Overview of the Dvorak Technique Visible and Infrared Technique Simplified Visible Technique given here (See Technical Report for full details) Uses patterns.

Slides:



Advertisements
Similar presentations
Operational Use of the Dvorak Technique at the NHC
Advertisements

Tropical Storms and Hurricanes
RAMMT/CIRA Tropical Cyclone Overview THE DVORAK TECHNIQUE Introduction Visible Technique IR Technique Strengths and Weaknesses Lab Exercise: Visible Pattern.
NAVY HYDROGRAPHIC CENTRE CHM CATARINA: A CASE STUDY ON THE SYSTEM FORMED IN THE SOUTH ATLANTIC.
HURRICANE GORDON and the NWP models near the Iberian Peninsula.
Where Do the Hurricanes Come From?. Radiation Vapor/Cloud/precipitation Shallow convection Boundary layer turbulence Mesoscale convective system Thunderstorm.
Part 4. Disturbances Chapter 12 Tropical Storms and Hurricanes.
Hurricanes. Tropical Weather Tropics: the belt between the Tropic of Cancer (23.5N) and the Tropic of Capricorn (23.5S) The weather is very different.
Forecasting Polar Lows Gunnar Noer The Norwegian Meteorological Institute in Tromsø.
TRMM Tropical Rainfall Measurement (Mission). Why TRMM? n Tropical Rainfall Measuring Mission (TRMM) is a joint US-Japan study initiated in 1997 to study.
TropicalM. D. Eastin Tropical Cyclone Climatology Where do TCs occur? When? Why? How Many?
Cloud Patterns in Subtropical Cyclones / Hybrid Systems Cloud Patterns in Subtropical Cyclones / Hybrid Systems AFWA/XOGM.
CORP Symposium Fort Collins, CO August 16, 2006 Session 3: NPOESS AND GOES-R Applications Tropical Cyclone Applications Ray Zehr, NESDIS / RAMM.
Lecture 14 Tropical disturbances, tropical depressions, tropical cyclones Other tropical systems, remember the ITCZ.
Typhoons and tropical cyclones
Lectures on Hurricanes Chanh Q. Kieu Department of Atmospheric and Oceanic Science University of Maryland AOSC400, Fall 2008.
Hurricanes. And finally… JOURNAL COLLECTION How they develop What they’re like Where to find them Andrew or Isabel Important test and other information.
Lecture 21: Hurricanes Typhoons (Western Pacific) Tropical Cyclones (anywhere) Cyclones (Indian Ocean + others) Hurricanes (near N. America) 4/22/03.
Andrew Burton Bureau of Meteorology, Perth, Australia Use of Scatterometer Winds in TC Forecasting Tropical Cyclone Warning Centre Perth.
USE OF HS3 DATA TO UNDERSTAND THE TROPICAL CYCLONE OUTFLOW LAYER John Molinari, Kristen Corbosiero, Stephanie Stevenson, and Patrick Duran University at.
Exercise – Constructing a best track from multiple data sources NATIONAL HURRICANE CENTER JACK BEVEN WHERE AMERICA’S CLIMATE AND WEATHER SERVICES BEGIN.
UNDERSTANDING TYPHOONS
Analysis of High Resolution Infrared Images of Hurricanes from Polar Satellites as a Proxy for GOES-R INTRODUCTION GOES-R will include the Advanced Baseline.
Depression 2/M John R. Jaromahum. Depressions  or 'lows' play an important part in the weather  tending to bring rain and strong winds. Depressions.
WIND.
Where Do the Hurricanes Come From?. Introduction A tropical cyclone is a rapidly- rotating storm system characterized by a low-pressure center, strong.
ATMS 373C.C. Hennon, UNC Asheville Observing the Tropics.
Application of the Computer Vision Hough Transform for Automated Tropical Cyclone Center-Fixing from Satellite Data Mark DeMaria, NOAA/NCEP/NHC Robert.
.  A tsunami is a wave or series of waves generated at sea by the abrupt movement of a mass of seawater. This is usually caused by the sea floor moving.
Tropical Meteorology I Weather Center Event #4 Tropical Meteorology What is Tropical Meteorology? – The study of cyclones that occur in the tropics.
STATISTICAL ANALYSIS OF ORGANIZED CLOUD CLUSTERS ON WESTERN NORTH PACIFIC AND THEIR WARM CORE STRUCTURE KOTARO BESSHO* 1 Tetsuo Nakazawa 1 Shuji Nishimura.
Chapter 11 Notes Hurricanes. Tropical Storms Boris and Christiana Together-2008 Profile of a Hurrican Most hurricanes form between the latitudes of 5.
NOAA’s Seasonal Hurricane Forecasts: Climate factors influencing the 2006 season and a look ahead for Eric Blake / Richard Pasch / Chris Landsea(NHC)
Chapter 11: Hurricanes Tropical weather Anatomy of a hurricane
Chapter 11 Hurricanes. Hurricane Katrina Flooded 80% of New Orleans The US’s deadliest hurricane in terms of deaths happened in 1900 in Galveston, Tx.
Benjamin A. Schenkel University at Albany, State University of New York, and Robert E. Hart, The Florida State University 6th Northeast.
Lecture 7 (10/21) Hurricanes and Tropical Meteorology.
Hurricane Intensity Estimation from GOES-R Hyperspectral Environmental Suite Eye Sounding Fourth GOES-R Users’ Conference Mark DeMaria NESDIS/ORA-STAR,
Applications of Satellite Derived
Hurricanes.
PREDICTABILITY OF WESTERN NORTH PACIFIC TROPICAL CYCLONE EVENTS ON INTRASEASONAL TIMESCALES WITH THE ECMWF MONTHLY FORECAST MODEL Russell L. Elsberry and.
05/06/2016 Juma Al-Maskari, 1 Tropical Cyclones.
 Hurricanes are cyclones that develop over the warm tropical oceans and have sustained winds in excess of 64 knots (74 miles/hour)  These storms are.
Hurricanes One of Natures most powerful and destructive storms.
1 Satellite Applications in Tropical Weather Forecasting Mark DeMaria Regional and Mesoscale Meteorology Team NESDIS/CIRA Colorado State University, Ft.
Can Dvorak Intensity Estimates be Calibrated? John A. Knaff NOAA/NESDIS Fort Collins, CO.
Training Session: Satellite Applications on Tropical Cyclones: Dvorak Technique NOAA/NESDIS STAR/CORP/RAMM CIRA / Fort Collins, CO.
Earth Science: Unit 1 (mini-unit) Hurricanes and Global Winds.
“It's tough to make predictions, especially about the future” HO fail all WEVER… HO fail all WEVER… “You can see a lot by looking” Yogi Berra High Pressure.
2015 HS3 Science Team Meeting Ames Research Center, Moffett Field, CA.
Doppler Lidar Winds & Tropical Cyclones Frank D. Marks AOML/Hurricane Research Division 7 February 2007.
The Controversy Regarding HS3 Surface Pressure Observations During The Rapid Intensification of Edouard on September Scott Braun NASA/GSFC.
Convective Oscillations in a Strongly Sheared Tropical Storm Jaclyn Frank and John Molinari The University at Albany, SUNY.
Tropical Cyclone Outflow Patterns and Intensity Change Kevin Mallen Joint Typhoon Warning Center.
Satellite Derived Ocean Surface Vector Winds Joe Sienkiewicz, NOAA/NWS Ocean Prediction Center Zorana Jelenak, UCAR/NOAA NESDIS.
Atmospheric Disturbances
Chapter 12 Tropical Storms and Hurricanes
Training Session: Satellite Applications on Tropical Cyclones
Accounting for Variations in TC Size
Oliver Elison Timm ATM 306 Fall 2016
By: Mike Vuotto and Jake Mulholland
More on tropical cyclones
Tropical Weather By Rick Garuckas and Andrew Calvi
Training Session: Satellite Applications on Tropical Cyclones
Earth’s Atmosphere.
Cloud Patterns in Subtropical Cyclones / Hybrid Systems
Tropical Cyclones EAS December 2018.
Following information taken from:
Hurricanes This chapter discusses:
Hurricanes.
Presentation transcript:

Overview of the Dvorak Technique Visible and Infrared Technique Simplified Visible Technique given here (See Technical Report for full details) Uses patterns and measurements as seen on satellite imagery to assign a number (T number) representative of the cyclone’s strength. The T number scale runs from 0 to 8 in increments of 0.5.

Overview of the Dvorak Technique Cont’d In the following examples, only the Data T Number (DT) will be calculated, the final (official) T number assigned to a tropical cyclone includes further considerations. DT computations familiarize one to various tropical cyclone patterns.

Four Basic Patterns Curved Band Pattern Shear Pattern Central Dense Overcast (CDO) Pattern Eye Pattern

Patterns and associated T Numbers

Empirical relationship between T number and wind speed

Finding the Cloud System Center (CSC) First step in the Dvorak technique From Dvorak (1985): “The cloud system center is defined as the focal point of all the curved lines or bands of the cloud system. It can also be thought of as the point toward which the curved lines merge or spiral.” Several situations

Curved Band Pattern

DT number determined by curvature of band around 10  log spiral

Curved Band Pattern Cont’d 1.0 to DT Number

Example: Tropical Storm Ivan 1115 UTC 23 September 1998

Example: Curved Band

Curved Band Pattern Tropical Storm Ivan curves 0.7 around log 10 spiral. This corresponds to DT=3

Shear Pattern

Shear Pattern DT Numbers 1° latitude = 60 nautical miles (nmi) = 111 km

Central Dense Overcast (CDO)

CDO No eye DT number determined by CF+BF=DT –CF=CENTRAL FEATURE –BF=BANDING FEATURE –DT=DATA T NUMBER

Example: Hurricane Georges 1545 UTC 21 September 1998

Example: CDO Central Feature (CF) Measure Diameter of CDO in degrees latitude For a well defined CDO –3/4 °CF=2 –1 1/4 °CF=3 –1 3/4 °CF=4 –>2 1/4 °CF=5 For an irregular CDO –1° to 1 1/2 °CF=2 –>1 1/2 °CF=3

Eye Pattern

DT number determined by CF+BF=DT –CF=CENTRAL FEATURE –BF=BANDING FEATURE –DT=DATA T NUMBER

Example: Hurricane Georges 1945 UTC 18 September 1998

Example: Eye - Central Feature (CF) CF=E-number+Eye Adjustment E-number a measure of the hurricane’s radius in degrees latitude –1/4°E-no.=3 –1/2° E-no.=4 –3/4°E-no.=5 –1°E-no.=6 –>1°E-no.=7

Eye Number

Eye - Central Feature Cont’d Eye adjustment 1. Poorly defined or ragged eyes: Subtract 0.5 for E-no.  4.5 and 1 for E-no.  Large eyes: Limit T-no. to T6 for round, well defined eyes, and to T5 for large ragged eyes. 3. For MET  6, 0.5 or 1 may be added to DT for well defined eye in smooth CDO when DT < MET.

Eye Adjustment

Example: Eye - Banding Feature (BF) ( Same as with CDO)

Banding Feature (BF)

Data T Number CF + BF = DT CF = = 5 BF = 0.5 DT = 5.5

Infrared (IR) Technique Can be used during night as well as during day At times more objective than visible technique

Example Digital IR: Hurricane Erika 1515 UTC 8 September 1997 Warmest eye pixel 16 °C Warmest pixel 30 nmi (55 km) from center - 71 °C Nomogram gives Eye no. =7

Summary The Dvorak technique uses patterns and measurements from satellite imagery to estimate the strength of a tropical cyclone. Four basic types –Curved band pattern –Shear pattern –CDO pattern –Eye pattern

ODT-Objective Dvorak Technique Original version – Dvorak (1984) – “analysis using digital IR data” Velden, Olander, Zehr (1998) – ODT Computation used for hurricane intensities remains essentially unchanged What is it? – Two IR temperature measurements, given a center location

Two IR temperature measurements 1) Surrounding temperature – Warmest pixel from those located on r=55 km circle 2) Eye temperature – Warmest pixel within the eye Table assigns intensity to nearest 0.1 T- No. Intensity increases as Surrounding T gets colder and as the Eye T gets warmer.

Isidore’02 vs Lili’02 Lowest MSLP –Isidore’02934 hPa –Lili’ hPa Maximum Surface Wind Speed –Lili’02125 kt –Isidore’ kt

Tropical Cyclone Pressure Wind Relationship Pressure : Wind = MSLP : Vmax –MSLP = minimum sea-level pressure –Vmax = maximum surface wind (10-m, 1-min wind)

P-Wind-Deviation (MSLP Vmax) Definition: Difference between observed MSLP and observed maximum wind speed converted to MSLP with a Pressure-Wind Relationship…. P-Wind Dev. = MSLP min – MSLP Dvorak, f (Vmax max )

95-F 95-O 98-G 01-E 01-M 02-I 02-L 95-M 96-F 99-B 99-L 01-I

Lili’02 Isidore’02

Lili’02 Isidore’02 Erin’01 Opal

Lili’02 Isidore’02

Isidore Lili

Tropical Cyclone Surface Wind Analysis -- based entirely on satellite data (along with center location and storm motion) --with sufficient resolution to depict intensity (maximum wind and its location) -- with sufficient coverage to depict size (area with winds exceeding gale force). -- frequent time intervals

Independent Surface Wind Analyses from Four Components IR-Inner core, time continuity, rapid changes AMSU-Inner and outer winds Scatterometer -Outer winds, weak TCs Satellite Winds -Outer winds, weak TCs

“Satellite only” Tropical Cyclone Surface Wind Analysis COMBINATION OF FOUR ANALYSES IR-Inner core, time continuity, rapid changes AMSU-Inner and outer winds Scatterometer -Outer winds, weak TCs Satellite Winds -Outer winds, weak TCs –Global coverage –Time continuity –Consistent analysis

Validation and developmental data sets Aircraft winds Dropsonde winds Conventional obs (surface, ship, buoy) HRD Wind Analyses Numerical Model Analyses

CONCLUSION: In order for a Combined Satellite Tropical Cyclone Surface Wind Analysis to be successful and reliable – i.e… capture the rapid changes and have consistency among analyses. …. it MUST incorporate the Objective Dvorak Technique (ODT)

32 Intense Hurricanes (Cat 3+) in Atlantic during 10-years, Characteristics at time of max. intensity R-34 kt, n. mi. (azimuthal average): –Ave. 142Max. 231Min. 69 R-50 kt, n. mi. (azimuthal average): –Ave. 82Max. 150Min. 23 RMW (Radius of Maximum Wind Speed), n. mi.: –Ave. 20 Max. 30Min. 5 MSLP (Minimum Sea-level Pressure), hPa: –Ave. 941Min. 905 Max. 968

Size differences – Atlantic Intense Hurricanes Cindy, ’99 – Average R-34 kt : 231 n.mi. – R-50 kt : 144 n.mi. – Intensity:120 kt, 942 hPa Iris, ’01 – Average R-34 kt: 69 n.mi. R-50 kt: 23 n.mi. -- Intensity:125 kt, 948 hPa

Hurricane CINDY – 0715 UTC 28 Aug 99

Hurricane IRIS – 0015 UTC 9 Oct 01

IR Cloud Area vs TC Size Hurricane Bret and Hurricane Floyd, at 125-kt intensity Bret’s Average R-34 kt is 68 n. mi. Floyd’s Average R-34 kt is 183 n. mi.

20 Atlantic Intense Hurricanes ’95-’99 LOWEST MINIMUM SEA-LEVEL PRESSURE 1. Mitch 905 hPa 2. Opal Floyd Felix Gert Edouard Lenny Luis Hortense Georges Cindy Bret Fran Erik Marilyn Bonnie Roxanne Bertha Lili Isidore960 MAXIMUM SURFACE WIND SPEED 1. Mitch 155 knots 2. Floyd Lenny Georges Opal Gert Edouard Bret Felix Luis Hortense Cindy Erika Fran Marilyn Bonnie Roxanne Bertha Lili Isidore100

Intensification Rate -- from “Best Track” data, greatest MSLP decrease in 24 hr (- hPa / day) 1. Mitch54 2. Opal49 3. Edouard47 4. Felix Floyd38 6. Bret35 7. Luis34 8. Lenny34 9. Hortense Georges31 – from Aircraft Center Fix MSLP, greatest decrease in 12 hr (- hPa / day) – limited to Cat 4 or greater hurricanes with aircraft observations 1. Opal80 2. Mitch54 3. Felix50 4. Floyd44 5. Hortense44 6. Lenny42 7. Bret42 NOTE: The following Cat 4’s did not have aircraft observations during initial intensification: Edouard, Luis, Georges, Cindy, Gert

Onset of Rapid Intensification Onset = Beginning of maximum intensification rate period Average Intensity at Onset (8 Atlantic cases) = 87 kt, 970 hPa What are IR image characteristics at Onset vs –Non – Intensifying Cat 2 at kt –Pre – Cat 3 at kt ?

IR Image Characteristics associated with Onset of Rapid Intensification Unusually cold IR temp.’s near the center Symmetric cloud patterns Outflow cirrus spreading all directions Trend of cold IR cloud becoming more concentrated toward the center Ragged eye becomes well-defined

Rapid vs Non-Rapid “Rapid” cases prior to onset have at least two and usually 5 of the characteristics “Non-Rapid” typically have one or less of the characteristics How can this be quantified and developed into an objective technique?

IR cloud asymmetries Measurements of IR temperature defined area centroid locations and their distance and bearing from surface center Related to : –Environmental vertical wind shear profile –TC motion –TC intensity and structure

OBTAINING WIND SPEED AND DIRECTION FROM THE OCEAN SURFACE USE SCATTEROMETRY (Theory) The scatterometer sensor is an active microwave imager that sends and receives microwave energy off the ocean surface Microwave energy is sensitive to the “roughness” of the ocean surface that is generated by the surface wind field. This roughness is manifested in small capillary size waves (or ripples) known as Brag Waves Due to the assymetric nature of these Brag Waves in relationship to the wind speed and direction, it is possible to derive a wind field from an inversion technique by viewing the same area of ocean from several angles

SCATTEROMER DAILY COVERAGE ERS-2 QUIKSCAT (ASCN) QUIKSCAT (DSCN)

BACKGROUND MICROWAVE RADIATION OVER THE OCEAN (Incident Angle Dependence) Fore and Aft look by the H-pol and V-pol sensor allow for up to 4 solutions No H-pol solution w/i 7 wind vector cells of edge Along subtrack, only get 180 deg opposite solutions EFFECTS ON POLARIZATION QuikSCAT (13.4 GHz) 52 o 46 o (13.4 GHz)

WIND RETRIEVAL and AMBIGUITY SOLUTIONS ERS-2 uses CMOD4 wind retrieval method to estimate wind speeds from Normalized Radar Cross-Section (Sigma-0) of backscatter microwave radiation over the oceans –3 Antenna at 3 different angles (can not see at nadir) –ECMWF used as initialization in ambiguity (direction) process QuikSCAT uses NSCAT2 (QuikSCAT1) wind retrieval method –Circular Scan at 2 zenith angles (46 o H-pol and 52 o V-pol) –Fore and Aft views allow up to 4 solutions –Solutions are “Ranked” based on Most Likelihood Estimator (MLE) –AVN used as initialization in ambiguity (direction) process –A multi-process “Buddy System” using a medium filter evaluates neighboring Wind Vector Cells (WVC) to make the final “Selection” –Each WVC is assigned a Rain Flag based on a likelihood determination

Model Function: Directional Ambiguities Model Function: Directional Ambiguities From Dr. M. Freilich, Oregon State University

QUIKSCAT PROBLEM AREAS ( Usually in Low Skill Areas) Edge of Swath (~ 7 wvc) and Along Sub-Track(3-4 wvc) Sensitivity to Heavy Rain –Surface Roughness (Especially in Low Wind areas!) –Rain Scattering Sensitivity to Errors in NWP Model in Low Skill Locations “Practical” Wind Regime between 05 AND 45 m/s –Problems in both LIGHT winds and very HEAVY winds Resolution (25 km) of Footprint will Limit Wind Retrieval in Tight Gradient Regions Ambiguity Selection Process and How Rain Flags are Treated (no direct measurement of rain on QuikSCAT) can Affect the Final Solution –Watch out for Rain Blocks caused by ‘rain contagion’

EDGE PROBLEMS Along the whole edge… OR small portion… FNMOC DISPLAY

PROBLEMS WITH RAIN CONTAMINATION and AMBIGUITY SELECTION PROCESS

RAIN SELECTION: MUDH vs RSS Which one correct?---Answer is somewhere in- between... TC Ando (04S) RSS FNMOC-NOGAPS FNMOC-NRT SAME Coverage MUCH LESS Coverage

Typical Rain Patterns Rain effects: Cross swath vectors Higher wind speeds Some intense rain not flagged RSS slide

TYPES OF RAIN PATTERNS and AMBIGUITY SELECTION ISSUES AND HOW TO SOLVE

RAIN EFFECTS (Rain Blocks--Perpendicular to Swath) In a ‘rain block’, one or two winds solutions may be bad due to excessive scattering of the signal. The ‘default’ direction appears to be perpendicular to the swath direction. Problem exists because of the buddy system approach to neighboring wind vector cells causing a ‘rain contagion’ effect. Rain Block Region Bad directions. Do not use! Speed may be ok.

RAIN EFFECTS (Solution: A fix position is possible. Use the good winds, outside of the rain-block) TY Jelawat, 05Aug 0942Z, TS Chanchu, 28 Jul 0624Z (90kt)

AMBIGUITY SELECTION (With Rain effects--TS 28W) FNMOC-NOGAPS FNMOC-NRT Compare the models and look for non-flagged winds This version treats non-flagged data separately from the ‘rain block’

AMBIGUITY SELECTION (With Rain effects--TY Soulik 31W) FNMOC-NOGAPSFNMOC-NRT

WHERE’S IS TROPICAL CYCLONE 21S (HUDAH)? Located within the trough--no Circulation! ? MAX WIND 95 KTS Try to fix in trough equator-ward of the strongest winds

QUIKSCAT-- MODEL INITIALIZATION TC 24S (Paul), 20 April ? ? c c MAX WIND 55 KTS (Light winds?) -----Low Skill AVN 19/12Z tau 24 20/2356Z 10S 20S In this case, poor model initialization combined with a lower skill nadir position, picks proper wind speed, but NO circulation center

SEA SURFACE TEMPERATURE FROM AUGUST 2001 FROM AUGUST 2001

OCEANIC HEAT CONTENT CLIMATOLOGY FOR AUGUST CLIMATOLOGY FOR AUGUST

Microwave Images DMSP SSMI – 85H Ghz NOAA AMSU-B – 89 GhZ

MODIS (Moderate Resolution Imaging Spectroradiometer) NASA Aqua and Terra 38-channel Imager, with Truecolor 250-m resolution

MODIS (Moderate Resolution Imaging Spectroradiometer) -- NASA EOS Terra and Aqua 38-channel imager– Truecolor images at 250-m resolution

NOAA N43RF departed 11:15am AST (1515 UTC), Sept 12, 2003, for 8-hour Ocean Winds mission into Hurricane Isabel

Hurricane Isabel near horizon through cockpit windows about half way between St Croix and the eye

Hurricane ISABEL’s Eye – 12 Sep 03

INTRODUCTION Definition -- SUBTROPICAL CYCLONE manifestation of “cut-off low” at the surface –definition -- cut-off low -- cold low displaced equatorward of westerly flow –occur in cool season –also called subtropical lows (Kona storms) –located in N. Pacific (15N to 35N W to 175E) and N. Atlantic (15N to 35N -- 30W to 60W) –primarily during November to March

Vertical Profile of Temperature Tropical Cyclone -- warm core through the troposphere, except in the lowest 1-2 km –warm core is strongest in the upper troposphere (~250 hPa), and over a broad area but very warm within the eye Easterly Waves and Monsoon Trough -- warm core in the upper troposphere, but cold core at lower levels (below ~600 hPa)

Vertical Temperature Profiles Subtropical Cyclone -- strong cold core in the upper/middle troposphere (~ hPa) and weak cold core at lower levels –warm core above the strong cold core in the upper troposphere (~ hPa), with a double tropopause structure OR in the stratosphere, with a tropopause lowering

Vertical Temperature Profiles Tropical Upper Troposphere Trough -- TUTT -- is comprised of upper level cyclones (TUTT cells) -- same as subtropical cyclones, except that the temperature anomalies are much weaker –shallow cyclones, confined to upper levels –lower troposphere winds and pressures are typically not influenced by TUTT cells above

Tangential Wind Profiles Tropical Cyclone -- strong, deep --maximum cyclonic wind at low-levels (1-2 km) Easterly Waves and Monsoon Trough -- weak, deep -- maximum cyclonic wind at mid- levels (~ 600 hPa)

Tangential Wind Profiles Subtropical Cyclone -- strong, deep -- maximum cyclonic wind at upper levels (~250 hPa) Tropical Upper Troposphere Trough -- weak, shallow -- maximum cyclonic wind at upper levels (~250 hPa)

Transition from Subtropical A few Tropical Cyclones originate from subtropical cyclones A few Subtropical Cyclones maintain subtropical characteristics but intensify to produce Storm Force winds (> 34 kt) (Subtropical Storm) During transition, a “hybrid” tropical storm has characteristics of both types

Terminology Clarifications The term “hybrid” is used to refer to a tropical cyclone that has originated not solely from “latent heat release” with a typical pre-existing tropical disturbance. This may involve baroclinic processes, as with extratropical cyclones, subtropical lows, etc. Other terms have been used for “hybrid” cyclone-- –half breed cyclone –neutercane –semitropical cyclone –intermediate cyclone

Terminology Clarifications Other tropical weather systems have been identified which may at times resemble or evolve into a “hybrid” cyclone –Monsoon Depressions –West African Cyclones –Arabian Sea Cyclones –Tropical Cyclones in Extratropical Transition

Extratropical Transition Extratropical: A term used in advisories and tropical summaries to indicate that a cyclone has lost its "tropical" characteristics. The term implies both poleward displacement of the cyclone and the conversion of the cyclone's primary energy source from the release of latent heat of condensation to baroclinic (the temperature contrast between warm and cold air masses) processes. It is important to note that cyclones can become extratropical and still retain wind of hurricane or tropical storm force.

The Hebert-Poteat Subtropical Cyclone Technique NATIONAL HURRICANE CENTER JACK BEVEN WHERE AMERICA’S CLIMATE AND WEATHER SERVICES BEGIN

What is the Hebert-Poteat Technique? A pattern-matching method of estimating the intensity of subtropical cyclones A compliment to the Dvorak technique

Similarities Between Hebert- Poteat and Dvorak Both techniques use convective overcast Both techniques use the distance of the Cloud System Center (CSC) from the overcast ST cloud features are selected so that ST- Numbers correspond to T-Numbers if the cyclone becomes tropical Both techniques assume modeled development of the cyclone, with the T or ST numbers normally changing by  1.0 per day

Differences Between Hebert-Poteat and Dvorak HP considers environment in determining cyclone type HP permits a classification of ST1.5 or ST2.5 on the first day HP cannot have the CSC under a Central Dense Overcast (CDO) HP uses curvature of convective features for all ST classifications in the absence of bands HP Designates a wind speed range for each ST category Translational speed excess above 20 kt added to the ST cloud feature wind estimate HP uses one rule regarding intensity changes

Hebert-Poteat Output

Hebert-Poteat Criteria ST 1.5 Low-level circulation center located 1/2 o to 2 o of latitude from the edge of poorly organized convection (not necessarily dense) For cold lows, connection may not be connected to other systems, and a small area (<3 o latitude) of deep layer convection exists near the center

Hebert-Poteat Criteria ST 2.5 Low-level circulation center located 1/2 o to 2 o from increased deep-layer convection (not necessarily dense) with greater curvature of broad cloud lines or bands than on the previous day Outer convective band 5 o -10 o east of the center, and possibly another convective band 2 o -4 o west-north of the center

Hebert-Poteat Criteria ST 3.0 Same criteria as for ST 2.5 except greater curvature of cloud lines or bands, and better organized convection Evidence of banding within 1 o of the circulation center

Hebert-Poteat Criteria ST 3.5 Deep-layer convection (frequently dense overcast) in band(s) 1 o -3 o from the center (no CDO) Outer convective band 5 o -10 o to the east weaker than for ST 3.0, but new band may form 5 o -10 o west of the center For systems moving rapidly eastward, there may be only a dense overcast (  3 o latitude) about 2 o -4 o east of the center

Hebert-Poteat Patterns