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

Matthias B. Schmidt 2 Motivation Extreme Flooding Examples from June 2011 [

Matthias B. Schmidt 3 Motivation [ Extreme Flooding Examples from June 2011

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

X-Band Radars Matthias B. Schmidt High spatial resolution (60m) High temporal resolution (30s) 5 [

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

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

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

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

“spatially-distributed“ Matthias B. Schmidt 10

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

Statistical Model Matthias B. Schmidt Example hydrological model 12

Masterthesis – Shetran Matthias B. Schmidt 13

Masterthesis – Shetran Matthias B. Schmidt 14

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

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

Masterthesis – Model Output Matthias B. Schmidt 17

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

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

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

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

Masterthesis – Radar Ensemble Matthias B. Schmidt 22

Masterthesis – Radar Ensemble Matthias B. Schmidt 23

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

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

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

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

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

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

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

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

1. unter-in-hamburg/ unter-in-hamburg/ 2. in-hamburg-hagel-in-bayern-fotostrecke htmlhttp:// in-hamburg-hagel-in-bayern-fotostrecke html Literature & Sources Matthias B. Schmidt 32

5.Germann, U., Berenguer, M., Sempere-Torres, D., Zappa, M. (2008) 6.SHETRAN water flow equations ( 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, ( Literature & Sources Matthias B. Schmidt 33

Matthias B. Schmidt 34

Appendix Matthias B. Schmidt 35

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

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

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

Student Research – clutter detection Matthias B. Schmidt 39

Matthias B. Schmidt 40