Opportunities and Challenges for Data Science in (Big) Environmental Science
I was asked to give a talk on data science in climate science. After working out what “data science” might mean for this audience, I took a rather larger view of what was needed and talked about data issues in environmental science, before quickly talking about hardware and software platform issues. Most of the talk covered a few applications of modern data science: data assimilation, classification, homogenising data, and using machine learning to infer new products. I finished by reminding everyone that in collaborations between climate science and statisticians and computer scientists, we need to be careful about our use of the word “model” (with a bit of help from xkcd). I finished with reminding everyone that climate science has always been a data science.
The full set of videos from all the speakers is available.