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Challenges of Predictability in NW Pacific Cyclogenesis

Explore predictability issues in explosive cyclogenesis over the NW Pacific, with insights on upstream wave impacts. Case studies and sensitivity analyses shed light on forecasting uncertainties and potential influencing factors.

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Challenges of Predictability in NW Pacific Cyclogenesis

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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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