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Abstract:
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High-resolution climate model simulations generate enormous data volumes that strain computing center storage resources at institutions such as the National Center for Atmospheric Research (NCAR). Further, storage limitations are negatively impacting science objectives by forcing scientists to run fewer or shorter simulations and/or output data less frequently. Therefore, NCAR has been investigating using data compression to reduce data volumes from the widely used Community Earth System Model (CESM). Striking a balance between meaningfully reducing data volume and preserving the integrity of the simulation data is non-trivial, particularly given the large and diverse set of climate variables. In this talk, we first discuss the challenges of compressing climate data. We then describe our efforts thus far to evaluate the effects of data compression on the original data, which we believe should, at a minimum, not be distinguishable from the natural variability of the climate system. The ultimate goal is that the reconstructed and original climate simulation data are indistinguishable during post-processing analyses, which vary widely according to climate scientists' interests.
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