January 30, 2012 at 9:04 am #256521owlbrudderMember
I have seen many people on the web complaining that climate scientists don’t release their models or data to allow others to check their work. The truth is that most source code and data is freely available, if one is willing to search for it. There is no ‘hiding’ of resources, but researchers are expected to be smart enough to know where to look and how to pull all the threads together.
Sometimes, however, a ‘packaged’ solution comes along, which is much easier for the layperson to deal with. I have looked at some of these and they seem agreeably open in their approach. The downside is that all I have looked at require some programming skills and a good deal of computer literacy, so they are not aimed at Mr. Average with a PC and some time to kill. You do have to know what you are doing.
Having said this, people (like me) with a programming background can download and run the packages with more or less convenience. Even just browsing the source code gives deep insights into how the programs work and opens the way for doubters to prove the models wrong by finding errors of logic, language or design. In fact, it is through peer review like this that models are improved and refined, so anyone finding a bug is welcome to point it out to the people who wrote it.
I thought it would be valuable to have a thread here for the purpose of locating and discussing the software behind the predictions. All are welcome to post links to downloadable models and datasets, so the rest of us can have a look ‘under the hood’ and, perhaps, allay the fears of those who doubt the models.
To start the ball rolling, here is a link to the Lawrence Livermore Laboratories Climate Science page, which in turn has links to their open-source climate data analysis tools, which can be freely downloaded. Linux and Mac users will need Python and some programming skills; Windows users download something called Panoply, which I guess does the same thing.
I hope this thread will become an informed discussion about climate modelling for the non-scientist.
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