Presentation is loading. Please wait.

Presentation is loading. Please wait.

1 Verification of wave forecast models Martin Holt Jim Gunson Damian Holmes-Bell.

Similar presentations


Presentation on theme: "1 Verification of wave forecast models Martin Holt Jim Gunson Damian Holmes-Bell."— Presentation transcript:

1 1 Verification of wave forecast models Martin Holt Jim Gunson Damian Holmes-Bell

2 2 Verification Models are verified against in-situ observations. Observations from moored buoys and platforms: wave height, wind speed, wave period. Observations from satellites: wave height, wind speed, wave energy spectrum Monthly performance statistics are produced and monitored. International collaboration to validate ERS-2 and Envisat missions.

3 3 Buoy locations (1995!)

4 4 Started 1995 Met Office, ECMWF, NCEP, FNMOC, Canada, Meteo- France Each centre co-locates model and moored buoy data in agreed format and exchanges monthly by ftp. Datasets collated and statistics prepared Published results: Bidlot, Holmes, Wittmann, Lalbeharry, Chen 2002, Weather and Forecasting 17 Global wave model verification exchange

5 5 timeseries wave height bias December 1996 to December 2002

6 6 Global wave model verification exchange timeseries peak period bias December 1996 to December 2002

7 7 Global wave model verification exchange timeseries wind speed bias December 1996 to December 2002

8 8 Global wave model verification exchange February 2003 Bias through 5 day forecast (top) Hs (middle) windspeed (lower) peak period

9 9 Global wave model verification exchange February 2003 SD through 5 day forecast (top) Hs (middle) windspeed (lower) peak period

10 10 Satellite radar altimeter ERS-2 (and now Envisat) Co-located wave height & wind speed 1 observation per second =7km use a 9 second average (for approx 60km interval) or 20 second average for assimilation needs careful quality control –buddy check –background check –climatology check

11 11 Satellite Altimeters along-track wave height ERS-2 Envisat 23 January 2003 Track crossing central South Pacific Some outliers are close to land

12 12 Satellite Altimeter ENVISAT RA-2 Ku Wave height March 2003 all data before quality control. Red indicates rain flag set black crosses show mean value in bin

13 13 Satellite Synthetic Aperture Radar 5km x 5km vignettes taken every 200km ERS-2 (every 100 km Envisat) Values at 12 wavelengths(100m - 1000m) and 12 directions in half-plane. Directional ambiguity Nonlinear transformation from wave energy spectrum from SAR product Software developed at DLR (Susanne Lehner, Johannes Schulz- Stellenfleth) and the Met Office to perform inversion. Azimuthal cutoff  wave model supplies info Compare modelled spectra with retrieved spectra Processing

14 14 Comparison of modelled spectra with SAR example 12 hours data compare Hs observed Model co-locations in time at 30 minute intervals

15 15 Comparison of modelled spectra with SAR example 12 hours data compare Hs for 18 second waves Demonstrates need for improved observation retrieval at longer wave periods

16 16 Comparison of modelled spectra with SAR example 12 hours data compare Hs for waves of 10 second period

17 17 Comparison of modelled spectra with ERS-2 SAR Pacific Swell example 6.68N 122W top left: SAR data top right model wave energy spectrum bottom left: retrieved SAR wave energy spectrum bottom right comparison 1d spectra (black model red SAR)

18 18 Comparison of modelled spectra with ERS-2 SAR Windsea example 48S 30W top left: SAR data top right model wave energy spectrum bottom left: retrieved SAR wave energy spectrum bottom right comparison 1d spectra (black model red SAR) Hs 4.62m model 3.13m SAR

19 19 Comparison of modelled spectra with ERS-2 SAR Windsea example 66S 91W top left: SAR data top right model wave energy spectrum bottom left: retrieved SAR wave energy spectrum bottom right comparison 1d spectra (black model red SAR) Hs 5.85m model 6.75m SAR

20 20 SUMMARY For global and regional wave models, validation is carried out against instrumented moored buoy observations of wave height, wave period and windspeed. Validation against altimeter data requires careful quality control when used in near-real time. Validation against satellite retrieved wave spectra needs further development of the retrieval scheme

21 21 SPARE SLIDES FOLLOW

22 22 Observing waves with SAR Synthetic Aperture Radar Flown on ERS-2, archived daily

23 23 The SAR observation Hydrodynamic modulation Tilt modulation Bragg scattering of microwaves Two-scale model of ocean surface: ripples and long waves Doppler effect used to resolve features

24 24 Remote Sensing of waves: SAR


Download ppt "1 Verification of wave forecast models Martin Holt Jim Gunson Damian Holmes-Bell."

Similar presentations


Ads by Google