Applied Statistics

Julien Emile-Geay writes about a postdoc opportunity for a postdoc in climate
dynamics, applied statistics, or applied mathematics:

“Beyond the Hockey Stick: new approaches to paleoclimate reconstruction”

hockey.png

In 1998, a seminal study by Mann, Bradley and Hughes took advantage of climate signals embedded in an array of high-resolution paleoclimate proxy data to conclude that “Northern Hemisphere mean annual temperatures for three of the past eight years are warmer than any other year since (at least) AD 1400.” The so-called “hockey stick” reconstruction showed relatively stable temperatures for most of the millennium, until the start of the Industrial Revolution, when reconstructed temperatures begin a rise to a level not seen in the last millennium (see Figure above). Since 2001, when the third assessment report by the IPCC featured the “hockey stick” prominently, this graph has become the emblem of the debate on anthropogenic global warming and the target of numerous attacks by global warming skeptics. No other picture conveys how anomalous recent climate change is in the context of natural variations in temperature of the past millennium. Defended as definitive proof of global warming by most climate scientists, hailed as a “misguided and illegitimate investigation” by skeptics, it remains one of the most hotly debated climate studies ever published. A decade later, and despite considerable work by the climate community to address original criticisms, the field of high-resolution paleoclimatology is still struggling to defend the foundations of multiproxy climate reconstruction against attacks by armchair skeptics and scientists alike. These criticisms generally fall in two categories : (1) unsound statistical methodology (cf the Wegman Report) (2) inappropriate selection of proxy predictors (e.g. tree rings). Both problems depend critically on innovations in the field of applied statistics to bring about radical progress on the very foundations of the field.

Applications are sought for a post-doctoral research position involving the development and implementation of cutting-edge geostatistical techniques to improve the objective analysis of historical climate datasets and multiproxy reconstruction of past climate variability. The work will build on current methodologies being developed at USC in collaboration with researchers at Stanford and CalTech. More information can be found on http://college.usc.edu/labs/jeg/ and http://geosystems.usc.edu. The successful candidate will have a Ph.D. in a relevant discipline (e.g., climate dynamics, applied statistics, applied mathematics) and will be expected to program in Matlab and Python to make use of USC’s large-scale computing resources. Experience working with geophysical data is desirable. The position is for 2 years, extendable to 3 with highly competitive compensation.

For full consideration, please send a letter of application, a current curriculum vitae, and the names and contact information of three references to:
Julien Emile-Geay,
Department of Earth Sciences & Center for Applied Mathematical Sciences
University of Southern California, 3651 Trousdale Parkway, ZHS 275. Los Angeles, CA
90089 – 0740. email: julieneg@usc.edu

http://geosystems.usc.edu/

http://college.usc.edu/labs/jeg/

One of my research projects here (with Matt, Upmanu, and Ed Cook) is on climate reconstruction using tree-ring data. So don’t forget our postdoc opportunities too!

Comments

  1. #1 El NiƱo
    November 27, 2009

    Thanks much for posting !

  2. #2 weathercast forecaster
    March 26, 2011

    These criticisms generally fall in two categories : (1) unsound statistical methodology (cf the Wegman Report) (2) inappropriate selection of proxy predictors (e.g. tree rings). Both problems depend critically on innovations in the field of applied statistics to bring about radical progress on the very foundations of the field.

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