DOTSTAR in the past ten years DOTSTAR in the past ten years DOTSTAR - - PowerPoint PPT Presentation

DOTSTAR in the past ten years DOTSTAR in the past ten years DOTSTAR in the past ten years DOTSTAR in the past ten years 追風十年回顧 追風十年回顧 追風十年回顧 追風十年回顧 -

• 中年

中年 中年 中年 Wu Wu Wu Wu & & & & LinPo LinPo LinPo LinPo 的奇幻歷程 的奇幻歷程 的奇幻歷程 的奇幻歷程

吳俊傑 國立台灣大學大氣科學系 2013年11月02日

感謝 感謝 感謝 感謝 NSC, CWB, RCEC/Academia Sinica, AIDC, ONR,DOTSTAR及T-PARC

綱要

• 構想/籌備
• 起飛/成長
• 團隊/合作
• 國際/接軌
• 成果/突破
• 傳承/感恩

國家科學委員會「颱風重點研究」 侵台颱風之飛機偵察及投落送觀測實驗

代號： 追風計畫

Dropsonde Observation for Typhoon Surveillance near the TAiwan Region (DOTSTAR)

吳俊傑（計畫主持人） 林博雄 葉天降（共同主持人）

致謝：國科會、行政院科技顧問組、中央氣象 局、民航局、漢翔公司、適航驗證中心等, DOTSTAR& COOK team members Grants: NSC, CWB, RCEC, ONR

Team work

• Wu, C.-C.*, P.-H. Lin, S. Aberson, T.-C. Yeh, W.-P. Huang, K.-H. Chou, J.-S. Hong, G.-C. Lu, C.-T. Fong, K.-C.

Hsu, I-I Lin, P.-L. Lin, C.-H. Liu, 2005: Dropwindsonde Observations for Typhoon Surveillance near the Taiwan Region (DOTSTAR): An overview. Bulletin of Amer. Meteor. Soc., 86, 787-790.

(Wu et al. 2005, BAMS)

Dropwindsonde Observations for Typhoon Surveillance near the Taiwan Region (DOTSTAR, 2003 – present)

• Useful real-time data available to major operational forecast centers
• Positive impact to the track forecasts to models in major operation

centers (NCEP/GFS, FNMOC/NOGAPS, JMA/GSM)

• Targeted observation

Wu et al. (2005 BAMS, 2007a JAS, 2007b WF, 2009a,b,c MWR), Chou and Wu (2008 MWR), Chen et al. (2009 MWR, JAS), Yamaguchi et al. (2009 MWR), Chou et al. (2010 JGR) Weissmann et al. (2010 MWR)

Up to present, Up to present, Up to present, Up to present, 69 69 69 69 missions have been missions have been missions have been missions have been conducted in DOTSTAR for conducted in DOTSTAR for conducted in DOTSTAR for conducted in DOTSTAR for 54 54 54 54 typhoons, typhoons, typhoons, typhoons, with with with with 1141 1141 1141 1141 dropwindsondes dropwindsondes dropwindsondes dropwindsondes deployed deployed deployed deployed during the during the during the during the 363 363 363 363 flight hours flight hours flight hours flight hours.

50 50 50 50 typhoons affecting Taiwan 36 36 36 36 typhoons affecting (mainland) China typhoons affecting (mainland) China typhoons affecting (mainland) China typhoons affecting (mainland) China 12 typhoons affecting Japan 12 typhoons affecting Japan 12 typhoons affecting Japan 12 typhoons affecting Japan 6 typhoons affecting Korea 6 typhoons affecting Korea 6 typhoons affecting Korea 6 typhoons affecting Korea 16 typhoons affecting Philippines 16 typhoons affecting Philippines 16 typhoons affecting Philippines 16 typhoons affecting Philippines

Real-time DOTSTAR data in CWB’s WINS and QPESUM

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Typhoon Sepat 2007/08/16/0000

• Ito, K., and C.-C. Wu*, 2013: Typhoon-position-oriented sensitivity analysis. Part I: Theory and verification. J. Atmos. Sci. (accepted).
• Wu, C.-C.*, S.-G. Chen, C.-C. Yang, P.-H. Lin, and S. D. Aberson, 2012: Potential vorticity diagnosis of the factors affecting the track
• f Typhoon Sinlaku (2008) and the impact from dropwindsonde data during T-PARC. Mon. Wea. Rev ., 140, 2670-2688.
• Jung, B.-J., H. M. Kim, F. Zhang, and C.-C. Wu, 2012: Effect of targeted dropsonde observations and best track data on the track

forecasts of Typhoon Sinlaku (2008) using an ensemble Kalman filter. Tellus A., 64, 1-19. doi: 10.3402/tellusa.v64i0.14984.

• Huang, Y.-H., M. T. Montgomery, and C.-C. Wu*, 2012: Concentric eyewall formation in Typhoon Sinlaku (2008) – Part II:

Axisymmetric dynamical processes. J. Atmos. Sci., 69, 662-674.

• Wu, C.-C.*, Y.-H. Huang, and G.-Y. Lien, 2012: Concentric eyewall formation in Typhoon Sinlaku (2008) – Part I: Assimilation of T-

PARC data based on the Ensemble Kalman Filter (EnKF). Mon. Wea. Rev., 140, 506-527.

• Chou, K.-H., C.-C. Wu*, P.-H. Lin, S. D. Aberson, M. Weissmann, F. Harnisch, and T. Nakazawa, 2011: The impact of dropwindsonde
• bservations on typhoon track forecasts in DOTSTAR and T-PARC. Mon. Wea. Rev. 139, 1728–1743.
• Chen, S.-G., C.-C. Wu*, J.-H. Chen, and K.-H. Chou, 2011: Validation and interpretation of Adjoint - Derived Sensitivity Steering

Vector as targeted observation guidance. Mon. Wea. Rev. 139, 1608–1625.

• Majumdar, S. J.*, S. -G. Chen, and C.-C. Wu, 2011: Characteristics of Ensemble Transform Kalman Filter adaptive sampling guidance

for tropical cyclones. Quart. J. Roy. Meteor. Soc. 137, 503-520.

• Weissmann M.*, F. Harnisch, C.-C. Wu, P.-H. Lin, Y. Ohta, K. Yamashita, Y.-K. Kim, E.-H. Jeon, T. Nakazawa, and S. Aberson, 2011: The

influence of dropsondes on typhoon track and mid-latitude forecasts. Mon. Wea. Rev. 139, 908-920.

• Wu, C.-C.*, G.-Y. Lien, J.-H. Chen, and F. Zhang, 2010: Assimilation of tropical cyclone track and structure based on the Ensemble

Kalman Filter (EnKF). J. Atmos. Sci., 67, 3806-3822.

• Chou, K.-H., C.-C. Wu*, P.-H. Lin, and S. Majumdar, 2010: Validation of QuikSCAT wind vectors by dropwindsonde data from

Dropwindsonde Observations for Typhoon Surveillance Near the Taiwan Region (DOTSTAR), J. Geophys. Res., 115, D02109, doi:10.1029/2009JD012131.

• Wu, C.-C.*, J.-H. Chen, S. J. Majumdar, M. S. Peng, C. A. Reynolds, S. D. Aberson, R. Buizza, M. Yamaguchi, S.-G. Chen, T. Nakazawa ,

and K.-H. Chou, 2009: Inter-comparison of targeted observation guidance for tropical cyclones in the North western Pacific. Mon.

• Wea. Rev., 137, 2471-2492.
• Yamaguchi M., T. Iriguchi, T. Nakazawa, and C.-C. Wu, 2009: An observing system experiment for Typhoon Conson (2004) using a

singular vector method and DOTSTAR data. Mon. Wea. Rev., 137, 2801-2816.

• Wu C.-C.*, S.-G. Chen, J.-H. Chen, K.-H. Chou, and P.-H. Lin, 2009: Interaction of Typhoon Shanshan (2006) with the mid-latitude

trough from both Adjoint-Derived Sensitivity Steering Vector and potential vorticity perspectives. Mon. Wea. Rev., 137, 852–862.

• Chou, K.-H., and C.-C. Wu*, 2008: Development of the typhoon initialization in a mesoscale model – Combination of the bogused

vortex with the dropwindsonde data in DOTSTAR. Mon. Wea. Rev., 136, 865-879.

• Wu, C.-C.*, K.-H. Chou, P.-H. Lin, S. D. Aberson, M. S. Peng, and T. Nakazawa, 2007: The impact of dropwindsonde data on typhoon

track forecasts in DOTSTAR. Weather and Forecasting, 22, 1157-1176.

• Wu, C.-C.*, J.-H. Chen, P.-H. Lin, and K.-S. Chou, 2007: Targeted observations of tropical cyclones based on the adjoint-derived

sensitivity steering vector. J. Atmos. Sci., 64, 2611-2626.

• Wu, C.-C.*, P.-H. Lin, S. Aberson, T.-C. Yeh, W.-P. Huang, K.-H. Chou, J.-S. Hong, G.-C. Lu, C.-T. Fong, K.-C. Hsu, I-I Lin, P.-L. Lin, C.-H. Liu,

2005: Dropwindsonde Observations for Typhoon Surveillance near the Taiwan Region (DOTSTAR): An overview. Bulletin of Amer.

• Meteor. Soc., 86, 787-790.

Highlighted Publications from DOTSTAR

Ensemble- based Adjoint- based NCEP/GFS ensemble variance Ensemble Transform Kalman Filter (ETKF) (Aberson 2003) (Majumdar et al. 2006) Singular Vector

NOGAPS JMA ECMWF

(Peng and Reynolds 2006) (Yamaguchi et al. 2009) (Buizza et al. 2006) Adjoint-Derived Sensitivity Steering Vector (ADSSV)

(Wu et al. 2007a, 2009a, Chen et al. 2011)

Since 2003, several

• bjective

methods, have been proposed and tested for

• perational/research surveillance missions in the environment of Atlantic hurricanes

conducted by HRD/NOAA (Aberson 2003) and NW Pacific typhoons by DOTSTAR (Wu et

• al. 2005).

• By defining the response function as a function of model output

variables, one can use the adjoint model to calculate the sensitivity: Verification area: square box (typically 600 km by 600 km) centered around the MM5-simulated storm location at the verification time. Define the response function: 0.875-0.225 deep-layer area- averaged zonal and meridional winds, respectively. Adjoint-Derived Sensitivity Steering Vector (ADSSV): ADSSV w.r.t. vorticity= (Wu et al. 2007a)

0.225 0.875 1 0.225 0.875 A A

u dxdyd R dxdyd σ σ =

• 0.225

0.875 2 0.225 0.875 A A

v dxdyd R dxdyd σ σ =

• 1

2

, R R ζ ζ

• ∂

∂

• ∂

∂

• ut

( ) R R = x

* in

• ut

R R ∂ ∂ = ∂ ∂ M x x

M*: adjoint operator (Errico 1997; Zou et al. 1997; Wu 2006)

• Wu, C.-C.*, J.-H. Chen, P.-H. Lin, and K.-S. Chou, 2007: Targeted observations of tropical cyclones

based on the adjoint-derived sensitivity steering vector. J. Atmos. Sci., 64, 2611-2626.

Typhoon Fungwong Typhoon Fengshen

Data impact

A new method for targeted

• bservations

is proposed and examined based

• n

the adjoint sensitivity. The locations of DOTSTAR’s dropwindsondes well match the sensitive region. Dropwindsonde data have a positive impact on the track forecasts of Meari. The ADSSV method is applied to identify the signals of the binary interaction. Typhoon Fengshen (2002) is sensitive to the steering flow of Typhoon Fungwong, but the sensitivity for Typhoon Fungwong to the steering flow of Typhoon Fengshen is rather insignificant. (one-way interaction)

(Wu et al. 2007, JAS)

• Yamaguchi M., T. Iriguchi, T. Nakazawa, and C.-C. Wu, 2009: An observing system

experiment for Typhoon Conson (2004) using a singular vector method and DOTSTAR

• data. Mon. Wea. Rev., 137, 2801-2816.

Red: (I) all dropsonde obs Blue: (II) no dropsonde obs Green: (III) Three dropsonde

• bs within the

sensitive region Light blue: (IV) Six dropsonde obs outside the sensitive region

• ×

CONSON’s center position

Sensitive analysis result

Sensitive region

shows vertically accumulated total energy by the 1st moist singular vector.

Targeted area for

the SV calculation is 25N-30N, 120E-130E. OSE result on CONSON’s (2004) track forecast

Wind & Z at 500hPa

×

(Yamaguchi et al. 2009, MWR)

• Wu, C.-C.*, J.-H. Chen, S. J. Majumdar, M. S. Peng, C. A. Reynolds, S. D. Aberson, R. Buizza, M.

Yamaguchi, S.-G. Chen, T. Nakazawa , and K.-H. Chou, 2009: Inter-comparison of targeted observation guidance for tropical cyclones in the North western Pacific. Mon. Wea. Rev., 137, 2471-2492.

Three special cases are selected to highlight and interpret the dynamical features affecting the TC motion, associated with the midlatitude trough (Typhoon Shanshan), the subtropical high (Typhoon Chanchu), and the subtropical jet (Typhoon Durian).

(Wu et al. 2009, MWR)

• Chou, K.-H., C.-C. Wu*, P.-H. Lin, and S. Majumdar, 2010: Validation of QuikSCAT wind

vectors by dropwindsonde data from Dropwindsonde Observations for Typhoon Surveillance Near the Taiwan Region (DOTSTAR), J. Geophys. Res., 115, D02109, doi:10.1029/2009JD012131.

Storm-relative Rain-flagged Non-rain-flagged

The absolute mean and RMS difference of wind speed are 2.2 and 3.2 m/s, respectively, while those of wind direction are 13.8° and 21.8°, respectively. QuikSCAT data slightly underestimates the wind speed of medium-wind regime and possesses some clockwise directional bias in the high-wind regime.

Rain-flagged Non-rain-flagged < 10 m/s > 17.2 m/s 10-17.2 m/s

(Chou et al. 2010, JGR)

Special Collection in Mon. Wea. Rev.: Targeted Observations, Data Assimilation, and Tropical Cyclone Predictability

• Chun-Chieh Wu, Sharanya J. Majumdar, Sim D.

Aberson, Tetsuo Nakazawa, and Carolyn Reynolds

18 papers published

http://journals.ametsoc.org/page/Cyclone_Predictability

Theme: Accurate tropical cyclone track forecasts are of foremost importance to the increasing population in coastal areas worldwide, necessitating advances in all facets of the numerical prediction process. These include the observational network, the data assimilation schemes that blend these observations with the numerical first guess field, the vortex initialization schemes and the dynamics, physics, and resolution

• f the models themselves, and methods to target observations to
• ptimize the reduction in forecast error. During the past 30 years, the

forecast skill for tropical cyclone track has increased steadily because

• f improvements in all of these areas. In particular, advances have been

made in targeted observations and data assimilation over the past

• decade. This Monthly Weather Review special collection gathers

together a series of timely papers on these topics, many of which have resulted from multinational collaborations.

• THORPEX-PARC Experiments (2008) and Collaborating

Efforts

NRL P-3 and HIAPER with the DLR Wind Lidar NRL P-3 and HIAPER with the DLR Wind Lidar

Upgraded Russian Radiosonde Network for IPY Winter storms reconnaissance and driftsonde

JAMSTEC/IORG G

6 9

Understand and improve the lifecycle of TC and its predictability –

• Genesis
• Intensity and structure

change,

• Recurvature (targeted obs.)
• Extra-tropical transition (ET)

Dop pler lidar 20°

• ff

nadir dropsondes, u, v, t, rh, p

DOTSTAR Falcon C-130 P-3

U.S. ONR/NSF TCS-08 [NRL P-3, WC-13 ProbeX

DOTSTAR Astra jet DLR Falcon 20 US Air Force WC-130 US NRL P-3

• F. Harnisch

First systematic targeting operation in WPAC 1 August – 30 September 2008

Multiple aircraft (up to 2 for targeting + 2 for structure missions) Comparison of several targeting methods ECMWF/UKMO Data Targeting System

DOTSTAR + Falcon + P3 + C130, 52h + 85h + 165h + 215h = 507h flight hours, unprecedented! 173 + 328 + 604 + 343 = 1448 dropwindsondes

17

Typhoon Sinlaku (2008) during T-PARC

Terrain effect

Wu et al. 2013

NRL

Targeted

• bservation

Recurvature

Extratropical transition Intensification Structure change

Wu et al. 2012b

TC-ocean interaction

Wu et al. 2012a; Huang et al. 2012 Wu et al. 2012c

9 flight missions Conventional radiosondes Dropwindsondes DOTSTAR ASTRA DLR Falcon NRL P-3 USAF C-130 inner core

• thers

Total available 623 36 (2 flights) 34 (2 flights) 12 (1 flight) 20 57 (4 flights) 159

• Wu, C.-C.*, S.-G. Chen, C.-C. Yang, P.-H. Lin, and S. D. Aberson, 2012: Potential vorticity diagnosis
• f the factors affecting the track of Typhoon Sinlaku (2008) and the impact from dropwindsonde

data during T-PARC. Mon. Wea. Rev., 140, 2670-2688.

In the NCEP GFS model, the assimilation of dropwindsonde data leads to an improvement in the 12–96-h mean track forecast

• f up to 76%.

The subtropical high to the northeast of Sinlaku in GFS-ND is weaker and smoother than that in GFS-WD. The geopotential height associated with the midlatitude trough in GFS-ND appears deeper than that in GFS-WD.

(Wu et al. 2012, MWR)

• Harnisch, F., and M. Weissmann, 2010: Sensitivity of typhoon forecasts to different subsets
• f targeted dropsonde observations. Mon. Wea. Rev., 138, 2664–2680.

ViObs CeObs ReObs AllObs

▽: CeObs △: ViObs ○: AllObs X: NoObs

ViObs CeObs ReObs Observations in the vicinity of the TC (“ViObs”) lead to the largest track error reduction. Results in “ReObs” do not show a large improvement. The influence in “CeObs” on track forecasts is neutral on average.

(Harnisch and Weissmann 2010, MWR)

• Chou, K.-H., C.-C. Wu*, P.-H. Lin, S. D. Aberson, M. Weissmann, F. Harnisch, and T.

Nakazawa, 2011: The impact of dropwindsonde observations on typhoon track forecasts in DOTSTAR and T-PARC. Mon. Wea. Rev. 139, 1728–1743.

Paired t-test statistical examination: statistically significant at the 90% (*) and 95% (**) confidence level GFS Impact from 2003 to 2009 (DOTSTAR) 2008 (T-PARC)

Sinlaku + Jangmi Sinlaku Jangmi

The mean 1- to 5-day track forecast error is reduced by about 10%–20% for both DOTSTAR and T-PARC cases in the NCEP system. The impact in the ECMWF system is not as beneficial as in the NCEP system, likely because of more extensive use of satellite data and more complex data assimilation.

(Chou et al. 2011, MWR)

16 18 20 22 23 24 25 26 28 30 33 36

v

v at the lowest model level

Ensemble mean Ensemble members C-130 dropsondes

940 950 960 970 980 990 1000

00Z13SEP 12Z12SEP 00Z12SEP 12Z11SEP 00Z11SEP 12Z10SEP 00Z10SEP 12Z09SEP

1 1.5 2 2.5 3 4 5 10 15 20 30 40

q

(mm hr-1) (cm s-1) (10 PVU)

w at 0.5 km Pmin (Pha) PV at 2km

(ms-1)

total column rainrate

SEF (H 0)

rainrate

6 8 10 20 30

H 0

w

• 1 -0.5 -0.1 1 2 3 4

6 8 10

SEF time: When a persistent secondary maximum in V at the lowest model level

sporadic convective cells concentric eyewalls New eyewall

H -14 H 23

H 0

• Wu, C.-C.*, Y.-H. Huang, and G.-Y. Lien, 2012: Concentric eyewall formation in Typhoon Sinlaku

(2008) – Part I: Assimilation of T-PARC data based on the Ensemble Kalman Filter (EnKF). Mon.

• Wea. Rev., 140, 506-527.

(Wu et al. 2012, MWR)

Internal wave and Typhoon-Ocean interaction Project in the Western North Pacific and Neighboring Seas (ITOP, 2010)

International collaboration:

ITOP planning meeting, Taipei, 2008

• DOTSTAR, TCS-10, and ITOP coordination
• Investigation of the roles of upper ocean thermal

structures (eddies and/or wakes) on typhoon-ocean interaction.

• Understanding the feedback of the typhoon-ocean

interaction to typhoon intensity and structure evolution.

• Numerical simulation experiments (coupled model) with

the T-PARC (and TCS-10) and ITOP data. DOTSTAR C130

Taiwan US Japan

ITOP operation, Guam, 2010

ITOP Facilities

C-130 R/V Revelle DOTSTAR ITOP Mooring EM- APEX Lagrang ian- Float

ITOP ensemble reanalysis based on EnKF ( ITOP_EnKF )

2013年 DOTSTAR

DOTSTAR DOTSTAR DOTSTAR 規劃會議

會議時間:2013/01/11 會議地點:氣象局B207

與會人員

氣象局:

科技中心 科技中心 科技中心 科技中心 主任 主任 主任 主任 程家平 陳得松 黃康寧 預報 預報 預報 預報中心 中心 中心 中心 主任 主任 主任 主任 鄭明典 副主任 副主任 副主任 副主任 林秀雯、呂國臣 課長 課長 課長 課長 陳怡良、黃椿喜 衛星 衛星 衛星 衛星中心 中心 中心 中心 主任 主任 主任 主任 陳嘉榮 資訊 資訊 資訊 資訊中心 中心 中心 中心 副主任 副主任 副主任 副主任 馮欽賜 洪景山

臺灣大學/文化

吳俊傑 林博雄 周昆炫 盧濟明 顏自雄

Standard Operation Procedure for DOTSTAR after 2012

Typhoon watching FNMOC,ECMWF,CWB (120~144hrs) ASTRA flight-route planning (1) sensitivity regions: DLM, ETKF, ADSSV 氣象局 Decision Making 預報中心討論會 Flight plan AIDC AIDC flight plan modification Debriefing (phone) Data archive (CWB/NTU – research) D-2~D-1 Mission briefing (skype) CWB + AIDC D-7~D-3 D-3~D-2 D-1 D-0 預報中心 NTU TTFRI ASPEN edit on ground (AIDC) WINS/QPESUMS check (CWB) D-0

再次感謝所有好友及研究伙伴的加持與合作

中年 中年 中年 中年 Wu Wu Wu Wu & & & & LinPo LinPo LinPo LinPo 的奇幻歷程 的奇幻歷程 的奇幻歷程 的奇幻歷程

2828

感 感 感 感 謝 謝 謝 謝 聆 聆 聆 聆 聽 聽 聽 聽

報告人 報告人 報告人 報告人： ： ： ： 吳俊傑 吳俊傑 吳俊傑 吳俊傑 ( ( ( (臺灣大學大氣科學系 臺灣大學大氣科學系 臺灣大學大氣科學系 臺灣大學大氣科學系) ) ) )

Look forward to more interactions and Look forward to more interactions and Look forward to more interactions and Look forward to more interactions and collaborations. collaborations. collaborations. collaborations.

致謝 致謝 致謝 致謝 感謝過去十年國科會、中央氣象局、中央研究院及美國NCEP、HRD/AOML/NOAA、海軍研 究中心（NRL及ONR）、日本氣象廳之支持與協助，以及追風計畫研究團隊（DOTSTAR & COOK）的努力與奉獻，國內外大氣科學界先進的加持與指點、相關研究專家學者的參與 合作，及中央氣象局、民用航空局與漢翔公司的全力配合協助，使得這極具開創性的先驅 研究計畫得以順利進展，並圓滿完成這十年共64次颱風飛行觀測任務，且在觀測作業應用 及科學論文都有突破的重大成果。 眾多單位及個人於經費、物資、人才及精神上的期許與鼓勵，在追風十年中都扮演了舉足 輕重的角色，這段奇幻歷程，參與者得到了寶貴的經驗與豐碩的成果，身為核心主持人員 的Wu＆LinPo涉入得最深、收穫也最為深刻。能有此機會，一路將「追風計畫」從籌畫、 執行到交付給可以永續經營的中央氣象局，是整個工作團隊的榮幸，也是我們最珍貴的歷 程。少年Pi上岸後開啟了人生的新篇章，中年Wu＆LinPo在奇幻歷程告一個段落之後，也 將開創其他更多更新的研究領域，繼續為科學界貢獻一己之力。至於追風計畫，或許就像 一路與Pi相互陪伴的威猛老虎，即使分離，在彼此的生命中都已佔有不可取代的一席之地。