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Scatterometers at KNMI; Towards Increased Resolution

Ad.Stoffelen@KNMI.nl Hans Bonekamp Marcos Portabella http://www.knmi.nl/scatterometer. Scatterometers at KNMI; Towards Increased Resolution. Isabel. Overview. Scatterometer winds contain mesoscale detail not captured by NWP fields, but also noise

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Scatterometers at KNMI; Towards Increased Resolution

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  1. Ad.Stoffelen@KNMI.nl Hans Bonekamp Marcos Portabella http://www.knmi.nl/scatterometer Scatterometers at KNMI;Towards Increased Resolution Isabel

  2. Overview • Scatterometer winds contain mesoscale detail not captured by NWP fields, but also noise • Mesoscale information is useful for nowcasting • MSS: an effective way of controling the noise • Spatial analysis in progress Miami Workshop 8-10 Feb ‘05

  3. Spectral tail • Spectral response is used in engineering for design of noise properties • Being used now to increase SeaWinds resolution at KNMI Energy density Noisy Ideal Truncated Wave number Miami Workshop 8-10 Feb ‘05

  4. Bad rainy case • Nadir noisy Miami Workshop 8-10 Feb ‘05

  5. Local minima Probability of f Wind direction (f) Broad Wind Direction Minima Solution bands • Local minima do not represent solution P Miami Workshop 8-10 Feb ‘05

  6. Broad Minima A wide range of probable solutions exists in nadir (of 144 solutions per WVC) Locally, 100-km product is pretty Unique (P threshold is 10-7) Miami Workshop 8-10 Feb ‘05

  7. Meteorological balance (2D-VAR) Spatial filter: • Mass conservation • Continuity equation  0U = 0 • Vertical motions < horizontal motion • Little divergence • Mostly rotation (extratropics) Miami Workshop 8-10 Feb ‘05

  8. 100 km • Multiple Solution • Scheme • Full use of solution probability info • Meteorological balance in Ambiguity Removal (2D-VAR) • (Portabella&Stoffelen, 2003) • Smooth solution exists @100 km Miami Workshop 8-10 Feb ‘05

  9. Standard scheme: < 4 solutions • Erratic at low wind speeds Miami Workshop 8-10 Feb ‘05

  10. Multiple Solution Scheme • Smooth representation • Mesoscale detail kept Miami Workshop 8-10 Feb ‘05

  11. ECMWF First Guess ECMWF First Guess • ECMWF Position error Miami Workshop 8-10 Feb ‘05

  12. General MSS performance @100 km Mean vector RMS difference with ECMWF FGAT (m/s) • MSS better than 4-solution standard, in particular at nadir • NCEP background for 2DVAR much worse Miami Workshop 8-10 Feb ‘05

  13. 50 km Plots ! NOAA MSS @ 25 km Improved coldfront Better Around rain Miami Workshop 8-10 Feb ‘05

  14. NOAA MSS @ 25 km Better Around rain Improved inflow Miami Workshop 8-10 Feb ‘05

  15. MSS @ 25 kmNOAA NCEP Improved inflow Miami Workshop 8-10 Feb ‘05

  16. Summary • The use of more wind retrieval information in MSS allows consistent mesoscale features in the 25-km product • A balanced spatial filter such as 2D-VAR is effective in removing noise and keeping meteorology, direction or vector uniformity constraints are less effective • At 100-km the background wind used for ambiguity removal appears irrelevant, but this needs checking at 25 km • The spectral behaviour of 2D-Var at 25-km needs to be evaluated • Verification against buoys is underway Miami Workshop 8-10 Feb ‘05

  17. Further References For scatterometer-related papers, documentation, and wind products of the SAFs please refer to http://www.knmi.nl/scatterometer We look forward to sharing • Our scatterometer processing software • Our ERS and QuikScat products • Our new wind stress products • Our experience We fund visiting scientists E-mail:scat@KNMI.nl Thank you! Miami Workshop 8-10 Feb ‘05

  18. DIRTH (NOAA product) JPL’s Direction Interval Retrieval Threshold Nudging DIRTH TN removes noise in 25-km product, but at some expense • Unnormalised notion of P (WVC and speed dependence) • P segments exclude probable solutions (T=0.8; 0.2 left out) • Medium filter ignores P within segment • No meteorological balance constraints DIRTH results in • Very smooth fields (> 100 km) • Loss of meteorological detail • KNMI proposes Multiple Solution Scheme Miami Workshop 8-10 Feb ‘05

  19. Scatterometer Data Processor INPUT OUTPUT OUTPUT Ocean Surface Radar Backscatter Observations Ambiguity Ambiguity Wind Wind Inversion Inversion Observations Removal Removal Field Field Pre- Process Quality Quality Control Monitor Miami Workshop 8-10 Feb ‘05

  20. Ambiguity Probability Quadratic inner loop approximation? IFS experiments from KNMI + some visits Miami Workshop 8-10 Feb ‘05

  21. QuikSCAT http://www.knmi.nl/scatterometer Miami Workshop 8-10 Feb ‘05

  22. 29 10 2002 NWP Impact @ 100 km Storm near HIRLAM misses wave; SeaWinds should be beneficial! Miami Workshop 8-10 Feb ‘05

  23. Satellite Application Facilities Scatterometer sea surface wind R&D • Quality control, rain and ice screening • Spatial averaging (100 km  25 km) • Inversion: Computation of wind solutions and associated probabilities frommeasurementinformation • Determination of information content; Observation operatorAmbiguity removal (spatial filter to determine unique field) • Active monitoring and control (of instrument and processing) • Web site (visualisation) and product distribution • Product enhancement • Preparation for ASCAT wind production (METOP; 2006) Miami Workshop 8-10 Feb ‘05

  24. Detail in 100-km product KNMI 100km Miami Workshop 8-10 Feb ‘05

  25. Product Verification with ECMWF Winds Comparison for a set of triple KNMI-NOAA-ECMWF points • KNMI 100-km product better for NWP assimilation than NOAA • NOAA wind speed score relatively bad due to wind direction spatial filter • KNMI rejects less high wind points (Portabella &, 2000) Miami Workshop 8-10 Feb ‘05

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