Earth's dynamo limit of predictability

[1] Earth's magnetic field is currently decreasing, reducing the protection it offers against charged particles coming from space and increasing space weather hazards within the near-Earth environment. Modeling the future evolution of the field is thus of considerable interest. But how far in the future this can conceivably be done is still an open question. Here we report on the first systematic investigation of the limit of predictability of fully consistent 3D numerical dynamo simulations, and suggest that the Earth's dynamo is likely unpredictable beyond a century, making decade timescale forecasts of the main magnetic field conceivable, but rendering longer-term predictions, such as the timing of the next reversal, totally unpredictable.

[1]  Fausto Cattaneo,et al.  Nonlinear dynamos: A complex generalization of the Lorenz equations , 1985 .

[2]  U. Christensen,et al.  8.08 – Numerical Dynamo Simulations , 2007 .

[3]  E. Lorenz.  A study of the predictability of a 28-variable atmospheric model , 1965 .

[4]  E. Lorenz.  Deterministic nonperiodic flow , 1963 .

[5]  Akira Kageyama,et al.  Formation of current coils in geodynamo simulations , 2008, Nature.

[6]  Peter Driscoll,et al.  Dipole collapse and reversal precursors in a numerical dynamo , 2009 .

[7]  U. R. Christensena,et al.  A numerical dynamo benchmark , 2001 .

[8]  Gauthier Hulot,et al.  Can core‐surface flow models be used to improve the forecast of the Earth's main magnetic field? , 2008 .

[9]  Ulrich R. Christensen,et al.  Power requirement of the geodynamo from ohmic losses in numerical and laboratory dynamos , 2004, Nature.

[10]  Ignasi Ribas,et al.  Planetary Magnetic Fields and Solar Forcing: Implications for Atmospheric Evolution , 2007 .

[11]  E. Al,et al.  The feasibility of a global observation and analysis experiment , 1966 .

[12]  Gauthier Hulot,et al.  A statistical approach to the Earth's main magnetic field , 1994 .

[13]  Jonathan M. Aurnou,et al.  The magnetic structure of convection-driven numerical dynamos , 2008 .

[14]  Graeme R. Sarson,et al.  The geodynamo as a low-dimensional deterministic system at the edge of chaos , 2008 .

[15]  U. Christensen,et al.  Energy flux determines magnetic field strength of planets and stars , 2009, Nature.

[16]  Mioara Mandea,et al.  Small-scale structure of the geodynamo inferred from Oersted and Magsat satellite data , 2002, Nature.

[17]  Alexandre Fournier,et al.  A case for variational geomagnetic data assimilation: insights from a one-dimensional, nonlinear, and sparsely observed MHD system , 2007, 0705.1777.

[18]  Rainer Hollerbach.  ON THE THEORY OF THE GEODYNAMO , 1996 .

[19]  Eugenia Kalnay,et al.  Atmospheric Modeling, Data Assimilation and Predictability , 2002 .

[20]  G. Glatzmaier,et al.  A three-dimensional convective dynamo solution with rotating and finitely conducting inner core and mantle , 1995 .

[21]  Ulrich R. Christensen,et al.  Numerical Dynamo Simulations , 2007 .

[22]  Nils Olsen,et al.  The 10th generation international geomagnetic reference field , 2005 .

[23]  Catherine Constable,et al.  Is Earth's magnetic field reversing? , 2006 .

[24]  D. Baker.  How to Cope with Space Weather , 2002, Science.

[25]  Christopher K. Wikle,et al.  Atmospheric Modeling, Data Assimilation, and Predictability , 2005, Technometrics.

[26]  U. Christensen,et al.  Scaling properties of convection-driven dynamos in rotating spherical shells and application to planetary magnetic fields , 2006 .

[27]  Zhibin Sun,et al.  MoSST-DAS: The First Generation Geomagnetic Data Assimilation Framework , 2008 .