Dear Colleague,
Special Issue: *Physics-driven data mining in climate change and weather
extremes*
Journal: *Nonlinear Processes in Geophysics*
Publishers: European Geophysical Union (EGU) and American Geophysical
Union (AGU)
*Submission Deadline: December 10, 2013*
We have obtained approval for the publication of a Special Issue in the
journal "Nonlinear Processes in Geophysics" (NPG)
(http://www.nonlin-processes-geophys.net/volumes_and_issues.htm)
"Physics-driven data mining in climate change and weather extremes" and
we would request a contribution from you.
New methods and algorithms in data mining, broadly construed to include
computational statistics, signal processing, information theory, machine
learning, network science, nonlinear dynamics, and database mining, are
motivated in climate change and weather extremes owing to (a) the
massive volume and complexity of the data, (b) strengths and limitations
of our physical understanding and of physics-based computer models, (c)
multivariate dependence in space-time, including long memory processes
and long-range spatial dependence, (d) the presence of colored and even
1/f noise, along with chaos and nonlinear dynamics, and (e) the growing
importance of extreme values and rare events. However, data mining may
lead to spurious insights unless appropriate precautions are taken, and
may even generate misleading results when complex dependence
predominates and if processes are chaotic. Under "non-stationary" or
changing conditions, confidence in data mining approaches alone may be
limited even further. Incorporating physics in data mining algorithms
and methods can help in the interpretability of results, lead to better
generalization, and produce meaningful insights.
The special issue encourages papers in physics-guided data mining, where
the physics may be incorporated within the data-driven models through,
for example, variable selection, learning of data-driven or network
models, effective pre- or post-processing, interpretability, and
explain-ability. The papers accepted in this special issue may be broad
in scope. However, the new methods, methodological adaptations, or novel
applications, in climate change and weather extremes, must have a clear
component where the physics either helps formulate or drive the data
mining approach and/or enables in the generalization and
interpretability of the corresponding results.
The focus of the special issue will be on physics-guided mining of
weather and climate data, where the data may be obtained from in-situ
and remote sensing observations, paleoclimate reconstructions,
reanalysis products, and numerical simulations from physics-based
weather and climate models. The novelty may be in approaches for
physics-guided climate or weather data mining and/or in the nature of
the insights obtained in climate change and/or weather extremes, such as
heat waves, cold snaps, heavy precipitation, floods, droughts, tropical
and extratropical cyclones, tornadoes, and storm surges, as well as
climate variability and change on interannual to glacial-interglacial
timescales, both historical and projected. In addition to mining of
temporal, spatial, and spatiotemporal data relevant for gaining novel
insights in climate change and/or weather extremes, statistical
downscaling, data assimilation, large-scale optimization, and stochastic
differential equation based methods may be considered as long as there
are clear innovations in computational data sciences and in strong
coupling of process physics and data-driven methods.
If you are interested in preparing an article for the special issue, we
would appreciate if you could let us know in advance. You can do so by
replying to this message. The submission deadline for articles in this
special issue is December 10, 2013. Please feel free to forward this
information to colleagues who may be interested.
"Nonlinear Processes in Geophysics" is a joint publication of the
European Geosciences Union (http://www.egu.eu/) and the American
Geophysical Union (http://www.agu.org/). NPG operates under the Open
Access model, which means that articles published there are freely
available, contributing to a maximum of diffusion. The current (2008)
5-year journal impact factor of NPG is 1.59. The Open Access model also
implies that there are publication charges
(http://www.nonlinear-processes-in-geophysics.net/submission/service_charges.html)
although there are schemes to help authors from developing countries
unable to meet these charges. There are also fee waivers for those
papers that have first authors from (a) Research Units of the Max Planck
Society, (b) Research Units of CNRS INSU & (c) Institutes of the
Georg-August-University Göttingen. See
http://www.nonlinear-processes-in-geophysics.net/general_information/financial_support_for_authors.html
Sincerely,
Guest Editors of the Special Issue
On "Physics-driven data mining in climate change and weather extremes"
in Nonlinear Processes in Geophysics published by the EGU and AGU
Auroop R. Ganguly, Northeastern University, Boston, MA, USA
Vimal Mishra, Indian Institute of Technology, Gadhinagar, India
David Wang, Northeastern University, Boston, MA, USA,
William Hsieh, University of British Columbia, Vancouver, Canada
Forrest Hoffman, Oak Ridge National Laboratory, Oak Ridge, TN, USA
Vipin Kumar, University of Minnesota, Minneapolis, MN, USA
Juergen Kurths, Potsdam Institute for Climate Impact Research, Postdam,
Germany
--
Forrest Hoffman [email protected]
Oak Ridge National Laboratory http://www.climatemodeling.org/~forrest
Computational Earth Sciences Group (865) 576-7680 voice
Building 2040, Room E249, MS 6301 (865) 574-9501 fax
P.O. Box 2008 Deliveries: One Bethel Valley Road
Oak Ridge TN 37831-6301 35° 55' 23" N 84° 19' 20" W
