Our specialissue of IEEE Software, for Nov/Dec 2011, is out! The title for the issue is Climate Change: Science and Software, and the guest editors were me, Paul Edward, Balaji, and Reinhard Budich.

There’s a great editorial by Forrest Shull, reflecting on interviews he conducted with Robert Jacob at Argonne National Labs and Gavin Schmidt at NASA GISS. The papers in the issue are:

Unfortunately most of the content is behind a paywall, although you can read our guest editors introduction in full here. I’m working on making some of the other content more freely available too.

Data Rescue
On the Lack of Consensus over the Meaning of Openness: An Empirical Study

6 Comments

  1. As you probably know, as long as the good guys hide their information behind a paywall while the bad guys hand it out for free, more people will listen to the bad guys.

  2. John: Agreed 100%. For IEEE Software it was a difficult choice whether to do this in the first place. On the one hand, the magazine reaches a massive segment of software professionals. OTOH, it’s paywalled. I’m in favour of the Open Access Pledge, but occasionally the chance to reach a particular community by breaking the pledge is hard to resist.

    Anyway, I’m working on making the complete set of papers for this special issue open access…

  3. Steve, could you please do a blog post addressing whether this David H. Freedman (shorter DHF: expertise is overrated) article saying that economic models’ calibration sends them astray is a) accurate and/or b) relevant to climate models?
    http://www.scientificamerican.com/article.cfm?id=finance-why-economic-models-are-always-wrong

  4. @Anna Haynes It’s completely OT, so we should probably take it somewhere else. But for now, a quick reaction: the phenomena described is completely correct. If you use empirical methods to tune the models, you’re in danger of getting bad forecasts. For models of the physical climate, this is avoided by paying more attention to the underlying physics – instead of empirical tuning, you work on understanding the underlying processes, and improving how they’re captured in the model. Then you do lots of different hindcasts, process studies, etc, to check how well you did. One of the problems with economics models is there is no set of basic physical principles to underpin them. Which makes it much harder to avoid the problem.

  5. I’m guessing the “Jonathan Carter” that Freedman refers to is Jonathan N. Carter of the UK; perhaps the research is this article of JNC’s in the Journal of Petroleum Science and Engineering? (Volume 59, Issues 3-4, November 2007, Pages 157-168 )
    A parallel real-coded genetic algorithm for history matching and its application to a real petroleum reservoir
    (from abstract: “… Our main conclusion is that, even with regularisation, many distinct history matched models are possible, which highlights the importance of applying optimisation methods capable of identifying all such solutions.”)

  6. @Anna Haynes (sorry Steve, I hadn’t seen your response; feel free to delete my 17:40 comment & this one please, and the earlier one if you’d like)

Join the discussion: