Overview of Korea Precipitation Observation Program(KPOP) in the Seoul Metropolitan Area

The Seoul metropolitan area is a residential area with a population of over 20 million and Korea’s major industrial facilities are closely located, so when hazardous weather events such as heavy rain and snow occur in this area, the social and economic damage is very significant. The region's localized heavy rainfall is challenging to observe and predict due to heterogeneity in surface conditions and the complexity of the terrain. This study introduces the Korea Meteorological Administration's (KMA) efforts in constructing an intensive observation network and utilizing the data to analyze rainfall mechanisms, and improve the accuracy of numerical weather models..

Since 2021, the KMA has conducted annual intensive observations during the summer in the Seoul metropolitan area. In 2023, international collaborative intensive observations were conducted in partnership with USA, Canada, Spain, and Korean universities, utilizing radar, storm trackers, and other tools. Furthermore, the National Institute of Meteorological Sciences (NIMS) established a supersite near Incheon International Airport, equipped with X and C-band radars, wind profiler, wind lidar, and rain gauges to collect real-time observation data and support operational forecasting.

Summer heavy rainfall in the Korean Peninsula is related to low-level jets. For instance, during heavy rainfall in July 2024 in the Seoul metropolitan area, wind lidar observations near Incheon International Airport showed that low-level jets extended vertically and contributed to the development of heavy rainfall through moisture fluxes. Additionally, to analyze the impact of intensive observation data on improving the accuracy of heavy rainfall predictions, the WRF mesoscale numerical model was used for simulations and analysis. The observation data collected by KMA's intensive observation network is shared and served through the KPOP-MS web page system. Detailed results on the observation network, heavy rainfall case studies, and numerical simulations will be presented at the conference.