# Presentation: 533503

## Developing an Inner-Core SST Cooling Parameter 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 2004 *
*Joint Hurricane Testbed*
*March 3, 2004*

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+ What is the magnitude of inner core SST cooling typically observed ?

+ What about storm to storm variability ?	

**+ What is the magnitude of inner core SST cooling typically observed ?**
**+ What about storm to storm variability ?**

**Project Motivation.....****On average do post storm ‘cold wake’ SST reductions on the order of 4-6****o****C  adequately approximate SST cooling patterns typically found within the high wind  TC inner core ?**

**Cione and Uhlhorn (2003) documented SST change within the high wind TC inner core environment**...
- Using existing surface **buoy and AXBT observations from 23 hurricanes (33 events) between 1975-2002.**

**A focused effort to answer these questions....****Cione and Uhlhorn (2003)**

## Defining the SST change Parameters used in Cione and Uhlhorn (2003) (inner-core minus ‘ambient’)

**	****‘****Ambient’ SST ****out AHEAD of the storm**** **
***(>200km from TC center in RF or LF quadrant)***
**	****‘****Inner core’ SST/mixed layer temperature **
***(<******60km ******or <******200km****** from TC center) -****** *****SST****IC *****; *****SST****ICW**
**	****Hurricanes only...**
**Pre-landfall**
**South of 36N**

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**+**** ****	****Inner core SST change ****(core - ambient)**** is MUCH less ****than**** 4-6****o****C ‘cold wake’ SST ****reductions typically observed**
**31/33 horizontal SST transects **_**<**_** 1.5****o****C (23 Hurricanes)**
**Mean ********SST****IC**** = 0.7****o****C**
**Relatively ****small  changes in inner-core SST**** ****(0.5****o****C) ****can significantly alter surface energy fluxes ****(-40% or more)**
**+**** ****	****For the 33 cases analyzed, the**** magnitude of inner core SST cooling (core - ambient) ****was**** highly correlated with subsequent changes storm intensity**

- Key Findings: Cione and Uhlhorn (2003)

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**In addition, ****TC latitude ****and**** initial storm speed****  were found to be statistically linked to observed ****changes in inner-core  SST**** for this 33 event sample.  **
**As a direct result of these findings a proposal entitled ****“Developing an Inner-Core SST Cooling Parameter for use in SHIPS”**** was submitted to the JHT In the spring of 2003....**

- Key Findings: Cione and Uhlhorn (2003) *Continued...*

## Developing an Inner-Core SST Cooling Parameter for use in SHIPS

**	****The **_**Overall**_** Goal of this JHT  project is...**
**  ****	**
**	****To Investigate how ****changes in the TC inner-core ocean surface boundary condition**** potentially ****impacts ****changes in storm intensity**** within the context of SHIPS operation model.**
**Early results....Algorithm Development **
**	****+ Since June 2003,**** several multiple linear regression relationships designed to *****predict inner core SST change***** have been tested and developed...**
**	****+ Continued analysis has ****yielded**** a statistically robust baseline ****TC Inner-Core SST Cooling Algorithm**** that utilizes three independent predictors:**
**	****	*****Initial TC latitude, storm speed and ambient SST***

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## Developing an Inner-Core SST Cooling Parameter for use in SHIPS

_**	**__**Current JHT Project -**_
**	****Early results....Dependant Testing in SHIPS**
**	****+ ****Preliminary**** testing**** of the ****TC Inner-Core SST Cooling Algorithm**** on thousands of TC forecast events found in the ****1989-2002 SHIPS storm database**** have**** yielded very encouraging results....**
**	****	****	**

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**	****Results using thousands of observations from the 1989-2002 SHIPS data archive show that the inner-core cooling algorithm developed under this JHT project is very stable...**
**	****Dependant sample testing in SHIPS illustrated ****significant improvements with respect to observed changes in TC intensity**** over ****ALL 12-120h forecast intervals****, **_**regardless of sample stratification.**_
**	****Some of the major highlights from this SHIPS analysis include:**
**For All TC cases (N=12887) an avg ****1.0-2.5% improvement in skill**** was found over the 24-120h fcst pd **
**For Hurricane cases (N=4528) an avg ****1.5-3.5%**** ****improvement in skill**** ****	****  “****	****“**
**For all **_**Major Hurricanes**_**  (N=1011) an avg ****2.7-7.0%**** ****improvement in skill****    ****	****       ****“****	****“**** **
**For the **_**Top 10% “Rapid Intensifier”**_** events ****an avg ****4.5-8.0%**** ****improvement in skill****    ****“            “**
**For the **_**Bottom 10% “Rapid Filler”**_** events ****an avg ****2.0-13.5%**** ****improvement in skill****    ****“            “**
**NOTE: Regardless of stratification or forecast interval, ****ZERO degradation in mean SHIPS forecast skill**** was found when the Inner core SST cooling algorithm was used...**
**	****Future work, if funded in year two, would include independent testing by running a parallel version of SHIPS during the 2004 Atlantic Hurricane Season.  In addition, attempts would be made to identify a reliable subsurface ocean predictor and improve upon existing Reynolds weekly SSTs currently used in SHIPS (Gentemann - high spatial and temporal resolution microwave SSTs).  Additionally, focused on potentially incorporating a version of the cooling algorithm into the Atlantic RI index have recently begun (Kaplan).  Preliminary findings have been promising.**

- SST Cooling Algorithm: Preliminary Findings....

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