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LI Yao, NIU Shengjie, LÜ Jingjing. 2020. PARSIVEL2 Revised Method and Error Calculation for Snow Measurement [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 44(4): 808−815. doi: 10.3878/j.issn.1006-9895.1908.19144
Citation: LI Yao, NIU Shengjie, LÜ Jingjing. 2020. PARSIVEL2 Revised Method and Error Calculation for Snow Measurement [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 44(4): 808−815. doi: 10.3878/j.issn.1006-9895.1908.19144

PARSIVEL2 Revised Method and Error Calculation for Snow Measurement

  • To obtain accurate winter precipitation data, this study focuses on the correction and error calculation of the influence of near-surface horizontal wind during snowfall measurement using particle size and velocity (PARSIVEL2). Revised results show that under certain wind speeds, ignoring the influence of wind can cause the significant underestimation of large particles’ diameter. By contrast, large wind speeds indicate that the underestimation of same-sized particles’ diameter during calculation is evident. When the wind speed does not exceed 2 m s−1, the calculation error of the falling speed of snowfall particles is approximately 3%, and the calculation error of diameters is within 7%. In the analysis of the real snowflake spectrum obtained during a snowfall in Nanjing on 4 January, 2018, ignoring the influence of wind shifts the peak of the snowflake spectrum and narrows the spectrum, resulting in the overestimated concentration of small particles and underestimated concentration of large particles, which in turn affect the calculation of microphysical quantities. Specifically, radar reflectivity factor Z and snowfall intensity I are underestimated, and the actual value of the ZI relationship fitting coefficient a is greater than the calculated value, whereas b is small. However, when the wind speed is large, the flow near the ground is complicated, and the vertical turbulent motion cannot be ignored. This correction method may no longer be applicable. Adding windbreakers in future observations or making corrections in subsequent data processing is recommended to eliminate the impact of wind on snowfall measurements.
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