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Wisconsin–Madison, 165 pp. Snook , N. , and M. Xue , 2008 : Effects of microphysical drop size distribution on tornadogenesis in supercell thunderstorms . Geophys. Res. Lett. , 35 , 851 – 854 , https://doi.org/10.1029/2008GL035866 . 10.1029/2008GL035866 Sobash , R. A. , G. S. Romine , C. S. Schwartz , D. J. Gagne , and M. L. Weisman , 2016 : Explicit forecasts of low-level rotation from convection-allowing models for next-day tornado prediction . Wea. Forecasting , 31 , 1591 – 1614
Wisconsin–Madison, 165 pp. Snook , N. , and M. Xue , 2008 : Effects of microphysical drop size distribution on tornadogenesis in supercell thunderstorms . Geophys. Res. Lett. , 35 , 851 – 854 , https://doi.org/10.1029/2008GL035866 . 10.1029/2008GL035866 Sobash , R. A. , G. S. Romine , C. S. Schwartz , D. J. Gagne , and M. L. Weisman , 2016 : Explicit forecasts of low-level rotation from convection-allowing models for next-day tornado prediction . Wea. Forecasting , 31 , 1591 – 1614
. Geophys. Union, 203–221. 10.1029/GM079p0203 Burgess , D. W. , M. A. Magsig , J. Wurman , D. C. Dowell , and Y. Richardson , 2002 : Radar observations of the 3 May 1999 Oklahoma City tornado . Wea. Forecasting , 17 , 456 – 471 , https://doi.org/10.1175/1520-0434(2002)017<0456:ROOTMO>2.0.CO;2 . 10.1175/1520-0434(2002)017<0456:ROOTMO>2.0.CO;2 Burgess , D. W. , E. R. Mansell , C. M. Schwarz , and B. J. Allen , 2010 : Tornado and tornadogenesis events seen by the NOXP X-band, dual
. Geophys. Union, 203–221. 10.1029/GM079p0203 Burgess , D. W. , M. A. Magsig , J. Wurman , D. C. Dowell , and Y. Richardson , 2002 : Radar observations of the 3 May 1999 Oklahoma City tornado . Wea. Forecasting , 17 , 456 – 471 , https://doi.org/10.1175/1520-0434(2002)017<0456:ROOTMO>2.0.CO;2 . 10.1175/1520-0434(2002)017<0456:ROOTMO>2.0.CO;2 Burgess , D. W. , E. R. Mansell , C. M. Schwarz , and B. J. Allen , 2010 : Tornado and tornadogenesis events seen by the NOXP X-band, dual
.1175/MWR-D-16-0410.1 Skamarock , W. C. , and Coauthors , 2008 : A description of the Advanced Research WRF version 3. NCAR Tech. Note NCAR/TN-475+STR, 113 pp., https://doi.org/10.5065/D68S4MVH . 10.5065/D68S4MVH Snook , N. , and M. Xue , 2008 : Effects of microphysical drop size distribution on tornadogenesis in supercell thunderstorms . Geophys. Res. Lett. , 35 , L24803 , https://doi.org/10.1029/2008GL035866 . 10.1029/2008GL035866 Sobash , R. A. , J. S. Kain , D. R. Bright , A. R. Dean
.1175/MWR-D-16-0410.1 Skamarock , W. C. , and Coauthors , 2008 : A description of the Advanced Research WRF version 3. NCAR Tech. Note NCAR/TN-475+STR, 113 pp., https://doi.org/10.5065/D68S4MVH . 10.5065/D68S4MVH Snook , N. , and M. Xue , 2008 : Effects of microphysical drop size distribution on tornadogenesis in supercell thunderstorms . Geophys. Res. Lett. , 35 , L24803 , https://doi.org/10.1029/2008GL035866 . 10.1029/2008GL035866 Sobash , R. A. , J. S. Kain , D. R. Bright , A. R. Dean
: 25 years of interactive processing . Bull. Amer. Meteor. Soc. , 80 , 271 – 284 , https://doi.org/10.1175/1520-0477(1999)080<0271:TMCIDA>2.0.CO;2 . 10.1175/1520-0477(1999)080<0271:TMCIDA>2.0.CO;2 Lemon , L. R. , and C. A. Doswell III , 1979 : Severe thunderstorm evolution and mesocyclone structure as related to tornadogenesis . Mon. Wea. Rev. , 107 , 1184 – 1197 , https://doi.org/10.1175/1520-0493(1979)107<1184:STEAMS>2.0.CO;2 . 10.1175/1520-0493(1979)107<1184:STEAMS>2.0.CO;2 Lenz , A
: 25 years of interactive processing . Bull. Amer. Meteor. Soc. , 80 , 271 – 284 , https://doi.org/10.1175/1520-0477(1999)080<0271:TMCIDA>2.0.CO;2 . 10.1175/1520-0477(1999)080<0271:TMCIDA>2.0.CO;2 Lemon , L. R. , and C. A. Doswell III , 1979 : Severe thunderstorm evolution and mesocyclone structure as related to tornadogenesis . Mon. Wea. Rev. , 107 , 1184 – 1197 , https://doi.org/10.1175/1520-0493(1979)107<1184:STEAMS>2.0.CO;2 . 10.1175/1520-0493(1979)107<1184:STEAMS>2.0.CO;2 Lenz , A
. 2019 ), replacing subgrid-scale parameterizations in a climate model ( Rasp et al. 2018 ), and forecasting tornadogenesis (McGovern et al. 2019, manuscript submitted to Bull. Amer. Meteor. Soc .) and large hail ( Gagne et al. 2019 ). Also, Reichstein et al. (2019) and Gil et al. (2019) have recently called for a vast expansion of our efforts to incorporate deep learning into geoscience. Section 2 describes CNNs, our chosen DL model; section 3 describes our input data and preprocessing
. 2019 ), replacing subgrid-scale parameterizations in a climate model ( Rasp et al. 2018 ), and forecasting tornadogenesis (McGovern et al. 2019, manuscript submitted to Bull. Amer. Meteor. Soc .) and large hail ( Gagne et al. 2019 ). Also, Reichstein et al. (2019) and Gil et al. (2019) have recently called for a vast expansion of our efforts to incorporate deep learning into geoscience. Section 2 describes CNNs, our chosen DL model; section 3 describes our input data and preprocessing
cannot compete. The largest differences between the 3- and 1-km tornado SSPFs occurred on scales between 150 and 300 km. We hypothesize that the peak in 3- and 1-km skill differences on the mesoscale exists since the minimum scales at which CAMs can accurately predict tornadic environments also exists on the mesoscale. Given that storm-scale processes that lead to tornadogenesis are not predictable within the forecast lead time range considered here, producing accurate next-day tornado forecasts with
cannot compete. The largest differences between the 3- and 1-km tornado SSPFs occurred on scales between 150 and 300 km. We hypothesize that the peak in 3- and 1-km skill differences on the mesoscale exists since the minimum scales at which CAMs can accurately predict tornadic environments also exists on the mesoscale. Given that storm-scale processes that lead to tornadogenesis are not predictable within the forecast lead time range considered here, producing accurate next-day tornado forecasts with
spatiotemporal approach to tornado prediction. Proc. Int. Joint Conf. on Neural Networks , Montreal, QC, Canada, IEEE , doi: 10.1109/IJCNN.2005.1556125 . Lakshmanan, V. , Hondl K. , and Rabin R. , 2009 : An efficient, general-purpose technique for identifying storm cells in geospatial images . J. Atmos. Oceanic Technol. , 26 , 523 – 537 , doi: 10.1175/2008JTECHA1153.1 . Lee, B. D. , and Wilhelmson R. B. , 1997 : The numerical simulation of non-supercell tornadogenesis. Part I: Initiation and
spatiotemporal approach to tornado prediction. Proc. Int. Joint Conf. on Neural Networks , Montreal, QC, Canada, IEEE , doi: 10.1109/IJCNN.2005.1556125 . Lakshmanan, V. , Hondl K. , and Rabin R. , 2009 : An efficient, general-purpose technique for identifying storm cells in geospatial images . J. Atmos. Oceanic Technol. , 26 , 523 – 537 , doi: 10.1175/2008JTECHA1153.1 . Lee, B. D. , and Wilhelmson R. B. , 1997 : The numerical simulation of non-supercell tornadogenesis. Part I: Initiation and
water—A new analysis tool . Mon. Wea. Rev. , 100 , 548 – 552 , doi: 10.1175/1520-0493(1972)100<0548:VILWNA>2.3.CO;2 . Houser, J. L. , Bluestein H. B. , and 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 . Mon. Wea. Rev. , 143 , 2685 – 2710 , doi: 10.1175/MWR-D-14-00253.1 . Houze, R. A., Jr. , Rutledge S. A. , Biggerstaff M. I. , and Smull B
water—A new analysis tool . Mon. Wea. Rev. , 100 , 548 – 552 , doi: 10.1175/1520-0493(1972)100<0548:VILWNA>2.3.CO;2 . Houser, J. L. , Bluestein H. B. , and 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 . Mon. Wea. Rev. , 143 , 2685 – 2710 , doi: 10.1175/MWR-D-14-00253.1 . Houze, R. A., Jr. , Rutledge S. A. , Biggerstaff M. I. , and Smull B
supercell event. The radar observations are assimilated every 5 min for a 45-min-long assimilation period prior to tornadogenesis, and 1-h ensemble forecasts are launched after 15, 30, and 45 min of radar DA. The goal is to see if the findings from the OSSE study of Yussouf and Stensrud (2010) hold true in a realistic mesoscale environment using real radar observations. The rest of this paper is organized as follows. A brief description of the supercell event is documented in section 2 . Section 3
supercell event. The radar observations are assimilated every 5 min for a 45-min-long assimilation period prior to tornadogenesis, and 1-h ensemble forecasts are launched after 15, 30, and 45 min of radar DA. The goal is to see if the findings from the OSSE study of Yussouf and Stensrud (2010) hold true in a realistic mesoscale environment using real radar observations. The rest of this paper is organized as follows. A brief description of the supercell event is documented in section 2 . Section 3
updrafts in low-buoyancy, highly sheared environments . Mon. Wea. Rev. , 128 , 449 – 461 , doi: 10.1175/1520-0493(2000)128<0449:SOORUI>2.0.CO;2 . Markowski, P. M. , and Richardson Y. P. , 2014 : The influence of environmental low-level shear and cold pools on tornadogenesis: Insights from idealized simulations . J. Atmos. Sci. , 71 , 243 – 275 , doi: 10.1175/JAS-D-13-0159.1 . McAvoy, B. P. , Jones W. A. , and Moore P. D. , 2000 : Investigation of an unusual storm structure associated
updrafts in low-buoyancy, highly sheared environments . Mon. Wea. Rev. , 128 , 449 – 461 , doi: 10.1175/1520-0493(2000)128<0449:SOORUI>2.0.CO;2 . Markowski, P. M. , and Richardson Y. P. , 2014 : The influence of environmental low-level shear and cold pools on tornadogenesis: Insights from idealized simulations . J. Atmos. Sci. , 71 , 243 – 275 , doi: 10.1175/JAS-D-13-0159.1 . McAvoy, B. P. , Jones W. A. , and Moore P. D. , 2000 : Investigation of an unusual storm structure associated
