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High-performance computing for the simulation of dust storms
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DOI：10.1016/j.compenvurbsys.2009.08.002.png)
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Dust storm is a primary natural hazard that impact human activities. Previous work has simulated dust events with Eta model. This paper reports our effort to migrate a Dust Regional Atmospheric Model (DREAM) to the Nonhydrostatic Mesoscale Model (NMM), core of the Weather Research and Forecasting (WRF) system's (WRF-NMM)-based dust model. The process is as follows: (1) the DREAM model is modified to fit into a high-performance computing environment by parallelizing the dust model based on the WRF-NMM weather forecasting model. We couple a dust module to the WRF-NMM model and parallelize the serial program using Message Passing Interface (MPI). (2) The performance of the parallel dust simulation model is tested using the southwestern United States as the experiment area and a dust event during 7 January 2008 for the case study. (3) The new dust model based on WRF-NMM is implemented and tested on a Linux cluster with 28 computing nodes and over 200 CPU cores. The new model can leverage high-performance computing clusters to reduce the execution time while at the same time enhancing the simulation resolution. As tested, when simulating a 72 h period, the WRF-NMM dust model took 1.8 h when using a resolution of 1/9 of a degree grid space, when 36 CPU cores were used for high-performance computing. The results show that the parallelized version of the dust simulation model can get a maximum speedup about 13.3. We also built a transformation component to export the model output to geographic information system (GIS) software through a Web Map Service (WMS). (C) 2009 Elsevier Ltd. All rights reserved.
Keyword:
Dust simulation
Eta
WRF-NMM
High-performance computing
Parallel computing
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