What is Climate Informatics? by Steve
From the post:
I’ve been using the term Climate Informatics informally for a few years to capture the kind of research I do, at the intersection of computer science and climate science. So I was delighted to be asked to give a talk at the second annual workshop on Climate Informatics at NCAR, in Boulder this week. The workshop has been fascinating – an interesting mix of folks doing various kinds of analysis on (often huge) climate datasets, mixing up techniques from Machine Learning and Data Mining with the more traditional statistical techniques used by field researchers, and the physics-based simulations used in climate modeling.
I was curious to see how this growing community defines itself – i.e. what does the term “climate informatics” really mean? Several of the speakers offered definitions, largely drawing on the idea of the Fourth Paradigm, a term coined by Jim Gray, who explained it as follows. Originally, science was purely empirical. In the last few centuries, theoretical science came along, using models and generalizations, and in the latter half of the twentieth century, computational simulations. Now, with the advent of big data, we can see a fourth scientific research paradigm emerging, sometimes called eScience, focussed on extracting new insights from vast collections of data. By this view, climate informatics could be defined as data-driven inquiry, and hence offers a complement to existing approaches to climate science.
However, there’s still some confusion, in part because the term is new, and crosses disciplinary boundaries. For example, some people expected that Climate Informatics would encompass the problems of managing and storing big data (e.g. the 3 petabytes generated by the CMIP5 project, or the exabytes of observational data that is now taxing the resources of climate data archivists). However, that’s not what this community does. So, I came up with my own attempt to define the term:
Fleshes out a term that gets tossed around without a lot of discussion.
Personally I have never understood the attraction of disciplinary boundaries. Other than as an “in” versus “out” crowd for journal/presentation acceptance.
Given the low citation rates in the humanities, being “in” a discipline, to say nothing of peer review, isn’t a guarantee of good work.