Something about DOTSTAR (Dropsonde Observations for Typhoon Surveillance near the Taiwan Region) Chun-Chieh Wu Department of Atmospheric Sciences National Taiwan University Collaborators: Po-Hsiung Lin, Jan-Huey Chen, K.-S. Chou (NTU), T.-C. Yeh (CWB), Sim Aberson (HRD), T. Nakazawa (JMA/MRI), Dave Parson (NCAR), Seon Park (Ewha Womans Univ.), Sharan Majumdar (U. of Miami), Melinda Peng, and C. Reynolds (NRL) (Wu et al. 2005a, b) Overview of DOTSTAR Real-time forecast/analysis application Impact evaluation Targeted observations Future Prospects

Flow chart of DOTSTAR Astra jet of AIDC 6 9 JMA, UKMO, …. (Wu et al. 2005a, BAMS) 6 9

DOTSTAR missions （ 2003 to 2006 ） Up to present, 24 missions have been conducted in DOTSTAR for 20 typhoons, with 386 dropsondes deployed during the 129 flight hours. 8 typhoons affecting mainland China 4 typhoons affecting Japan 2 typhoons affecting Korea 23. Saomai22. Bopha 21. Kaemi20. Bilis 24. Shanshan

Real-time DOTSTAR data in CWB’s WINS Meari, 1200 UTC, 25 September, 2004 Dropsonde sounding data Flight-level wind and sfc. wind

Dropsonde MBL WML150 Unit: m/s Real-time surface wind analysis Bilis ( 碧利斯 ) : A weak typhoon (V max = 25 m/s), yet with very large and moisture-laden outer circulation

NCEP GFS : 14% JMA GSM : 19% NOGAPS : 14% ENSEMBLE : 22% The impact on global models in 2004 (Wu et al. 2006a, WF) Sim Aberson Tetsuo Nakazawa Melinda Peng

Impact to mesoscale models: Combination of the Dropwindsonde data and the bogused vortex (Chou and Wu 2006)

Targeted observation in DOTSTAR Adaptive observations : observations targeted in sensitive regions can reduce the initial condition’s uncertainties, and thus decrease forecast error. Factors associated with targeted observations - Magnitude of uncertainty - Growth of uncertainty - Data assimilation system plans for field programstests of new observing systems predictability and data assimilationTargeted observation is an active research topic in NWP, with plans for field programs, tests of new observing systems, and application of new concepts in predictability and data assimilation. (Langland 2005) In DOTSTAR, due to limited aircraft resources, targeted observing strategies for these missions must be developed. –NOGAPS Singular Vector (collaborating with Reynolds) –NCEP/GFS ETKF (collaborating with Majumdar) –NCEP/GFS DLM variance (collaborating with Aberson) –MM5 adjoint sensitivity (ADSSV) (Wu et al. 2005, BAMS; 2006, JAS)

Verifying area ： A box is centered on the forecast location of typhoon at the verifying time. Response function ： Define the average wind field within the verifying area at the verifying time. The forward and backward integrations of the adjoint modeling system ： ADSSVAdjoint-Derived Sensitivity Steering Vector (ADSSV) –A unique new definition to identify the sensitive (and targeted observing) areas to the steering flow at the verifying time. ADSSV w.r.t. vorticity ： Magnitude degree ofsensitivity Magnitude – the degree of sensitivity Direction steering flow direction Direction – the change of the steering flow direction w.r.t. the vorticity variation. (Wu et al. 2006c, JAS)

Higher sensitivity to the northeast of Typhoon Mindulle More impact on the meridional movement Typhoon Mindulle (2004) Results 0629_00Z 0627_12Z MM5 (Wu et al. 2006c, JAS) ADSSV w.r.t. vorticity ：

Targeted observations in DOTSTAR DLM Variances, Toth and Kalnay (1993) ETKF, Bishop and Majumdar (2001) FNMOC SV, Palmer et al. (1998)ADSSV, Wu et al. (2005) Operation of ADSSV DOTSTAR (Wu et al. 2006c) G-IV surveillance (Etherton et al. 2006) Session Rapporteur of the IWTC VI meeting, Nov , 2006 Singular Vector, JMA, Yamaguchi

How the dropsonde data improve the forecast? Typhoon Conson (2004) as an example Typhoon Conson (2004) 8 June 1200UTC (Nakazawa 2004, THORPEX meting) JMA-GSM

Evaluate a SV method as a strategy for Targeting Observation JMA has executed Observing System Experiments (OSEs) to investigate the usefulness of the singular vector method as a strategy for sensitive analysis. For the initial time of 12UTC 08 June 2004 when totally 16 dropsondes were dropped into typhoon CONSON by the DOTSTAR (Dropsonde Observation for Typhoon Surveillance near the Taiwan Region) project, 4 predictions with JMA Global Spectral Model (TL319L40) about the use of the dropsondes in the global 4D-Var analysis are executed. (I)all dropsonde observations are used for making the initial condition (II)dropsondes are not used at all (III)only 3 data within a sensitive region are used (4, 9, 12) (IV)only data outside of a sensitive region are used (6, 8, 10, 13, 15, 16) The distribution means vertically accumulated total energy by the 1st moist singular vector. Targeted area for the SV calculation is N25-N30, E120-E130. Optimization time interval is 24 hours. Sensitive analysis result x CONSON’s center position (From Yamaguchi)

OSEs result on CONSON’s track forecast (III)(I)(IV) (II) is almost same with (IV) similar Red: (I) all dropsonde observations are used for making the initial condition Blue: (II) dropsondes are not used at all Green: (III) only 3 data within a sensitive region are used (4, 9, 12) Water: (IV) only data outside of a sensitive region are used (6, 8, 10, 13, 15, 16) (From Yamaguchi)

Exp.Dropsonde dataDA schemeOthers CTLNoneX 3DVARAll3DVAR 3DVAR-N10Northern 10 drops3DVAR 3DVAR-S6Southern 6 drops3DVAR 3DVAR hPa3DVAR 3DVAR hPa3DVAR 3DVAR hPa3DVAR 3DVAR hPa3DVAR CRSSMNAllCressman CTL-nTWNoneXNo Taiwan 3DVAR-nTWAll3DVARNo Taiwan CTL-BGNoneXbogused 3DVAR-BGAll3DVARbogused Scientific objectives: To evaluate the impact of different subsets of the dropwindsonde data, the data assimilation schemes, the presence of Taiwan terrain, and the bogusing scheme to the typhoon track simulation. A B C D E Impact Study (Wu et al. 2006b) Impact from Wind vs. mass

Future prospects Data – no data can stand alone Models – dynamics and physics Data assimilation and targeted observation Collaborating with CWB, NSC, and Typhoon and Flood Research Center, … International joint program – THORPEX/PARC, HRD, NRL, ONR… Typhoon reconnaissance

THORPEX-PARC Experiments and Collaborating Efforts (from Dave Parsons) 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