NASA/NOAA MOU Annex Final Report: Evaluating Model Advancements for Predicting CME Arrival Time
M. L. Mays, P. J. MacNeice, A. Taktakishvili, C. P. Wiegand, J. Merka, E. T. Adamson, V. J. Pizzo, D. A. Biesecker, A. R. Marble, D. Odstrcil, C. J. Henney, C. N. Arge, S. I. Jones, S. Wallace

TL;DR
This study evaluates the improvements in predicting CME arrival times at Earth using an advanced data-driven model, showing that time-dependent magnetogram inputs can reduce forecast errors compared to older methods.
Contribution
The paper introduces an enhanced CME prediction approach using the ADAPT-WSA-ENLIL model with time-dependent magnetogram data, demonstrating improved accuracy over previous benchmarks.
Findings
CME arrival time error decreased by up to 0.9 hours with time-dependent data.
Using zero-point corrected magnetograms improved forecast accuracy.
The new model outperformed the operational benchmark in recent events.
Abstract
The purpose of this project was to assess improvements in CME arrival time forecasts at Earth using the Air Force Data Assimilative Photospheric Flux Transport (ADAPT) model driven by data from the Global Oscillation Network Group (GONG) ground observatories. These outputs are then fed into the coupled Wang-Sheeley-Arge (WSA) - ENLIL model and compared to an operational version of WSA-ENLIL (without ADAPT). SWPC selected a set of 38 historical events over the period of five years from 2012--2014 (33 events) and 2017--2019 (5 events). The overall three-year project consisted of multiple simulation validation studies for the entire event set (1292 simulations): (a) benchmark single map (operational version prior to May 2019) (b) time-dependent sequence of GONG maps driving WSA-ENLIL with 4 different model settings (c) single test simulation of a time-dependent sequence of GONG maps…
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Taxonomy
TopicsIonosphere and magnetosphere dynamics · Meteorological Phenomena and Simulations · Atmospheric Ozone and Climate
