Nah, don’t believe it

all_seeing_eye_dollar_pyramid-normal Science (the mag, not the concept) sez:

Science is driven by data. New technologies… blah… publishers, including Science, have increasingly assumed more responsibility for ensuring that data are archived and available after publication… blah… Science’s policy for some time has been that “all data necessary to understand, assess, and extend the conclusions of the manuscript must be available to any reader of Science” (see www.sciencemag.org/site/feature/contribinfo/)… blah… Science is extending our data access requirement listed above to include computer codes involved in the creation or analysis of data

Well, jolly good. I look forward to them insisting the full code for HadCM3 / HadGEM / whatever is published before accepting any GCM papers using them (which, amusingly, will now include all the papers doing the increasingly fashionable “multi-model” studies using the widely available AR4 data archives).

Come to think of it, it would also prevent S+C (but not RSS?) ever publishing in Science.

[Update: meanwhile, Werner Kraus, not content with being a tosser has decided that he is an idiot -W]

Refs

* One of James / Jules’s posts pushing the appropriate model journalGeoscientific Model Development.
* Eli comments on Nature’s policy, which is more nuanced.
* Devil in the details Nature 470, 305-306 (17 February 2011) doi:10.1038/470305b To ensure their results are reproducible, analysts should show their workings – nice Nature article on Genomics trubbles, h/t NB.
Continue reading “Nah, don’t believe it”

Validating Climate Models

SE has an excellent post about Validating Climate Models. It is all good, but I particularly liked

when we ask climate scientists for future projections, we’re asking the question of the scientists, not of their models. The scientists will apply their judgement to select appropriate versions/configurations of the models to use, they will set up the runs, and they will interpret the results in the light of what is known about the models’ strengths and weaknesses and about any gaps between the comptuational models and the current theoretical understanding. And they will add all sorts of caveats to the conclusions they draw from the model runs when they present their results.