Vol. 33, issue 02, article # 11

Sin’kevich A. A., Popov V. B., Mikhailovskii Yu. P., Toropova M. L., Dovgalyuk Yu. A., Veremei N. E., Starykh D. S. Characteristics of Cb with waterspout over Ladoga Lake derived from remote measurements. // Optika Atmosfery i Okeana. 2020. V. 33. No. 02. P. 153–158. DOI: 10.15372/AOO20200211 [in Russian].
Copy the reference to clipboard

Abstract:

Characteristics of the thunderstorm with a waterspout over Ladoga Lake obtained with the help of C-band radar, lightning detection system, and radiosonde data are studied. The analysis of instability indices shows low and moderate probability of developing intensive convective processes. The hydrometeor classification and the updraft identification algorithms are used for the first time for the DMRL-C radar and are based on processing of polarization measurements. These algorithms made it possible to detect the appearance of big ice particles when lightning began and to extended updraft associated with the waterspout. The correlation analysis of the frequency of lightning and cloud characteristics, obtained by radar, was carried out. It showed the closest correlation of the frequency  with the number of big ice particles, characterized by supercooled part of the cloud (above the 0 °C level)  with the reflectivity higher than 50 dBZ.

Keywords:

waterspout, polarimetric radar, hydrometeor classification algorithm, updraft, instability indices, lightning frequency

References:

  1. Bedritskij A.I. Rossijskij gidrometeorologicheskij slovar'. SPb.: Letnij sad, 2009. 66 p.
  2. Park H.S., Ryzhkov A.V., Zrnic D.S., Kim K.-E. The hydrometeor classification algorithm for the polarimetric WSR-88D: Description and application to an MCS // Weather Forecast. 2009. V. 24. P. 730–748.
  3. Dolan B., Rutledge S.A. A theory-based hydrometeor identification algorithm for X-band polarimetric radars // J. Atmos. Ocean. Technol. 2009. V. 26. P. 2071–2088.
  4. Dolan B., Rutledge S.A., Lim S., Chandrasekar V., Thurai M. A robust C-band hydrometeor identification algorithm and application to a long-term polarimetric radar dataset // J. Appl. Meteorol. Climatol. 2013. V. 52. P. 2162–2186.
  5. Ryzhkov A.V., Zrnic D.S. Radar Polarimetry for Weather Observations. Switzerland: Springer, 2019. 486 p.
  6. Carlin T.J., Gao J., Snyder J.C., Ryzhkov A.V. Assimilation of ZDR columns for improving the spinup and forecast of convective storms in storm-scale models: Proof-of-concept experiments // Mon. Weather Rev. 2017. V. 145. P. 5033–5057.
  7. Sin'kevich A.A., Dovgalyuk Yu.A. Koronnyj razryad v oblakah // Radiofizikasostoyanij molekul: dis. ... dokt. fiz.-mat. nauk. Tomsk, In-t optika atmosfery i okeana. 2014. VТ. LVI, N 11–12. P. 1–12.
  8.  Popov V.B., Sin'kevich A.A., Yang Dzh., Mihajlovskij Yu.P., Toropova M.L., Dovgalyuk Yu.A., Veremej N.E., Staryh D.S. Harakteristiki i struktura kuchevo-dozhdevogo oblaka s vodyanym smerchem v Severo-Zapadnom regione Rossii // Meteorol. i gidrol. (in print).
  9.  Lal D.M., Pawar S.D. Relationship between rainfall and lightning over central Indian region in monsoon and premonsoon seasons // Atmos. Res. 2009. V. 92, iss. 4. P. 402–410.
  10.  Karagiannidis A., Lagouvardos K., Lykoudis S., Kot­roni V., Giannaros T., Betz H.-D. Modeling lightning density using cloud top parameters // Atmos. Res. 2019. V. 222. P. 163–171.
  11.  Pessi A.T., Businger S. Relationships among lightning, precipitation, and hydrometeor characteristics over the North Pacific Ocean // J. Appl. Meteorol. Climatol. 2009. V. 48, N 4. P. 833–848.
  12.  Stasenko V.N. Radiolokatsionnoe issledovanie mnogoyacheistyh konvektivnyh (grozovyh) oblakov. SPb.: Gidrometeoizdat, 2004. 101 p.
  13.  Stepanenko V.D. Radiolokatsiya v meteorologii (radiometeorologiya). L.: Gidrometeoizdat, 1973. 343 p.
  14.  Mihajlovskij Yu.P., Sin'kevich A.A., Pavar S.D., Gopalakrishnan V., Dovgalyuk Yu.A., Veremej N.E., Bogdanov E.V., Kurov A.B., Adzhiev A.H., Malkarova A.M., Abshaev A.M. Issledovaniya razvitiya grozo-gradovogo oblaka. Part 2. Analiz metodov prognoza i diagnoza elektricheskogo sostoyaniya oblakov // Meteorol. i gidrol. 2017. N 6. P. 31–45.
  15. Wanke E., Andersen R., Volgnandt T. A world-wide low-cost community-based time-of-arrival lightning detection and lightning location network [Electronic Resource]. URL: http://en.blitzortung.org/Compendium/ Documentations/Documentation_2014-05-11_Red_ PCB_ 10.4_PCB_12.3_PCB_13.1_PCB_14.1.pdf (last access: 13.01.2020).
  16.  Armstrong R.W., Glenn J.G. Electrical role for severe storm tornadogenesis (and modification) // J. Climatol. Weather. Forecast. 2015. V. 3, iss. 3. P. 1–8.
  17.  Stough M.S., Carey L.D., Schultz C.J. Total lightning as an indicator of mesocyclone behavior // XV Int. Conf. Atmos. Electr. Norman, Oklahoma, June 15–20, 2014. P. 1–15.
  18.  Sin'kevich A.A., Mihajlovskij Yu.P., Dovgalyuk Yu.A., Veremej N.E. Bogdanov E.V., Adzhiev A.H., Malkarova A.M., Abshaev A.M. Issledovaniya razvitiya grozo-gradovogo oblaka. Part 1. Razvitie oblaka i formirovanie elektricheskih razryadov // Meteorol. i gidrol. 2016. N 9. P. 27–40.
  19.  Sin'kevich A.A., Mihajlovskij Yu.P., Matrosov S.Yu., Popov V.B., Snegurov V.S., Snegurov A.V., Dovgalyuk Yu.A., Veremej N.E. Svyaz' struktury konvektivnyh oblakov s chastotoj molnij po rezul'tatam radiofizicheskih izmerenij // Meteorol. i gidrol. 2019. N 6. P. 37–51.