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  • 826 VOLUME 12W E A T H E R A N D F O R E C A S T I N G

    q 1997 American Meteorological Society

    Understanding and Forecasting Tropical Cyclone Intensity Change with theTyphoon Intensity Prediction Scheme (TIPS)


    Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado

    (Manuscript received 15 August 1996, in final form 30 July 1997)


    A multiple regression scheme with tropical cyclone intensity change as the dependent variable has beendeveloped. The new scheme is titled the Typhoon Intensity Prediction Scheme (TIPS) and is similar to one usedoperationally at the National Hurricane Center. However, TIPS contains two major differences: it is developedfor the western North Pacific Ocean, and utilizes digitized satellite data; the first time such satellite informationhas been combined with other predictors in a tropical cyclone multiple regression scheme. It is shown that thesatellite data contains vital information that distinguishes between fast and slow developing tropical cyclones.The importance of other predictors (such as wind shear, persistence, climatology, and an empirical formuladependent on sea surface temperature) to intensity change are also clarified in the statistical analysis. A nor-malization technique reveals threshold values useful to forecasters. It is shown that TIPS may be competitivewith the Joint Typhoon Warning Center in forecasting tropical cyclone intensity change.

    1. Introduction

    a. Overview of intensity prediction accuracy

    According to a 1987 survey of all tropical cyclone(TC) forecast centers in the world, the overriding TCresearch emphasis has been placed on track forecastingwith little investigation on intensity change (McBride andHolland 1987). The past decade has witnessed little im-provement (DeMaria and Kaplan 1994b; Elsberry et al.1992). As a result, systematic and skillful intensity fore-casting techniques have yet to be established, and muchis still not understood about TC intensity change. A Na-tional Disaster Survey Report (1993) noted that hurricaneintensity forecasts lack accuracy and lag far behind otherforecasting applications such as track prediction. The re-port urges scientists to redouble their efforts to developmodels and operational techniques to forecast tropicalcyclone intensity changes more effectively.

    Not surprisingly, large errors occur when forecastingTC intensity. The measure of intensity forecast aroundthe world is the maximum sustained surface wind speed(Vmax), often tabulated in knots. The mean 24-h Joint

    * Current affiliation: Department of Physics, Atmospheric Sci-ences, and General Science, Jackson State University, Jackson, Mis-sissippi

    Corresponding author address: Dr. Patrick J. Fitzpatrick, Depart-ment of Physics, Atmos. Sciences and General Science, Jackson StateUniversity, P.O. Box 17660, Jackson, MS 39217-0460.E-mail: patrick@stallion.jsums.edu

    Typhoon Warning Center (JTWC) absolute error was12.5 kt for intensity forecasts during 198085 (Mundell1990). Furthermore, the Australian Bureau of Meteor-ology Research Center (BMRC) reports that their TCintensity forecasts were not even as accurate as a pre-diction based on persistence or climatology (Elsberryet al. 1992). DeMaria and Kaplan (1994b) noted thatofficial National Hurricane Center (NHC) forecast skillwas comparable to a regression forecast based on cli-matology and persistence, and only slightly better thanpersistence.

    The largest errors in TC intensity forecasting occurwith rapidly intensifying systems (Mundell 1990),defined as a central pressure drop of at least 42 mb day21by Holliday and Thompson (1979). (This correspondsto an approximate Vmax increase of 45 kt day21.) Otherclassifications exist to delineate abrupt TC development,such as explosive deepening (Dunnavan 1981) de-fined as a 12-h central pressure drop of at least 30 mb.However, these definitions only apply to one time period(24 h) and would provide too few cases in the com-parison of different intensification rates (section 4). Inthis paper, a broader category of fast intensificationis used, defined as a 24-h (48-h) increase of Vmax by 25kt day21 [45 kt (2 day)21] or more. As shown by Mundell(1990) and by this paper, all three classifications areassociated with errors that are roughly twice the averageintensity error, and result in underforecasting intensity.

    b. Consequences of underforecasting TC intensity

    Unanticipated fast development is currently a fore-cast reality. Some storms that experienced unpre-

  • DECEMBER 1997 827F I T Z P A T R I C K

    dicted fast intensification are Typhoon Nina (1987),which struck the Philippines, killed hundreds, and lefthalf a million homeless (Mundell 1990); HurricaneHugo (1989) before its South Carolina landfall; Ty-phoon Omar (1992) before it impacted Guam, causing$457 million in damage and grounding two navy sup-ply ships; Hurricane Andrew (1992) before its Floridalandfall, resulting in record property damage esti-mated at $25 billion, destroying 25 524 homes, dam-aging 101 241 homes, and putting eight insurancecompanies out of business (Mayfield et al. 1994;Sheets 1994); and Hurricane Opal (1995) the nightbefore its Florida landfall, surprising awakening res-idents who congested the road systems in last-minuteevacuation attempts (Fitzpatrick 1996).

    It is the prospect of more such dangerous situationsthat motivates this paper, which describes a new mul-tiple regression scheme for TC intensity change. De-veloped on western North Pacific data, this statisticalanalysis yields an intensity forecast scheme, whichmay be used as guidance in real-time operations, andalso generates understanding about TC intensitychange.

    c. Previous TC intensification research

    Theoretical intensity change work concentrates onthree areas: 1) interaction with upper-tropospherictroughs and angular momentum fluxes, categorized hereas upper-level forcing; 2) inner-core convective pro-cesses; and 3) environmental factors such as sea surfacetemperature (SST) and vertical wind shear. The impor-tance of upper-level forcing has been a contentious issuein tropical meteorology (Fitzpatrick 1996). The dis-agreement stems from the fact that fast TC developmentis a relatively unusual event. One interpretation is thatan extra ingredient must be required to enhance TCintensification, and that extra factor is upper-level forc-ing. The other interpretation is that the combination ofwarm water and low wind shear is an infrequent eventand that fast TC intensification is generally more fa-vorable in an environment free of upper-level anomaliessince upper-tropospheric troughs are often associatedwith wind shear.

    Two scenarios of trough interactions that might in-tensify a TC have been proposed: 1) enhancement ofthe storms outflow by favorable positioning of atrough (Sadler 1978; Shi et al. 1990; Rodgers et al.1991) and/or 2) enhancement of the storms devel-opment through dynamical forcing, viewed in the con-text of differential vorticity advection and potentialvorticity coupling (Montgomery and Farrell 1993).Upper-level asymmetries (eddy fluxes), which are of-ten but not always associated with troughs, also mayaffect intensification. One azimuthally averaged quan-tity, known as the relative eddy angular momentumflux convergence (REFC), can theoretically contributeto TC development. Many researchers have attributed

    REFC forcing to fast TC intensification in modelingstudies (Pfeffer and Challa 1980), theoretical discus-sions (Holland and Merrill 1984), observational stud-ies (Molinari and Vollaro 1989; Rodgers and Pierce1995), and statistical studies (DeMaria et al. 1993).Other eddy flux terms may also be important, such asplanetary eddy angular momentum flux convergence(PEFC) (DeMaria and Kaplan 1994b; Molinari andVollaro 1990).

    In contrast with these findings, Merrill (1988) couldfind no relationship between REFC and intensitychange. He speculated that any positive influences ofupper-level forcing is usually offset by the negativeinfluences of increased vertical wind shear associatedwith a trough. Merrill also stated that, in a generalsense, environmental interactions must contributenegatively to intensity change since most TCs do notreach moderate to extreme intensities. Merrill notedthe existence of a maximum potential intensity (MPI)as a function of SST. MPI represents an upper boundfor which TCs of stronger intensity do not exist fora given SST. An example of an empirical MPI curveis shown for western Pacific TCs in Fig. 1 (Kubat1995). Since few TCs reach their MPI (Merrill 1987;Evans 1993; DeMaria and Kaplan 1994a), Merrill ar-gued the environment is exerting a negative influencemost of the time.

    The effect of SST on TC development has beenknown for decades (Palmen 1948). The ultimate en-ergy source for the TC is the latent and sensible heatflux from the ocean. As air spirals into a TC, it issubjected to sea level pressure reductions that woulddecrease the air temperature substantially due to ad-iabatic expansion; however, because of ocean fluxes,an air parcel is able to (mostly) preserve its air tem-perature. As originally discussed by Riehl (1954), anair parcel following a mostly isothermal path towardthe eyewall region and experiencing a pressure dropwill obtain buoyancy as it ascends in the eyewall; thisgain offsets the stabilization effect of the developingwarm-core aloft. Therefore, the secondary circulationis maintained and the TC can continue to intensifythrough this feedback mechanism (Fitzpatrick 1996;Holland 1997). As SSTs increase, this feedback in-creases the MPI nonlinearly as shown in Fig. 1. Aswill be seen, the most important statistical TC inten-sity predictor is a variation of the MPI threshold.

    Another important contributor to intensification maybe eye formation (Fitzpatrick 1996).