Sensitivity of the Statistical Hurricane Intensity Prediction Scheme (SHIPS) to

Sea Surface Temperature Analyses

Joe Cione

NOAA/OAR/HRD

Mark DeMariaNOAA/NESDIS/ORA

Chelle L. GentemannRemote Sensing Systems

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Mean Absolute Error of NHC Official Atlantic Track and Intensity Errors1985-2006

NHC Operational Intensity Forecast Models

• Hurricane WRF coupled model– Next generation 3-D coupled model– First operational forecasts in 2007

• NCEP/GFDL hurricane model– 3-D dynamical model with coupled ocean

• SHIPS: Statistical Hurricane Intensity Prediction Scheme – Statistical regression model with input from SST analyses

and global model forecasts• SHIFOR

– Simple statistical model with climatology and persistence input (baseline for comparison)

2003-2006 Intensity Model Error

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Average Error (kt)

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2003-2006 Intensity Model Skill

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Forecast Skill (%)

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Comparison of GFDL and SHIPS Models(Atlantic Operational Forecasts 2003-2006)

The SHIPS Intensity Model

• Statistical-regression model– 1982-2006 sample for 2007 version

• 18 basic predictors– atmospheric from GFS forecast fields– oceanic from Reynold’s weekly 111km SST– cloud top structure from GOES– climatology and persistence

• Empirical decay rate once storm is over land

SST in the SHIPS Model

Reynolds weekly SST vs Max Wind, Atl- 1982-2005

• SST provides upper bound on max winds

• SHIPS SST predictor is the intensification “potential”

• SST potential is difference between black curve and current intensity

Primary Predictors for 72 hr Atlantic SHIPS Model Forecast

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SST Potential

200-850 mb Vertical Shear

Upper Level Temperature

Global Model Tangential Wind Forecast

850 mb Environemental Vorticity

200 mb Environmental Divergence

Mid-Level Moisture

Persistence

Normalized Regression Coefficient

SST Sensitivity Testing in SHIPSSST Sensitivity Testing in SHIPS

• Start with 2007 operational SHIPS model

• Re-run all 2004-2006 storm cases– Atlantic and east Pacific

• Four Sensitivity Tests… – Reynold’s weekly 111km SST, hurricane-induced, inner-core (eyewall) SST

cooling algorithm not used (control)– TMI/AMSR-E microwave 25km ‘foundation’ (diurnal bias removed) daily SST, no storm-induced cooling– Reynold’s weekly 111km SST, storm-induced cooling included (Atlantic only)– Microwave SST, storm-induced cooling included (Atlantic only)

Developing a TC Inner-Core SST Algorithm for SHIPSDeveloping a TC Inner-Core SST Algorithm for SHIPS

Background/Project motivation…

+ Currently, SHIPS uses ‘pre-storm’, ambient SSTs obtained from weekly 111km 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 ‘SST potential term’, is defined in SHIPS as:SST Potential = MPI(fn of SST only) - TC intensity

and as previously shown, the SST potential term is a highly significant predictor (R~.65) in the statistical model…

+ Therefore….even modest improvements to SST may result in significant improvements in SHIPS intensity forecasts…

Developing a TC Inner-Core SST Algorithm for SHIPSDeveloping a TC Inner-Core SST Algorithm for 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 an algorithm to predictto predict hurricane inner core SST was hurricane inner core SST was developed….developed….(ambient SST,TC lat, TC speed)(ambient SST,TC lat, TC speed)

Scatter plot of in-situ SST vs. predicted inner-core SST [using the hurricane inner-core SST cooling algorithm developed from the 23-hurricane (1975-2002) sample from Cione and Uhlhorn (2003)].

SST is given in oC.

SHIPS 2004-06 Re-Run Results

(Control Runs: Reynold’s weekly 111km SST, No Cooling)

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SHIPS 2004-06 Re-Run Results:SHIPS 2004-06 Re-Run Results:

Impact of TMI/AMSR-E Microwave 25km ‘Foundation’ (diurnal bias removed) Daily SST

on Hurricane Intensity Forecasts

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% Improvement after replacing weekly ReynoldsSST with daily microwave analyses

SHIPS 2004-06 Re-Run Results:SHIPS 2004-06 Re-Run Results:

Impact of Hurricane Inner-Core SST Cooling Algorithm on Hurricane Intensity Forecasts

% Improvement after including storm-induced SST cooling algorithm (% Improvement after including SST cooling algorithm & microwave SSTs)

(Atlantic Cases Only)

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SST Cooling

SST Cooling and mwave SST

ConclusionsOverall…Overall…Improving the SST (that the storm ‘sees’) improves the forecastImproving the SST (that the storm ‘sees’) improves the forecast

• The daily microwave SST analysis improved the Atlantic SHIPS intensity forecasts for the 2004-2006 Independent sample

– Positive to neutral impact for the east Pacific– Very active 2004-2005 Atlantic season, quiet east Pacific seasons may explain these results

• previous studies showed positive impact in the east Pacific, neutral in the Atlantic

• SST cooling algorithm improved the Atlantic SHIPS forecasts for all periods

– Additional gain at 72-120 hr by including SST cooling and microwave SSTs– Note: Cione SST cooling algorithm (V 1.0) is now being used operationally (since 2005) by NHC

Looking forward….Looking forward….

• Operationally test ‘new’ SST analyses Operationally test ‘new’ SST analyses (Reynolds AVHRR/AMSR-E 25km daily SST)(Reynolds AVHRR/AMSR-E 25km daily SST)

andand• Include Cione inner-core SST cooling algorithm V 2.0 Include Cione inner-core SST cooling algorithm V 2.0 (under construction)(under construction)

WhenWhen combined, additional improvements to future SHIPS forecasts ? combined, additional improvements to future SHIPS forecasts ?