13
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, Spain e-mail: [email protected] Universitat de les Illes Balears Reunión PREDIMED 2014A 5-6 Junio

A. Amengual and V. Homar

  • Upload
    inez

  • View
    35

  • Download
    0

Embed Size (px)

DESCRIPTION

Universitat de les Illes Balears. Reunión PREDIMED 2014A 5-6 Junio. 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, - PowerPoint PPT Presentation

Citation preview

Page 1: 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: [email protected]

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

Page 2: A.  Amengual  and V. Homar

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

Page 3: A.  Amengual  and V. Homar

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

Page 4: A.  Amengual  and V. Homar

• 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

40

50

60

75

100

125

150

175

200

225

(a)

Page 5: A.  Amengual  and V. Homar

1. The Guadalentín flash-flood event

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

Page 6: A.  Amengual  and V. Homar

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)

Page 7: A.  Amengual  and V. Homar

2. Hydrological and meteorological tools

0

250

500

750

1000

1250

1500

1750

2000

2500

3000

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

Page 8: A.  Amengual  and V. Homar

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

0

10

25

50

75

100

125

150

175

200

225

(b) m m Paretón (2384.7 km2)

0

100

200

300

400

500

600

700

800

900

1000

1100

1200

27/09/201200:00

27/09/201212:00

28/09/201200:00

28/09/201212:00

29/09/201200:00

29/09/201212:00

30/09/201200:00

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)

0

100

200

300

400

500

600

700

800

900

1000

1100

1200

27/09/201200:00

27/09/201212:00

28/09/201200:00

28/09/201212:00

29/09/201200:00

29/09/201212:00

30/09/201200:00

30/09/201212:00

01/10/201200:00

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.

Page 9: A.  Amengual  and V. Homar

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

Page 10: A.  Amengual  and V. Homar

(d) Probability-matched ensemble mean

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

• Important spread on rainfall values

• Essential role of atmospheric dynamical forcing

0

10

25

50

75

100

125

150

175

200

225

(c) m m

0

10

25

50

75

100

125

150

175

200

225

(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

Page 11: A.  Amengual  and V. Homar

4. Probabilistic versus deterministic QDFs

• Elements of the HEPS are considered equally-like

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

0

20

40

60

80

100

120

140

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48

forecast time-step

cum

ula

tive

ho

url

y ar

eal-

aver

age

pre

cip

itat

ion

(m

m)

observed

control

ensemble mean

probability-matched

Page 12: A.  Amengual  and V. Homar

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)

0.1

1

0.02

0.04

0.06

0.08

0.2

0.4

0.6

0.8

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)

0.1

1

0.02

0.04

0.06

0.08

0.2

0.4

0.6

0.8

P[Q

q]

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

Q p(T=35yrs)

Paretón (2384.7 km 2)(b)

Page 13: A.  Amengual  and V. Homar

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]