Joint System of the National Hydrometeorology for disaster prevention

Abstract:

Hydrological disaster relief expenditure accounts for as much as 70 percent of total expenditure of disasters occurring in Korea. Since the response to and recovery of disasters are normally based on previous experiences, there have been limitations when dealing with ever-increasing localized heavy rainfall with short range in the era of climate change. Therefore, it became necessary to establish a system that can respond to a disaster in advance through the analysis and prediction of hydrometeorological information.
Because a wide range of big data is essential, it cannot be done by a single agency only. That is why the three hydrometeorology-related agencies cooperated to establish a pilot (trial) system at Soemjingang basin in 2013. The three governmental agencies include the National Emergency Management Agency (NEMA) in charge of disaster prevention and public safety, the National Geographic Information Institute (NGII under Ministry of Land, Infrastructure and Transport) in charge of geographical data, and the Korea Meteorological Administration (KMA) in charge of weather information.
This pilot system was designed to be able to respond to disasters in advance through providing a damage prediction information for flash flood to public officers for safety part using high resolution precipitation prediction data provided by the KMA and high precision geographic data by NGII. To produce precipitation prediction data with high resolution, the KMA conducted downscaling from 25km×25km global model to 3km×3km local model and is running the local model twice a day.
To maximize the utility of weather prediction information, the KMA is providing the prediction information for 7 days with 1 hour interval at Soemjingang basin to monitor and predict not only flood but also drought.
As no prediction is complete without a description of its uncertainty, it is planned to continuously develop the skills to improve the uncertainty of the prediction on weather and its impact. I will introduce more the flow chart to produce and provide the weather prediction information in AGU fall meeting.