Trend and abrupt changes in long‐term geomagnetic indices

Advanced statistical methods are employed to analyze three long-term time series of geomagnetic activity indices (aa, IHV, and IDV) together with sunspot number (Rz) to examine whether or not the aa index can realistically represent long-term variations of geomagnetic activity. We make use of a decomposition method called STL, which is a time domain filtering procedure that decomposes a time series into trend, cyclic, and residual components using nonparametric regression. A Bayesian change point analysis is also applied to the geomagnetic indices, as well as to sunspot number, to detect abrupt changes that may be caused by either instrumental changes, calibration errors, or sudden changes in solar activity. Our analysis shows that all three long-term geomagnetic indices share a similar centennial-scale variation that resembles the long-term trend of sunspot number Rz. The amplitude ratio between the centennial-scale variation and 11-year cycle of aa and IHV are closely comparable. Overall, our analysis suggests that the majority of the changes in the aa index are controlled by solar activity. Instrumental change or site relocation has only a limited effect on the long-term trend of aa. This is in good agreement with those previous studies which have shown aa to be a reliable long-term index.

[1]  K. Mursula,et al.  Effects of station relocation in the aa index , 2009 .

[2]  V. Courtillot,et al.  Evidence for solar forcing in variability of temperatures and pressures in Europe , 2008 .

[3]  J. Love Long-term biases in geomagnetic K and aa indices , 2011 .

[4]  Thomas Ulich,et al.  Reconstructing the long‐term aa index , 2005 .

[5]  J. Love Secular trends in storm-level geomagnetic activity , 2011 .

[6]  R. Stamper,et al.  A doubling of the Sun's coronal magnetic field during the past 100 years , 1999, Nature.

[7]  M. Lockwood,et al.  THE RISE AND FALL OF OPEN SOLAR FLUX DURING THE CURRENT GRAND SOLAR MAXIMUM , 2009 .

[8]  Edward W. Cliver,et al.  IHV: a new long-term geomagnetic index , 2004 .

[9]  Bruce T. Tsurutani,et al.  Interplanetary origin of geomagnetic storms , 1999 .

[10]  J. Bartels Terrestrial-magnetic activity and its relations to solar phenomena , 1932 .

[11]  Chandra Erdman,et al.  bcp: An R Package for Performing a Bayesian Analysis of Change Point Problems , 2007 .

[12]  Thomas Ulich,et al.  The causes of long-term change in the aa index , 2002 .

[13]  Irma J. Terpenning,et al.  STL : A Seasonal-Trend Decomposition Procedure Based on Loess , 1990 .

[14]  H. Rishbeth,et al.  Increased magnetic storm activity from 1868 to 1995 , 1998 .

[15]  M. Raupach,et al.  Decomposition of vegetation cover into woody and herbaceous components using AVHRR NDVI time series , 2003 .

[16]  D. Barry,et al.  Bayesian disease mapping using product partition models , 2008, Statistics in medicine.

[17]  Chandra Erdman,et al.  A fast Bayesian change point analysis for the segmentation of microarray data , 2008, Bioinform..

[18]  J. Hartigan,et al.  A Bayesian Analysis for Change Point Problems , 1993 .

[19]  Edward W. Cliver,et al.  Solar variability and climate change: Geomagnetic aa index and global surface temperature , 1998 .

[20]  E. Cliver,et al.  Heliospheric magnetic field 1835-2009 , 2010, 1002.2934.

[21]  W. Cleveland,et al.  Locally Weighted Regression: An Approach to Regression Analysis by Local Fitting , 1988 .

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

[23]  M. Lockwood,et al.  Centennial changes in the heliospheric magnetic field and open solar flux: The consensus view from geomagnetic data and cosmogenic isotopes and its implications , 2011 .

[24]  M. Lockwood,et al.  Solar causes of the long-term increase in geomagnetic activity , 1999 .

[25]  O. Martius,et al.  Long‐term trends of synoptic‐scale breaking Rossby waves in the Northern Hemisphere between 1958 and 2001 , 2008 .

[26]  Kalevi Mursula,et al.  A new verifiable measure of centennial geomagnetic activity: Modifying the K index method for hourly data , 2007 .

[27]  E. Cliver,et al.  Determination of interplanetary magnetic field strength, solar wind speed and EUV irradiance, 1890-2003 , 2003 .

[28]  V. Dobrica,et al.  Signature of Hale and Gleissberg solar cycles in the geomagnetic activity , 2008 .

[29]  E. Cliver,et al.  The IDV index: Its derivation and use in inferring long‐term variations of the interplanetary magnetic field strength , 2005 .

[30]  S. Harkema,et al.  A Bayesian change-point analysis of electromyographic data: detecting muscle activation patterns and associated applications. , 2003, Biostatistics.

[31]  N. Crooker,et al.  The solar wind at the turn of the century , 1978, Nature.

[32]  W. N. Venables,et al.  Statistical forecasting of soil dryness index in the southwest of Western Australia , 2003 .

[33]  P. Mayaud,et al.  The aa indices: A 100-year series characterizing the magnetic activity , 1972 .