Abstract
To predict extreme weather events, we conducted high-resolution global atmosphere modeling and simulation using high-performance computing. Using a new-generation global weather/climate prediction model called MPAS (Model for Prediction Across Scales) with variable resolution, we tested strong scalability on the KISTI (Korea Institute of Science and Technology Information) supercomputer NURION. In addition to assessing computational performance, we simulated three typhoons that occurred in 2019 to analyze the forecast accuracy of MPAS. MPAS results were also applied to force an ADCIRC (The Advanced CIRCulation) + SWAN (Simulating Waves Nearshore) model to predict coastal flooding over southern Korea. The time-integration of MPAS showed excellent scalability up to 4096 cores of NURION KNL (KNight Landing) nodes, but a serious I/O bottleneck issue was still found after trying two additional I/O strategies (i.e., adjusting the stripe count and using a burst buffer). On the other hand, the forecast accuracy of MPAS showed very encouraging results for wind and pressure during typhoons. ADCIRC+SWAN also generated a good estimate of significant wave height for typhoon Mitag. The proposed variable-resolution MPAS model, under an efficient computational environment, could be utilized to predict and understand the highly nonlinear chaotic atmosphere and coastal flooding in typhoons.
Highlights
Extreme weather events tend to occur more frequently and severely under climate change with global warming [1,2]
In this study we explored the computational efficiency of a new-generation global numerical weather prediction (NWP) model using the Korea Institute of Science and Technology Information (KISTI) supercomputer NURION and its possible application to the prediction of natural disasters caused by typhoons
Areas around the Korean Peninsula and typhoon tracks could be resolved with 15 km resolution, while the rest of the globe was computed with a 60 km resolution
Summary
Extreme weather events tend to occur more frequently and severely under climate change with global warming [1,2]. To better resolve such highly nonlinear extreme weather events with unstable climate regimes, it is necessary to operate the global NWP models with temporally and spatially high resolution, which requires proportionally increasing computational resources. That is, such a detailed forecast from a fine-grid modeling system cannot be done in a timely manner without the technical support of high-performance computing (HPC) [4,5]. In this study we explored the computational efficiency of a new-generation global NWP model using the Korea Institute of Science and Technology Information (KISTI) supercomputer NURION and its possible application to the prediction of natural disasters caused by typhoons. Radiation (long/short waves) Cloud fraction for radiation Gravity wave drag by orography
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