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A Study of Quantitative Snow Water Equivalent (SWE) Estimation by Comparing the Snow Measurement Data

적설 관측자료 비교를 통한 정량적 SWE 산출에 관한 연구

  • Ro, Yonghun (Applied Meteorology Research Division, National Institute of Meteorological Sciences/KMA) ;
  • Chang, Ki-Ho (Radar Planning Team, Weather Radar Center) ;
  • Cha, Joo-Wan (Applied Meteorology Research Division, National Institute of Meteorological Sciences/KMA) ;
  • Chung, Gunhui (Department of Civil Engineering, Hoseo University) ;
  • Choi, Jiwon (Applied Meteorology Research Division, National Institute of Meteorological Sciences/KMA) ;
  • Ha, Jong-Chul (Applied Meteorology Research Division, National Institute of Meteorological Sciences/KMA)
  • 노용훈 (국립기상과학원 응용기상연구과) ;
  • 장기호 (기상레이더센터 레이더기획팀) ;
  • 차주완 (국립기상과학원 응용기상연구과) ;
  • 정건희 (호서대학교 건축토목환경공학부) ;
  • 최지원 (국립기상과학원 응용기상연구과) ;
  • 하종철 (국립기상과학원 응용기상연구과)
  • Received : 2019.04.12
  • Accepted : 2019.06.29
  • Published : 2019.09.30

Abstract

While it is important to obtain the accurate information on snowfall data due to the increase in damage caused by the heavy snowfall in the winter season, it is not easy to observe the snowfall quantitatively. Recently, snow measurements using a weighing precipitation gauge have been carried out, but there is a problem that high snowfall intensity results in low accuracy. Also, the observed snowfall data are sensitive depending on wind speed, temperature, and humidity. In this study, a new process of quality control for snow water equivalent (SWE) data of the weighing precipitation gauge were proposed to cover the low accuracy of snow data and maximize the data utilization. Snowfall data (SWE) observed by Pluvio, Parsivel, snow-depth meter using laser or ultrasonic, and rainfall gauge in Cloud Physics Observation Site (CPOS) were compared and analyzed. Applying the QC algorithm including the use of number of hydrometeor particles as reference, the increased SWE per the unit time was determined and the data noise was removed and marked by flag. The SWE data converted by the number concentration of hydrometeor particles are tested as a method to restore the QC-removed data, and show good agreement with those of the weighing precipitation gauge, though requiring more case studies. The three events data for heavy snowfall disaster in Pyeongchang area was analyzed. The SWE data with improved quality was showed a good correlation with the eye-measured data ($R^2$ > 0.73).

Keywords

Snowfall;weighing precipitation gauge;snow water equivalent;concentration of hydrometeor particles

Acknowledgement

Grant : 기상항공기 활용기술개발연구

Supported by : 국립기상과학원

References

  1. Baxter, M. A., C. E. Graves, and J. T. Moore, 2005: A climatology of snow-to-liquid ratio for the contiguous United States. Wea. Forecasting, 20, 729-744. https://doi.org/10.1175/WAF856.1
  2. Doesken, N. J., and A. Judson, 1996: The Snow booklet: a guide to the science, climatology, and measurement of snow in the United States, Colorado State Univercity, 86 pp.
  3. Egli, L., T. Jonas, and R. Meister, 2009: Comparison of different automatic methods for estimating snow water equivalent. Cold Reg. Sci. Technol., 57, 107-115. https://doi.org/10.1016/j.coldregions.2009.02.008
  4. Grant, L. O., and J. O. Rhea, 1974: Elevation and meteorological controls on the density of snow. Proc. Adv. Concepts Tech. Study Snow Ice Resourc. Interdisciplinary Symp., Monterey, CA, National Academy of Science, 169-181.
  5. Gunn, K. L. S., and J. S. Marshall, 1958: The distribution with size of aggregate snowflakes. J. Meteor., 15, 452-461. https://doi.org/10.1175/1520-0469(1958)015<0452:TDWSOA>2.0.CO;2
  6. Henry, A., 1917: The density of snow. Mon. Wea. Rev., 45, 102.
  7. Judson, A., and N. Doesken, 2000: Density of freshly fallen snow in the central Rocky Mountains. Bull. Amer. Meteor. Soc., 81, 1577-1587. https://doi.org/10.1175/1520-0477(2000)081<1577:DOFFSI>2.3.CO;2
  8. KMA, 2002: Annual climatological report. Korea Meteorological Administration, 256 pp (in Korean).
  9. KMA, 2014: Monthly weather report. Korea Meteorlogical Administration, 119 pp (in Korean).
  10. LaChapelle, E. R., 1962: The density distribution of new snow. USDA Forest Service Tech. Rep. No. 2, Wasatch National Forest, Alta Avalanche Study Center, Project F, 15 pp.
  11. Lee, B., and H. Kim, 2007: Outdoor observation of weight type snow-depth meter Development of weight type rounded snow plate. Proc., Kor. Environ. Sci. Soc. Conf., The Korean Environmental Sciences Society, 136-138 (in Korean).
  12. Lee, B., and H. Kim, 2009: Development of weight type rounded snow plate. Atmosphere, 19, 1-8 (in Korean with English abstract).
  13. Lee, W. J., 2006: Weather chart and weather analysis. Kwanggyo It'aeks Publising Co., 97 pp (in Korean).
  14. Nitu, R., 2013: Cold as SPICE, Meteor. Tech. Int., 148-150.
  15. NIMS, 2018: Advanced research on applied meteorology -Development of weather modification technology. Nat. Ins. Meteor. Sci., 45 pp (in Korean).
  16. Potter, J. G., 1965: Water content of freshly fallen snow, Meteorological Branch, 12 pp.
  17. Rasmussen, R., M. Dixon, S. Vasiloff, F. Hage, S. Knight, J. Vivekanandan, and M. Xu, 2003: Snow nowcasting using a real-time correlation of radar reflectivity with snow gauge accumulation. J. Appl. Meteor. Climatol., 42, 20-36. https://doi.org/10.1175/1520-0450(2003)042<0020:SNUART>2.0.CO;2
  18. Rasmussen, R., and Coauthors, 2012: How well are we measuring snow: The NOAA/FAA/NCAR winter precipitation test bed. Bull. Amer. Meteor. Soc., 93, 811-829, doi:10.1175/BAMS-D-11-00052.1. https://doi.org/10.1175/BAMS-D-11-00052.1
  19. Roebber, P. J., S. L. Bruening, D. M. Schultz, and J. V. Cortinas Jr., 2003: Improving snowfall forecasting by diagnosing snow density. Wea. Forecasting, 18, 264-287. https://doi.org/10.1175/1520-0434(2003)018<0264:ISFBDS>2.0.CO;2
  20. Schmidt, R. A., 1982: Vertical profiles of wind speed, snow concentration, and humidity in blowing snow. Bound.-Layer Meteor., 23, 223-246. https://doi.org/10.1007/BF00123299
  21. Solomon, S., D. Qin, M. Manning, M. Marquis, K. Averyt, M. M. B. Tignor, H. L. Miller Jr., and Z. Chen, 2007: Climate change 2007-The physical science basis: Working group I contribution to the fourth assessment report of the IPCC. Cambridge University Press, 996 pp.
  22. Super, A. B., and E. W. Holroyd, 1997: Snow accumulation algorithm for the WSR-88D radar: Second annual report. US Bureau of Reclamation, 77 pp.
  23. Ulbrich, C. W., 1983: Natural variations in the analytical form of the raindrop size distribution. J. Climate Appl. Meteor., 22, 1764-1775. https://doi.org/10.1175/1520-0450(1983)022<1764:NVITAF>2.0.CO;2
  24. Vuerich, E., C. Monesi, L. Lanza, L. Stagi, and E. Lanzinger, 2009: WMO field intercomparison of rainfall intensity gauges. World Meteorological Organization-Instruments and Observing Methods Report No. 99, 290 pp [Available online at http://library.wmo.int/pmb_ged/wmo-td_1504.pdf].
  25. WMO, 2012: International organizing committee for the WMO solid precipitation intercomparison experiment, third session. World Meteorological Organization, 5-74.