A. Walser 1) M. Arpagaus 1) M. Leutbecher 2) C. Appenzeller 1) 1) MeteoSwiss, Zurich

The Impact of Moist Singular Vectors and Horizontal Resolution on Short-Range Limited-Area Ensemble Forecasts for Extreme Weather Events A. Walser1) M. Arpagaus1) M. Leutbecher2) C. Appenzeller1) 1)MeteoSwiss, Zurich 2)ECMWF, Reading, GB

Perturbations of initial conditions • 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 account for a more reliable spread in the short-range.

Moist vs. operational singular vectorsCoutinho et al. (2004) • ‚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 in SV calculation, but same norm (‚total energy norm‘)  no humidity perturbations.

dynamical downscaling SLEPS • SLEPS: Short-range Limited-area Ensemble Prediction System • Variant of the operational COSMO-LEPS • Motivation: Early warnings for extreme weather events Limited-area ensemble Global ensemble • 51 ensemble members • LM with 10 km grid-spacing and 32 levels • 72-h forecasts • IFS members use „moist“ singular vectors LM, x~10 km IFS (ECMWF), ∆x~80 km, moist SVs

SLEPS simulations • LM 3.92 ensembles using Brasseur (2001) wind gust formulation: • ∆x ~80 km (as ECMWF EPS) • ∆x ~10 km but ECMWF EPS topography • ∆x ~10 km (as COSMO-LEPS) • Storm Lothar: 26 December 1999 • moist SVs ECMWF EPS  SLEPS 19991224 00 UTC, + 72 h • opr SVs ECMWF EPS  SLEPS 19991224 00 UTC, + 72 h • Storm Martin: 27/28 December 1999 • moist SVs ECMWF EPS  SLEPS 19991226 00 UTC, + 72 h • opr SVs ECMWF EPS  SLEPS 19991226 00 UTC, + 72 h

Wind gusts storm Lothar (26.12.1999) LM analysis with nudging: Proxy for observations

2-day forecast max. wind gusts storm Lothar (1) SLEPS with opr SVs, x~80 km

2-day forecast max. wind gusts storm Lothar (2) SLEPS with opr SVs, ECMWF EPS topography

2-day forecast max. wind gusts storm Lothar (3) SLEPS with moist SVs, ECMWF EPS topography

2-day forecast max. wind gusts storm Lothar (4) SLEPS with moist SV

2-day forecast max. wind gusts storm Lothar (5) SLEPS with moist SV, only 10 members (as COSMO-LEPS)

Wind gusts storm Martin (27.-28.12.1999) LM analysis with nudging: Proxy for observations

2-day forecast max. wind gusts storm Martin (1) SLEPS mit opr SVs, x~80 km

2-day forecast max. wind gusts storm Martin (2) SLEPS with opr SVs, ECMWF EPS topography

2-day forecast max. wind gusts storm Martin (3) SLEPS with moist SVs, ECMWF EPS topography

2-day forecast max. wind gusts storm Martin (4) SLEPS with moist SVs

2-day forecast max. wind gusts storm Martin (5) SLEPS with moist SVs, only 10 members (as COSMO-LEPS)

Conclusions • High-Resolution ensemble predictions have potential to detect storms earlier and more reliably in the future. • Contribution from moist singular vectors is crucial. Questions?

Extra Slides

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)

SLEPS clustering Global ECMWF EPS ensembles with moist singular vectors 50+1 members Hierarchical Cluster Analysis area: 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 10 10 clusters Representative Member Selection one per cluster: member nearest (3D) to the mean of its own cluster AND most distant to the other clusters’ means 10 representative members (RMs) 10 Lokal Modell (limited-area) integrations nested into 5 RMs SLEPS: Short-range limited-area Ensemble Prediction System

A. Walser 1) M. Arpagaus 1) M. Leutbecher 2) C. Appenzeller 1) 1) MeteoSwiss, Zurich