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Model and Data Hierarchies for Simulating and Understanding Climate

Chris Wiggins points us to this announcement for a conference next year:

Simulation has greatly advanced climate science, but not sufficiently to the profit of theory and understanding. How can simulation better advance climate science and what mathematical issues does this raise? Our hypothesis is that the development of climate science (i.e., theory and understanding) will be best served by focusing computational and intellectual resources on model and data hierarchies. By bringing together physicists, mathematicians, statisticians, engineers and climate-scientists, and focusing on several themes that reach across scales and scientific methodologies, our program will provide a framework for advancing our use of hierarchical methods in our attempt to understand the climate system.

There will be an active program of research activities, seminars and workshops throughout the March 8 – June 11, 2010 period and core participants will be in residence at IPAM for fourteen weeks. The program will open with tutorials, and will be punctuated by four major workshops and a culminating workshop.

This all makes sense to me, although, given the topic, I’m surprised that no statisticians seem to be involved. Lots of potential for interesting models and graphs.

7 Comments

  1. bill r says:

    Well, Ed Wegman got involved and look what happened to him. Instant demonization!

  2. Bruce McCullough says:

    Andrew writes: "I'm surprised that no statisticians seem to be involved."

    It is amazing, isn't it? Lots of lots of "sophisticated" statistical analyses, and not a statistician in sight.

    Why is that?

    Because if statisticians were involved, the so-called "climate scientists" might not be able to make sure that the results are consistent with the pre-ordained conclusion.

    For example, the famous Hockey-stick graph that purports to show a recent rise in global temperature was produced using (among other bad choices) a hand-coded "principal components" routine that does NOT give the same answer as SAS, R, or any reliable statistical package.

    Hmmmm. I wonder why they used hand-coded principal components instead of just using SAS or R? Perhaps becuase using SAS or R would not have produced "evidence" of a rise in global temperature.

    The use of "statistics" by the so-called "climate scientists" was roundly criticized for ineptness and inaptness by the Wegman Report (Wegman, of course, is a statistician of no small repute).

    http://climateaudit.org/pdf/others/07142006_Wegma

  3. pwyll says:

    I had read that one criticism of current climate modeling was insufficient use of statistical expertise and insufficient involvement of statisticians, so to the extent that more get involved, it sounds like a win to me.

  4. jerry says:

    another similar school, likely with more stats, less majda: http://www.mpipks-dresden.mpg.de/~dswc09/

  5. Nick Cox says:

    There's plenty of evidence for statisticians (however defined) getting involved in climate science.

    Whatever the intentions, the so-called Wegman report was widely resented for the way it was set up. It focused on a small group of papers published some years earlier but was widely quoted as if it was an assessment or indictment of climate science as a whole. In fact Bruce McCullough seems here to add yet another example of that practice.

    Let's imagine the reverse as a thought experiment: three climatologists are invited by a U.S. congressman (Democrat, say) to set themselves up to review some area of statistical science. The climatologists are of course well-known in their fields and have long experience and good backgrounds ranging from physics to environmental science. That would seem fairly absurd or objectionable to many in statistical science, would it not?

  6. Barry says:

    Re: the 'hockey stick'. Tim Lambert at Deltoid has been dealing with this for years.

    Try (from 2006):
    http://scienceblogs.com/deltoid/2006/02/moving_go

    Climate Audit is a well-known denialist blog.

  7. Amy Braverman says:

    I am the organizer of the Data Hierarchies portion of the IPAM 2010 Workshop. I am a statistician at the Jet Propulsion Laboratory and UCLA. I have seen to it that a number of distinguished people from our profession are invited and will participate. Of those who are invited, several have direct experience in climate studies, and others are experts in technical areas that have not yet been applied to climate problems, but have the potential to be very fruitful. The purpose of this IPAM program is to bring new ideas to the table in a collaborative environment. I believe this is a better approach than hitting climate scientists over the head with congressional testimony about what bad statistics they have done in the past.