Advisor: Dr. Fuqing Zhang

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Presentation transcript:

Advisor: Dr. Fuqing Zhang Ensemble Forecast and predictability of Rapid Intensification of Super Typhoon Usagi (2013) Simon Liu Masashi Minamide Dandan Tao Advisor: Dr. Fuqing Zhang Dr. Kun Zhao

Outline Background and Motivation Assimilate Atmospheric Motion Vector experiments Ensemble Forecast Role of Moisture in forecast: Switch moisture experiment Conclusion

Outline Background and Motivation Assimilate Atmospheric Motion Vector experiments Role of Moisture during DA: DA without updating hydrometers Ensemble Forecast Conclusion

Super Rapid Intensification- NASA Super Typhoon Usagi (2013) is one of the most powerful typhoon at 2013 at West Pacific Basin Usagi intensified by 65 knots (33 m/s) at 24 hours, double of standard of rapid intensification (30 knots).

Super rapid intensification storm can be predicted 1 days ahead! 24 hours Super rapid intensification storm can be predicted 1 days ahead! RI timing is wrong! Questions: Can data assimilate help improve intensity forecast? What factors cause forecast intensity divergence?

Outline Background and Motivation Assimilate Atmospheric Motion Vector experiments Role of Moisture during DA: DA without updating hydrometers Ensemble Forecast Conclusion

DA: HPI (Best Track SLP)+GTS data every 3 hours initial DA every 3 hours DA configuration DA: HPI (Best Track SLP)+GTS data every 3 hours D01: 379*244, 27 km D02: 298*298, 9 km D03: 298*298, 9 km WSM6 physics YSU PBL Modified Tiedtke cumulus scheme Flux from ocean=1

Intensity Forecast Intensity forecast improve significantly after more DA cycles Forecast tracks are getting better Prior Posterior Increment Vortex strength (represent by tangential wind) is weaken by 1 m/s during most of EnKF cycles

Outline Background and Motivation Assimilate Atmospheric Motion Vector experiments Ensemble Forecast Role of Moisture in forecast: Switch moisture experiment Conclusion

Ensemble Forecast Color based on RI onset time (the earlier, the warmer) Questions: What factors cause the RI timing variation/ intensity divergence?

What factors cause the RI timing variation/ intensity divergence? Environmental factors: Deep layer shear? Environment shear? Dry air intrusion? SST? Internal factors: Tilt between low-level and middle-level vortex center? Initial vortex strength? Inner core moistures? × ×

All members intensify before 36 h Weak Member Strong Member Correlated <vortex vorticity, RI timing>= 0.7, explaining 50% variation However, for similar initial vortex strength, intensity could have huge variation as well. Questions: What other factors caused these members to diverge in intensity?

Partial Correlation X: RI timing Y: RH Z1: current minSLP shear Median Partial correlation between RH and RI timing, consider current intensity as constant

Moisture Equivalent Potential Temperature Strong Member Weak Member Difference Moisture Equivalent Potential Temperature Strong Member Weak Member Weak Member with strong member moisture

Equivalent Potential Temperature Cross Section from south to north Atmospheric instability come from moisture difference Strong Member Weak Member Weak Member with strong member moisture

Outline Background and Motivation Assimilate Atmospheric Motion Vector experiments Ensemble Forecast Role of Moisture in forecast: Switch moisture experiment Conclusion

Additional Experiment 2- Switch Moisture Hypnosis: Initial inner core moisture field could impact the RI process Keep inner core (300 km), replace environment (>600 km), relaxing linearly in between. Replace all Qvapor fields in D01,D02,D03 Strong Member Weak Member Weak Member with strong member moisture

Replace RH do impact storm intensity to expected direction Hypnosis confirmed !

Weak Member with strong member moisture 0° 90° 180° 270° 360° Precipitation Weak Member shear Weak Member with strong member moisture

RH change regarding to RI time Ensemble Mean RH Idea 100 km, no flow Surface centered RH is perfected moisten up to 7 km at RI onset

Conclusion Forecasts of super rapid intensification of TC Usagi surprisingly over-strong predict of RI process. Data Assimilation of GTS data help weaken the initial vortex, then significantly improve the storm intensity / RI timing forecast. Ensemble Forecast from EnKF members predicted huge RI timing variation (35 hours) with large storm intensify spread (60 hPa). Correlation between initial vortex vorticity with RI timing/minSLP at 19 Sep is 0.7. Initial vortex strength explain 50 % intensity variation. Besides initial vortex strength, sensitivity experiments demonstrate inner core moisture have significant impact on RI timing as well. Moisture control instability of air. Strong member has large moisture/instability around vortex center, especially at north part. Moisture help initial convection and storm more easily become axisymmetric, facilitating RI process Inner core is perfectly moisten from surface to 7 km at RI onset, consistent with idea study by Dandan.

Intensity Forecast Intensity forecast error decrease after more DA cycles Forecast tracks are getting better Maybe because we introduce GFS information every 6 hours

Equivalent Potential Temperature Strong Member Weak Member Weak Member with strong member moisture

Tilt of all members reduce to less than 40 km at RI onset Tilt of all members reduce to less than 40 km at RI onset. The correlation, around 0.2 before 36h, is significant but smaller than Munsell et al. 2016 paper