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

TCS TCS­ ­08, ITOP 08, ITOP

International Workshop on Tropical Cyclones VII International Workshop on Tropical Cyclones VII La Reunion, France La Reunion, France 15 15­ ­20 November, 2010 20 November, 2010

Topic 1 Topic 1­ ­ TC Structure and Intensity Change TC Structure and Intensity Change

Special Focus Topic 1b: Special Focus Topic 1b: Ocean Field Experiments and New Research Findings Ocean Field Experiments and New Research Findings

Peter Black Peter Black 1 1 , Jeff Hawkins , Jeff Hawkins 1 1 , Eric D , Eric D’ ’Asaro Asaro 2 1 Naval Research Lab, Marine Meteorology Div. and SAIC, Inc., Mont Naval Research Lab, Marine Meteorology Div. and SAIC, Inc., Monterey, CA USA erey, CA USA

2 University of Washington, Seattle, WA USA University of Washington, Seattle, WA USA

Contributors: Jun Zhang, NOAA/HRD; Yi Jin, NRL; Michael Bell, Contributors: Jun Zhang, NOAA/HRD; Yi Jin, NRL; Michael Bell, NPS/Dept of Meteorology; C.C. Wu, NTU; I NPS/Dept of Meteorology; C.C. Wu, NTU; I­ ­I Lin NTU I Lin NTU

Field Program Operations Field Program Operations

7

2

3

Deploy

3

4

4

TCs

6

Low

11 11 298 34 ITOP

12 12 300 33 TCS­08

8 123 17 CBLAST

Mid High Hours Flights Program

CBLAST: Includes G CBLAST: Includes G­ ­IV flights IV flights

TCS TCS­ ­08: Includes DOTSTAR 08: Includes DOTSTAR

ITOP: Includes DOTSTAR, AXBTs: digital BT data sent near ITOP: Includes DOTSTAR, AXBTs: digital BT data sent near real real­ ­time time from WC from WC­ ­130J 130J

Field Program Field Program Airborne Deployed Obs Airborne Deployed Obs

C­130 X 24 65 43 822 828 ITOP

Eldora C­130

X 24 250 1074 TCS­08

P­3 X 20 54 6 330 CBLAST

Radar SFMR Float Profiler Drifters

AXCTD AXCP

AXBT GPS Sondes

Program

Unique: Measurements: Unique: Measurements:

CBLAST: SRA, BAT, Whitecap Photography CBLAST: SRA, BAT, Whitecap Photography

TCS TCS­ ­08: Eldora, Lidar boundary layer winds 08: Eldora, Lidar boundary layer winds

ITOP: AXCTD, AXCP ITOP: AXCTD, AXCP

Key CBLAST03 Key CBLAST03­ ­04 Results 04 Results

• Extension/confirmation of Powell03 and Donelan04 high wind drag coefficients­Validation 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

BAT Probe

LICOR Intake Port

CBLAST Momentum and Moisture Flux

Measurement, 2003­04: BAT and

LICOR probes on NOAA WP­3D

EC Data from 8 field experiments : AGILE, AWE, ETCH,GASEX,HEXOS,RASEX, SHOWEX, SWADE, WAVES (4322 pts).

— Smith (1980)

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)

COARE­3 ­­­ COARE 2.5 —

Pre­2003

Pre­2003 2007

2007

Location of Location of “ “flux runs flux runs” ” in Hurricanes Fabian and Isabel in Hurricanes Fabian and Isabel

Satellite/radar composites Satellite/radar composites

2010

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

Composite wind profiles from CBLAST Isabel (3 Composite wind profiles from CBLAST Isabel (3­ ­days) dropsonde/radar observations days) dropsonde/radar observations

Tangential Tangential

Top of Top of inflow inflow layer layer

Weakens during passage over prior storm wake Weakens during passage over prior storm wake

Courtesy: Bell Courtesy: Bell

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 storm­relative 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.

Directional Wave Spectra Directional Wave Spectra ­ ­ Scanning Radar Altimeter Scanning Radar Altimeter

Courtesy: Walsh Courtesy: Walsh

Spectrum of vertical momentum flux along a 120 m altitude radial flight leg into Hurricane Isidore, 2002.

RADARSAT SAR image (top) from RADARSAT SAR image (top) from right right­ ­front quadrant of Hurricane front quadrant of Hurricane Floyd, similar to that obtained for Floyd, similar to that obtained for Hurricane Is Hurricane Isi idore, 2002. Spectr dore, 2002. Spectrum um of wavelengths from ENVISAT image of wavelengths from ENVISAT image of Hurricane Is of Hurricane Isi idore, 2002 (bottom dore, 2002 (bottom­ ­ left). Red arrow indicates peak in left). Red arrow indicates peak in aircraft aircraft­ ­derived spectrum in Isidore derived spectrum in Isidore (bottom (bottom­ ­right). right).

THORPEX Pacific Asian Regional Campaign/Tropical Cyclone Structure­08 (TCS­08)

Experiments and Collaborative Efforts

Upgraded Russian Upgraded Russian Radiosonde Network for IPY Radiosonde Network for IPY

U.S. (NOAA) U.S. (NOAA)

Winter Winter

NOAA G

NOAA G­ ­4 and 4 and

Air Force

Air Force C C­ ­130s 130s

Japan Japan Palau Palau

Typhoon Landfall

U.S.(NSF/ONR), EU, Japan, Korea,

[DLR Falcon, NRL P­3 WC­130]

U.S.(NSF/ONR), EU, Japan, Korea,

[DLR Falcon, NRL P­3 WC­130]

WMO WMO WCRP/WWRP WCRP/WWRP Asian/Indian Asian/Indian Monsoon Monsoon

U.S. U.S. ONR/NSF ONR/NSF TCS TCS­ ­08 08

[NRL P [NRL P­ ­3, WC 3, WC­ ­130] 130] SoWMEX

TCS TCS­ ­08 Airborne 08 Airborne Deployed Probes Deployed Probes

­ ­ GPS Drops GPS Drops

­ ­ AXBTs AXBTs

­ ­ Drifters, profilers Drifters, profilers

TCS08 AXBT Locations Ko, NRL Stennis

Ocean Heat Content • Concurrent with GPS dropsondes • Preview of ITOP2010

AXBT vs NRL Ocean Model Initial Conditions

Model underpredicts high heat content

Ocean Heat Content (OHC)

TCS08 Ocean Heat

Jangmi OHC 27 Aug

Cold Eddy

Warm Eddy

Jangmi SST Before 25 Aug Sinlaku

Hagupit

Hagupit 100

m

50 m

D26 100

m

50 m

Typhoon Jangmi Ocean Thermal Structure Typhoon Jangmi Ocean Thermal Structure

Typhoon Jangmi Aircraft Typhoon Jangmi Aircraft – – Buoy Deployment 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

P­3 flight track

2313 UTC 26 September

First buoy deployment In TY Hagupit several days earlier

Second deployment in STY Jangmi

Buoy, aircraft, and satellite data in Google Earth

Eddy Boundary

Landfall

24 25 26 27 28 29 30 Sept, 2008

JTWC BT­ blue dotted line CIMSS SATCON, AMSU­ black solid Aircraft­ open diamond

Eddy Boundary

Landfall

24 25 26 27 28 29 30 Sept, 2008

Typhoon Jangmi Intensity Timeline – Environmental Factors

Monitoring warm and cold eddies over weeks

Warm Eddy Cold

Eddy

Aircraft, satellite and land­based radar observed Rapid Intensification (RI), Rapid Structure Change (SC) and Rapid Decay (RD) as Jangmi crossed eddy pair.

Data Gap

Data Gap

AXBT’s act to fill data gaps in drifter coverage and define instantaneous spatial gradients

NRL (Ko) Model Ocean NRL (Ko) Model Ocean Heat Content Heat Content

Super Typhoon Jangmi Structure Changes

28 Sept, 0006

DRY Slot expands downstream DRY Slot expands downstream from band & SSTA from band & SSTA

SSTA SSTA 27 Sept, 2132

Inner Bands Decay: Inner Bands Decay: Outer Band Forms Outer Band Forms

27 Sept, 1134 Eyewall shrinks, Eyewall shrinks, asymmetric band asymmetric band structure forms structure forms

27 Sept, 0445

Concentric Eyewalls: Concentric Eyewalls: Peak Intensity Peak Intensity

Result: Ocean eddy pair interacts

with storm dynamics to produce immediate rapid decay and

structure change prior to landfall.

880

900

920

940

960

980

1000

0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96

Fo r e c a s t h o u r

JMA JTWC Coupl ed Uncoupl ed (a)

Jangmi intensity Jangmi intensity – – Nowcasts/Forecasts Nowcasts/Forecasts

2 0

3 0

4 0

5 0

6 0

7 0

8 0

0 6 12 18 2 4 3 0 3 6 4 2 4 8 5 4 6 0 6 6 7 2 7 8 8 4 9 0 9 6

Fo r e c a s t ho u r

JM A JTWC Coupled Un coupled (b)

­ Questionable initial intensities from JTWC/JMA even though WC­130J vortex messages denote higher Vmax values in near real­time ­­ Coupled COAMPS continued RI until cold eddy passage and began weakening following passage. Uncoupled COAMPS began weakening only after landfall.

JMA JTWC Coupled Un coupled

Min Sea Level Pressure (hPa) Surface Max Winds (m s ­1 )

25 26 27 28 29 25 26 27 28 29

Eddy

Landfall

Eddy

Landfall

Courtesy: Li Jin Courtesy: Li Jin

Typhoon Jangmi Obs and Modeling Typhoon Jangmi Obs and Modeling

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.

Uncoupled Coupled Dry Slot

72­h forecast valid for 0000 UTC 28 Sept.

Brightness Temp.

0000 UTC 28 Sept.

Courtesy: Courtesy: Li Jin Li Jin

1. COAMPS­TC 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?

Coupled/uncoupled COAMPS­TC

1) How does the cold wake of a typhoon form and dissipate?

2) What are the air­sea 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?

Impact of Typhoons on the Ocean in the Pacific

Field Program Objectives

ITOP Field Program Schematic

Courtesy: D Courtesy: D’ ’Asaro Asaro

Internal Tide in the Philippine Sea ‘Noise’ in AXBT data Interesting physics

Ridges generate internal tide Geometry makes a focus point

9 hr AXBT repeat pattern

100m vertical displacements With 12 hr period

Courtesy D Courtesy D’ ’Asaro Asaro

Tem

p Diff from

Mean

Tem

p Diff from

Mean

Typhoon Fanapi and Malakas Ocean Probes Typhoon Fanapi and Malakas Ocean Probes

ITOP DOTSTAR/C130 joint ITOP DOTSTAR/C130 joint obs obs: Fanapi (2010 : Fanapi (2010) )

0000 UTC, Sept. 18th

0000 UTC, Sept. 16th

0000 UTC, Sept. 17th

Typhoon Fanapi 3 Typhoon Fanapi 3­ ­D Atm/Ocean Monitoring D Atm/Ocean Monitoring

Courtesy: D Courtesy: D’ ’Asaro Asaro

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

OHC26 14 Sept, 2010 EASNFS­ Ko

NRL NRL­ ­ Ko Ko

NTU Lin

NRL

AMSR­E Fanapi Cold Wake Monitoring

1 day later 1 day later

B

C

A

D

E

Typhoon Fanapi Cold Wake Evolution

• 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

X

Courtesy: D Courtesy: D’ ’Asaro Asaro

A B C

D

.

E

Typhoon Fanapi Cold Wake Evolution: R/V Revelle Cross Sections

Intense cold surface wake: 2 C Intense cold surface wake: 2 C

Solar radiation quickly capped cold wake, monitoring via satelli Solar radiation quickly capped cold wake, monitoring via satellite SSTs difficult te SSTs difficult

In In­ ­situ observations revealed cold wake persisted for several weeks situ observations revealed cold wake persisted for several weeks

Courtesy: D Courtesy: D’ ’Asaro Asaro Courtesy: D Courtesy: D’ ’Asaro Asaro

d

Argo profiles showing ocean pre­condition for the 3

typhoons in 2010, Fanapi (Cat. 3),

Malakas (Cat. 2), and STY Megi (Cat.5),

Ocean pre­condition 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

Megi Malakas

Fanapi

Cosmo/ Skymed3

31 km 36 km

SAR Digital Data

Courtesy: Graber Courtesy: Graber

3­D Ocean Thermal Structure & WPAC TCs

Oceanic eddies (warm/cold) interact with many typhoons and Oceanic eddies (warm/cold) interact with many typhoons and require real require real­ ­time monitoring to forecast intensity trends well. time monitoring to forecast intensity trends well.

Both IR and microwave SST products need to be used in Both IR and microwave SST products need to be used in conjunction with satellite altimeter and ocean model data sets t conjunction with satellite altimeter and ocean model data sets to o provide ocean front and eddy locations and map OHC signal provide ocean front and eddy locations and map OHC signal. .

SST wake signal can be rapidly modified while subsurface SST wake signal can be rapidly modified while subsurface thermal structure persists for weeks, potentially impacting thermal structure persists for weeks, potentially impacting subsequent TCs. subsequent TCs.

Storm track through 3 Storm track through 3­ ­D thermal structure plays key role in TC D thermal structure plays key role in TC intensity changes. intensity changes.

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 mid­level 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.

Peter wishes he was here!