Development of Optimal Modeling System for Analyzing Mountain Micrometeorology

Division of Forest Disaster Management, Korea Forest Research Institute(Received April 2, 2015; Revised April 9, 2015; Accepted June 28, 2015)ABSTRACTThe extreme weather conditions become frequent and severe with global warming. To prevent andcope forest disaster like a forest fire, we need an accurate micrometeorological prediction system formountainous regions. This study addressed the forest fires occurred at Bonghwa and Gangneung inMarch, 2013. We constructed and optimized the prediction system that were required to interpret andsimulate the forest micrometeorology. At first, we examined WRF physical sensitivity. Subsequently,KMA AWS observation data were assimilated using three-dimensional variation data assimilationmethod. The effectiveness of the assimilation was examined by using AWS observations enhanced withthe Forest Research Institute observations. Finally, The 100 meters spatial resolution wind data wereobtained by using the MUKLIMO for the given wind vector from WRF. Key words: Forest fire, Forest micrometeorology, 3D-var, MUKLIMO