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http://dx.doi.org/10.5532/KJAFM.2015.17.2.165

Development of Optimal Modeling System for Analyzing Mountain Micrometeorology  

Lee, SukJun (School oh Earth and Environmental Science, Seoul National University)
choi, YongHan (School oh Earth and Environmental Science, Seoul National University)
Jung, JeaHee (School oh Earth and Environmental Science, Seoul National University)
Won, MyoungSoo (Division of Forest Disaster Management, Korea Forest Research Institute)
Lim, Gyu-Ho (School oh Earth and Environmental Science, Seoul National University)
Publication Information
Korean Journal of Agricultural and Forest Meteorology / v.17, no.2, 2015 , pp. 165-172 More about this Journal
Abstract
The extreme weather conditions become frequent and severe with global warming. To prevent and cope forest disaster like a forest fire, we need an accurate micrometeorological prediction system for mountainous regions. This study addressed the forest fires occurred at Bonghwa and Gangneung in March, 2013. We constructed and optimized the prediction system that were required to interpret and simulate the forest micrometeorology. At first, we examined WRF physical sensitivity. Subsequently, KMA AWS observation data were assimilated using three-dimensional variation data assimilation method. The effectiveness of the assimilation was examined by using AWS observations enhanced with the Forest Research Institute observations. Finally, The 100 meters spatial resolution wind data were obtained by using the MUKLIMO for the given wind vector from WRF.
Keywords
Forest fire; Forest micrometeorology; 3D-var; MUKLIMO;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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