Information on thunderstorm initiation, nowcast, and forecast for aviation safety and efficiency
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1 Information on thunderstorm initiation, nowcast, and forecast for aviation safety and efficiency by Dennis Stich, C. Forster, A. Tafferner, M. Köhler, I. Sölch, and T. Gerz 1 st ECATS Conference (on Technical challenges for aviation in a changing environment) Berlin, Germany, November 2013
2 Chart 2 > ECATS 2013 > Dennis Stich > November 2013 Thunderstorm information for air traffic - why? Adverse weather is responsible for 40-50% of all delays in Europe Hazards: Thunderstorm activity is the reason for up to 90 % of all delays in the airspace Hail over the USA during the summer months. Up to 96% of all delays at Munich Airport are due to adverse weather with thunderstorms Turbulence and fog as the primary reasons Icing Thunderstrom information for aviation is still rudimentary these days! Lightning
3 Chart 3 > ECATS 2013 > Dennis Stich > November 2013 Thunderstorms as weatherobjects with multiple object attributes Cb top: conv. turbulence, lightning activity, etc. detected by satellite (Cb-TRAM) Cb bottom: hail, icing, lightning, heavy rain, turbulence, etc. detected by radar (Rad-TRAM) Vortrag > Autor > Dokumentname > Datum Picture by Martin Köhler, DLR
4 Chart 4 > ECATS 2013 > Dennis Stich > November 2013 Cb-TRAM - Cumulonimbus TRacking And Monitoring Used MSG (rapidscan) data: WV 6.2 IR 10.8 IR 12.0 HRV Detection stages: 1: Convection Initiation (CI) development in HRV IR 10.8 cooling 2: Rapid development WV 6.2 rapid cooling (> 1K/15min) 3: Mature storms T T 10.8 HRV texture Lightning (LINET) Extrapolation up to 60 min (here 30 minute nowcast plotted) Description: Zinner et al., 2008,09 & 13
5 Chart 5 > ECATS 2013 > Dennis Stich > November 2013 CI postprocessing with additional data LINET data & ingredients describing moisture, instability, and lift (equivalent potential temperature θ e, KO-Index, vertical motion ω in 500 hpa ) Generation of a CI forcing value for each CI detection with fuzzy logic CI forcing values can be translated into a statistical probability of further development Lowest probabilities can be filtered The probability of further development is an additional information which can be treated as a kind of confidence level assigned to the CI detection
6 Chart 6 > ECATS 2013 > Dennis Stich > November 2013 Cb-TRAM: area of application
7 first successful data link tests cooperation DLR - DLH Foto: Capt. Andreas Borengässer (Lufthansa Cityline) Foto: Capt. Andreas Ritter (Deutsche Lufthansa) Lufthansa GADCom project (Ground Air Data Link Communication): Real time link of Rad-TRAM and Cb-TRAM data in 5 EFBs (Electronic Flight Bags) of Lufthansa Cityline aircraft via mobile network on the ground and later in 5 EFBs of Lufthansa aircraft via FlyNet during cruise-flight
8 The Test Flight: Rio de Janeiro to Frankfurt, February 2013 According to the charts: Business as usual at the ITCZ courtesy of A. Ritter, DLH
9 The Test Flight: Rio de Janeiro to Frankfurt, February 2013 But once we got there, the weather radar showed large red cells, embedded in amber Initially without the help of Cb-TRAM, the crew decided to deviate 90 degrees to the right courtesy of A. Ritter, DLH
10 Then, we uplinked the latest Cb-TRAMs to the erm... planned the safest route with the erm and flew it tactically by looking at the weather radar after A. Ritter, DLH
11 The result courtesy of A. Ritter, DLH
12 If we would have uplinked the Cb-TRAM a few minutes earlier. we would have seen the gap on the PUGSU DIKEB route or the gap on the ORARO-TASIL route and could have avoided a 300 NM deviation courtesy of A. Ritter, DLH
13 Chart 13 > ECATS 2013 > Dennis Stich > November 2013 Rad-TRAM - Radar Tracking and Monitoring Based on DWD radar data: RX and EURADCOM Black contours: areas > 37 dbz Dotted contours: 60 min nowcast Tracking and nowcasting based on pyramidal matching like in Cb-TRAM Available every 5th minute
14 > ECATS 2013 > Dennis Chart Stich 14 > November 2013 Rad-TRAM: area of application Rad-TRAM Rad-TRAM EURADCOM RX for Germany for for TMA FABEC MUC (Functional Airspace Block European Central)
15 Chart 15 > ECATS 2013 > Dennis Stich > November 2013 Automated thunderstorm warnings (AutoAlert) Aims: Raise situational awareness DLR Oberpfaffenhofen, 20 June 2012, Gewitterwarnhinweis um 14:40 UTC ********************************************************* Es wurden Gewittertops bis ca. 14 km Höhe und länger anhaltender Hagel beobachtet. Presentation of the same information to describe the current situation to all stakeholders at an airport to support CDM Gewitterzelle Nr. 281 etwa 31 km von MUC entfernt wird laut Prognose in 50 Min. den Flughafen MUC treffen. Weitere Gewitterzellen weniger als 100 km von MUC entfernt. Betroffene Bereiche: NW, SW, SE Mittlere Zugrichtung aller Zellen: nord-oestlich Zur Erläuterung: Gewitterzellen sind schwarz umrandet (Bereich mit Starkniederschlag). Die Verlagerung nach 60 Minuten ist mit einem Pfeil und einer schwarz-weiß gestrichelten Linie markiert. Blitze (LINET) sind mit blauen Kreuzen markiert. Weitere Informationen: Siehe Anhang, MetFROG und (User: nowcasting, Passwd: drizzle) Mit freundlichen Grüßen, das Gewitterteam des DLR Instituts für Physik der Atmosphäre Feedback, Fragen und Anregungen bitte an Tel.: oder
16 Chart 16 > ECATS 2013 > Dennis Stich > November 2013 Cb indicator forecasts up to 6 hrs (Cblike) Fuzzy logic combination of CAPE, 500 hpa vertical velocity, synthetic satellite and radar data from the DWD COSMO-DE model Cb observation 21 June :00 Cblike 6 hrs forecast for 21 June 2012UTC 18:00 UTC White contours: Cblike indicator exceeding a certain threshold Pink contours: Rad-TRAM cells Blue crosses: Lightning data (LINET)
17 Chart 17 > ECATS 2013 > Dennis Stich > November 2013 Short-range limited area NWP (COSMO-MUC) For seemless prediction of airtraffic relevant phenomena Forecast skill Nowcasting COSMO- MUC COSMO- DE Theory (60 min) (30 min - 4h) (3h +) Nowcast NWP Forecast lead time
18 Chart 18 > ECATS 2013 > Dennis Stich > November 2013 Weather Forecast User-oriented System Including Object Nowcasting Cloud tracker weather object specification oriented at user requirements POLDIRAD Lightning Surface Analysis Radar tracker Combination of data sources through fuzzy logic: Initiation Track Nowcast Forecast Decision finding technique allowing for parameter ranges instead of fixed thresholds Takes into account the meteorological experience and concepts as well as local effects Object Comparison SYNSAT COSMO-DE & Ensemble Local forecasting SYNRAD Object Comparison
19 Chart 19 > ECATS 2013 > Dennis Stich > November 2013 Thank you for your attention! contact: Decrease of information detail over forecast time 75% 50% 25%
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