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)

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Presentation transcript:

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 vectors Coutinho 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: Global ensemble Limited-area ensemble Lokal Modell with x~10 km and 32 levels 72-h forecasts 51 members dynamical downscaling LM, x~10 km ECMWF, ∆x~80 km, opr/moist SVs

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: Minimum sea level pressure of 980 hPa. At least 1000 km west-east elongation. 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 Impact of perturbations Configuration: dry SVs/51 RMs moist SVs/51 RMs < 970 hPa < 960 hPa

Lothar: Predicted storm tracks t+(42-66) < 980 hPa (2)  ensemble members: 36 tracks ▬ analysis Impact of perturbations Configuration: dry SVs/51 RMs moist SVs/51 RMs < 970 hPa < 960 hPa

Martin: Predicted storm tracks t+(42-66) < 980 hPa (1)  ensemble members: 2 tracks ▬ analysis Impact of perturbations Configuration: dry SVs/51 RMs moist SVs/51 RMs < 970 hPa < 960 hPa

Martin: Predicted storm tracks t+(42-66) < 980 hPa (2)  ensemble members: 12 tracks ▬ analysis Impact of perturbations Configuration: dry SVs/51 RMs moist SVs/51 RMs < 970 hPa < 960 hPa

Impact of ensemble size

Lothar: Predicted storm tracks t+(42-66) < 980 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 < 970 hPa < 960 hPa

Lothar: Predicted storm tracks t+(42-66) < 980 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 < 970 hPa < 960 hPa

Lothar: Predicted storm tracks t+(42-66) < 980 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 < 970 hPa < 960 hPa

Lothar: Predicted storm tracks t+(42-66) < 980 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 < 970 hPa < 960 hPa

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) Brasseur: berücksichtigt die bodennahe Turbulenz. Dabei wird angenommen, dass aus höheren Schichten Luftpakete (welche grössere Geschwindigkeit haben) bis zum Boden transportiert werden. Je grösser die Turbulenz ist, aus um so grösserer Höhe stammen die Luftpakete.