Ukrainian Antarctic Journal

Vol 20 No 1(24) (2022): Ukrainian Antarctic Journal
Articles

Measured and modeled vertical structure of precipitation during mixed-phase event near the West Coast of the Antarctic Peninsula

D. Pishniak
State Institution National Antarctic Scientific Center, Ministry of Education and Science of Ukraine, Kyiv, 01601, Ukraine
S. Razumnyi
State Institution National Antarctic Scientific Center, Ministry of Education and Science of Ukraine, Kyiv, 01601, Ukraine
Published August 4, 2022
Keywords
  • bright band,
  • melting layer,
  • mixed-phase precipitation,
  • precipitation bands,
  • reflectivity,
  • wind shear
  • ...More
    Less
How to Cite
Pishniak, D., & Razumnyi, S. (2022). Measured and modeled vertical structure of precipitation during mixed-phase event near the West Coast of the Antarctic Peninsula. Ukrainian Antarctic Journal, 20(1(24), 55-66. https://doi.org/10.33275/1727-7485.1.2022.689

Abstract

Precipitation structures are easy to detect, however, the mesoscale atmospheric processes which they reflect are challenging to understand in Polar Regions and hard to model numerically. Currently, the spatial distribution of precipitation can be tracked at the resolution of minutes and seconds. For this purpose, the researchers at the Ukrainian Antarctic Akademik Vernadsky station employ several near-ground measurement systems and the Micro Rain Radar for remote vertical measurements. Measurements show stochastic precipitation variability caused by turbulence, precipitation bands related to the atmospheric processes of its formation, phase transition (melting) zones, and wind shears. The time scale of bands in the stratiform precipitation typically varied in the range of 5—15 minutes and corresponded to the 2—15 km spatial scale of atmospheric circulations according to the modeled parameters of the atmosphere. The Polar Weather Research and Forecast (Polar WRF) model was used to reveal the general atmospheric conditions. We also tested and evaluated its ability to reproduce small structures. A simple method based on typical model variables is proposed to identify the precipitation melting layer in the simulation data, similar to that determined by radars. The results were satisfyingly consistent with the position of the 0 °C isotherm in the model and with the radar measurements. In addition, the method highlighted supercooled mixed-phase precipitation. Modeling showed good results for large-scale processes like atmospheric fronts and general air mass features in the case study. However, even at the 1 km resolution the simulation reproduced thin mesoscale precipitation features smoothly, which sometimes looks unrealistic. As for other precipitation peculiarities, like band inclination, melting layer position, and mixed-phase zones, the Polar WRF model demonstrates high consistency with observations. The model can describe the atmospheric conditions except for the investigation of precipitation-initiating mechanisms, which still is a challenge for modeling at a small scale.

References

  1. Austin, P. M., & Bemis, A. C. (1950). A quantitative study of the “bright band” in radar precipitation echoes. Journal of the Atmospheric Sciences, 7(2), 145—151. https://doi.org/10.1175/1520-0469(1950)007<0145:AQSOTB>2.0.CO;2
  2. Awaka, J., Iguchi, T., & Okamoto, K. (2009). TRMM PR standard algorithm 2A23 and its performance on bright band detection. Journal of the Meteorological Society of Japan. Ser. II, 87A, 31—52. https://doi.org/10.2151/jmsj.87A.31
  3. Bauer, H-S., Schwitalla, T., Wulfmeyer, V., Bakhshaii, A., Ehret, U., Neuper, M., & Caumont, O. (2015). Quantitative precipitation estimation based on high-resolution numerical weather prediction and data assimilation with WRF — a performance test. Tellus A: Dynamic Meteorology and Oceanography, 67(1), 25047. https://doi.org/10.3402/tellusa.v67.25047
  4. Brast, M., & Markmann, P. (2020). Detecting the melting layer with a micro rain radar using a neural network approach. Atmospheric Measurement Techniques, 13(12), 6645—6656. https://doi.org/10.5194/amt-13-6645-2020
  5. Chyhareva, A., Gorodetskaya, I., Krakovska, S., Pishniak, D., & Rowe, P. (2021). Precipitation phase transition in austral summer over the Antarctic Peninsula. Ukrainian Antarctic Journal, 1, 32—46. https://doi.org/10.33275/1727-7485.1.2021.664
  6. Drummond, F. J., Rogers, R. R., Cohn, S. A., Eck lund, W. L., Carter, D. A., & Wilson, J. S. (1996). A new look at the melting layer. Journal of the Atmospheric Sciences, 53(5), 759—769. https://doi.org/10.1175/1520-0469(1996)053<0759:ANLATM>2.0.CO;2
  7. Durán-Alarcón, C., Boudevillain, B., Genthon, C., Grazioli, J., Souverijns, N., van Lipzig, N. P. M., Gorodetskaya, I. V., & Berne, A. (2019). The vertical structure of precipitation at two stations in East Antarctica derived from micro rain radars. The Cryosphere, 13, 247—264. https://doi.org/10.5194/tc-13-247-2019
  8. Gorodetskaya, I. V., Kneifel, S., Maahn, M., van Tricht, K., Thiery, W., Schween, J. H., Mangold, A., Crewell, S., & van Lipzig, N. P. M. (2015). Cloud and precipitation properties from ground-based remote-sensing instruments in East Antarctica. The Cryosphere, 9, 285—304. https://doi.org/10.5194/tc-9-285-2015
  9. Heymsfield, A. J., Bansemer, A., Poellot, M. R., & Wood, N. (2015). Observations of ice microphysics through the melting layer. Journal of the Atmospheric Sciences, 72(8), 2902—2928. https://doi.org/10.1175/JAS-D-14-0363.1
  10. Hines, K. M., & Bromwich, D. H. (2008). Development and testing of polar Weather Research and Forecasting (WRF) Model. Part I: Greenland ice sheet meteorology. Monthly Weather Review, 136(6), 1971—1989. https://doi.org/10.1175/2007MWR2112.1
  11. Hines, K. M., Bromwich, D. H., Silber, I., Russell, L. M., & Bai, L. (2021). Predicting frigid mixed-phase clouds for pristine coastal Antarctica. Journal of Geophysical Research: Atmospheres, 126(23), e2021JD0 3 5112. https://doi.org/10.1029/2021JD035112
  12. Iguchi, T., Matsui, T., Tao, W.-K., Khain, A. P., Phillips, V. T. J., Kidd, C., L’Ecuyer, T., Braun, S. A., & Hou, A. (2014). WRF–SBM simulations of melting-layer structure in mixed-phase precipitation events observed during LPVEx. Journal of Applied Meteorology and Climatology, 53(12), 2710—2731. https://doi.org/10.1175/JAMC-D-13-0334.1
  13. Lenaerts, J. T. M., Medley, B., van den Broeke, M. R., & Wouters, B. (2019). Observing and modeling ice sheet surface mass balance. Reviews of Geophysics, 57(2), 376—420. https://doi.org/10.1029/2018RG000622
  14. Matsui, T., Zeng, X., Tao, W.-K., Masunaga, H., Olson, W. S., & Lang, S. (2009). Evaluation of long-term cloud-resolving model simulations using satellite radiance observations and multifrequency satellite simulators. Journal of Atmospheric and Oceanic Technology, 26(7), 1261—1274. https://doi.org/10.1175/2008JTECHA1168.1
  15. Paul, S., Wang, C. C., Tseng, L. S., Lee, D. I., Hong, J. S., Leou, T. M. (2021). Evaluation of rainfall forecasts by three mesoscale models during the Mei-yu season of 2008 in Taiwan. Part I: Subjective comparison. Asia-Pacific Journal of Atmospheric Sciences, 57(4), 817—838. https://doi.org/10.1007/s13143-021- 00229-2
  16. Pishniak, D., & Beznoshchenko, B. (2020). Improving the detailing of atmospheric processes modelling using the Polar WRF model: a case study of a heavy rainfall event at the Akademik Vernadsky station. Ukrainian Antarctic Journal, 2, 26—41. https://doi.org/10.33275/1727-7485.2.2020.650
  17. Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Liu, Z., Berner, J., Wang, W., Powers, J. G., Duda, M. G., Barker, D., & Huang, X.-Y. (2021). A description of the advanced research WRF Model Version 4.3 (No. NCAR/TN-556+STR). https://doi.org/10.5065/1dfh-6p97
  18. Souverijns, N., Gossart, A., Lhermitte, S., Gorodetskaya, I. V., Kneifel, S., Maahn, M., Bliven, F. L., & van Lipzig, N. P. M. (2017). Estimating radar reflectivity — snowfall rate relationships and their uncertainties over Antarctica by combining disdrometer and radar observations. Atmospheric Research, 196, 211—223. https://doi.org/10.1016/j.atmosres.2017.06.001
  19. Szeto, K. K., Lin, C. A., & Stewart, R. E. (1988). Mesoscale circulations forced by melting snow. Part I: Basic simulations and dynamics. Journal of the Atmospheric Sciences, 45(11), 1629—1641. https://doi.org/10.1175/1520-0469(1988)045<1629:MCFBMS>2.0.CO;2
  20. Thurai, M., Deguchi, E., Iguchi, T., & Okamoto, K. (2003). Freezing height distribution in the tropics. International Journal of Satellite Communications and Networking, 21(6), 533—545. https://doi.org/10.1002/sat.768
  21. Zheng, J., Zhang, P., Liu, L., Liu, Y., & Che, Y. (2019). A study of vertical structures and microphysical characteristics of different convective cloud—precipitation types using Kaband millimeter wave radar measurements. Remote Sensing, 11(15), 1810. https://doi.org/10.3390/rs11151810