Application of objective classifications of 'air masses' in modelling heat-related mortality in Korea

Objective classifications of weather types ('air masses', AMs) are frequently used for evaluating and predicting increased mortality due to heat stress in summer. The air-mass-based approach takes into account the entire weather situation rather than single elements; it identifies 'oppressive' AMs associated with elevated mortality in a given location/area, and applies regression models within the oppressive AMs in order to account for excess mortality. Principal component analysis and cluster analysis are used to define the AMs from basic input meteorological data. The present study examines the applicability of the methodology for the area and population of South Korea. After presenting basic characteristics of the oppressive AMs of two selected classifications, recognized as superior in terms of the mean relative mortality increase in the oppressive AM and the coverage of days with large excess mortality by the oppressive AM, we focus on the development of regression models that account for variations in excess mortality within the oppressive AMs. Both meteorological and non-meteorological parameters are found to be important predictors in regression models for excess mortality within the oppressive AMs of the two classifications. The results suggest that the coverage of days with large excess mortality by the oppressive AM is the most important criterion for the application into predicting elevated mortality risks. The classification with a relatively small number of AMs (6) shows better predictive skills in spite of smaller mean excess mortality on days classified with the oppressive AM. The relationships of excess mortality within the oppressive AM to meteorological and non-meteorological factors may be found useful also for the development of a heat-watch-warning system that is currently tested for Seoul and other large Korean cities. The study is supported by the Korea Research Foundation and the Czech Science Foundation under joint project KRF-2006-C00005 / 205/07/J044.