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MSG cloud mask initialisation in hydrostatic and non-hydrostatic NWP models

Sibbo van der Veen KNMI De Bilt, The Netherlands. EMS conference, 10 -14 September 2012, Lodz, Poland. MSG cloud mask initialisation in hydrostatic and non-hydrostatic NWP models. Changing initial clouds in Hirlam / Harmonie:. Use: cloud mask nowcasting SAF MSG cloud top temperatures

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MSG cloud mask initialisation in hydrostatic and non-hydrostatic NWP models

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  1. Sibbo van der Veen KNMI De Bilt, The Netherlands EMS conference, 10 -14 September 2012, Lodz, Poland MSG cloud mask initialisation in hydrostatic and non-hydrostatic NWP models

  2. Changing initial clouds inHirlam / Harmonie: Use: • cloud mask nowcasting SAF • MSG cloud top temperatures • Synoptic cloud base heights

  3. Relation between cloud amount and specific humidity: (N>0) (N=0) N: 3-D cloud cover Preserve buoyancy when changing humidity (keep virtual T constant) especially important in Harmonie! Correction:

  4. Apply to: 1) Hirlam (hydrostatic) * 4 seasons verification See Van der Veen, S. H., 2012: Improving NWP model cloud forecasts using Meteosat Second Generation imagery. Accepted for publication in Mon. Wea. Rev. * RUC (in cooperation with Siebren de Haan, KNMI) 2) Harmonie (non-hydrostatic)

  5. Spin up / spin down rainfall / cloud cover Limit initial humidity changes to 10% (optimisation of precipitation forecasts) results based on ~ 140 runs

  6. Example: cloud creation and cloud removal

  7. 1. Hirlam Rapid Update Cycle • Semi-operational (version 7.3), 11 km • 3d VAR • Observations: Mode S, AMDAR, synop, GPS • Analysis every hour • Forecast length: 6 h • Period: 5 May – 23 December 2011 • Control run and ‘MSG’ run (Kain-Fritsch)

  8. Observations used for verification: • AMDAR: upper air temperatures • Synop: cloud amounts • Synop: pressure • Synop: 2-m temperature

  9. Verification of forecast cloud amounts:

  10. Standard deviation / bias cloudiness averaged over whole period

  11. Verification of precipitation forecasts

  12. Verification of upper air temperatures:

  13. Verification of 2-m temperatures: • Standard deviation: slightly better • Bias: worse! (radiation module?)

  14. Verification of forecast surface pressure:

  15. 2a) Convection in HarmonieCase study: 10 July 2010Analysis times: 12 / 18 UTCSevere thunderstorms overthe Netherlands

  16. CNTR 18+(3-2) MSG

  17. CNTR 12+(9-8) MSG

  18. 2b) Fog in Harmonie Two experiments: with and without cloud mask / synop initialisation Cycling frequency: once every 6 hours Period: 15 – 30 March 2012 Area: The Netherlands / North Sea Example showing impact: 22 March, 06 UTC + 24h forecast

  19. CNTR +1 MSG

  20. CNTR +2 MSG

  21. CNTR +3 MSG

  22. CNTR +4 MSG

  23. CNTR +5 MSG

  24. CNTR +6 MSG

  25. CNTR +7 MSG

  26. CNTR +8 MSG

  27. CNTR +9 MSG

  28. CNTR +10 MSG

  29. CNTR +11 MSG

  30. CNTR +12 MSG

  31. CNTR +13 MSG

  32. CNTR +14 MSG

  33. CNTR +15 MSG

  34. CNTR +16 MSG

  35. CNTR +17 MSG

  36. CNTR +18 MSG

  37. CNTR +19 MSG

  38. CNTR +20 MSG

  39. CNTR +21 MSG

  40. CNTR +22 MSG

  41. CNTR +23 MSG

  42. CNTR +24 MSG

  43. Summary (1): > Initialisation procedure Hirlam / Harmonie: * change spec. humidity after analysis (MSG, synoptic cloud base) > Verification results for Hirlam: * better cloud cover, precipitation, upper air temperatures, surface pressure for forecasts * worse bias of2-m temperatures > Conclusion: * (variational) data assimilation not necessary for humidity in Hirlam…

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