Presentation

DescriptionThe study of many extreme weather events requires simulations with high spatiotemporal data that can grow in size quickly. Storing the raw data from such a large-scale simulation for traditional post hoc analyses is soon going to be prohibitive as the data generation speed is outpacing the data storage capability. In situ analysis has emerged as a solution to this problem; data is analyzed when it is being produced, bypassing the slower disk I/O. In this work, we develop an in situ analysis for Energy Exascale Earth System Model and propose an algorithm for analyzing the impacts of sudden stratospheric warmings (SSWs), which can cause extreme cold temperature outbreaks at the surface, resulting in hazardous weather and disrupting many socioeconomic sectors. We detect SSWs and model the surface temperature distributions in situ and show that post hoc analysis using the distribution models can predict the impact of SSWs.

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