Heat Exposure Information at Screen Level for an Impact-Based Forecasting and Warning Service for Heat-Wave Disasters

Abstract

The importance of impact-based forecasting services, which can support decision-making, is being emphasized to reduce the damage of meteorological disasters, centered around the World Meteorological Organization. The Korea Meteorological Administration (KMA) began developing impact-based forecasting technology and warning services in 2018. This paper proposes statistical downscaling and bias correction methods for acquiring high-resolution meteorological data for the heat-wave impact forecast system operated by KMA. Hence, digital forecast data from KMA, with 5 km spatial resolution, were downscaled and corrected to a spatial resolution of 1 km using statistical interpolation methods. Cross-validation indicated the superior performance of the Gaussian process regression model (GPRM) technique with low root mean square error and percent bias values and high CC value. The GPRM technology had the lowest forecast error, especially during the hottest period in Korea. In addition, temperatures for land-use areas with low elevations and high activity, such as the urban, road, and agricultural areas, were high. It is essential to provide accurate heat exposure information at the screen level with high human activity. Spatiotemporally accurate heat exposure information can be used more realistically for risk management in agriculture, livestock and fishery, and for adjusting the working hours of outdoor workers in construction and shipbuilding.

Spatial Relationship between Heat Illness Incidence and Heat Vulnerability in Gurye and Sunchang, South Korea, 2018

“…Thus, grid-based temperature data that allow detailed analysis of neighborhood weather forecasts of KMA were used. Yi et al [17] used the KMA neighborhood weather forecast data (5 km resolution) and the Gaussian process regression model (GPRM) to predict the impact of heatwaves and calculated detailed weather data with a 1 km resolution by interpolating sub-variables, such as the altitude above the sea level, inclination angle, distance from the shoreline, land cover, depth of depressed topography, east-west slope, north-south slope, and slope direction. The detailed weather data generated through GPRM are suitable for the analysis of the impacts of heatwaves on pedestrian environments, as they yield the daily maximum and minimum temperatures with higher accuracy than those of the neighborhood weather forecasts in dry urban areas and farmlands.…”

Spatial Distribution and Future Projections of Thermal Comfort Conditions during the Hot Period of the Year in Diyarbakır City, Southeastern Turkey

“…in the last century have made it widespread to analyze thermal comfort conditions closely related to human life and to reveal their spatial distribution. It has been explained in many studies that thermal comfort conditions affect cardiovascular diseases, respiratory system diseases, and mortality [5][6][7][8][9]. It is stated that cities are among the leading areas to be affected by changing climatic conditions and that disaster-scale impacts will be experienced in cities in the coming years [10][11][12].…”

Challenges in Applied Human Biometeorology

“…The complex interactions between temperature and respiratory and ischemic heart mortalities, and their relationship to the thermal environment, are shown for Germany [12]. The heat exposure at screen-level, for an impact-based forecasting and warning service for heat-wave disasters, is also of interest [13]. Long-term temperature-related mortality in Helsinki in the urban and rural context was studies [14].…”