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Predictability Issues Associated with Explosive Cyclogenesis in the North-West Pacific

Predictability Issues Associated with Explosive Cyclogenesis in the North-West Pacific. Edmund K.M. Chang School of Marine and Atmospheric Sciences Stony Brook University. Collaborators: Kevin Raeder, Nancy Collins and Jeff Andersen (DAReS, NCAR).

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Predictability Issues Associated with Explosive Cyclogenesis in the North-West Pacific

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  1. Predictability Issues Associated with Explosive Cyclogenesis in the North-West Pacific Edmund K.M. Chang School of Marine and Atmospheric Sciences Stony Brook University Collaborators: Kevin Raeder, Nancy Collins and Jeff Andersen (DAReS, NCAR) Third THORPEX International Science Symposium

  2. Why do we care? • Local weather • Downstream impacts

  3. Time Taken from THORPEX International Science Plan (Shapiro and Thorpe, 2004)

  4. Initial analysis error structure 12-hr forecast uncertainty 24-hr forecast uncertainty Taken from U.S. PARC science plan. Adopted from Hakim (2005)

  5. An example from winter TPARC Time Verification Target Target: T+60 Verify: T+144

  6. Cyclogenesis over W. Pacific often triggered by waves propagating out from Asia (Chang and Yu, 1999; Hoskins and Hodges, 2002) Dashed: 250 hPa Trough Tracks Solid: 850 hPa Tracks Hoskins and Hodges (2002)

  7. Question: • Is cyclogenesis triggered by upstream waves more predictable?

  8. Current Study • Case Selection (based on Chang 2005): • Explosive cyclogenesis over W. Pacific (Day 0) • Upstream wave packet over Asia at Day -3 • Methodology • Ensemble forecasts and sensitivity analyses • CAM3 at T85, 80-member ensemble • Ensemble assimilation using DART at NCAR • OBS: Radiosondes, aircrafts, and SAT winds • Kevin Reader, Nancy Collins and Jeff Anderson at NCAR • Feature based sensitivity analyses • Preliminary studies using dry model (Chang 2006)

  9. Up to now, several cases have been examined • Here, results from 1 quite predictable case, and 1 not so predictable case will be presented

  10. An example of explosive cyclogenesis 3 days after N packet “Predictable” Case ERA40 MSLP (contour interval 5 hPa)

  11. ERA40 Z500 (contour interval 60 m)

  12. 80-member Ensemble mean from Day -3 ERA40 Ensemble mean from Day -5 Ensemble mean from Day -6

  13. Between Day -1 and Day 0: • ERA40: cyclone deepened by 28.3 hPa • Ensemble forecast from Day -5: • Average deepening of 23.3 hPa • 60 of 80 members give deepening > 1 Bergeron • RMS cyclone position error of 533 km at day 0 • Average cyclone MSLP bias of +2.9 hPa at day 0

  14. Feature Based Sensitivity Analysis using dry model Forecast from Day -5 Remove upstream waves (10-90E) Control Retain only upstream waves (10-90E) (Remove waves in 90E-10E) Remove all waves (15-day mean)

  15. 2nd example of explosive cyclogenesis 3 days after N packet “Not so Predictable” Case ERA40 MSLP (contour interval 5 hPa)

  16. ERA40 Z500 (contour interval 60 m)

  17. ERA40 Ensemble mean from Day -3 Ensemble mean from Day -4 Ensemble mean from Day -5

  18. Case 1 apparently much more predictable than case 2. Why? • Some speculations: • Upstream wave packet appears stronger in case 1: stronger dynamical forcing • Structure of cyclone much simpler in case 1, but much more complex in case 2 • Cyclone development in case 2 apparently quite dependent on diabatic effects • Case 1 qualitatively similar results when CAM is run in “adiabatic” mode, or when water (vapor, liquid, and ice) quantities are all reset to 0 every 12 hours

  19. CASE 2 ERA40 Control forecast from day -2 CAM run in adiabatic mode from day -2 Moisture reset to 0 every 12 hours

  20. Speculations: • Strongly dynamically forced cases are more predictable • Cases in which diabatic processes are important are less predictable • How general are these results? • Are strongly forced cases sensitive to existence of near surface diabatically generated vortices? • Further work: How do these developments affect downstream cyclone events and weather? Third THORPEX International Science Symposium

  21. CASE 1 ERA40 Control forecast from day -2 CAM run in adiabatic mode from day -2 Moisture reset to 0 every 12 hours

  22. Shaded: 95% significant From Chang (2005)

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