Grant support

  1. ONR-N00014-12-1-0911, FY2012 Multi-University Research Initiative (MURI) Topic #16: Extended-Range Environmental Prediction Using Low-Dimensional Dynamic Modes, Office of Naval Research, 2012-2015.

  2. NSF 1049253Collaborative Research, Type 1, L02170206: Climate Sensitivity, Stochastic Models and GCM-EaSM Optimization, U.S. National Science Foundation (DMS + MPS Divisions), 2011-2014.

  3. DOE DE-SC0006694Decadal Prediction and Stochastic Simulation of Hydroclimate over Monsoonal Asia, U.S. Department of Energy, 2011-2014.

Additional acknowledgments

The development and application of SSA to geophysical time series was carried out by the present authors in collaboration with M. Kimoto, J.M. Lees, N. Jiang, C.L. Keppenne, K.-C. Mo, J.D. Neelin, J. Park, M.C. Penland, G. Plaut, A. Saunders, E. Simmonet, L.A. Smith, A.W. Robertson, S. Speich, C. Taricco, Y.S. Unal, R. Vautard and W. Weibel. Comments by these collaborators and numerous other colleagues on test versions of the Toolkit are gratefully acknowledged. The Toolkit was developed mostly on equipment and with support provided by Digital Equipment Corporation to the University of California, Los Angeles, Department of Atmospheric Sciences, as part of the Sequoia 2000 project. Research for the development of the methods and their applications to climatic time series was supported by NSF Grant ATM93-13217, NOAA Grant NA36G90245, and an NSF Special Creativity Award to M. Ghil. Use of trade names in this article is for identification purposes only and does not constitute endorsement by the U.S. Geological Survey.