A. Amengual and V. Homar

Hydrometeorological ensemble forecasts for the 28 September 2012 (IOP8) extreme flash-

flood in Murcia, Spain

A. Amengual and V. Homar

Grup de Meteorologia, Departament de Física, Universitat de les Illes Balears,

Palma, Mallorca, Spaine-mail: arnau.amengual@uib.es

Universitat de les Illes Balears Reunión PREDIMED 2014A5-6 Junio

Hydrometeorological ensemble forecasts for the 28 September 2012 (IOP8) extreme flash-flood in Murcia,

Spain

1. The Guadalentín flash-flood event

2. Hydrological and meteorological tools

3. Probabilistic versus deterministic QPFs

4. Probabilistic versus deterministic QDFs

5. Conclusions and further remarks

1. The Guadalentín flash-flood event: synoptic situation

• Entrance of a deep upper-level closed trough • Generation of a surface mesoscale cyclone • Advection of warm and moist air toward Almería and Murcia from the Mediterranean

Convergence zone between easterly advection and westerly low-level flow+ orographic enhancement

quasi-stationary mesoscale convective system

H500+T500+PV250

T850+SLP

27 September 2012 12 UTC 28 September 2012 12 UTC

• Torrential precipitation took place on 27, 28 and 29 September 2012

• Daily precipitation amounts: 214 mm in Andalucía, 240 mm in Murcia and 230 mm in Valencia

• The Guadalentín catchment is a medium size basin with an area of 3343 km2 and a length close to 121 km

• Accumulated rainfall in 8 h up to 214 mm inside the basin

• Peak discharges: - 616.3 m3s-1 in Lorca- 1081.2 m3s-1 in Paretón de Totana

1. The Guadalentín flash-flood event: observations

m m

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(a)

1. The Guadalentín flash-flood event

• 10 casualties. Material losses estimated at about 120 M€

2. Hydrological and meteorological tools

WRF model set-up

• Initial and boundary conditions: ECMWF forecasts (update 6h, 0.3º; 62 vertical levels)

• One domain: 4 km and 28 vertical eta-levels

• Schemes: Microphysics ─ WSM6; Long-wave radiation ─ RRTM ; Short wave radiation ─ Dudhia; surface model ─ NOAH; time-step ─ 30 s

• The experiments consider a 48 h period simulation (27/09/2012 - 29/09/2012 00 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

• Reservoirs: elevation-storage-outflow relationship + initial elevation of the water level

• The experiments consider a 72 h period simulation (27/09/2012-01/10/2012 00 UTC)

2. Hydrological and meteorological tools

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m eters (asl)

MEDITERRANEAN SEA

SPAIN

FRANCE

ITALY

ALGERIA

Pyrenees

Baetic system

Iberian system

M urcia

CHS

Alps

Atlas

Alm eria

Balearic Is lands

Catalonia

Valencia

Andalusia

Alboran sea

Gulf of Lyon

3. Probabilistic versus deterministic QPFs

Difficulties to correctly forecast precise location and timing of convectively-driven rainfall system affecting a medium size basin

-88.4

-5.7

EV (%)

-89.90.12control

-2.60.91rain-gauges

EP (%)NSEGuadalentín

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(b) m m Paretón (2384.7 km2)

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29/09/201212:00

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30/09/201212:00

01/10/201200:00

date

Q (

m3 s

-1)

Q observed

Q rain-gauges

Q WRF control

(b)Paretón (2384.7 km2)

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27/09/201200:00

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30/09/201212:00

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date

Q (

m3 s

-1)

Q observed

Q rain-gauges

Q WRF control

(b)

Flow observations only available for this study case: perfect-model assumption. Optimal estimation of the initial conditions and dynamical formulation after calibration.

3. Probabilistic versus control QPFs

Mesoscale EPS (WRF)

• Diversity source only from IC/BC (dynamical downscaling)

• Obtained from ECMWF-EPS forecast (Global Singular Vectors)

• 50 equally-likely members

Study of the spatial and temporal uncertainties of QPFs into a medium-sized catchment

(d) Probability-matched ensemble mean

• WRF ensemble comprises 51 elements (control + 50 perturbed)

• Important spread on rainfall values

• Essential role of atmospheric dynamical forcing

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(c) m m

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(d) m m

(c) Ensemble mean ( in mm, shaded) and standard deviation (in mm, continuous line starting at 10 mm interval)

3. Probabilistic versus control QPFs

4. Probabilistic versus deterministic QDFs

• Elements of the HEPS are considered equally-like

• Cumulative distribution functions (CDFs) of driven runoff peak flows

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forecast time-step

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url

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eal-

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cip

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ion

(m

m)

observed

control

ensemble mean

probability-matched

4. Probabilistic versus deterministic QDFs

• Elements of the HEPS are considered equally-like

• Cumulative distribution functions (CDFs) of driven runoff peak flows

0 200 400 600 800 1000 1200 1400 1600Q p(m 3s -1)

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P[Q

q]

observedcontro lensem bleensem ble m eanprobability-m atchedQ p(T=25 yrs)

Q p(T=35 yrs)

Lorca (1827.1 km 2)(a)

0 200 400 600 800 1000 1200 1400 1600 1800Q p(m 3s -1)

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1

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P[Q

q]

observedcontro lensem bleensem ble m eanprobability-m atchedQ p(T=25yrs)

Q p(T=35yrs)

Paretón (2384.7 km 2)(b)

5. Conclusions and further remarks

• WRF control simulation is deficient for the Guadalentín event: maximum precipitation amounts are obtained quite far away from the basin

• EPS reduce biases obtained for the control forecast

• For civil protection purposes, a hypothetical first warning for a peak flow exceeding Qp (T = 25 yrs) would have produced a probability of exceedence of 0.4 and 0.3 at Lorca and Paretón. This fact points out the benefits of a HEPS versus a deterministic prediction system • The performance of the hydrometeorological simulations strongly depends on the

initial conditions of the databases and on the case under study

• References:

Amengual et al. (2014): Hydrometeorological ensemble forecasts for the 28 September 2012 (IOP8) extreme flash-flood in Murcia,Spain. Quart. J. R. Meteorol. Soc [submitted]