Snowfall Estimation Using Dual-wavelength Radar during the PyeongChang 2018 Olympics and Paralympic Winter Games

Abstract

 Accurate estimation of snowfall rate during snowstorms is crucial. This estimate directly impacts the hydrological and atmospheric models. The density of snow plays a very important role in estimating the snowfall rate. In this paper, the density of snow is investigated during a huge snowstorm event during the International Collaborative Experiment held during the PyeongChang 2018 Olympics and Paralympic winter games (ICE-POP 2018). The density is calculated using the terminal velocities and diameters of the snow particles measured by a disdrometer. In this study, we not only use radar reflectivity factor (Z) for snowfall rate (S) estimation, but also use dual-frequency ratio (DFR). We derive S-Z and S-Z-DFR relations for snowfall estimation during this snowstorm event after considering the density of snow. The comparisons are performed between National Aeronautics and Space Administration (NASA) Dual-frequency Dual-polarization Doppler Radar (D3R) and precipitation gauges using these two power-law relations. The results show that the two relations for snowfall rate estimation agree well with gauges, but the S-Z-DFR method performs the best, which has a lower normalized standard error. The error in the snowfall rate estimates decreases as the time scale becomes large. This shows that the S-Z-DFR algorithm is a promising way for snowfall quantitative precipitation estimation (QPE) and can be used as a ground validation tool for Global Precipitation Measurement (GPM) snowfall production evaluations.