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Objective Dvorak Technique (ODT) AFWA/XOGM

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 :

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Objective Dvorak Technique (ODT) AFWA/XOGM

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  1. Objective Dvorak Technique (ODT)AFWA/XOGM

  2. 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

  3. Objective Dvorak Technique (ODT) Overview - What is the ODT?- How does it work?- Why use it?- How will we use it here?

  4. 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?

  5. ODT Methodology

  6. 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

  7. 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

  8. 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

  9. ODT Methodology

  10. Warmest value = 'eye temperature'

  11. 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

  12. ODT Methodology

  13. ODT Methodology

  14. ODT Methodology The warmest temperature is found on each ring...

  15. ODT Methodology This ring has “Light Grey” as its warmest temp.

  16. ODT Methodology Of those temps that are left, the coldest is taken as the surrounding ring

  17. “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

  18. 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

  19. 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

  20. 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

  21. 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

  22. 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

  23. 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

  24. 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

  25. 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

  26. 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

  27. 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!

  28. ODT Implementation

  29. ODT Implementation

  30. ODT Implementation

  31. ODT Implementation

  32. ODT Implementation

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  34. ODT Implementation

  35. ODT Implementation Previous SIDAS Method ODT Method

  36. ODT Methodology ODT uses rings….

  37. Previous SIDAS Method The SIDAS method uses radial measurements of temperature. ODT and SIDAS are different! Neither include any banding features!

  38. 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

  39. ODT Implementation Once you hit the button, the names of all available ODT storm archives will appear Hit the button:

  40. ODT Implementation Highlight the ODT storm archive file that you need

  41. Highlight the ODT storm archive file that you need ODT Implementation Then Hit the button:

  42. ODT Implementation Remember that you will need to do this every hour (while the storm has an EYE!)

  43. Questions?Objective Dvorak Technique (ODT)AFWA/XOGM

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