Deutscher Wetterdienst COPS DWD Contributions HansJoachim Koppert Michael

Deutscher Wetterdienst COPS – DWD Contributions Hans-Joachim Koppert, Michael Baldauf, Michael Denhard, Werner Wergen Koppert et al. , DWD 4 COPS FE 1

Overview n COSMO-K 4 Goals 4 Case Studies & Verification 4 Status n Nin. Jo n PEPS 4 Background 4 Implementation 4 Micro PEPS n Data-Assimilation Issues Koppert et al. , DWD 4 COPS FE 1

COSMO-K (formerly known as LMK Lokal-Modell-Kürzestfrist) Goals Development of a model-based NWP system for very short range (‘Kürzestfrist’) forecasts (18 h) of severe weather events on the meso- scale, especially those related to 4 deep moist convection (super- and multi-cell thunderstorms, squall-lines, MCCs, rainbands, . . . ) 4 interactions with fine-scale topography (severe downslope winds, Föhn-storms, flash floodings, fog, . . . ) Koppert et al. , DWD 4 COPS GME (global) x = 40 km 368642 * 40 GP t = 133 sec. T = 7 days COSMO-E (Europe) x = 7 km 665 * 657 * 40 GP t = 40 sec. T= 78 h COSMO-K (regional) x = 2. 8 km 421 * 461 * 50 GP t = 25 sec. T = 18 h 8 forecasts / day FE 1

Convectively enhanced frontal precipitation, 1. 10. 2006, 18 UTC Obs. : up to 20 mm/12 h Koppert et al. , DWD 4 COPS FE 1

LAF-ensemble, 1 h-precip. -sum, target time: 1. 10. 2006, 18 UTC 0 + 18 h 3 + 15 h 6 + 12 h 9+9 h 12 + 6 h 15 + 3 h Koppert et al. , DWD 4 COPS FE 1

Convectively enhanced frontal precipitation 1. 10. 2006, +06 -30 h (from 0 UTC & 12 UTC-run) Koppert et al. , DWD 4 COPS FE 1

Problem: missed convection initiation in LMK 11. 09. 2006 other examples: July 2006 Koppert et al. , DWD 4 COPS FE 1

Synop-Verification RMSE of wind speed |v|10 m Sept. 2006 Oct. 2006 LMK LME 0 UTC-runs Koppert et al. , DWD 4 COPS 12 UTC-runs U. Damrath FE 1

Synop-Verification of pre-operational LMK Gusts and Precipitation, 01. -31. Oct. 2006, 12 UTC-runs Gusts: ETS generally higher (but sometimes also higher FBI) ETS Gusts TSS Precipit ation LMK LME Koppert et al. , DWD 4 COPS Precipitation: July ‘ 05: TSS generally higher Sept. ‘ 06: LMK higher TSS due to LHN, Oct. + Nov. ‘ 06: LMK mostly higher TSS (FBI ~ equal) Dec. ‘ 06: LMK smaller TSS (no LHN? ) FE 1

Status and Summary COSMO-K n COSMO-K in pre-operational use since 14. 08. 2006 n 18 h- (21 h-) forecasts are simulated every 3 h (LAFensemble) n explicit simulation of deep moist convection with its life cycle generates good predicitions of precipitation in the case of synoptic forced events (e. g. lines of thunderstorms) n dynamical effects better represented due to higher resolution 4 strong downslope winds 4 lee waves (e. g. improved glider forecasts) n radar observations of the DWD-radar network have an essential influence on the initial state (improved precipitation forecast for the first ~ 4. . 5 h) Koppert et al. , DWD 4 COPS FE 1

Nin. Jo n Nin. Jo is an international Workstation project 4 Partners are: Meteo. Suisse, DMI, MSC n Focus on Supporting Process Weather Forecasting n Base Functionality 4 Data decoding 4 Data storage 4 2 D-display of all data types needed for operations 4 Smooth 3 D-extension currently worked on, prototype exists 4 Interactive and batch ( this summer ) processing 4 Chart-based display with zooming and panning 4 Diagram-based display: time series, cross sections, tephigramms 4 Data display in different layers 4 Animation and automatic updates n Meteorological Functionality 4 Interactive chart generation ( fronts etc. ) 4 “On Screen” analyses 4 Weather monitoring and warning generation n Old workstation system is currently phased out Koppert et al. , DWD 4 COPS FE 1

Nin. Jo Supported Data Types n Surface and upper air observations 4 Synop, Ship, Metar, Temp …. n Grid 4 GME, COSMO, ECMWF, HIRLAM, GEM, GFS, n Satellite 4 Geostationary satellite 4 Polar orbiters n Radar SCIT 4 Storm cell and identification n Lightning 4 Different networks n Geo data 4 Vector 4 Raster Koppert et al. , DWD 4 COPS FE 1

Nin. Jo The Application n n The main window Multiple scenes Layers Basic operation bar 4 Zoom, pan, measure , reproject, print … n Layer bar n Layer specific tool bar n Layer specific menu bar n Animation bar Koppert et al. , DWD 4 COPS FE 1

Nin. Jo - Diagrams n A COSMO-E (LME) sounding 4 With several derived parameters ( CAPE. . ) 4 Available interactively for every point on the map and every model that’s in the database Koppert et al. , DWD 4 COPS n A COSMO-K (LMK) Cross-Section 4 Works with model and p-surfaces 4 2 D-cross sections ( wind, temperature, clouds, …. ) 4 1 D- cross section ( hourly rainrates, T 2 m… ) FE 1

Nin. Jo-Status Karlsruhe and Hohenheim n Nin. Jo servers and clients available 4 Software installed by Consultant (paid by DWD) 4 Single server installation 4 Currently runs on data provided by DWD and routed through FU Berlin 4 Supply through DWDSAT also possible 42 MBit satellite data stream 4 Observations ( surface, Upper air, lightning, radar … ) and model data 4 Subsampled GME and COSMO-E, no COSMO-K 4 Prepared for additional data e. g. COSMO-K 4 Additional data needed ( e. g. Konrad ) has to reported – FTP based supply has to be set-up well in advance – Band-widths issues ? n Standard operational DWD-installation, based on Nin. Jo 1. 22 n Still low-cost alternative Java. MAP Koppert et al. , DWD 4 COPS FE 1

European regional multi-model ensemble SRNWP-PEPS Combines the most sophisticated operational limited area models in Europe the ensemble size depends on location Koppert et al. , DWD 4 COPS ensemble size FE 1

SRNWP-PEPS …. used to generate warnings of extreme events Products: 4 Ensemble mean 4 Probabilities of exceeding thresholds 4+18 h and +30 h 46 AM and 6 PM Output variables (surface fields only) 4 Total precipitation 4 Total snow 4 Maximum 10 m wind speed 4 Maximum 10 m wind gust speed 4 2 m temperature 4 relative humidity 2 m 4 global radiation at surface Koppert et al. , DWD 4 COPS FE 1

Participating Models Koppert et al. , DWD 4 COPS FE 1

24 h precipitation run: 22. 08. 05 0 UTC, available: 22. 08. 05 6: 05 UTC valid: 22. 8. - 23. 8. , 6 UTC ensemble mean observations [mm] probabilities RR >50 mm Koppert et al. , DWD 4 COPS [%]FE 1

MICRO-PEPS ensemble size 4 5 9 6 7 8 Output variables: tigge+ list Models: model hor. res. institution COSMO-CH 2 2, 2 Meteo. Swiss ITA-LM 2, 8 CNMCA COSMO-LAMI 2, 8 ARPA-SIM COSMO-K 2, 8 DWD MOLOCH 2, 2 ISAC-CNR / ARPAL-CFMI Time schedule: AROME 2, 5 Météo-France GEM-LAM Ø March dry-run : Thu 29. 03 - Wed 04. 04 2, 5 Environment Canada Ø April: set up of MICRO-PEPS Ø April dry-run : Tue 24. 04 - Mon 30. 04 Koppert et al. , DWD 4 COPS FE 1

Scenarios for Data Assimilation Real time Delayed mode • Experiment data are available for operational runs • • Impact studies in delayed mode by excluding data from experiment Operational runs only use standard observations • Pro: Potentially better operational forecasts, direct feedback from monitoring Impact studies in delayed mode by including data from experiment • Pro: More controlled set-up and easier monitoring, complete data set • Con: No impact on operational forecasts • • Con: More difficult to monitor and need for extra delayed mode assimilations because of incomplete coverage Common requirements Detailed list of experimental stations for blacklist and possibly whitelist. Distribution of data in agreed formats and in known ways Koppert et al. , DWD 4 COPS FE 1