SLEPS

First Results from SLEPS

A. Walser, M. Arpagaus, C. Appenzeller, J. Quiby

MeteoSwiss

Andre

.Wals

er@

Mete

oSw

iss.

chC

OSM

O G

enera

l M

eeti

ng,

20

03

, La

ngen

2

SLEPSSLEPS

SLEPS: Short-range limited-area ensemble prediction system.

Within project ‘Extreme Events’ of the Swiss national research project NCCR.

Strategy bases on an adapted COSMO-LEPS for the short-range.

Should be considered as a first step towards a short-range EPS.

The smaller scales resolved in SLEPS implies the consideration of alternative growth mechanisms beyond the baroclinic growth accounted for by the SV analysis.

Strategies for the definition of optimal small-scale perturbations have to be found.

Andre

.Wals

er@

Mete

oSw

iss.

chC

OSM

O G

enera

l M

eeti

ng,

20

03

, La

ngen

3

SLEPSSLEPS: Short-range adaptation of COSMO-LEPS

Start of COSMO-LEPS integrations

? members

COSMO-LEPS clustering times

short-range clustering times

number of RMs?

horizontal resolution?

day:

12

n-112

n+212

n+312

n+412

n+512

n+112

n0000 00 00 0000

moist? EPS

moist? EPS

moist? EPS

Andre

.Wals

er@

Mete

oSw

iss.

chC

OSM

O G

enera

l M

eeti

ng,

20

03

, La

ngen

4

SLEPSSLEPS: current setup

50+1 members

5 representative members (RMs)

5 Lokal Modell (limited-area) integrations nested into 5 RMsSLEPS: Short-range limited-area Ensemble Prediction System5 Lokal Modell (limited-area) integrations nested into 5 RMs

SLEPS: Short-range limited-area Ensemble Prediction System

5 clusters

Hierarchical Cluster Analysisarea: Europe

fields: 4 variables (U,V,Q,Z) at 3 levels (500, 700, 850) for 3 time steps (24h, 48h, 72 h),

number of clusters: fixed to 5

Hierarchical Cluster Analysisarea: Europe

fields: 4 variables (U,V,Q,Z) at 3 levels (500, 700, 850) for 3 time steps (24h, 48h, 72 h),

number of clusters: fixed to 5

Representative Member Selection one per cluster:

member nearest (3D) to the mean of its own cluster AND most distant to the other clusters’

means

Representative Member Selection one per cluster:

member nearest (3D) to the mean of its own cluster AND most distant to the other clusters’

means

Global ECMWF EPS ensembles with moist singular vectorsGlobal ECMWF EPS ensembles with moist singular vectors

Andre

.Wals

er@

Mete

oSw

iss.

chC

OSM

O G

enera

l M

eeti

ng,

20

03

, La

ngen

5

SLEPSSLEPS: model domain with topography

10 km mesh-size horizontally, 32 vertical levels.

Andre

.Wals

er@

Mete

oSw

iss.

chC

OSM

O G

enera

l M

eeti

ng,

20

03

, La

ngen

6

SLEPSMoist vs. operational singular vectorsCoutinho et al. (2003)

‚opr‘ SVs (T42L31, OTI 48 h): linearized physics package with

surface drag

simple vertical diffusion

‚moist‘ SVs (T63L31, OTI 24 h): linearized physics package includes additionally:

gravity wave drag

long-wave radiation

deep cumulus convection

large-scale condensation

moist SVs: use of moist processes during SV evolution, but same norm (‚total energy norm‘) no humidity perturbations.

Andre

.Wals

er@

Mete

oSw

iss.

chC

OSM

O G

enera

l M

eeti

ng,

20

03

, La

ngen

7

SLEPS2 case studies:

Storm Lothar (“Christmas Storm”): 26 December 1999

moist SV ECMWF EPS SLEPS 19991224 00 UTC, + 72 h

opr SV ECMWF EPS SLEPS 19991224 00 UTC, + 72 h

Storm Martin: 27/28 December 1999

moist SV EPS ECMWF SLEPS 19991226 00 UTC, + 72 h

opr SV EPS ECMWF SLEPS 19991226 00 UTC, + 72 h

Andre

.Wals

er@

Mete

oSw

iss.

chC

OSM

O G

enera

l M

eeti

ng,

20

03

, La

ngen

8

SLEPSMean RMS error Z@850 hPa of ECMWF EPS to

opr analysis in SLEPS domainR

MS

EN

S [m

]

Forecast time [h]

red: opr SVs EPS

blue: moist SVs EPS

solid: Storm Lothar

dotted: Storm Martin

N

n

I

iiiENS oy

INRMS

1 1

211 y: predicted value

o: values of analysis

N: number of members

I: number of grid points

Andre

.Wals

er@

Mete

oSw

iss.

chC

OSM

O G

enera

l M

eeti

ng,

20

03

, La

ngen

9

SLEPSStorm Lothar: probability forecast of SLEPS for 10 m wind gusts

moist SVs opr SVs

ECMWF opr analysis

Lothar

Andre

.Wals

er@

Mete

oSw

iss.

chC

OSM

O G

enera

l M

eeti

ng,

20

03

, La

ngen1

0

SLEPSLothar: 6 hours later…

moist SVs

opr SVs

opr SVs

Andre

.Wals

er@

Mete

oSw

iss.

chC

OSM

O G

enera

l M

eeti

ng,

20

03

, La

ngen1

1

SLEPSLothar: again 6 hours later…

moist SVs opr SVs

Andre

.Wals

er@

Mete

oSw

iss.

chC

OSM

O G

enera

l M

eeti

ng,

20

03

, La

ngen1

2

SLEPSLothar: again 6 hours later…

moist SVs opr SVs

Andre

.Wals

er@

Mete

oSw

iss.

chC

OSM

O G

enera

l M

eeti

ng,

20

03

, La

ngen1

3

SLEPSLothar: probability forecast for 10 m wind gusts over the 24 hours storm period

moist SVs opr SVs

Both ensemble quite similar. Moist SVs SLEPS predicts a higher risk for strong wind

gusts over northern France.

Andre

.Wals

er@

Mete

oSw

iss.

chC

OSM

O G

enera

l M

eeti

ng,

20

03

, La

ngen1

4

SLEPSLothar: ECMWF EPS using only LEPS representative members over the 24 hours storm period

moist SVs opr SVs

Rather reduced probabilities compared to SLEPS in particular over the Atlantic. SLEPS downscaling seems to be beneficial in this case.

Andre

.Wals

er@

Mete

oSw

iss.

chC

OSM

O G

enera

l M

eeti

ng,

20

03

, La

ngen1

5

SLEPSLothar: ECMWF EPS using all 51 members over the 24 hours storm period

moist SVs opr SVs

Very similar Effect of moist SVs not obvious.

Andre

.Wals

er@

Mete

oSw

iss.

chC

OSM

O G

enera

l M

eeti

ng,

20

03

, La

ngen1

6

SLEPSStorm Martin: probability forecast of SLEPS for 10 m wind gusts

opr SVsmoist SVs

Martin

Andre

.Wals

er@

Mete

oSw

iss.

chC

OSM

O G

enera

l M

eeti

ng,

20

03

, La

ngen1

7

SLEPSStorm Martin: 6 hours later…

moist SVs opr SVs

Andre

.Wals

er@

Mete

oSw

iss.

chC

OSM

O G

enera

l M

eeti

ng,

20

03

, La

ngen1

8

SLEPSStorm Martin: 6 hours later…

moist SVs opr SVs

Andre

.Wals

er@

Mete

oSw

iss.

chC

OSM

O G

enera

l M

eeti

ng,

20

03

, La

ngen1

9

SLEPSStorm Martin: 6 hours later…

moist SVs opr SVs

Andre

.Wals

er@

Mete

oSw

iss.

chC

OSM

O G

enera

l M

eeti

ng,

20

03

, La

ngen2

0

SLEPSStorm Martin: probability forecast for 10 m wind gusts over the 24 hours storm period

moist SVs opr SVs

moist SVs SLEPS predicts a risk in south-western France and northern Mediterranean Sea.

opr SVs SLEPS misses the storm.

Andre

.Wals

er@

Mete

oSw

iss.

chC

OSM

O G

enera

l M

eeti

ng,

20

03

, La

ngen2

1

SLEPSMartin: ECMWF EPS using only LEPS RMsover the 24 hours storm period

moist SVs opr SVs

Provided risk from moist SVs ECMWF EPS lower over southwestern France and northern Mediterranean sea.

Opr SVs ECMWF EPS also misses the storm.

Andre

.Wals

er@

Mete

oSw

iss.

chC

OSM

O G

enera

l M

eeti

ng,

20

03

, La

ngen2

2

SLEPSMartin: ECMWF EPS using all 51 members over the 24 hours storm period

moist SVs opr SVs

Using all EPS members, differences between moist and opr SVs EPS smaller moist SVs SLEPS additionally favoured by the clustering procedure.

Andre

.Wals

er@

Mete

oSw

iss.

chC

OSM

O G

enera

l M

eeti

ng,

20

03

, La

ngen2

3

SLEPSConclusions from first SLEPS simulations

Wind gust prediction for storm Lothar:

Effect of moist SVs in SLEPS and ECMWF EPS small.

Downscaling effect with SLEPS beneficial but not crucial.

Wind gust prediction for storm Martin:

Effect of moist SVs clearly positive both in SLEPS and ECMWF EPS.

opr SVs SLEPS does not provide a storm warning.

Downscaling effect with moist SVs SLEPS beneficial.