EGU23-10436
https://doi.org/10.5194/egusphere-egu23-10436
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Comparison of correlations between radar reflectivity and radar precipitation intensity for snow depth

Narae Kang1, Seokhwan Hwang2, and Jungsoo Yoon3
Narae Kang et al.
  • 1KOREA INSTITUTE of CIVIL ENGINEERING and BUILDING TECHNOLOGY, Department of Hydro Science and Engineering Research, Goyang-si, Korea, Republic of (naraekang@kict.re.kr)
  • 2KOREA INSTITUTE of CIVIL ENGINEERING and BUILDING TECHNOLOGY, Department of Hydro Science and Engineering Research, Goyang-si, Korea, Republic of (sukany@kict.re.kr)
  • 3KOREA INSTITUTE of CIVIL ENGINEERING and BUILDING TECHNOLOGY, Department of Hydro Science and Engineering Research, Goyang-si, Korea, Republic of (jungsooyoon@kict.re.kr)

In order to more quantitatively compare the differences between radar reflectivity and snowfall intensity against ground-observed snow depth, snow depth ground observation data and weather radar observation data were analyzed. For radar observation data, cumulative reflectivity and precipitation intensity derived from reflectivity, differential reflectivity, and specific differential phase (Quantitative Precipitation Estimation) were compared. As a result of the analysis, it was found that the precipitation intensity was similar to the variation according to the snow depth and time compared to the radar reflectivity. However, although the initial accumulation tendency of snow fall was very well matched due to the characteristics of snow cover, which is sensitive to temperature and has accumulation and melting characteristics, the melting tendency from daytime showed a difference. Therefore, it is judged that more accurate snow depth can be estimated only when precipitation intensity estimation method according to temperature is derived and used in addition to methods such as accumulation of reflectivity.

 

Acknowledgement

This research was supported by a grant(2022-MOIS61-003) 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., Hwang, S., and Yoon, J.: Comparison of correlations between radar reflectivity and radar precipitation intensity for snow depth, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-10436, https://doi.org/10.5194/egusphere-egu23-10436, 2023.