• Wednesday/Thursday, 9.10./10.10.2019
• Room A249
• each talk is based on 2 publications
• 30 min presentation, 10-15 minutes discussion
• Language: English or Deutsch

Wednesday, 9.10.2019

9:15
„The GOES-R geostationary lightning mapper“, Sebastian Stadler

10:15
„Lightning and severe weather: A comparison between total and cloud-to-ground lightning trends“, Sabrina Pavicic

11:15
Combining lightning, radar, and satellite data to improve thunderstorm warnings, Lucie Chabert

13:30
Radar‐based cell tracking with a fuzzy logic approach, Eric Reusch

15:30
Determining the flight icing threat to aircraft from operational satellite data, Felicitas Sakellariou

Thursday, 10.10.2019

9:15
Nowcasting challenges during the Beijing Olympics: Successes, failures, and implications for future, Jonas Späth

10:15
Use of NWP for nowcasting convective precipitation: Recent progress and challenges, Matjaz Puh

11:15
Estimating the uncertainty of areal precipitation using data assimilation, Paul Ockenfuß

13:30
Probabilistic precipitation forecasting using nowcast and NWP model, Felix Negwer

Sebastian Stadler, (Fabian Jakub)

• Goodman, S.J., R.J. Blakeslee, W.J. Koshak, D. Mach, J.C. Bailey, L.D. Carey, D.E. Buechler, C.D. Schultz, M. Bateman, E. McCaul and G. Stano, 2013: The GOES-R geostationary lightning mapper. Atmospheric Research, 125–126:34–49, http://dx.doi.org/10.1016/j.atmosres.2013.01.006.
• TBD

Sabrina Pavicic, (Tobias Zinner)

• Schultz, C.J., W.A. Petersen and L.D. Carey, 2011: Lightning and severe weather: A comparison between total and cloud-to-ground lightning trends. Weather Forecasting, 26:744–755. https://journals.ametsoc.org/doi/full/10.1175/WAF-D-10-05026.1
• Schultz, C.J., W.A. Petersen, and L.D. Carey, 2009: Preliminary Development and Evaluation of Lightning Jump Algorithms for the Real-Time Detection of Severe Weather. J. Appl. Meteor. Climatol., 48, 2543–2563, https://doi.org/10.1175/2009JAMC2237.1

Lucie Chabert (Tobias Zinner)

• Bedka, K., C. Wang, R. Rogers, L.D. Carey, W. Feltz and J. Kanak, 2015: Examining deep convective cloud evolution using total lightning, WSR-88D, and GOES-14 super-rapid scan datasets. Weather Forecasting, 30:571–590, https://journals.ametsoc.org/doi/10.1175/WAF-D-14-00062.1
• Cintineo, J.L., M.J. Pavolonis, J.M. Sieglaff, and D.T. Lindsey, 2014: An Empirical Model for Assessing the Severe Weather Potential of Developing Convection. Wea. Forecasting, 29, 639–653, https://journals-ametsoc-org.emedien.ub.uni-muenchen.de/doi/full/10.1175/WAF-D-13-00113.1

Eric Reusch (Gregor Möller)

• Jung, S.H. and G. Lee, 2015: Radar‐based cell tracking with fuzzy logic approach. Meteorological Applications, 22(4):716–730, https://rmets.onlinelibrary.wiley.com/doi/full/10.1002/met.1509
• Han L, Fu SX, Zhao LF, Zheng YZ, Wang HQ, Lin YJ. 2009a. 3D Convective storm identification, tracking, and forecasting – an enhanced TITAN algorithm. J. Atmos. Ocean. Technol. 26: 719–732, https://journals.ametsoc.org/doi/full/10.1175/2008JTECHA1084.1

Jonas Späth (Christian Keil)

• Wilson, J., Y. Feng, M. Chen and R.D. Roberts, 2010: Nowcasting challenges during the Beijing Olympics: Successes, failures, and implications for future nowcasting system. Weather and Forecasting, 25:1691–1714, https://journals.ametsoc.org/doi/full/10.1175/2010WAF2222417.1
• Nerini, D., L. Foresti, D. Leuenberger, S. Robert, and U. Germann, 2019: A Reduced-Space Ensemble Kalman Filter Approach for Flow-Dependent Integration of Radar Extrapolation Nowcasts and NWP Precipitation Ensembles. Mon. Wea. Rev., 147, 987–1006, https://doi.org/10.1175/MWR-D-18-0258.1

Felix Negwer (Christian Keil)

• Bowler, N.E., C.E. Pierce and A.W. Seed, 2006: STEPS: A probabilistic precipitation forecasting scheme which merges an extrapolation nowcast with downscaled NWP. Quarterly Journal of the Royal Meteorological Society, 132:2127–2155, https://rmets.onlinelibrary.wiley.com/doi/abs/10.1256/qj.04.100#references-section
• Simonin, Pierce, Roberts, Ballard, Li, 2017, Performance of Met Office hourly cycling NWP‐based nowcasting for precipitation forecasts, 143, 2862-2873, https://rmets.onlinelibrary.wiley.com/doi/10.1002/qj.3136

Felicitas Sakellariou (Julien Savre)

• Smith, W.L., P. Minnis, C. Fleeger, D. Spangenberg, R. Palikonda and L. Nguyen, 2012: Determining the flight icing threat to aircraft with single-layer cloud parameters derived from operational satellite data. Journal of Applied Meteorology and Climatology, 51:1794–1810., https://journals.ametsoc.org/doi/full/10.1175/JAMC-D-12-057.1
• Cao Y, Tan W, Wu Z. (2018). Aircraft icing: An ongoing threat to aviation safety. Aerospace Science and Technology, 75, 2018., https://www.researchgate.net/publication/322849261_Aircraft_icing_An_ongoing_threat_to_aviation_safety

Paul Ockenfuß (Tijana Janjic-Pfander)

• Merker, C & Geppert, G & Clemens, M & Ament, F & Planck, M. (2019). Estimating the uncertainty of areal precipitation using data assimilation. Tellus A: Dynamic Meteorology and Oceanography. 71. 1-16., https://pure.mpg.de/rest/items/item_3057745_3/component/file_3057747/content
• van Horne, M.P., (2003), Short-Term Precipitation Nowcasting for Composite Radar Rainfall Fields, Master thesis, MIT, September 2003 ( Thesis PDF ).

Matjaz Puh (Tijana Janjic-Pfander)

• Juanzhen, S., M. Xue, J.W. Wilson, I. Zawadzki, S.P. Ballard, J. Onvlee-Hooimeyer, P. Joe, D. Barker, P.W. Li, B. Golding, M. Xu and J. Pinto, 2014: Use of NWP for nowcasting convective precipitation: Recent progress and challenges. Bulletin of the American Meteorological Society, 95:409–426., https://journals.ametsoc.org/doi/full/10.1175/BAMS-D-11-00263.1
• Aksoy et al. 2010: A Multicase Comparative Assessment of the Ensemble Kalman Filter for Assimilation of Radar Observations. Part II: Short-Range Ensemble Forecasts, Mon. Wea. Rev., Vol. 138, 1273-1292., https://journals.ametsoc.org/doi/full/10.1175/2009MWR3086.1