Open AccessExploring predictive performance: A reanalysis of the geospace model transition challenge
Author(s) -
Welling D. T.,
Anderson B. J.,
Crowley G.,
Pulkkinen A. A.,
Rastätter L.
Publication year - 2017
Publication title -
space weather
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.254
H-Index - 56
ISSN - 1542-7390
DOI - 10.1002/2016sw001505
Subject(s) - empirical modelling , earth's magnetic field , computer science , function (biology) , environmental science , range (aeronautics) , meteorology , econometrics , physics , mathematics , simulation , aerospace engineering , magnetic field , engineering , quantum mechanics , evolutionary biology , biology
Abstract The Pulkkinen et al. (2013) study evaluated the ability of five different geospace models to predict surface d B /d t as a function of upstream solar drivers. This was an important step in the assessment of research models for predicting and ultimately preventing the damaging effects of geomagnetically induced currents. Many questions remain concerning the capabilities of these models. This study presents a reanalysis of the Pulkkinen et al. (2013) results in an attempt to better understand the models' performance. The range of validity of the models is determined by examining the conditions corresponding to the empirical input data. It is found that the empirical conductance models on which global magnetohydrodynamic models rely are frequently used outside the limits of their input data. The prediction error for the models is sorted as a function of solar driving and geomagnetic activity. It is found that all models show a bias toward underprediction, especially during active times. These results have implications for future research aimed at improving operational forecast models.