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Data Assimilation with the HRRRAK

Data Assimilation with the HRRRAK Kayla Harrison, Don Morton, Brad Zavodsky , Shih-Hung Chou. Don Morton’s HRRRAK. 1050x1050x51 grid points 3 km resolution Initialized by RR Lateral boundary conditions from NAM12. Project simulations. Use HRRRAK domain

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Data Assimilation with the HRRRAK

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  1. Data Assimilation with the HRRRAK Kayla Harrison, Don Morton, Brad Zavodsky, Shih-Hung Chou

  2. Don Morton’s HRRRAK • 1050x1050x51 grid points • 3 km resolution • Initialized by RR • Lateral boundary conditions from NAM12

  3. Project simulations • Use HRRRAK domain • Use HRRRAK input and boundary conditions files • Ran WRF simulations without hourly updates

  4. Data Assimilation • Update wrfinput_d01 and wrfbdy_d01 files with GSI • Focus on AQUA satellite data • Atmospheric Infrared Sounder (AIRS) • Comparing prepbufr files: GDAS, NDAS, AIRS profiles, AIRS radiances

  5. Expected Limitations • GDAS vs. NDAS • Part of GDAS dataset not interpolated • AIRS profiles vs. radiances • SPoRT found better precipfrom profiles • Elevation errors in AIRS data • Considered pressure levels • AIRS works best over open ocean on calm days

  6. Case Studies • Case study #1: • August 20, 2011 • High wind event in southeast, AK • Case study #2: • March 6, 2012 • Snow in central, AK

  7. Case 1: Temp at first model level Control GDAS GDAS+profiles GDAS+radiance NDAS

  8. Case 1: QVAPOR at 850 mb Control GDAS GDAS+profiles GDAS+radiance NDAS

  9. Control: Case 1, Fairbanks Skew T

  10. GDAS: Case 1, Fairbanks Skew T

  11. GDAS: Case 1, Fairbanks Skew T

  12. NDAS: Case 1, Fairbanks Skew T

  13. AIRS profiles: Case 1, Fairbanks Skew T

  14. AIRS radiances: Case 1, Fairbanks Skew T

  15. Case Studies • Case study #1: • August 20, 2011 • High wind event in southeast, AK • Case study #2: • March 6, 2012 • Snow in central, AK

  16. Case 2: Temp at first model level Control GDAS GDAS+profiles GDAS+radiance NDAS

  17. Case 2: QVAPOR at 850 mb Control GDAS GDAS+profiles GDAS+radiance NDAS

  18. Control: Case 2, Fairbanks Skew T

  19. GDAS: Case 2, Fairbanks Skew T

  20. NDAS: Case 2, Fairbanks Skew T

  21. AIRS profiles: Case 2, Fairbanks Skew T

  22. AIRS radiances: Case 2, Fairbanks Skew T

  23. Summary • GDAS and NDAS are very similar • AIRS Profiles predict less moisture and lower temperatures • Prepbufrchoice has smaller influence on wind speed and direction than initially expected • From these case studies: GDAS, NDAS, and GDAS+radiances are best

  24. Future Work • Using GSI in HRRRAK runs

  25. Acknowledgements Don Morton Brad Zadovsky Shih Chou OraleeNudson Greg Newby

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