Forecast and verification of perceived temperature using a mesoscale model over the Korean Peninsula during 2007 summer

중규모 수치 모델 자료를 이용한 2007년 여름철 한반도 인지온도 예보와 검증

  • Byon, Jae-Young (National Institute of Meteorological Research, Korea Meteorological Administration) ;
  • Kim, Jiyoung (National Institute of Meteorological Research, Korea Meteorological Administration) ;
  • Choi, Byoung-Cheol (National Institute of Meteorological Research, Korea Meteorological Administration) ;
  • Choi, Young-Jean (National Institute of Meteorological Research, Korea Meteorological Administration)
  • Received : 2008.06.03
  • Accepted : 2008.09.22
  • Published : 2008.09.01

Abstract

A thermal index which considers metabolic heat generation of human body is proposed for operational forecasting. The new thermal index, Perceived Temperature (PT), is forecasted using Weather Research and Forecasting (WRF) mesoscale model and validated. Forecasted PT shows the characteristics of diurnal variation and topographic and latitudinal effect. Statistical skill scores such as correlation, bias, and RMSE are employed for objective verification of PT and input meteorological variables which are used for calculating PT. Verification result indicates that the accuracy of air temperature and wind forecast is higher in the initial forecast time, while relative humidity is improved as the forecast time increases. The forecasted PT during 2007 summer is lower than PT calculated by observation data. The predicted PT has a minimum Root-Mean-Square-Error (RMSE) of $7-8^{\circ}C$ at 9-18 hour forecast. Spatial distribution of PT shows that it is overestimated in western region, while PT in middle-eastern region is underestimated due to strong wind and low temperature forecast. Underestimation of wind speed and overestimation of relative humidity have caused higher PT than observation in southern region. The predicted PT from the mesoscale model gives appropriate information as a thermal index forecast. This study suggests that forecasted PT is applicable to the prediction of health warning based on the relationship between PT and mortality.

Keywords