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Developing an Inner-Core SST Algorithm for use in SHIPS

Developing an Inner-Core SST Algorithm for use in SHIPS. Principal Investigator : Joseph J. Cione NOAA’s Hurricane Research Division Co-Investigators: John Kaplan (HRD) ; Chelle Gentemann (Remote Sensing Systems) ; Mark Demaria (NESDIS) IHC 2005 Joint Hurricane Testbed March 9, 2005.

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Developing an Inner-Core SST Algorithm for use in SHIPS

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  1. Developing an Inner-Core SST Algorithm for use in SHIPS Principal Investigator: Joseph J. Cione NOAA’s Hurricane Research Division Co-Investigators:John Kaplan (HRD); Chelle Gentemann (Remote Sensing Systems); Mark Demaria (NESDIS) IHC 2005 Joint Hurricane Testbed March 9, 2005

  2. Developing an Inner-Core SST Algorithm for use in SHIPS The Goal of this JHT project is to… Improve SHIPS intensity forecasts by incorporating realistic SST estimates in the TC high wind inner core.

  3. Developing an Inner-Core SST Algorithm for use in SHIPS Background/Project motivation… + Currently, SHIPS uses ‘pre-storm’, ambient SSTs obtained from weekly 100km resolution Reynolds analyses. + As such, SHIPS is unable to account for any storm-induced ocean cooling that occurs within the high wind inner core environment. + Furthermore….The ‘potential term’, PI, is defined in SHIPS as: PI = MPI(fn of SST only) - TC intensity and is a highly significant predictor in the statistical model… + Therefore….even modest improvements to SST may result in significant improvements in SHIPS intensity forecasts…

  4. Developing an Inner-Core SST Algorithm for use in SHIPS The Problem… Routine observation of the inner core hurricane ocean environment is often impractical and in many cases impossible… + However… recent multi-hurricane observations (1975-2002) from Cione and Uhlhorn (2003), have provided an improved representation of inner core (<60km) SST conditions… + Using storm-specific information in conjunction with ambient and inner core SST observations from the 33 TC events documented in Cione and Uhlhorn (2003)…. an algorithm to predict hurricane inner core SST was developed….

  5. Developing an Inner-Core SST Algorithm for use in SHIPS “Dependent Sample” Testing in SHIPS… + The Inner-Core SST Algorithm was recently tested on thousands of individual SHIPS forecast events between 1989-2002… …For the Inner-core SHIPS re-runs, Reynolds SST was replaced with the algorithm-derived…. Inner-Core SST

  6. Inner-Core SST Algorithm:Dependent Sample Summary… Some major highlights from the dependent SHIPS analysis: * ZER0 degradation in mean SHIPS forecast skill was found when the inner core SST algorithm was used, regardless of sample stratification… * The algorithm is very stable…Analysis used 1000s of individual forecast events from the 1989-2002 SHIPS storm database * Biggest improvement in skill was found later in the forecast period (48h-96h) Specifics…. • For All Hurricanes (N=4528) • an average 1.5-3.5%improvement in skill over the 12-120h period • For all Major Hurricanes (N=1011) • an average 2.7-7.0%improvement in skill over the 12-120h period • For the Top 10% “Rapid Intensifiers” • an average 4.5-8.0%improvement in skill over the 12-120h period • For the Bottom 10% “Rapid Fillers” • an average 2.0-13.5%improvement in skill over the 12-120h period

  7. Developing an Inner-Core SST Algorithm for use in SHIPS …. Independent Sample Testing in SHIPS… + Investigate the impact of the TC Inner-Core SST Algorithmon SHIPS 2003/04 Atlantic hurricane season forecasts… …For the Inner-Core SHIPS re-runs, Reynolds SST was replaced with the algorithm-derived…. Inner-Core SST

  8. Inner-Core SST Algorithm:Independent Sample Summary… Highlights from the 2003/04 independent sample SHIPS analysis: When the SST inner core algorithm was used in SHIPS…. + No mean degradation of forecast skill was found over any forecast interval for Hurricane events + A significant increase in forecast skill was found for 2003/04 Rapid Intensifiers + The largest increase in absolute skill was found over the 72-120h forecast interval, regardless of sample stratification (similar to the dependent analysis) Specifics…. • For All Hurricane Cases (N=147-207) • an average 7%improvement in skill over the 72-120h period (2kts) • For All Rapid Intensifiers (N=27-33) • an average 33%improvement in skill over the 72-120h period (5kts)

  9. Ongoing/Future work… +Run a parallel version of SHIPS that uses the Inner-Core SST Algorithm in real-time during the 2005 N. Atlantic Hurricane Season(Planned activity…Coordination with M Demaria) + Test the impact of high resolution (time and space) SSTs on SHIPS forecasts (Recently completed..2003 N. Atlantic hurricane season) + Investigate the possibility of incorporating a sub-surface ocean predictor into the algorithm (Ongoing…near completion) + Given the algorithm’s success with RI events, investigate the feasibility of using a version of the algorithm in the Atlantic RI Index (Preliminary work recently started with J. Kaplan) + Use hurricane inner core air-sea composite analyses from Cione et al 2000 to help develop a bulk enthalpy flux predictor for possible future use in SHIPS (Future…begin late 2005)

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