Emulating and Calibrating the Lyon-Fedder-Mobarry Magnetosphere-Ionosphere Coupled Computer Model Using Predictive Processes

• Activity Number: 456
• Type: Topic Contributed
• Date/Time: Wednesday, August 1, 2012 : 8:30 AM to 10:20 AM
• Sponsor: Section on Statistics and the Environment
• Author(s): Matthew Heaton*+ and Stephan Sain and William Kleiber and Michael Wiltberger
• Companies: National Center for Atmospheric Research and Geophysical Statistics Project and National Center for Atmospheric Research and National Center for Atmospheric Research
• Keywords: Gaussian Process ; Dimension Reduction ; Ionosphere ; Magentosphere

Abstract

The Lyon-Fedder-Mobarry global magnetosphere-ionosphere coupled (LFM-MIX) model is a multiple fidelity computer model used to study sun-earth interactions by simulating aspects of geomagnetic storms. Higher fidelities of the LFM-MIX model require more computation but, ultimately, more accurately capture the governing physical processes under study. This work focuses on relating the output from the LFM-MIX model run at different fidelities to field observations of ionospheric energy. Of particular interest here are the input settings (and their uncertainties) for the LFM-MIX model such that output most closely matches the field observations. To estimate these input settings, a low rank spatio-temporal statistical LFM-MIX model emulator is constructed using predictive processes. The statistical emulator leverages the multiple fidelities of the LFM-MIX model to achieve calibration of the input variables to field observations. In this way, the less computationally demanding yet lower fidelity LFM-MIX modl is leveraged to provide estimates of the higher fidelity LFM- MIX model output. The higher fidelity LFM-MIX output is then, in turn, used for calibration of the input parameters.