Browse > Article
http://dx.doi.org/10.5532/KJAFM.2012.14.1.001

Prediction of Forest Fire Danger Rating over the Korean Peninsula with the Digital Forecast Data and Daily Weather Index (DWI) Model  

Won, Myoung-Soo (Division of Forest Disaster Management, Korea Forest Research Institute)
Lee, Myung-Bo (Division of Forest Disaster Management, Korea Forest Research Institute)
Lee, Woo-Kyun (Department of Environmental Science & Ecological Engineering, Korea University)
Yoon, Suk-Hee (Division of Forest Disaster Management, Korea Forest Research Institute)
Publication Information
Korean Journal of Agricultural and Forest Meteorology / v.14, no.1, 2012 , pp. 1-10 More about this Journal
Abstract
Digital Forecast of the Korea Meteorological Administration (KMA) represents 5 km gridded weather forecast over the Korean Peninsula and the surrounding oceanic regions in Korean territory. Digital Forecast provides 12 weather forecast elements such as three-hour interval temperature, sky condition, wind direction, wind speed, relative humidity, wave height, probability of precipitation, 12 hour accumulated rain and snow, as well as daily minimum and maximum temperatures. These forecast elements are updated every three-hour for the next 48 hours regularly. The objective of this study was to construct Forest Fire Danger Rating Systems on the Korean Peninsula (FFDRS_KORP) based on the daily weather index (DWI) and to improve the accuracy using the digital forecast data. We produced the thematic maps of temperature, humidity, and wind speed over the Korean Peninsula to analyze DWI. To calculate DWI of the Korean Peninsula it was applied forest fire occurrence probability model by logistic regression analysis, i.e. $[1+{\exp}\{-(2.494+(0.004{\times}T_{max})-(0.008{\times}EF))\}]^{-1}$. The result of verification test among the real-time observatory data, digital forecast and RDAPS data showed that predicting values of the digital forecast advanced more than those of RDAPS data. The results of the comparison with the average forest fire danger rating index (sampled at 233 administrative districts) and those with the digital weather showed higher relative accuracy than those with the RDAPS data. The coefficient of determination of forest fire danger rating was shown as $R^2$=0.854. There was a difference of 0.5 between the national mean fire danger rating index (70) with the application of the real-time observatory data and that with the digital forecast (70.5).
Keywords
Forest fire danger rating; Digital weather forecast data; Daily weather index; Logistic regression; Korean peninsula;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
연도 인용수 순위
1 산림청, 2005: 2005년 산불통계연보.
2 Davis, K. P., 1959: Forest Fire-Control and Use. 584pp.
3 Glahn, H. R. and D. P. Ruth, 2003: The new digital forecast database of the national weather service. Bull. Amer. Meteor. Soc., 84, 195-201.   DOI   ScienceOn
4 Lee, S. H., 1997: The state of forest resources in North Korea overlooking at the satellite. Forest Science Information 74. Korea Forest Research Institute.
5 Lee, S. Y., S. Y. Han, M. S. Won, S. H. An, and M. B. Lee, 2004: Developing of forest fire occurrence probability model by using the meteorological characteristics in Korea. Korean Journal of Agricultural and Forest Meteorology 6(4), 242-249. (In Korean with English abstract)   과학기술학회마을
6 Ruth, D. P., 2002: Interactive Forecast Preparation-the future has come. Preprints 18th Int. Conf. on Interactive Information and Proceeding Systems for Meteorology, Oceanography and Hydrology. Orlando, Amer, Meteor. Soc., 20-22.
7 Shin, K. S., 2005: The Development and Operation Plan for Digital Forecast in KMA. Proceedings of the Spring Meeting, Korean Meteorological Society, 2-5.
8 Won, M. S., K. S. Koo, and M. B. Lee, 2006: An Analysis of Forest Fire Occurrence Hazards by Changing Temperature and Humidity of Ten-day Intervals for 30 Years in Spring. Korean Journal of Agricultural and Forest Meteorology 8(4), 250-259. (in Korean with English abstract)   과학기술학회마을
9 http://www.digital.go.kr (2009. 10. 26)
10 기상청, 2006: 디지털예보모델 운영체계 디지털예보모델자료 규격. 기상청 DFS TN 2006-2. 52p.
11 기상청, 2007: 2006년 디지털예보 검증. 디지털예보개발과 기술노트 2007-1. 16p.