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Implementation of the UW-CIMSS Advanced Objective Dvorak Technique (AODT) into TPC

Implementation of the UW-CIMSS Advanced Objective Dvorak Technique (AODT) into TPC (NOAA USWRP Joint Hurricane Testbed Project) Jim Kossin, Chris Velden, and Tim Olander University of Wisconsin Cooperative Institute for Meteorological Satellite Studies Madison, WI

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Implementation of the UW-CIMSS Advanced Objective Dvorak Technique (AODT) into TPC

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  1. Implementation of the UW-CIMSS Advanced Objective Dvorak Technique (AODT) into TPC (NOAA USWRP Joint Hurricane Testbed Project) Jim Kossin, Chris Velden, and Tim Olander University of Wisconsin Cooperative Institute for Meteorological Satellite Studies Madison, WI Interdepartmental Hurricane Conference, March 2004

  2. JHT Project – Primary Objective: Implement the latest version of the UW-CIMSS AODT onto the NOAA Computing Development Branch N-AWIPS architecture for operational use at TPC.

  3. Brief Review of the UW-CIMSS Advanced ODT (AODT) • Originally designed to imitate the Dvorak technique while removing operator subjectivity. • Employs geostationary satellite IR imagery to estimate current TC intensity. • Computer-based algorithm that can be executed in a fully automated mode, or with manual over-ride capability. • Includes an algorithm designed to locate the TC center. • Applicable to all stages of the TC lifecycle. • Thorough statistical analysis indicates the AODT is competitive with the operational (subjective) Dvorak technique. • The AODT predecessor, the ODT, has been running experimentally at various forecasting centers for a number of years.

  4. Latest version of the AODT: • Time averaging scheme reduced from 12h to 6h to better allow for • identification of rapid intensity change events. • Modified land interaction rules to better handle transient land • interaction (e.g. TC traversing large islands). • Inclusion/modification of Dvorak rules 8/9 to better estimate • initial and final intensities during TC lifetime. • Implementation of new automated TC center positioning scheme. • Latitude-dependent MSLP bias removed.

  5. Performance of the latest version of the AODT (estimated MSLP versus recon-measured MSLP) rmse aae bias Manually fixed images: 9.50 7.48 +0.09 (mb) Auto-fixed images: 10.04 7.60 +1.70 OpCenterAvg 10.65 8.09 +0.22 *dependent testing based on the AODT training sample (n = 1630); distribution inherently skewed toward stronger TC cases. rmse aae bias Auto-fixed images: 10.10 8.19 -1.26 (mb) OpCenterAvg 9.29 6.79 +0.95 *independent testing (n = 2221) on a more natural distribution of TC cases.

  6. Implementation onto N-AWIPS: • Restructure the AODT algorithm for congruence with the NOAA CDB N-AWIPS architecture. This requires • Re-creation of the AODT algorithm as a library function. • Creation of an Application Program Interface (API). This requires creation of new library functions enabling communication between the AODT and the N-AWIPS NMAP application. • Timeline: • Delivery of API variable passing library functions - Feb 2004 • Delivery of API data passing library functions - Mar 2004 • Test run of partial AODT library function on NAWIPS - Apr 2004 • Comparison of McIDAS-AODT with NAWIPS-AODT - May 2004 • Delivery of complete NAWIPS-AODT to TPC in NMAP upgrades • - June 2004

  7. Summary: • A fully automated version of the UW-CIMSS AODT is expected to be functional at TPC in time for the 2004 Atlantic Hurricane season. • The 2004 season will be used to evaluate the NAWIPS-AODT at TPC. • The TPC evaluation will be used to examine and implement post-season modifications. • UW-CIMSS will continue to improve the AODT and provide upgrades to CDC for implementation into the NAWIPS version. The recent expansion of the AODT training sample to include more weak cases will provide a means of improving the overall performance characteristics.

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