slide1
Download
Skip this Video
Download Presentation
Objective Dvorak Technique (ODT) AFWA/XOGM

Loading in 2 Seconds...

play fullscreen
1 / 44

Objective Dvorak Technique (ODT) AFWA/XOGM - PowerPoint PPT Presentation


  • 132 Views
  • Uploaded on

Objective Dvorak Technique (ODT) AFWA/XOGM. Material for this training module largely comes from:. UW-CIMSS Objective Dvorak Technique. Tim Olander and Chris Velden University of Wisconsin - Madison Cooperative Institute for Meteorological Satellite Studies In cooperation with :

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about ' Objective Dvorak Technique (ODT) AFWA/XOGM' - ranit


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
uw cimss objective dvorak technique

Material for this training module largely comes from:

UW-CIMSS Objective Dvorak Technique

Tim Olander and Chris Velden

University of Wisconsin - Madison

Cooperative Institute for Meteorological Satellite Studies

In cooperation with :

Jeff Hawkins

Naval Research Laboratory - Monterey, CA

Office of Naval Research

slide3

Objective Dvorak Technique (ODT)

Overview

- What is the ODT?- How does it work?- Why use it?- How will we use it here?

slide4

Objective Dvorak Technique (ODT)

What is the ODT?ODT is a computerized method for determining the intensity of tropical cyclones. It was originally developed by the University of Wisconsin, and we are able to perform some ODT functions currently.Ok, so how does it work?

odt methodology1
Identification of two environmental temperatures (BTs)

Uses IR data only

Eye Temperature (0-40 km)

Cloud Temperature (26-136 km)

Scene identification performed

ODT is only performed for four types of features:

Eye, Embedded Center, CDO, and Shear

SIDAS version only handles EYE currently

Based on histogram and Fourier Transform Analysis

ODT Methodology
odt methodology2
Determination of the cloud pattern is performed objectively (in other words, by the computer) by examining area histograms of cloud top temperatures and corresponding Fourier Analysis for the eye region and surrounding cloud region. Based on this analysis, four scene patterns can be categorized by ODT: Eye, Central Dense Overcast, Embedded Center, and Shear.ODT Methodology
odt methodology3
Storm Center Location

The only user input is the specification of the storm center location

ODT only does intensities

EYE determination

If the storm has an eye, it uses the warmest pixel temperature within a 40 km radius of the chosen storm center

Warm values represent ocean surface or low cloud within the eye

This value is retained as the \'eye temperature\'.

ODT Methodology
odt methodology5
EYE determination (con’t)

ODT analyzes temperatures on concentric rings (1 pixel wide) centered on the eye between 24 km and 136 km from the eye location (this range was empirically determined by many observations of coldest ring radii).

For GOES data with 4km pixel resolution, this results in a total of 28 rings that are analyzed to determine the \'surrounding temperature\'.

In addition, a continuous ring of cold temperatures surrounding the eye is more indicative of an organized (and more intense) storm than one with breaks in the convection.

Therefore, the warmest temperature found on each ring is identified and stored, with the coldest of these retained as the final surrounding temp value.

ODT does not reposition the storm center, since it has been found that the subsequent analysis of the surrounding temperature field may be improperly influenced by this adjustment in some cases (\'false\' eyes).

ODT Methodology
odt methodology8
ODT Methodology

The warmest temperature

is found on each ring...

odt methodology9
ODT Methodology

This ring has “Light Grey”

as its warmest temp.

odt methodology10
ODT Methodology

Of those temps that are

left, the coldest is taken

as the surrounding ring

odt methodology11
“No Eye” Condition

ODT can handle Central Dense Overcast (CDO)/Embedded Center

Temperatures near the storm center are dominated by cold cloud tops and a warm eye is not resolvable.

The value of the pixel at the user-defined storm center location is used as the \'eye’ temperature

Shear scenario is also detected in ODT

The SHEAR, CDO/EMBD CTR ARE NOT YET AVAILABLE IN SIDAS VERSION OF SOFTWARE

ODT Methodology
odt methodology12
Initial intensity estimate determined (Raw T#)

Based on original Dvorak Rules for different patterns and cloud top temperatures. Eye temperature serves as adjustment

Use history file with previous storm analysis data

(Final T#)

Provide data for 12-hour time weighted time averaging scheme

This means we have to perform ODT every hour

Data is saved in SIDAS interface

Implementation of Dvorak Rule 9 for weakening storms (CI#)

Corrects underestimate bias in weakening storms

Hold T# constant for 12 hours after initial weakening, add 1.0 T# until dissipation or restrengthening

Not currently implemented in SIDAS

ODT Methodology
odt purpose
ODT Purpose
  • Ok, but why use it?
  • 1. It’s OBJECTIVE
      • Doesn’t depend on opinions of human being
      • Done the same way every time
      • Can be more accurate (sometimes)
  • 2. It’s FAST
      • Computer derived
      • Some storms are harder than others
  • 3. It’s WANTED
      • JTWC has formally requested that we do this
      • We are holding off until full capability is here
      • Test mode only for now
current user status
Operational Use

NOAA/NESDIS Satellite Analysis Branch

NHC/Tropical Analysis Forecast Branch

Experimental Use

Joint Typhoon Warning Center

Air Force Weather Agency

Central Pacific Hurricane Center

Australian Bureau of Meteorology

Japanese Meteorological Agency

Current User Status
odt past performance

Developmental Data Sample

1995-1997

Independent Data Sample

1998-1999

Units in hPaBiasRMSESample

ODT +1.69 7.34 407

Op. Center +4.31 10.35 407

Units in hPaBiasRMSESample

ODT -0.72 7.97 397

Op. Center -0.05 10.38 397

Units in hPaBiasRMSESample

TAFB +2.29 10.76 305

ODT +1.58 7.46 305

SAB +4.88 10.42 319

ODT +1.45 7.35 319

AFWA +5.55 12.06 146

ODT +0.53 7.39 146

Units in hPaBiasRMSESample

TAFB -1.25 10.65 341

ODT -0.62 8.72 341

SAB +0.58 9.91 334

ODT -0.53 8.75 334

AFWA +1.83 10.40 334

ODT -0.43 8.07 334

ODT Past Performance

Legend : TAFB - Tropical Analysis Forecast Branch - NOAA/NCEP

SAB - Satellite Analysis Branch - NOAA/NESDIS

AFWA - U.S. Air Force Weather Agency

super typhoon bilis 18w
Super Typhoon Bilis (18W)

http://pzal.npmoc.navy.mil/jtwc_archive/2000/STORM_FOLDERS/NORTHWEST_PACIFIC/18W/Time_Intensity_Chart/18W_ti.gif

  • Good agreement with operational center and Best Track estimates
    • Slight overestimate during intensification and at peak
    • CI#s compare better with Best Track during weakening than Final T#s
    • Rapid weakening indicated by Final T#s supported by AMSU data (landfall)
    • SAB ODT estimates differ from JTWC ODT during intensification
slide24

Super Typhoon Saomai (22W)

http://pzal.npmoc.navy.mil/jtwc_archive/2000/STORM_FOLDERS/NORTHWEST_PACIFIC/22W/Time_Intensity_Chart/22W_ti.gif

  • Good agreement with operational center and Best Track estimates
    • Underestimate during weakening with Final T#s (should use CI#s)
    • Initial estimates off due to very cold cloud top temperatures (~-80ºC)
    • SAB ODT analysis very similar to JTWC ODT analysis
slide25

Super Typhoon Shanshan (26W)

http://pzal.npmoc.navy.mil/jtwc_archive/2000/STORM_FOLDERS/NORTHWEST_PACIFIC/26W/Time_Intensity_Chart/26W_ti.gif

  • Slight disagreement with operational center and Best Track estimates
    • Over/Underestimate during strengthening/weakening processes
    • CI#s compare better with Best Track during weakening than Final T#s
    • Rapid intensification cycles noted but led to ODT overestimates
    • SAB ODT analysis very similar to JTWC ODT analysis
summary and conclusions
6 storm sample for 2000 West Pacific season

Overall, good comparison between JTWC and SAB ODT estimates

JTWC and SAB ODT Final T# estimates were typically within 0.5 T# of JTWC Best Track estimates

Very cold cloud temperatures led to high bias in Final T# relative to JTWC Best Track estimates (cloud temperatures < upper -70°C)

Rapid intensification flag correctly identified events but led to large Final T# high bias when coupled with very cold cloud top temperatures (tuning to West Pacific needed)

Slight differences between JTWC and SAB ODT estimates

Possible errors with ocean basin identification (basin flag is manually adjusted; could be automated)

Implementation of 48 Hour Rule is slightly different between JTWC and SAB due to different ODT versions (fixed vs. time-weighted value)

Overall, CI#s provided better fit to JTWC Best Track estimate than Final T#s during weakening

Summary and Conclusions
future directions
Operational ODT Usage

Full operational test at JTWC during 2001 with devoted analyst (patterned after SAB and TAFB evaluation)

Experimental use only here at AFWA

Research Focus

Further tune ODT for West Pacific based on JTWC and SAB 2000 results

Expand analysis range for tropical storms and weaker systems (will remove need for 48 Hour Rule)

Investigate application of rapid intensification flag based on user analysis and feedback

Begin development of Multispectral Dvorak Technique (MDT), incorporating multiple satellite and channel information(AMSU, SSM/I, visible, water vapor, etc.)

Future Directions
slide28

ODT Implementation

  • JTWC uses it on NSDS-E
  • SAB uses it in MCIDAS
  • How will we use it here?
    • SIDAS
    • New Eye Intensity Calculation

ODT IS ALWAYS TO BE PERFORMED AFTER YOU COMPLETE YOUR OWN INDEPENDENT ANALYSIS!

slide36

ODT Implementation

Previous

SIDAS

Method

ODT Method

odt methodology13
ODT Methodology

ODT uses rings….

previous sidas method
Previous SIDAS Method

The SIDAS method uses

radial measurements of

temperature. ODT and

SIDAS are different!

Neither include

any banding features!

slide39

ODT Implementation

The SIDAS method

is only for a “point

in time”. The ODT

is time averaged.

~

So…..we need to

save this ODT

calculation……..

Hit the button

slide40

ODT Implementation

Once you hit

the button,

the names of

all available

ODT storm

archives will

appear

Hit the button:

slide41

ODT Implementation

Highlight the

ODT storm

archive file

that you need

slide42

Highlight the

ODT storm

archive file

that you need

ODT Implementation

Then Hit

the button:

slide43

ODT Implementation

Remember that

you will need to

do this every hour

(while the storm

has an EYE!)

ad