Abstract
Synoptic and mesoscale analyses indicate environmental conditions favorable to the development of tornados and downbursts in Eastern São Paulo State, Brazil, between 16 May and 06 June 2016 under El Niño Sothern Oscillation (ENSO) condition. A subtropical jet stream strengthened by the 2015/2016 El Niño event over southeast Brazil and low-level moisture advection from the Amazon induced mid-level mesoscale vorticity and strong updrafts, respectively. These synoptic summer-like conditions yielded high dynamic and thermodynamic instability, producing deep convection and supercells with high lightning and precipitation rates with golf ball-sized hail stones and high winds at the surface, causing damages to trees, houses, towers and other structures with debris features associated with tornadoes and microbursts. Cellular phone photos and movies of severe weather events in Campinas and Janiru cities on 05 and 06 June 2016 suggest wind damage features caused by tornadoes ranked in the enhanced Fujita (EF) wind scale as EF1 (38–49 m s−1) and EF2 (49–60 m s−1), respectively. Similarly, cellular phone movies of Embu-Guaçu City severe weather event on 16 May 2016 suggest a microburst case. The present study is based on quantitative and qualitative records of three high-impact rainfall, hail, lightning and wind gust episodes in the extra tropics during late fall 2016.
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References
Akter, F., & Ishikawa, H. (2014). Synoptic features and environmental conditions of the tornado outbreak on March 22, 2013 at Brahmanbaria in the east-central region of Bangladesh. Natural Hazards,74, 1309–1326.
Allen, J. T., Tippet, M. K., & Sobel, A. H. (2015). Influence of the El Niño/Southern Oscillation on tornado and hail frequency in the United States. Nature Geoscience,8, 278–283.
Atkins, N. T., Butler, K. M., Flynn, K. R., & Wakimoto, R. M. (2014). An integrated damage, visual, and radar analysis of the 2013 Moore, Oklahoma, EF5 tornado. American Meteorological Society, BAMS,95, 1549–1561.
Bech, J., Pascual, R., Rigo, T., Pineda, N., Lopez, J. M., Arús, J., et al. (2007). An observational study of the 7 September 2005 Barcelona tornado outbreak. Natural Hazards and Earth System Sciences,7, 129–139.
Beck, V., & Dotzek, N. (2010). Reconstruction of near-surface tornado wind fields from forest damage. Journal of Applied Meteorology and Climatology,49, 1517–1537.
Bedka, M. K. (2011). Overshooting cloud top detections using MSG SEVIRI Infrared brightness temperatures and their relationship to severe weather over Europe. Atmospheric Research,99, 175–189.
Bluestein, H. B. (2005). A review of ground-based, mobile, W-band Doppler-radar observations of tornadoes and dust devils. Dynamics of Atmospheres and Oceans,40, 163–188.
Bluestein, H. B., French, M. M., Popstefanija, I., Bluth, R. T., & Knorr, J. B. (2010). A mobile (pp. 579–600). BAMS: Phased-array doppler radar for the study of severe convective storms.
Bluestein, H. B., French, M. M., & Tanamachi, R. L. (2017). Close-range observations of tornadoes in supercells made with a dual-polarization, X-band, mobile Doppler radar. Monthly Weather Review,135, 1522–1543.
Bolton, N., Elsom, D. M., & Meaden, G. T. (2003). Forecasting tornadoes in the United Kingdom. Atmospheric Research,67–68, 53–72.
Broeke, M. S. V. D. (2015). Polarimetric tornadic debris signature variability and debris fallout signatures. Journal of Applied Meteorology and Climatology,54, 2389–2405.
Broeke, M. S. V. D., & Straka, J. M. (2008). Polarimetric radar observations at low levels during tornado life cycles in a small sample of classic southern plains supercells. Journal of Applied Meteorology and Climatology,47, 1232–1247.
Brooks, H. E., Carbin, G. W., & Marsh, P. T. (2016). Increased variability of tornado occurrence in the United States. Climate Change,346, 349–352.
Brown, R. A., & Wood, V. T. (2015). Detection of the presence of tornadoes at the center mesocyclones using simulated Doppler velocity measurements. Weather and Forecasting,30, 957–963.
Brown, R. A., Wood, V. T., & Sirmans, D. (2002). Improved tornado detection using simulated and actual WSR-88D data with enhanced resolution. Journal of Atmospheric and Oceanic Technology,19, 1759–1771.
Burgess, D., Ortega, K., Stumpf, G., Garfield, G., Karstens, C., Meyer, T., et al. (2014). 20 May 2013 Moore, Oklahoma, tornado: Damage survey and analysis. Weather and Forecasting,29, 1229–1237.
Cook, A. R., & Schaefer, J. T. (2008). The relation of El Niño–Southern Oscillation (ENSO) to winter tornado outbreaks. Monthly Weather Review,136, 3121–3137.
Davis, J. M., & Parker, M. D. (2014). Radar climatology of tornadic and nontornadic vortices in high-shear, low-CAPE environments in the mid-Atlantic and southeastern United States. Weather and Forecasting,29, 828–853.
Ellrod, G. P., Nelson, J. P., III, Witiw, M. R., Bottos, L., & Roeder, W. P. (2000). Experimental GOES sounder products for the assessment of downburst potential. Weather and Forecasting,15, 527–542.
Elsner, J. B., & Widen, H. W. (2014). Predicting spring tornado activity in the central Great Plains by 1 March. Monthly Weather Review,142, 1–10.
French, M. M., Bluestein, H. B., Popstefanija, I., Baldi, C. A., & Bluth, R. T. (2013). Reexamining the vertical development of tornadic vortex signatures in supercells. Monthly Weather Review,141, 4576–4601.
French, M. M., Burgess, D. W., Mansell, E. R., & Wicker, L. J. (2015). Bulk hook echo raindrop sizes retrieved using mobile, polarimetric Doppler radar observations. Journal of Applied Meteorology and Climatology,54, 423–450.
Giaiotti, D. B., & Stel, F. (2007). A multiscale observational case study of an isolated tornadic supercell. Atmospheric Research,83, 152–161.
Gravelle, C. M., Mecikalski, J. R., Line, W. E., Bedka, K. M., Petersen, R. A., Sieglaff, J. M., et al. (2016). Demonstration of a GOES-R satellite convective toolkit to “Bridge the Gap” between severe weather watches and warnings: An example from the 20 May 2013 Moore, Oklahoma, Tornado Outbreak. Bulletin of the American Meteorological Society, 97, 69–84.
Houser, J. L., Bluestein, H. B., & Snyder, J. C. (2015). Rapid-scan, polarimetric Doppler radar observations of tornadogenesis and tornado dissipation in a tornadic supercell: The “El Reno, Oklahoma” storm of 24 May 2011. Monthly Weather Review,143, 2685–2710.
Jedlovec, G. J., Nair, U., & Haines, S. L. (2006). Detection of storm damage tracks with EOS data. Weather and Forecasting,21, 249–253.
Kingfield, D. M., & LaDue, J. G. (2015). The relationship between automated low-level velocity calculations from the WSR-88D and maximum tornado intensity determined from damage surveys. Weather and Forecasting,30, 1125–1139.
Knox, J. A., Rackley, J. A., Black, A. W., Gensini, V. A., Butler, M., Dunn, C., et al. (2013). Tornado debris characteristics and trajectories during the 27 April 2011 super outbreak as determined using social media data. American Meteorological Society,94, 1371–1380.
Krishnamurthy, L., Vecchi, G. A., Msadek, R., Wittenberg, A., Delworth, T. L., & Zeng, F. (2015). The seasonality of the great plains low-level jet and ENSO relationship. Journal of Climate,28, 4525–4544.
Kumjian, M. R., & Ryzhkov, A. (2008). Polarimetric signatures in supercell thunderstorms. Journal of Applied Meteorology and Climatology,47, 1940–1961.
Lee, S. K., Atlas, R., Enfield, D., Wang, C., & Liu, H. (2013). Is there an optimal ENSO pattern that enhances large-scale atmospheric process conducive to tornado outbreaks in the United States? Journal of Climate,26, 1626–1642.
Lee, S. K., Wittenberg, A. T., Enfield, D. B., Weaver, S. J., Wang, C., & Atlas, R. (2016). US regional tornado outbreaks and their links to spring ENSO phases and North Atlantic SST variability. Environmental Research Letters, 11, 044008. https://doi.org/10.1088/1748-9326/11/4/044008.
Leeman, J. R., & Schmitter, E. D. (2009). Electric signals generated by tornados. Atmospheric Research,92, 277–279.
Mahale, J. A., Brotzge, J. A., & Bluestein, H. B. (2014). The advantages of a mixed-band radar network for severe weather operations: a case study of 13 May 2009. Weather and Forecasting,29, 78–98.
Malamud, B. D., & Turcotte, D. L. (2012). Statistics of severe tornadoes and severe tornado outbreaks. Atmospheric Chemistry and Physics,12, 8459–8473.
Mccaul, E. W., Buechler, D. E., Goodman, S. J., & Cammarata, M. (2004). Doppler radar and lightning network observations of a severe outbreak of tropical cyclone tornadoes. Monthly Weather Review,132, 1747–1763.
Meng, Z., & Yao, D. (2014). Damage survey, radar, and environment analyses on the first-ever documented tornado in Beijing during the heavy rainfall event of 21 July 2012. Weather and Forecasting,29, 702–724.
Morales, C. A. R., Anagnostou, E. N., Williams, E., & Stanley Kriz, J. (2007). Evaluation of peak current polarity retrieved by the ZEUS long-range lightning monitoring system. IEEE Geoscience and Remote Sensing Letters,4(1), 32–36.
Mulder, K. J., & Schultz, D. M. (2015). Climatology, storm morphologies, and environments of tornadoes in the British Isles: 1980–2012. Monthly Weather Review,143, 2224–2240.
Mynt, S. W., Yuan, M., Cerveny, R. S., & Giri, C. (2008). Categorizing natural disaster damage assessment using satellite-based geospatial techniques. Natural Hazards and Earth System Sciences,8, 707–719.
Palmer, R. D., Bodine, D., Kumjian, M., Cheong, B., Zhang, G., Cao, Q., et al. (2011). Observations of the 10 May 2010 tornado outbreak using OU-Prime. BAMS,92, 871–891.
Pereira Filho, A. J. (2012). A mobile X-POL weather radar for hydrometeorological applications in the metropolitan area of São Paulo, Brazil. Geoscientific Instrumentation, Methods and Data Systems,1, 169–183. https://doi.org/10.5194/gi-1-169-2012.
Pereira Filho, A. J., Pereira, J. D., Vemado, F., & Silva, I. W., Jr. (2015). Operational hydrometeorological forecast system for Espírito Santo State, Brazil. Journal of Hydrologic Engineering. https://doi.org/10.1061/(asce)HE.1943-5584.0001215.
Rauhala, J., Brooks, H. E., & Schultz, D. M. (2012). Tornado climatology of Finland. Monthly Weather Review,140, 1446–1456.
Ryzhkov, A. V., Schuur, T. J., & Burgess, D. W. (2005). Polarimetric tornado detection. Journal of Applied Meteorology,44, 557–570.
Schmid, W., Shiesser, H.-H., Furger, M., & Jenni, M. (2000). The origin of severe winds in a tornadic bow-echo storm over Northern Switzerland. Monthly Weather Review,128, 192–207.
Schneider, D., & Sharp, S. (2007). Radar signatures of tropical cyclone tornadoes in central North Carolina. Weather and Forecasting,22, 278–286.
Sills, D. M., Wilson, J. W., Joe, P. I., Burgess, D. W., Webb, R. M., & Fox, N. I. (2004). The 3 November tornadic event during Sydney 2000: Storm evolution and the role of low-level boundaries. Weather and Forecasting,19, 22–31.
Smith, T. M., Elmore, K. L., & Dulin, S. A. (2004). A damaging downburst prediction and detection algorithm for the WSR-88D. Weather and Forecasting,19, 240–250.
Smith, B. T., Thompson, R. L., Dean, A. R., & Marsh, P. T. (2015). Diagnosing the conditional probability of tornado damage rating using environmental and radar attributes. Weather and Forecasting,30, 914–932.
Thompson, D. B., & Roundy, P. E. (2013). The relationship between the Madden–Julian Oscillation and U.S. violent tornado outbreaks in the spring. Monthly Weather Review,141, 2087–2095.
Tippett, M. K., Sobel, A. H., & Camargo, S. J. (2012). Association of U.S. tornado occurrence with monthly environmental parameters. Geophysical Research Letters,39, L02801.
Tochimoto, E., & Niino, H. (2016). Structural and environmental characteristics of extratropical cyclones that cause tornado outbreaks in the warm sector: A composite study. Monthly Weather Review,144, 945–969.
Toth, M., Trapp, R. J., Wurman, J., & Kosiba, K. A. (2013). Comparison of mobile-radar measurements of tornado intensity with corresponding WSR-88D measurements. Weather and Forecasting,28, 418–426. https://doi.org/10.1175/WAF-D-12-00019.1.
Trapp, R. J., Tessendorf, S. A., Godfrey, E. S., & Brooks, H. E. (2005). Tornadoes from squall lines and bow echoes. Part I: Climatological distribution. Weather and Forecasting,20, 23–34.
Wang, Y., & Yu, T.-Y. (2015). Novel tornado detection using an adaptive neuro-fuzzy system with S-band polarimetric weather radar. Journal of Atmospheric and Oceanic Technology,32, 195–208.
Wapler, K., Hengstebeck, T., & Groenemeijer, P. (2016). Mesocyclones in Central Europe as seen by radar. Atmospheric Research,168, 112–120.
Wesolek, E., & Mahieu, P. (2011). The F4 tornado of August 3, 2008, in Northern France: Case study of a tornadic storm in a low CAPE environment. Atmospheric Research,100, 649–656.
Wurman, J., Koshiba, K., Markowski, P., Richardson, Y., Dowell, D., & Robinson, P. (2010). Finescale single- and dual-Doppler analysis of tornado intensification, maintenance, and dissipation in the Orleans, Nebraska, supercell. Monthly Weather Review,138, 4439–4455.
Yuan, M., Micozzi, M. D., & Magsig, M. A. (2002). Analysis of tornado damage tracks from the 3 May tornado outbreak using multispectral satellite imagery. Weather and Forecasting,17, 382–398.
Acknowledgements
The authors are grateful to Departamento de Águas e Energia Elétrica (DAEE) for providing SPWR datasets. The first author is partially supported by the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) under grant 301149/2017-8.
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Pereira Filho, A.J., Vemado, F. & Karam, H.A. Evidence of Tornadoes and Microbursts in São Paulo State, Brazil: A Synoptic and Mesoscale Analysis. Pure Appl. Geophys. 176, 5079–5106 (2019). https://doi.org/10.1007/s00024-019-02276-3
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DOI: https://doi.org/10.1007/s00024-019-02276-3