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To address this issue, a method of reducing the I\/O latency of high-resolution climate models by identifying and selectively outputting regions of interest is presented. Working with a global cloud-resolving model and running with up to 10,240 processors on a Cray XE6, this method provides significant I\/O bandwidth reduction depending on the frequency of writes and the size of the region of interest. The implementation challenges of determining global parameters in a strictly core-localized model and properly formatting output files that only contain subsections of the global grid are addressed, as well as the overall bandwidth impact and benefits of the method. 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