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Nowcasting thunderstorms in complex cases using radar data

Nowcasting thunderstorms in complex cases using radar data. Alessandro Hering* Stéphane Sénési # Paolo Ambrosetti* Isabelle Bernard-Bouissières # * MeteoSwiss ML/RASA, Locarno-Monti # Météo-France DPREVI/PI, Toulouse. TRT application output ( T hunderstorms R adar T racking). 21:00.

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Nowcasting thunderstorms in complex cases using radar data

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  1. Nowcasting thunderstorms in complex cases using radar data Alessandro Hering* Stéphane Sénési# Paolo Ambrosetti* Isabelle Bernard-Bouissières# *MeteoSwiss ML/RASA, Locarno-Monti #Météo-France DPREVI/PI, Toulouse

  2. TRT application output (Thunderstorms Radar Tracking) 21:00 17:00 100 km 330 km 13dBZ 25dBZ 40dBZ 55dBZ

  3. TRT input/output Monte Lema, 1625 m 46.04N, 8.83E Swiss radar network: • 3 volumetric C-band Doppler radars • 20 elevation scan (-0.3° / 40°) every 5 min Input: 1. Radar • Cartesian composite (3 radars); 5 min • vertical maximum projection (from 12 CAPPI between 1 and 12 km) • resolution: 2 km on 16 reflectivity classes between <13 and >55 dBZ 2. Lightning data (Météorage): CG Output:TRT-objects (attributes: geographical location, area, motion vector, velocity, trajectories, lightning...) Visualisation: - 2003: Browser - 2006: NinJo workstation (P.Joe, 7.13)

  4. cell 1 cell 2 cell 3 54 ΔdBT ΔdBT ΔdBT = 6dB Reflectivity [dBZ] 45 dBth ΔdBT dBth dBmin = 36 50 100 150 Range [km] TRT cells detection principle • TRT developed by MeteoSwiss and Météo-France (RDT) • TRT algorithm: modification of RDT satellite-algorithms for Alpine radar images • ADAPTIVEREFLECTIVITY THRESHOLDING: cells at individual thresholds

  5. t0+Δt t0+adv t0 + + v(t0) TRT tracking principle • Method: GEOGRAPHICAL OVERLAPPING of cells • - Advection (estimated displacement velocity or cross-correlation) • Complex cases / splits / merges considered • Good tracking also for small objects

  6. GERMANY MAX > 55 dBZ 550 km A L P S FRANCE ITALY 600 km 36 [dBZ] >55 [dBZ]

  7. TRT drill down product

  8. TRT cell velocity estimates • Unstability of centroid velocity caused by splits, merges, significant area changes • New: cross-correlation at object scale (∆area > 30%) and centroid displacement • Temporal smoothing filter • Better performance in complex cases Previous algorithm Improved actual algorithm splits/merges

  9. TRT cell area and CG lightning evolution • Cell area evolution at different reflectivities (>45 dBZ) in 3 dB steps; real-time • Complex case: splits/merges, significant area changes • Total, negative/positive CG lightning

  10. Broadcasting “Thunderstorm Flash-news” • During this summer MeteoSwiss started the diffusion of heavy thunderstorms warnings based on TRT and other sources • In whole Switzerland for the general public and the authorities • Use simple flash-news diffused by local and national radio stations • Lead time:30-120 min. • June-September 2005: 70 Flash-news on 18 warning days • Forecasters: substantialTRT contibution to flash-news

  11. “Thunderstorm Flash-news”: tipical timing Time [min] 0 Actual Radar image available TRT algorithm (+ other data sources) Analysis by forecaster Edit Flash message Transmission of Flash message SMS, fax... Message Broadcast by radio (local, national) Actions by users (authorities,general public) 2 4 A severe thunderstorm is presently located over Geneva and will probably move in the next 60 minutes to the region of Lausanne. It can produce wind gust over 75 km/h or hail. 12 16 19 24-50 ?

  12. “Thunderstorm Flash”: experience summer 2005

  13. TRT: Summary and outlook • TRT: automatic identification, tracking and monitoring of convective systems using radar and lightning data • Adaptive reflectivity thresholding • Splits / merges, complex cases • Time histories of cell attributes • 2003: TRT operational at MeteoSwiss for nowcasting • 2005: thunderstorms Flash-news warnings (positive preliminary assessment) • 2006: visualisation in the NinJo workstation • Outlook: more extensive use of 3D reflectivity data (echo top, VIL, probability of hail,...)

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