Assessing the performance of community‐available global MHD models using key system parameters and empirical relationships

Global magnetohydrodynamic (MHD) modeling is a powerful tool in space weather research and predictions. There are several advanced and still developing global MHD (GMHD) models that are publicly available via Community Coordinated Modeling Center's (CCMC) Run on Request system, which allows the users to simulate the magnetospheric response to different solar wind conditions including extraordinary events, like geomagnetic storms. Systematic validation of GMHD models against observations still continues to be a challenge, as well as comparative benchmarking of different models against each other. In this paper we describe and test a new approach in which (i) a set of critical large-scale system parameters is explored/tested, which are produced by (ii) specially designed set of computer runs to simulate realistic statistical distributions of critical solar wind parameters and are compared to (iii) observation-based empirical relationships for these parameters. Being tested in approximately similar conditions (similar inputs, comparable grid resolution, etc.), the four models publicly available at the CCMC predict rather well the absolute values and variations of those key parameters (magnetospheric size, magnetic field, and pressure) which are directly related to the large-scale magnetospheric equilibrium in the outer magnetosphere, for which the MHD is supposed to be a valid approach. At the same time, the models have systematic differences in other parameters, being especially different in predicting the global convection rate, total field-aligned current, and magnetic flux loading into the magnetotail after the north-south interplanetary magnetic field turning. According to validation results, none of the models emerges as an absolute leader. The new approach suggested for the evaluation of the models performance against reality may be used by model users while planning their investigations, as well as by model developers and those interesting to quantitatively evaluate progress in magnetospheric modeling.

[1]  A. Vapirev,et al.  Geospace Environment Modeling 2008–2009 Challenge: Geosynchronous magnetic field , 2011 .

[2]  A. Ridley A new formulation for the ionospheric cross polar cap potential including saturation effects , 2005 .

[3]  Hideaki Kawano,et al.  Magnetopause location under extreme solar wind conditions , 1998 .

[4]  T. Pulkkinen,et al.  Stormtime energy transfer in global MHD simulation , 2003 .

[5]  Frederick J. Rich,et al.  A nearly universal solar wind-magnetosphere coupling function inferred from 10 magnetospheric state variables , 2007 .

[6]  V. Angelopoulos,et al.  Dynamical response of the magnetotail to changes of the solar wind direction: an MHD modeling perspective , 2008 .

[7]  Raymond A. Greenwald,et al.  Dependencies of high-latitude plasma convection: Consideration of interplanetary magnetic field, seasonal, and universal time factors in statistical patterns , 2005 .

[8]  V. Sergeev,et al.  Verification of the GUMICS‐4 global MHD code using empirical relationships , 2013 .

[9]  T. Fuller‐Rowell,et al.  OpenGGCM Simulations for the THEMIS Mission , 2008 .

[10]  W. Hughes,et al.  Finding the Lyon-Fedder-Mobarry magnetopause : A statistical perspective , 2007 .

[11]  J. Lyon,et al.  Initial results from a dynamic coupled magnetosphere‐ionosphere‐ring current model , 2012 .

[12]  Daniel T. Welling,et al.  Geospace environment modeling 2008–2009 challenge: Dst index , 2013 .

[13]  D. L. De Zeeuw,et al.  Multi-Scale Modeling of Magnetospheric Reconnection. , 2007 .

[14]  T. Pulkkinen,et al.  The GUMICS-4 global MHD magnetosphere-ionosphere coupling simulation , 2012 .

[15]  R. Walker,et al.  Observations and simulations of a highly structured plasma sheet during northward IMF , 2010 .

[16]  A. Ridley,et al.  On the performance of global magnetohydrodynamic models in the Earth's magnetosphere , 2013 .

[17]  A. Vapirev,et al.  Geospace Environment Modeling 2008–2009 Challenge: Ground magnetic field perturbations , 2011 .

[18]  Toshiaki Tanaka,et al.  Substorm convection and current system deduced from the global simulation , 2010 .

[19]  Freddy Christiansen,et al.  A new model of field‐aligned currents derived from high‐precision satellite magnetic field data , 2002 .

[20]  Patricia H. Reiff,et al.  Empirical polar cap potentials , 1997 .

[21]  Daniel T. Welling,et al.  Validation of SWMF magnetic field and plasma , 2010 .

[22]  F. Rich,et al.  High‐latitude ionospheric convection models derived from Defense Meteorological Satellite Program ion drift observations and parameterized by the interplanetary magnetic field strength and direction , 2002 .

[23]  J. Borovsky Physics‐based solar wind driver functions for the magnetosphere: Combining the reconnection‐coupled MHD generator with the viscous interaction , 2013 .

[24]  D. Fairfield,et al.  Variability of the tail lobe field strength , 1996 .

[25]  R. Greenwald,et al.  On the observed variability of the cross–polar cap potential , 2004 .

[26]  Xiaoye Zhang,et al.  A three-dimensional asymmetric magnetopause model , 2010 .

[27]  R. McPherron,et al.  7 – Physical Processes Producing Magnetospheric Substorms and Magnetic Storms , 1991 .

[28]  John Lyon,et al.  The Lyon-Fedder-Mobarry (LFM) global MHD magnetospheric simulation code , 2004 .

[29]  T. Mukai,et al.  Tail plasma sheet models derived from Geotail particle data , 2003 .

[30]  F. Toffoletto,et al.  Inner magnetospheric modeling with the Rice Convection Model , 2003 .

[31]  T. Pulkkinen,et al.  Magnetospheric convection during intermediate driving: Sawtooth events and steady convection intervals as seen in Lyon-Fedder-Mobarry global MHD simulations , 2007 .

[32]  David R. Chesney,et al.  Space Weather Modeling Framework: A new tool for the space science community , 2005, Journal of Geophysical Research.

[33]  N. Tsyganenko Solar wind control of the tail lobe magnetic field as deduced from Geotail, AMPTE/IRM, and ISEE 2 data , 2000 .

[34]  D. Weimer,et al.  Improved Ionospheric Electrodynamic Models and Application to Calculating Joule Heating Rates , 2005 .

[35]  J. Ruohoniemi,et al.  Substorm‐associated changes in large‐scale convection during the November 24, 1996, Geospace Environment Modeling event , 2001 .

[36]  Gábor Tóth,et al.  Sun‐to‐thermosphere simulation of the 28–30 October 2003 storm with the Space Weather Modeling Framework , 2007 .

[37]  R. Walker,et al.  On the importance of accurate solar wind measurements for studying magnetospheric dynamics , 2008 .

[38]  Toshiaki Tanaka,et al.  Fundamental properties of substorm time energetic electrons in the inner magnetosphere , 2013 .