1. High-Res. Flash Flooding Estimation Tropos Leipzig 26. January 2016 - Or why do we measure precipitation?

2. Matthias B. Schmidt 2 Motivation Extreme Flooding Examples from June 2011 [http://www.altona.info/2011/06/07/gewitter-regen-hagel-land-unter-in-hamburg/]

3. Matthias B. Schmidt 3 Motivation [http://www.spiegel.de/fotostrecke/unwetter-ueberschwemmung-in-hamburg-hagel-in-bayern-fotostrecke-68908-2.html] Extreme Flooding Examples from June 2011

4. What can we do? Matthias B. Schmidt Change weather? Fortunately we can’t Estimate flooding possibility? We might! 4

5. X-Band Radars Matthias B. Schmidt High spatial resolution (60m) High temporal resolution (30s) 5 [http://pattern.zmaw.de/Hamburg.2106.0.html]

6. What I‘d like to talk about Matthias B. Schmidt Shetran RENS Radar Calibration Only a good tuned radar produces good data 6

7. Masterthesis - Goals Matthias B. Schmidt Hydrology: Higher resolution (X-Band) better? Flash flooding forecasting possible? Calculation of flooding probability 7

8. Masterthesis - Tools Matthias B. Schmidt Shetran “a physically-based spatially-distributed hydrological model“ (J. Ewen et al. (2000)) Radar Ensemble Covariance (U. Germann et al. (2008)) Fractals 8

9. Masterthesis - Shetran Matthias B. Schmidt Water Flow component Canopy interception Evaporation and transpiration Surface run-off Transfer between subsurface and river water Storage and flow in VSS 9

10. “spatially-distributed“ Matthias B. Schmidt 10

11. Masterthesis - Shetran Matthias B. Schmidt “physically based” Conservation of mass Saint-Venant Eq. (a.k.a. Shallow Water Eq.) Penman-Monteith Eq. Boussinesq and Richards Eq. Numerically solved Implicit, finite differences 11

12. Statistical Model Matthias B. Schmidt Example hydrological model 12

13. Masterthesis – Shetran Matthias B. Schmidt 13

14. Masterthesis – Shetran Matthias B. Schmidt 14

15. Matthias B. Schmidt Masterthesis – Model Output Input Vegetation Soil / VSS Run-Off / Overflow / Saturation 15

16. Masterthesis – Model Experiments Matthias B. Schmidt What is more severe? In terms of hydrology Precipitation event 1 High intensity Short duration Precipitation event 2 Low intensity Long duration 16 Time (5*30min) 1 2 Same Precipitation Amount

17. Masterthesis – Model Output Matthias B. Schmidt 17

18. Masterthesis – Radar Ensemble Matthias B. Schmidt 18 Statistically based Radar Ensemble Generator Covariance approach

19. Masterthesis – Radar Ensemble Matthias B. Schmidt 19 3 mm/h 2.5 mm/h 2 mm/h

20. Masterthesis – Radar Ensemble Matthias B. Schmidt 20 3 mm/h 2.5 mm/h 2 mm/h 1 mm/h 4 mm/h 2.2 mm/h

21. Masterthesis – Radar Ensemble Matthias B. Schmidt 21 3 mm/h 2.5 mm/h 2 mm/h 1 mm/h 4 mm/h 2.2 mm/h

22. Masterthesis – Radar Ensemble Matthias B. Schmidt 22

23. Masterthesis – Radar Ensemble Matthias B. Schmidt 23

24. Early-Warning System Matthias B. Schmidt Concept demonstration Implementation beyond scope of masterthesis 24

25. Early-Warning System Matthias B. Schmidt 25 Houston “Hamburg, do we have a problem?” [http://texasstorm chasers.com/tag/ squall-line/]

26. Early-Warning System Matthias B. Schmidt 26 Precipitation Ensemble Ensemble Generator

27. Early-Warning System Matthias B. Schmidt 27 Shetran Discharge Ensemble

28. Early-Warning System Matthias B. Schmidt 28 Shetran Discharge Ensemble

29. Early-Warning System Matthias B. Schmidt 29 Houston “Hamburg, do we have a problem?” [http://texasstorm chasers.com/tag/ squall-line/] “15 out of 25 members issue a warning!”

30. Summing Up Matthias B. Schmidt Higher Resolution has an impact on results 30 Time (5*30min)

31. Summing Up Matthias B. Schmidt Higher Resolution has an impact on results Flooding estimation might become possible 31

32. 1.http://www.altona.info/2011/06/07/gewitter-regen-hagel-land- unter-in-hamburg/http://www.altona.info/2011/06/07/gewitter-regen-hagel-land- unter-in-hamburg/ 2.http://www.spiegel.de/fotostrecke/unwetter-ueberschwemmung- in-hamburg-hagel-in-bayern-fotostrecke-68908-2.htmlhttp://www.spiegel.de/fotostrecke/unwetter-ueberschwemmung- in-hamburg-hagel-in-bayern-fotostrecke-68908-2.html 3.http://pattern.zmaw.de/Hamburg.2106.0.htmlhttp://pattern.zmaw.de/Hamburg.2106.0.html 4.http://texasstormchasers.com/tag/squall-line/http://texasstormchasers.com/tag/squall-line/ Literature & Sources Matthias B. Schmidt 32

33. 5.Germann, U., Berenguer, M., Sempere-Torres, D., Zappa, M. (2008) 6.SHETRAN water flow equations (http://research.ncl.ac.uk/shetran/water%20flow%20equations.pdf)http://research.ncl.ac.uk/shetran/water%20flow%20equations.pdf 7.Ewen, J., Parkin, G. and O'Connell, P.E. (2000). SHETRAN: Distributed River Basin Flow and Transport Modelling System. ASCE J. Hydrologic Eng., 5, 250-258. (http://research.ncl.ac.uk/shetran/SHETRAN_ASCE_paper.pdf)http://research.ncl.ac.uk/shetran/SHETRAN_ASCE_paper.pdf Literature & Sources Matthias B. Schmidt 33

34. Matthias B. Schmidt 34

35. Appendix Matthias B. Schmidt 35

36. Student Research Matthias B. Schmidt Real-time Radar calibration Based on single pulse data Dynamic Clutter detection Without Doppler and Polarimetry 36

37. Student Research – Radar calibration Matthias B. Schmidt Single-Pulse data Time-critical code necessary Fortran core real-time calibration possible 37

38. Student Research – clutter detection Matthias B. Schmidt Difficult: No Doppler, no dual pol Statistical approach Not only clutter map Not much recent research (everybody has Doppler) 38

39. Student Research – clutter detection Matthias B. Schmidt 39

40. Matthias B. Schmidt 40