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COPS – DWD Contributions

Deutscher Wetterdienst. COPS – DWD Contributions. Hans-Joachim Koppert, Michael Baldauf, Michael Denhard, Werner Wergen. Overview. COSMO-K Goals Case Studies & Verification Status NinJo PEPS Background Implementation Micro PEPS Data-Assimilation Issues.

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COPS – DWD Contributions

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  1. Deutscher Wetterdienst COPS – DWDContributions Hans-Joachim Koppert, Michael Baldauf, Michael Denhard, Werner Wergen Koppert et al., DWD4COPS

  2. Overview • COSMO-K • Goals • Case Studies & Verification • Status • NinJo • PEPS • Background • Implementation • Micro PEPS • Data-Assimilation Issues Koppert et al., DWD4COPS

  3. 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 • deep moist convection (super- and multi-cell thunderstorms, squall-lines, MCCs, rainbands,...) • interactions with fine-scale topography(severe downslope winds, Föhn-storms, flash floodings, fog, ...) 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 Koppert et al., DWD4COPS

  4. Convectively enhanced frontal precipitation, 1.10.2006, 18 UTC Obs.: up to 20 mm/12 h Koppert et al., DWD4COPS

  5. LAF-ensemble, 1h-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., DWD4COPS

  6. Convectively enhanced frontal precipitation1.10.2006, +06-30 h (from 0 UTC & 12 UTC-run) Koppert et al., DWD4COPS

  7. Problem: missed convection initiation in LMK 11.09.2006 other examples: July 2006 Koppert et al., DWD4COPS

  8. Synop-Verification RMSE of wind speed |v|10m Sept. 2006 Oct. 2006  LMK  LME 12 UTC-runs U. Damrath 0 UTC-runs Koppert et al., DWD4COPS

  9. 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 Precipitation 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?)  LMK  LME Koppert et al., DWD4COPS

  10. Status and Summary COSMO-K • COSMO-K in pre-operational use since 14.08.2006 • 18 h- (21 h-) forecasts are simulated every 3 h (LAF-ensemble) • 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) • dynamical effects better represented due to higher resolution • strong downslope winds • lee waves (e.g. improved glider forecasts) • 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., DWD4COPS

  11. NinJo • NinJo is an international Workstation project • Partners are: MeteoSuisse, DMI, MSC • Focus on Supporting Process Weather Forecasting • Base Functionality • Data decoding • Data storage • 2D-display of all data types needed for operations • Smooth 3D-extension currently worked on, prototype exists • Interactive and batch ( this summer ) processing • Chart-based display with zooming and panning • Diagram-based display: time series, cross sections, tephigramms • Data display in different layers • Animation and automatic updates • Meteorological Functionality • Interactive chart generation ( fronts etc. ) • “On Screen” analyses • Weather monitoring and warning generation • Old workstation system is currently phased out Koppert et al., DWD4COPS

  12. Surface and upper air observations Synop, Ship, Metar, Temp …. Grid GME, COSMO, ECMWF, HIRLAM, GEM, GFS, Satellite Geostationary satellite Polar orbiters Radar SCIT Storm cell and identification Lightning Different networks Geo data Vector Raster NinJoSupported Data Types Koppert et al., DWD4COPS

  13. NinJoThe Application • The main window • Multiple scenes • Layers • Basic operation bar • Zoom, pan, measure , reproject, print … • Layer bar • Layer specific tool bar • Layer specific menu bar • Animation bar Koppert et al., DWD4COPS

  14. A COSMO-E (LME) sounding • With several derived parameters ( CAPE .. ) • Available interactively for every point on the map and every model that’s in the database • A COSMO-K (LMK) Cross-Section • Works with model and p-surfaces • 2D-cross sections ( wind, temperature, clouds, …. ) • 1D- cross section ( hourly rainrates, T2m… ) NinJo - Diagrams Koppert et al., DWD4COPS

  15. NinJo-StatusKarlsruhe and Hohenheim • NinJo servers and clients available • Software installed by Consultant (paid by DWD) • Single server installation • Currently runs on data provided by DWD and routed through FU Berlin • Supply through DWDSAT also possible • 2MBit satellite data stream • Observations ( surface, Upper air, lightning, radar … ) and model data • Subsampled GME and COSMO-E, no COSMO-K • Prepared for additional data e.g. COSMO-K • Additional data needed ( e.g. Konrad ) has to reported • FTP based supply has to be set-up well in advance • Band-widths issues ? • Standard operational DWD-installation, based on NinJo 1.22 • Still low-cost alternative JavaMAP Koppert et al., DWD4COPS

  16. European regional multi-model ensemble SRNWP-PEPS Combines the most sophisticated operational limited area models in Europe ensemble size the ensemble size depends on location Koppert et al., DWD4COPS

  17. SRNWP-PEPS …. used to generate warnings of extreme events Products: • Ensemble mean • Probabilities of exceeding thresholds • +18h and +30h • 6 AM and 6 PM Output variables (surface fields only) • Total precipitation • Total snow • Maximum 10 m wind speed • Maximum 10 m wind gust speed • 2 m temperature • relative humidity 2m • global radiation at surface Koppert et al., DWD4COPS

  18. Participating Models Koppert et al., DWD4COPS

  19. 24h 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 >50mm Koppert et al., DWD4COPS [%]

  20. ensemble size 4 5 6 7 8 9 MICRO-PEPS Output variables: tigge+ list Models: • Time schedule: • March dry-run :Thu 29.03 - Wed 04.04 • April:set up of MICRO-PEPS • April dry-run :Tue 24.04 - Mon 30.04 Koppert et al., DWD4COPS

  21. Scenarios for Data Assimilation • Real time • Experiment data are available for operational runs • Impact studies in delayed mode by excluding data from experiment • Pro: Potentially better operational forecasts, direct feedback from monitoring • Con: More difficult to monitor and need for extra delayed mode assimilations because of incomplete coverage • Delayed mode • Operational runs only use standard observations • 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 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., DWD4COPS

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