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Distilling Regional Climate Model Data from NARCCAP for Use in Impacts Analysis
The North American Regional Climate Change Assessment Program (NARCCAP) is an international, multi-institution collaboration to simulate climate change over North America using high-resolution regional models. The data archive for NARCCAP is more than forty terabytes in size and includes more than fifty variables.
As data providers, to make these results usable by impacts users and other non-specialists, we need to do more than just publish the raw model output; we need to encapsulate our knowledge and understanding of the models by providing derived data products that are well-matched to end-user needs.
In this talk, I will discuss some of the complicating factors that make bias-correction, regridding and interpolation, and climatology creation more difficult than may be expected, and the statistical methods that we use in generating derived data products. I will also cover some lessons learned about the practicalities of archiving large datasets, and the implications of these issues for data analytics and publishing as we move into the era of big data.