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Binary Forecast of Heavy Snow Using Statistical Models
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 Title & Authors
Binary Forecast of Heavy Snow Using Statistical Models
Sohn, Keon-Tae;
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 Abstract
This Study focuses on the binary forecast of occurrence of heavy snow in Honam area based on the MOS(model output statistic) method. For our study daily amount of snow cover at 17 stations during the cold season (November to March) in 2001 to 2005 and Corresponding 45 RDAPS outputs are used. Logistic regression model and neural networks are applied to predict the probability of occurrence of Heavy snow. Based on the distribution of estimated probabilities, optimal thresholds are determined via true shill score. According to the results of comparison the logistic regression model is recommended.
 Keywords
Binary forecast;Heavy snow;MOS;logistic regression;Neural networks;
 Language
Korean
 Cited by
1.
Statistical Models for Fog Advisory over Jindo Area,;

Journal of the Korean Data Analysis Society, 2010. vol.12. 5, pp.2419-2429
2.
남한지역 봄철 안개발생에 대한 이 범주 예측모형 개발,손건태;

Journal of the Korean Data Analysis Society, 2010. vol.12. 2, pp.949-960
1.
Guidance on the choice of threshold for binary forecast modeling, Advances in Atmospheric Sciences, 2008, 25, 1, 83  crossref(new windwow)
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