Snow-depth Spatial Distribution Analysis Technology linked to Ground Observation Network
- KOREA INSTITUTE of CIVIL ENGINEERING and BUILDING TECHNOLOGY, Department of Hydro Science and Engineering Research, Goyang-si, Korea, Republic of (naraekang@kict.re.kr)
In this study, we attempted to classify snowfall patterns using multiple dual-polarization radars and quantitatively review the amount of snowfall observed from radar using a ground observation network (snow depth). In order to more quantitatively compare the difference between radar reflectivity and precipitation (snow) intensity compared to ground observed snow depth, comparison was made on an hourly basis, taking into account the Korea Meteorological Administration's snow observation data provision period (1 hour). Radar observation data were compared with precipitation intensity based on cumulative reflectivity, differential reflectivity, and specific differential phase difference. Compared to radar reflectivity, there were various delays ranging from 2 to 7 hours from the time the precipitation intensity accumulated with the snow depth. In addition, the difference between the time of increase in snow cover is judged to be an error generated by the wind, and it is necessary to expand the range of radar pixels as well as the blinding factor to take into account the influence of wind.
Acknowledgments
This research was supported by a grant(2022-MOIS61-003(RS-2022-ND634022)) of Development Risk Prediction Technology of Storm and Flood for Climate Change based on Artificial Intelligence funded by Ministry of Interior and Safety(MOIS, Korea).
How to cite: Kang, N., Yoon, J., and Hwang, S.: Snow-depth Spatial Distribution Analysis Technology linked to Ground Observation Network, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14040, https://doi.org/10.5194/egusphere-egu24-14040, 2024.