A. Walser 1) M. Arpagaus 1) M. Leutbecher 2) 1) MeteoSwiss, Zurich 2) ECMWF, Reading, GB
description
Transcript of A. Walser 1) M. Arpagaus 1) M. Leutbecher 2) 1) MeteoSwiss, Zurich 2) ECMWF, Reading, GB
The impact of moist singular vectors and ensemble size on predicted storm tracks for the winter storms Lothar and Martin
A. Walser1)
M. Arpagaus1)
M. Leutbecher2)
1)MeteoSwiss, Zurich
2)ECMWF, Reading, GB
Storms Lothar & Martin
Occurred on 24 Dec (Lothar) and 26/27 Dec 1999 (Martin) in Central Europe
At least 80 casualties
Economic losses of ~18 billions USD
Not predicted by the national weather services
→ Motivation for the study: Improvement of early warnings for such extreme weather events
Ensemble forecasts
Initial perturbations should match the uncertainties in the initial conditions.
Ideally, an ensemble span the entire range of possible solutions.
Ensemble forecasts
Initial perturbations should match the uncertainties in the initial conditions.
Ideally, an ensemble span the entire range of possible solutions.
Initial perturbations using “moist” singular vectors (SVs) might lead to a more reliable spread for short lead-times.
Moist vs. operational singular vectorsCoutinho et al. (2004)
‚opr‘ SVs (T42L31, OT 48 h): linearized physics package with surface drag simple vertical diffusion
‚moist‘ SVs (T63L31, OT 24 h): linearized physics package includes additionally: gravity wave drag long-wave radiation deep cumulus convection large-scale condensation
Ensemble strategy
Variant of the operational COSMO-LEPS:
dynamical
downscaling
Global ensemble Limited-area ensemble
Lokal Modell with x~10 km and 32 levels
72-h forecasts
51 membersECMWF, ∆x~80 km, opr/moist SVs
LM, x~10 km
Ensemble simulations
Storm Lothar: 26 December 1999 moist SVs ensembles, 19991224 00 UTC, + 72 h opr SVs ensembles, 19991224 00 UTC, + 72 h
Storm Martin: 27/28 December 1999 moist SVs ensembles, 19991226 00 UTC, + 72 h opr SVs ensembles,19991226 00 UTC, + 72 h
LM 3.9 ensembles: ∆x ~10 km (as COSMO-LEPS)
“Pronounced” storm track
In the forecast range considered:
1) Minimum sea level pressure of 980 hPa.
2) At least 1000 km west-east elongation.
3) For each ensemble member, the track with the earliest and southernmost starting point of the tracks which fulfill 1) and 2) is considered.
Lothar: Predicted storm tracks t+(42-66) < 980 hPa (1)
ensemble members: 32 tracks ▬ analysis
< 970 hPa< 960 hPa
Impact of perturbations
Configuration:
• dry SVs/51 RMs
• moist SVs/51 RMs
Lothar: Predicted storm tracks t+(42-66) < 980 hPa (2)
< 970 hPa< 960 hPa
ensemble members: 36 tracks ▬ analysis
Impact of perturbations
Configuration:
• dry SVs/51 RMs
• moist SVs/51 RMs
Martin: Predicted storm tracks t+(42-66) < 980 hPa (1)
ensemble members: 2 tracks ▬ analysis
< 970 hPa< 960 hPa
Impact of perturbations
Configuration:
• dry SVs/51 RMs
• moist SVs/51 RMs
Martin: Predicted storm tracks t+(42-66) < 980 hPa (2)
ensemble members: 12 tracks ▬ analysis
< 970 hPa< 960 hPa
Impact of perturbations
Configuration:
• dry SVs/51 RMs
• moist SVs/51 RMs
Impact of ensemble size
Lothar: Predicted storm tracks t+(42-66) < 980 hPa
< 970 hPa< 960 hPa
ensemble members: 36 tracks (71%) ▬ analysis
Impact of ensemble size
Configuration:
• moist SVs/51 RMs
• moist SVs/20 RMs
• moist SVs/10 RMs
• moist SVs/5 RMs
Lothar: Predicted storm tracks t+(42-66) < 980 hPa
< 970 hPa< 960 hPa
ensemble members: 14 tracks (70%) ▬ analysis
Impact of ensemble size
Configuration:
• moist SVs/51 RMs
• moist SVs/20 RMs
• moist SVs/10 RMs
• moist SVs/5 RMs
Lothar: Predicted storm tracks t+(42-66) < 980 hPa
< 970 hPa< 960 hPa
ensemble members: 7 tracks (70%) ▬ analysis
Impact of ensemble size
Configuration:
• moist SVs/51 RMs
• moist SVs/20 RMs
• moist SVs/10 RMs
• moist SVs/5 RMs
Lothar: Predicted storm tracks t+(42-66) < 980 hPa
< 970 hPa< 960 hPa
ensemble members: 4 tracks (80%) ▬ analysis
Impact of ensemble size
Configuration:
• moist SVs/51 RMs
• moist SVs/20 RMs
• moist SVs/10 RMs
• moist SVs/5 RMs
Forecast storm Lothar: max. wind gusts t+(42-66) (1)
Impact of ensemble size
Configuration:
• moist SVs/51 RMs
• moist SVs/20 RMs
• moist SVs/10 RMs
• moist SVs/5 RMs
Forecast storm Lothar: max. wind gusts t+(42-66) (2)
Impact of ensemble size
Configuration:
• moist SVs/51 RMs
• moist SVs/20 RMs
• moist SVs/10 RMs
• moist SVs/5 RMs
Forecast storm Lothar: max. wind gusts t+(42-66) (3)
Impact of ensemble size
Configuration:
• moist SVs/51 RMs
• moist SVs/20 RMs
• moist SVs/10 RMs
• moist SVs/5 RMs
Forecast storm Lothar: max. wind gusts t+(42-66) (4)
Impact of ensemble size
Configuration:
• moist SVs/51 RMs
• moist SVs/20 RMs
• moist SVs/10 RMs
• moist SVs/5 RMs
Forecast storm Martin: max. wind gusts t+(30-54) (1)
Impact of ensemble size
Configuration:
• moist SVs/51 RMs
• moist SVs/20 RMs
• moist SVs/10 RMs
• moist SVs/5 RMs
Forecast storm Martin: max. wind gusts t+(30-54) (2)
Impact of ensemble size
Configuration:
• moist SVs/51 RMs
• moist SVs/20 RMs
• moist SVs/10 RMs
• moist SVs/5 RMs
Forecast storm Martin: max. wind gusts t+(30-54) (3)
moist SVs, x~10 km, 10 members
Impact of ensemble size
Configuration:
• moist SVs/51 RMs
• moist SVs/20 RMs
• moist SVs/10 RMs
• moist SVs/5 RMs
Forecast storm Martin: max. wind gusts t+(30-54) (4)
Impact of ensemble size
Configuration:
• moist SVs/51 RMs
• moist SVs/20 RMs
• moist SVs/10 RMs
• moist SVs/5 RMs
Summary
Use of moist SVs leads to a larger number of members with a storm track similar to the observed one. Potential for earlier warnings However, consequence for false alarm rate unknown
Ensemble reduction method of COSMO-LEPS works well. 10 RMs seems to be a good compromise between required computing resources and forecast accuracy.
Extra Slides
Wind gusts storm Martin (27.-28.12.1999)
LM analysis with nudging: Proxy for observations
“Brasseur (2001) wind gusts”
Wind gusts storm Lothar (26.12.1999)
LM analysis with nudging: Proxy for observations
“Brasseur (2001) wind gusts”
Parameterization for 10m wind gusts
LM („operational“):
3 x double turbulent kinetic energy in Prandtl-Layer:
U* : Friction velocity
Brasseur wind gust formulation(Mon. Wea. Rev. 129, 5-25, 2001)
)()(max 22pp zVzUWg