data assimilation models cover the globe, and ensemble modeling can be conducted for mid-low latitude ionospheric studies because 5 different data assimilation models cover this domain. For this domain, the comparison of the resulting reconstructions should help distinguish between the underlying physics and model artifacts. The MEPS models can assimilate a range of ground and space observations, including GPS-TEC, ionosonde-digisonde, in situ electron density, occultation, and ultraviolet emission measurements. The long-range goal of the program is to improve space weather specification and forecasting with ensemble modeling. Selected ionospheric events that were reconstructed with more than one data assimilation model will be presented and compared.
