MM5/COSMO-DE Model Inter-Comparison and Model Validation

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1 MM5/COSMO-DE Model Inter-Comparison and Model Validation Klaus Dengler and Christian Keil DLR, Institute of Atmospheric Physics Assessment of forecast quality using observations of the FRA airport campaign in 6/7

2 Outline 1. Motivation 2. Instrumentation during the FRA campaign ( ) 3. Configuration of high-res models MM5 and COSMO 4. A case study 5. Systematic evaluation of wind and temperature 6. Summary & Outlook 2

3 Approaching Airport Hongkong 3

4 Challenge: Capacity - ICAO rules additional WV separations, often too conservative 4

5 meteo measurements SODAR/RASS USA 3 gates, NM numerical weather prediction NOWVIV 10 gates, 2-11 NM WSVBS wake-vortex prediction P2P envelopes for y(t), z(t), Γ(t) in 13 gates for 8 a/c parameter classes (heavy) safety area prediction SHAPe ellipses in 13 gates for HH, HM temporal a/c separations for 6 a/c-rwy class combinations procedures AMAN STG, MSR, MSL, ICAO glide path adherence statistics FLIP standard deviations in 13 gates wake-vortex monitoring LIDAR 3 planes, NM conflict detection issue warning / adapt predictions 5

6 WSB: set-up at Frankfurt Airport right/east left/west 1070 m centre 1460 m LOZ & SODAR/RASS/SONIC 518 m 892 m m LIDAR for monitoring / safety net 0 m 6

7 Instrumentation at Frankfurt airport: location and setup WSWS anemometer SODAR/RASS 10 min averages 20 m vertical resolution, 3 wind components, virtual temperature, σ w sonic DWD station SODAR/RASS 7

8 Forecasting for airports: model chain with nesting LM1 forecasting domain MM5 forecasting domain 1 MM5 forecasting domain 2 Cross section along glideslope Airport area

9 Configuration of high res models MM5 MM5 daily two 24 hr runs: 00 and 12 UTC two nested domains: 2 x 2 km 2 (Δx=6.3 km), 90 x 90 km 2 (Δx=2.1 km) 10 min output of wind, temperature, density, tke and edr + BL data. vertical resolution 8 m (26 levels up to z=1 m, in total 60 levels). 25 grid points along glide paths (important to consider spatial variations!). Forcing with COSMO-EU analyses 9

10 Configuration of high res models MM5 and COSMO MM5 daily two 24 hr runs: 00 and 12 UTC two nested domains: 2 x 2 km 2 (Δx=6.3 km), 90 x 90 km 2 (Δx=2.1 km) 10 min output of wind, temperature, density, tke and edr + BL data. vertical resolution 8 m (26 levels up to z=1 m, in total 60 levels). 25 grid points along glide paths (important to consider spatial variations!). Forcing with COSMO-EU analyses COSMO-FRA daily two 24 hr runs: 00 and 12 UTC Model domain centered at FRA airport: 280 x 280 km 2 (Δx=2.8 km) 10 min output of wind, temperature, density, tke vertical resolution 15 1 m (13 levels up to z=1 m, in total levels). Forcing with hourly COSMO-EU analyses 10

11 SODAR/RASS Measurements 08. February 7 SODAR wind speed [m/s] wind speed 20 m/s from 2 : 00:00 02:00 04:00 06:00 08:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 00:00 0 hr:mm UTC Significant change in wind speed/direction at all heights around 12 UTC 11

12 MM5 - SODAR/RASS - Wind Speed SODAR MM Δu = u obs -u fc [m/s] wind speed [m/s] -20 wind speed 20 m/s from 2 : 00:00 02:00 04:00 06:00 08:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 00:00 0 hr:mm UTC red: MM5 12 black: SODAR

13 COSMO-FRA - SODAR/RASS - Wind Speed Δu = u obs -u fc [m/s] wind speed [m/s] wind speed 20 m/s from 2 : 00:00 02:00 04:00 06:00 08:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 00:00 0 hr:mm UTC red: LMK 13 black: SODAR

14 Results from case study COSMO_FRA forecast of change in wind speed and direction better than MM5 (~ 90 min delay in latter) Overestimation of wind speed by both models 14

15 SODAR/RASS - data sample Comparison Comparison COSMO-FRA/MM5 LMK/MM5 Sample Sample Jan Feb Jan+Feb 10 min average of wind, T v, σ(w) Vertical resolution 20 m Decreasing data sample above 1 m (less data at high wind speeds) Statistical analysis up to max. m Sample 15

16 COSMO-FRA/MM5 - SODAR/RASS - wind speed January 7 Comparison LMK/MM5 January 7 February 7 Comparison LMK/MM5 February RMS median Δ U RMS COSMO-FRA median Δ U COSMO-FRA mean U wind speed [m/s] 0 RMS median Δ U RMS COSMO-FRA median Δ U COSMO-FRA mean U wind speed [m/s] January & February 7 Comparison LMK/MM5 January + February 7 2 Only minor differences in RMS 1 0 RMS median Δ U RMS COSMO-FRA median Δ U COSMO-FRA mean U wind speed [m/s] MM5 slightly better for higher wind speeds (RMS) Overestimation of wind speed by MM5 16

17 COSMO-FRA/MM5 - SODAR/RASS - virtual Temp January 7 Comparison LMK/MM5 January 7 February 7 Comparison LMK/MM5 February RMS median Δ T v RMS COSMO-FRA median Δ T v COSMO-FRA Virtual Temp [K] RMS median Δ T v RMS COSMO-FRA median Δ T v COSMO-FRA Virtual Temp [K] 2 January & February 7 Comparison LMK/MM5 January + February 7 Average error and RMS smaller for COSMO-FRA compared with MM5 1 RMS median Δ T v RMS COSMO-FRA median Δ T v COSMO-FRA

18 Summary & Outlook Summary: Systematic evaluation of high-res MM5 and COSMO-FRA shows only minor differences in RMS for wind speed & wind direction Overestimation of wind speed by MM5 COSMO-FRA forecast of temperature shows smaller errors compared with MM5 Outlook: Comparison using WTR data provided by DFS (measurements up to 16 m) Additional case studies (Kyrill) Analysis using new COSMO version 18

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