TC Ocean Field Experiments and New Research Findings: Examples from CBLAST, TPARC/ TCS 08, ITOP

Transcription

1 Topic 1 1 TC Structure and Intensity Change Special Focus Topic 1b: Ocean Field Experiments and New Research Findings TC Ocean Field Experiments and New Research Findings: Examples from CBLAST, TPARC/ TCS 08, ITOP Peter Black 1, Jeff Hawkins 1, Eric D Asaro D 2 1 Naval Research Lab, Marine Meteorology Div. and SAIC, Inc., Monterey, CA USA 2 University of Washington, Seattle, WA USA Contributors: Jun Zhang, NOAA/HRD; Yi Jin, NRL; Michael Bell, NPS/Dept of Meteorology; C.C. Wu, NTU; I I I I Lin NTU International Workshop on Tropical Cyclones VII La Reunion, France November, 2010

2 Field Program Operations Program Flights Hours High Mid Low Deploy TCs CBLAST TCS ITOP CBLAST: Includes G IV G flights TCS 08: Includes DOTSTAR ITOP: Includes DOTSTAR, AXBTs: digital BT data sent near real time from WC 130J

3 Field Program Airborne Deployed Obs Program GPS Sondes AXBT AXCTD AXCP Profiler Drifters Float SFMR Radar CBLAST X P 3 TCS X Eldora C 130 ITOP X C 130 Unique: Measurements: CBLAST: SRA, BAT, Whitecap Photography TCS 08: Eldora, Lidar boundary layer winds ITOP: AXCTD, AXCP

4 Key CBLAST Results Extension/confirmation of Powell03 and Donelan04 high wind drag coefficients Validation byvickery09. Development of high wind enthalpy exchange coefficient Validation by Haus10 Boundary layer flux extends to twice mixed layer depth New model for TC boundary layer flow Observe relation between local sea and swell directional wave spectra Establish existence of boundary layer roll vortices in TC New insight into ocean interaction/cold wake formation

5 CBLAST Momentum and Moisture Flux Measurement, : BAT and LICOR probes on NOAA WP 3D BAT Probe LICOR Intake Port

6 EC Data from 8 field experiments : AGILE, AWE, ETCH,GASEX,HEXOS,RASEX, SHOWEX, SWADE, WAVES (4322 pts). Smith (1980) Pre O AGILE (Donelan & Drennan 1995) X HEXOS (DeCosmo et al 1996) GASEX (McGillis et al 2004) SOWEX (Banner et al 1999) SWADE (Katsaros et al 1993) COARE 3 COARE 2.5 Pre

7 Location of flux runs in Hurricanes Fabian and Isabel Satellite/radar composites

8 2010 Cd remains constant, or decreases slightly with wind speed at values near those from CBLAST

9 Composite wind profiles from CBLAST Isabel (3 days) dropsonde/radar observations Weakens during passage over prior storm wake Top of inflow layer Tangential Courtesy: Bell

10 Directional Wave Spectra Scanning Radar Altimeter The center of the figure shows wind speed contours (m/s) from the HRD HWIND surface wind analysis based mainly on SFMR surface wind speed measurements in Hurricane Ivan at 2230 UTC on 14 September 2004 for a 2 box in latitude and longitude centered on the eye. Arrow at the center indicates Ivan s direction of motion (330 シ ). The storm relative locations of twelve 2D surface wave spectra measured by the SRA are indicated by the black dots. The spectra have nine solid contours linearly spaced between the 10% and 90% levels relative to the peak spectral density. The dashed contour is at the 5% level. The outer solid circle indicates a 200 m wavelength and the inner circle indicates a 300 m wavelength. The dashed circles indicate wavelengths of 150, 250, and 350 m (outer to inner). The thick line at the center of each spectrum points in the downwind direction, with its length proportional to the surface speed. The upper number at the center of each spectrum is the significant wave height and the lower number is the distance from the center of the eye. The average radial distance for the twelve spectral locations is 80 km. Courtesy: Walsh

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12 RADARSAT SAR image (top) from right front quadrant of Hurricane Floyd, similar to that obtained for Hurricane Isidore, Spectrum of wavelengths from ENVISAT image of Hurricane Isidore, 2002 (bottom left). Red arrow indicates peak in aircraft derived spectrum in Isidore (bottom right). Spectrum of vertical momentum flux along a 120 m altitude radial flight leg into Hurricane Isidore, 2002.

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14 THORPEX Pacific Asian Regional Campaign/Tropical Cyclone Structure 08 (TCS 08) Experiments and Collaborative Efforts Upgraded Russian Radiosonde Network for IPY O AA) U. S. (N Winter d 4 4 an G A A NO 1 130s C e c r o F AirEU, U.S.(NSF/ONR), U.S.(NSF/ONR), EU, Japan, Japan, Korea, Korea, [DLR [DLR Falcon, Falcon, NRL NRL P 3 P 3 WC 130] WC 130] WMO WCRP/WWRP Asian/Indian Typhoon Monsoon U.S. ONR/NSF SoWMEX TCS 08 [NRL P 3, WC 130] Landfall Japan Palau

15 TCS 08 Airborne Deployed Probes GPS Drops AXBTs Drifters, profilers

16 TCS08 Ocean Heat Ocean Heat Content Concurrent with GPS dropsondes Preview of ITOP2010 AXBT vs NRL Ocean Model Initial Conditions Ocean Heat Content (OHC) TCS08 AXBT Locations Ko, NRL Stennis Model underpredicts high heat content

17 Typhoon Jangmi Ocean Thermal Structure Sinlaku Hagupit Jangmi SST Before 25 Aug 50 m Hagupit D m Jangmi OHC 27 Aug Cold Eddy Warm Eddy

18 Typhoon Jangmi Aircraft Buoy Deployment 1st deployment of drifting buoys ahead of a Cat 5 typhoon (Jangmi). Chart at left and imagery below are from a few hours after the deployment of the buoys along the diagonal to the northwest of the TC 2313 UTC 26 September First buoy deployment In TY Hagupit several days earlier Second deployment in STY Jangmi P 3 flight track Buoy, aircraft, and satellite data in Google Earth

19 Typhoon Jangmi Intensity Timeline Environmental Factors JTWC BT blue dotted line CIMSS SATCON, AMSU black solid Aircraft open diamond Eddy Boundary Landfall Eddy Boundary Landfall Sept, Sept, 2008

20 Monitoring warm and cold eddies over weeks Data Gap NRL (Ko) Model Ocean Heat Content Cold Eddy Data Gap Warm Eddy AXBT s act to fill data gaps in drifter coverage and define instantaneous spatial gradients Aircraft, satellite and land based radar observed Rapid Intensification (RI), Rapid Structure Change (SC) and Rapid Decay (RD) as Jangmi crossed eddy pair.

21 Super Typhoon Jangmi Structure Changes DRY Slot expands downstream from band & SSTA SSTA 27 Sept, 2132 Inner Bands Decay: Outer Band Forms 28 Sept, Sept, 1134 Eyewall shrinks, asymmetric band structure forms Result: Ocean eddy pair interacts with storm dynamics to produce immediate rapid decay and structure change prior to landfall. Concentric Eyewalls: Peak Intensity 27 Sept, 0445

22 Jangmi intensity Nowcasts/Forecasts 1000 Min Sea Level Pressure (hpa) Surface Max Winds (m s 1 ) Eddy Landfall Eddy Landfall F o r e c a s t h o u r JM A JT WC Coupl ed Uncoupl ed (a) F o r e c a s t h o u r JM A JT WC Coupled Un coupled (b) JM A JT WC Coupled Un coupled Questionable initial intensities from JTWC/JMA even though WC 130J vortex messages denote higher Vmax values in near real time Coupled COAMPS continued RI until cold eddy passage and began weakening following passage. Uncoupled COAMPS began weakening only after landfall. Courtesy: Li Jin

23 Typhoon Jangmi Obs and Modeling Brightness Temp. Uncoupled Coupled Dry Slot 0000 UTC 28 Sept. 72 h forecast valid for 0000 UTC 28 Sept. The coupled run captured to some extent the dry slot over the cold eddy before landfall. The cold ocean eddy reduced the latent heat flux substantially (~30%) in the dry slot region in the coupled run compared to the uncoupled run. Courtesy: Li Jin

24 Coupled/uncoupled COAMPS TC 1. COAMPS TC coupled model more accurately simulates rapid intensification/decay cycle over ocean eddy pair than uncoupled version. 2. Development of outer band and dry slot may hasten decay, an effect that is weakly simulated. 3. Unanswered question: What dynamic factors trigger development of outer band and how to simulate? Aerosols?

25 Impact of Typhoons on the Ocean in the Pacific 1) How does the cold wake of a typhoon form and dissipate? Field Program Objectives 2) What are the air sea fluxes for winds greater than 30 m/s? 3) How do ocean eddies affect typhoons and the response to typhoons? 4) What is the surface wave field under typhoons? 5) How is typhoon genesis related to environmental factors?

26 ITOP Field Program Schematic Courtesy: D Asaro D

27 Ridges generate internal tide Geometry makes a focus point Internal Tide in the Philippine Sea Noise in AXBT data Interesting physics 9 hr AXBT repeat pattern 100m vertical displacements With 12 hr period Temp Diff from Mean Courtesy D Asaro D

28 Typhoon Fanapi and Malakas Ocean Probes

29 ITOP DOTSTAR/C130 joint obs: : Fanapi (2010) 0000 UTC, Sept. 16th 0000 UTC, Sept. 17th 0000 UTC, Sept. 18th

30 Typhoon Fanapi 3 D 3 D Atm/Ocean Monitoring Courtesy: D Asaro D

31 Fanapi: Sonde/ AXBT grid OHC26 13 Sept, 2010 EASNFS Ko OHC26 14 Sept, 2010 EASNFS Ko NRL Ko

32 AMSR E Fanapi Cold Wake Monitoring NTU Lin 1 day later NRL

33 Typhoon Fanapi Cold Wake Evolution D C B A X E A B C D E. Storm induced mixing and upwelling create a cold wake (A,B) Solar radiation stratifies the upper ocean (C), leaving subsurface wake (D) Wake is advected and strained by mesoscale eddies (C,D,E upper right) Weak SST signature despite strong subsurface signal Courtesy: D Asaro D

34 Typhoon Fanapi Cold Wake Evolution: R/V Revelle Cross Sections Intense cold surface wake: 2 C Solar radiation quickly capped cold wake, monitoring via satellite SSTs difficult In situ observations revealed cold wake persisted for several weeks Courtesy: Courtesy: D Asaro D D Asaro D

35 Argo profiles showing ocean pre condition for the 3 typhoons in 2010, Fanapi (Cat. 3), Malakas (Cat. 2), and STY Megi (Cat.5), Ocean pre condition and its role in limiting the peak intensity for the 3 cases in 2010 (ITOP results) the tracks of the 3 cases are plotted over the depth of 26 degree C isotherm map d Fanapi Megi Malakas

36 SAR Digital Data Cosmo/ Skymed3 36 km 31 km Courtesy: Graber

37 3 D Ocean Thermal Structure & WPAC TCs Oceanic eddies (warm/cold) interact with many typhoons and require real time monitoring to forecast intensity trends well. Both IR and microwave SST products need to be used in conjunction with satellite altimeter and ocean model data sets to t provide ocean front and eddy locations and map OHC signal. SST wake signal can be rapidly modified while subsurface thermal structure persists for weeks, potentially impacting subsequent TCs. Storm track through 3 D 3 D thermal structure plays key role in TC intensity changes.

38 Summation We are at an historic potential turning point in history for improving hurricane intensity observation and forecasting where the capability to observe the TC surface and mid level wind domain concurrent with subsurface ocean thermal structure matches the improved coupled model capabilities to assimilate and model the total TC environment. This alignment could provide the next best opportunity for improving hurricane intensity and structure forecasting.

39 Peter wishes he was here!