The analysis and nowcasting system INCA. T. Haiden, A. Kann, K. Stadlbacher, G. Pistotnik, M. Steinheimer, F. Wimmer, C. Wittmann

Transcription

1 The analysis and nowcasting system INCA T. Haiden, A. Kann, K. Stadlbacher, G. Pistotnik, M. Steinheimer, F. Wimmer, C. Wittmann

2 Contents INCA system overview INCA performance Applications & cooperations Benefit to ALADIN / ALARO / AROME Next steps

3 INCA system overview Observations ALADIN Trilinear interpolation Observation corrections First guess IDW interpolation Correction field Weighting INCA forecast Weighting INCA nowcast SL advection Corrected field Corrected field = INCA analysis Corrected field =INCA analysis =INCA analysis ANALYSIS Motion vectors FORECAST

4 Geometry and variables Horizontal Lambert projection 1x1 km 3 domains (AU, SK, CH) INCA-SK INCA-AU INCA-CH Vertical True z-coordinate Shaved elements dz = m layers Variables θ, q, u, v, w Shaved elements z 2-D analyses and forecasts Precipitation, cloudiness, global radiation 3-D analyses and forecasts Temperature, humidity, wind x,y

5 Analysis strategy Ψ INCA analysis NWP analysis Observation x,y,z

6 Analysis strategy z z ALADIN INCA Free atmsophere: NWP model ~ok PBL & mountain atmosphere: corrections x T, Td

7 Forecast strategy ANALYSIS 1 NOWCASTING Weight ALADIN ECMWF h -15 min +00 h +06 h +31 bis +43 h Lead time +48 h

8 Analysis examples Z: 2m Temperature

9 Analysis examples Z: 2m Relative humidity

10 Analysis examples Z: 2m Relative humidity

11 Analysis examples Z: Precipitation (mm/15min)

12 Analysis examples Z: CAPE INCA Convective Analysis Fields: LCL CAPE CIN SHO LI MOCON DT_TRIG THETA_E

13 INCA performance: temperature T2M verification (all stations) MAE (K) Column B Column C Lead time (h)

14 INCA performance: precipitation MAE [mm/15min] MAE der INCA-Prognosen, (3312 Faelle) Lower Austria catchments, (3312 forecasts) Effect of nowcasting: ~2 hours Row 2 Row 3 Row 4 Row 5 Row 6 Row Vorhersagezeit [h]

15 INCA performance: precipitation Kamp catchment, stratiform period Kamp catchment, (288 forecasts) Effect of nowcasting: ~4 hours MAE (mm/15min) Row Column A Lead time (h)

16 Applications Operational flood forecasting and warning: Kamp, Danube+tributaries Niederschlagsensembles Kamptal (aufsummiert), :00 UTC 120 Kamp catchment, forecast :00Z Precipitation (mm) Niederschlag [mm] observation Column BA Column BE Column BC Column BD Column BB forecast Vorhersagezeit [h] Lead time (h)

17 Applications Web applications: transportation, energy, sports, tourism WSG station

18 Cooperations Flood forecasting, precipitation analysis - University of Technology, Vienna - University of Agriculture, Vienna - Institute for Meteorology und Geophysics, University of Vienna - Austrian Hydrological Services Nowcasting, data exchange - DWD - SHMU - MeteoSwiss - CHMI (planned)

19 Benefit to ALADIN / ALARO / AROME (AAA) 1) Use of INCA analyses for verification and model intercomparison 2) Use of INCA forecast as benchmark for AAA 3) Convection nowcasting feedback for AAA developments 4) Gathering experience with use of non-standard obs from various sources 5) Nowcasting tool ready for operational use with any NWP model

20 1) Verification and model intercomparison ARPEGE fcst ALADIN fcst AROME fcst INCA analysis E. Bazile, EGU2006, Vienna

21 2) INCA forecast as benchmark for AAA Kamp catchment, stratiform period MAE (mm/15min) ALADIN+3DVAR, AROME? Column A Lead time (h) Row 1

22 3) Convection nowcasting: feedback for AAA CAPE, CIN, Moisture convergence, visible sat image cell developments

23 4) Experience with diverse non-standard obs Currently in the INCA system: - SYNOP+TAWES sfc obs - HYDRO sfc obs - RADAR data - SAT data (hires vis, cloud types) Planned or in progress: - D, CH, SK, CZ sfc obs + RADAR - Radiosonde data

24 5) Tool ready for operations with any NWP model Currently: ALADIN, ECMWF In progress: ALMO Planned: LM (LMK?), ALARO, AROME?

25 Next steps (2006/2007) Operationalize INCA-SK, INCA-CH Move towards multivariate analysis (use θl,qt) Move towards unified nowcast method (error motion vectors) Improve interpolation (anisotropy, correlations) Include more model physics (sfc energy budget, PBL processes)