1. Inclusion of potential vorticity uncertainties into a hydrometeorological forecasting chain: Application to a flash-flood event over Catalonia, Spain A. Amengual, R. Romero, M. Vich and S. Alonso Grup de Meteorologia, Departament de Física, Universitat de les Illes Balears, Palma, Mallorca, Spain e-mail: arnau.amengual@uib.esarnau.amengual@uib.es Universitat de les Illes Balears

2. Inclusion of potential vorticity uncertainties into a hydrometeorological forecasting chain: Application to a flash-flood event over Catalonia, Spain 1.General aspects of flood events in the Western Mediterranean area 2.Hydrometeorological forecasting chain 3.The “Montserrat” flash-flood event 4.Hydrological and meteorological tools 5.Probabilistic versus deterministic QPFs: Inclusion of Potential Vorticity uncertainties 6.Probabilistic versus deterministic QPFs and driven runoff simulations 7.Conclusions and further remarks

3. Floods are hydrometeorological events: depend on both hydrological and meteorological factors 1. Meteorological conditions: 1.1 Incursion of cold air masses: increase in the probability of heavy precipitations 1.2 Closed and warm sea: - surrounded by coastal high mountains - extreme rainfalls favoured by high SST Convective instabilities along the cold fronts producing interactions between frontal and orographic enhancement 1. General aspects of flood events in the Western Mediterranean area

4. 2. Hydrological conditions: 2.1 antecedent moisture of the soil: infiltration properties 2.2 terrain and surface runoff characteristics: mountain systems and high urbanization rates near the coast Flash-floods are often associated with quasi-stationary convective events: high precipitation rates + periods of several hours These are experienced in urban areas frequently in time and randomly in space Short temporal scale of these episodes (~ hours): occurrence too rapid to attempt damage mitigation Flash-floods are dangerous in terms of human lives and properties 1. General aspects of flood events in the Western Mediterranean area

5. Hydrometeorological modeling chain: spatial and temporal scales of the numerical weather predictions GCMs / NWP (~10 3 -10 4 km 2, several days) LAMs / NWP (~10 km 2, 48 h) HMS Mesoscale models provide realistic rainfall distributions for heavy precipitation episodes Supply a useful support for flood simulation and forecasting: further extension lead times Coupled atmospheric-hydrologic system: advanced validation tool for the simulated rainfall amounts 2. Hydrometeorological forecasting chain

6. Sources of uncertainty and limitations Errors in initial and boundary conditions Approximations in physical parameterizations Models’ structures impacts on the hydrometeorological simulations 2. Hydrometeorological forecasting chain

7. 3. The “Montserrat” flash-flood event Synoptic situation 1. Entrance of an Atlantic low- level cold front and an upper- level trough 2. Generation of a mesoscale cyclone in the Mediterranean Sea 3. Advection of warm and moist air toward Catalonia from the Mediterranean Easterly flow + Atlantic front + orographic enhancement quasi-stationary convective system 9 June 2000 00 UTC10 June 2000 00 UTC

8. Torrential precipitation took place on 10 June 2000 from 00 to 06 UTC: hourly quantities above 100 mm and 6 h maximum up to 224 mm The Llobregat catchment is a medium-size basin with an area of 5040 km 2 and a length close to 170 km. Accumulated rainfall reached over 200 mm inside this basin 3. The “Montserrat” flash-flood event

9. Huge increase in the river flow, producing 5 fatalities, 500 evacuated people and material damage estimated at over 65 M€ Return period: Q= 1550 m 3 s -1 25 yrs

10. 4. Hydrological and meteorological tools MM5 model set-up Meteorological simulations have used the same model configuration as in the real-time operational version at UIB (http://mm5forecasts.uib.es)http://mm5forecasts.uib.es Initial and boundary conditions: ECMWF forecasts (update 6h, 0.3º) Two domains: 22.5 and 7.5 km, interacting with each other and 30 vertical σ-levels Kain-Fritsch scheme is used to parameterise convection for both domains The experiments consider a 54h period simulation (09/06/00 00 UTC - 11/06/00 06 UTC) HEC-HMS model set-up Loss rate: Soil Conservation Service Curve Number (SCS-CN) model Transform: SCS Unit Hydrograph model Flow routing: Muskingum method The experiments consider a 96h period simulation (09/06/2000 00 UTC-13/06/2000 00 UTC)

11. 5. Probabilistic versus deterministic QPFs Spatial distribution of accumulated precipitation for the control simulation Difficulties to correctly forecast precise location and timing of convectively-driven rainfall system affecting small and medium size basins -99.7 1.1 EV (%) -99.7-0.05control -7.80.84rain-gauges EP (%)NSEMontserrat event

12. 5. Probabilistic versus deterministic QPFs: Inclusion of Potential Vorticity uncertainties Initial conditions of the upper- level precursor trough Slight perturbations on the initial state: study of the spatial and temporal uncertainties of QPFs into a medium-sized catchment To introduce realistic perturbations in the ensemble prediction system (EPS), a PV error climatology (PVEC) has been carried out. This allows to perturb the PV fields using the appropriated error range

13. The PVEC is calculated using a large collection of MEDEX cases (19 cases, 56 days of simulation; further information available at: http://medex.inm.uib.es/), and provides displacement and intensity errors of the PV fields in the study region The displacement error (DE) corresponds to the displacement of the ECMWF 24 h forecast PV field showing local maximum correlation with the ECMWF analyses PV field Percentile levels of displacement errors at 300 hPa 5. Probabilistic versus deterministic QPFs: Inclusion of Potential Vorticity uncertainties

14. Intensity error (IE) corresponds to the difference between the displaced ECMWF 24 h forecast and analyses PV fields PVEC is used to implement the EPS by randomly perturbing the PV field Perturbations are applied along the areas with the most intense PV values and gradients PV Inversion Technique consistently perturb the mass and wind fields, but conserving the energetic balance Percentile levels of intensity errors at 300 hPa 5. Probabilistic versus deterministic QPFs: Inclusion of Potential Vorticity uncertainties

16. Ensemble mean (in mm, shaded) and standard deviation (in mm, continuous line at 5 mm interval) MM5 ensemble comprises 21 elements (control + 20 PV-perturbed) Important spread on rainfall values Highly sensitive to PV perturbations Essential role of atmospheric dynamical forcing 5. Probabilistic versus deterministic QPFs

17. 6. Probabilistic versus deterministic QPFs driven runoff simulations Elements of the driven runoff ensemble are considered equally-like Cumulative distribution functions (CDFs) of driven runoff peak flows

18. 7. Conclusions and further remarks MM5 control simulation is deficient for the Montserrat event: maximum precipitation amounts are obtained quite far away from the Llobregat basin PQPFs reduce biases obtained for the deterministic forecast For civil protection purposes, a hypothetical first warning for a peak flow exceeding Qp (T = 5 yrs) would have produced a probability of exceedence over 0.25. This fact points out the benefits of a probabilistic versus a deterministic prediction system The performance of the hydrometeorological simulations strongly depends on the initial and boundary conditions of the databases and on the case under study References: Amengual et al. (2009): Inclusion of potential vorticity uncertainties into a hydro- meteorological forecasting chain: Application to a medium size basin of Mediterranean Spain. Hydrol. Earth Syst. Sci., 13, 793-811