Statistical modelling of North Atlantic tropical cyclone tracks

Timothy M. Hall; Stephen Jewson

doi:10.1111/j.1600-0870.2007.00240.x

Authors:

Timothy M. Hall ,

NASA GISS, New York, NY, US

Stephen Jewson

Risk Management Solutions, London, GB

Abstract

We present a statistical model of North Atlantic tropical cyclone tracks from genesis site through lysis. To propagate tracks we use the means and variances of latitudinal and longitudinal displacements and model the remaining anomalies as autoregressive. Coefficients are determined by averaging near-neighbour historical track data, with ‘near’ determined optimally by using jackknife out-of-sample validation to maximize the likelihood of the observations. The number of cyclones in a simulated year is sampled randomly from the historical record, and the cyclone genesis sites are simulated with a spatial probability density function using kernels with optimized bandwidths. Simulated cyclones suffer lysis with a probability again determined from optimal averaging of historical lysis rates. We evaluate the track model by comparing an ensemble of 1950–2003 simulations to the historical record using several diagnostics, including landfall rates. In most regions, but not all, the observations fall within the variability across the ensemble members, indicating that the simulations and observations are statistically indistinguishable. An intensity component to the TC model, necessary for risk assessment applications, is currently under development.

How to Cite: Hall, T.M. and Jewson, S., 2007. Statistical modelling of North Atlantic tropical cyclone tracks. Tellus A: Dynamic Meteorology and Oceanography, 59(4), pp.486–498. DOI: http://doi.org/10.1111/j.1600-0870.2007.00240.x

Accepted on 19 Feb 2007 Submitted on 15 Aug 2006

References

Bishop , J. A. , Chalcraborti , S. and Thistle , P. D. 1989 . Asymptotically distribution-free statistical inference for generalized Lorenz curves . Rev. Econ. StaL 71 , 725 – 727 .

Casson , E. and Coles , S. 2000 . Simulation and extremal analysis of hurricane events . AppL StaL 49 , 227 – 245 .

Chu , P. and Wang , J. 1998 . Modeling return periods of tropical cyclone intensities in the vicinity of Hawaii . J. AppL MeteoroL 37 , 951 – 960 .

Darling , R. 1991 . Estimating probabilities of hurricane wind speeds using a large-scale empirical model . J. Clim . 4 , 1035 – 1046 .

Emanuel , K. A. , Ravela , S. , Vivant , E. and Risi , C. 2006 . A statistical-deterministic approach to hurricane risk assessment . Bull. Amer Meteor Soc . 87 , 299 – 312 .

Gray , W. M. , Landsea , C. W. , Mielke , P. W. and Berry , K. J. 1992 . Predicting Atlantic seasonal hurricane activity 6-11 months in advance . Wea. Forecasting 7 , 440 – 455 .

Jagger , T. , Elsner , J. B. and Niu , X. 2001 . A dynamic probability model of hurricane winds in coastal counties of the United States . AppL StaL 40 , 853 – 863 .

James , M. K. and Mason , L. B. 2005 . Synthetic tropical cyclone database . J. Wtrwy., Port, Coastal, and Oc. Engrg . 131 , 181 – 192 .

Jarvinen , B. R. , Neumann , JC. J. and Davis , M. A. S. 1984 . A tropical cyclone data tape for the North Atlantic Basin, 1886-1983, contents, limitations, and uses. NOAA Tech. Memo., NWS NHC 22.

Rumpf , J. , Weindl , H. , Hoppe , P. , Rauch , E. and Schmidt , V. 2007 . Stochastic modelling of tropical cyclone tracks. Math. Meth. Oper Res . 65 , in press .

Vickery , P. J. , Lin , J. , Skerlj , P. F. , Twisdale , L. A. and Huang , K. 2006 . HAZUS-MH hurricane model methodology. I: hurricane hazard, terrain, and wind load modeling . Natural Hazards Re v . 7 , 82 – 93 .

Vickery , P. J. , Skerlj , P. F. and Twisdale , L. A. 2000 . Simulation of hurricane risk in the US using an empirical track model . J. StrucL Engin . 126 , 1222 – 1237 .

Webster , P. J. , Holland , G. J. , Curry , J. A. and Chang , H.-R. 2005 . Changes in tropical cyclone number, duration, and intensity in a warming environment . Science 309 , 1844 – 1846 .

[CIT0001] Bishop , J. A. , Chalcraborti , S. and Thistle , P. D. 1989 . Asymptotically distribution-free statistical inference for generalized Lorenz curves . Rev. Econ. StaL 71 , 725 – 727 .

[CIT0002] Casson , E. and Coles , S. 2000 . Simulation and extremal analysis of hurricane events . AppL StaL 49 , 227 – 245 .

[CIT0003] Chu , P. and Wang , J. 1998 . Modeling return periods of tropical cyclone intensities in the vicinity of Hawaii . J. AppL MeteoroL 37 , 951 – 960 .

[CIT0004] Darling , R. 1991 . Estimating probabilities of hurricane wind speeds using a large-scale empirical model . J. Clim . 4 , 1035 – 1046 .

[CIT0005] Emanuel , K. A. , Ravela , S. , Vivant , E. and Risi , C. 2006 . A statistical-deterministic approach to hurricane risk assessment . Bull. Amer Meteor Soc . 87 , 299 – 312 .

[CIT0006] Gray , W. M. , Landsea , C. W. , Mielke , P. W. and Berry , K. J. 1992 . Predicting Atlantic seasonal hurricane activity 6-11 months in advance . Wea. Forecasting 7 , 440 – 455 .

[CIT0007] Jagger , T. , Elsner , J. B. and Niu , X. 2001 . A dynamic probability model of hurricane winds in coastal counties of the United States . AppL StaL 40 , 853 – 863 .

[CIT0008] James , M. K. and Mason , L. B. 2005 . Synthetic tropical cyclone database . J. Wtrwy., Port, Coastal, and Oc. Engrg . 131 , 181 – 192 .

[CIT0009] Jarvinen , B. R. , Neumann , JC. J. and Davis , M. A. S. 1984 . A tropical cyclone data tape for the North Atlantic Basin, 1886-1983, contents, limitations, and uses. NOAA Tech. Memo., NWS NHC 22.

[CIT0010] Rumpf , J. , Weindl , H. , Hoppe , P. , Rauch , E. and Schmidt , V. 2007 . Stochastic modelling of tropical cyclone tracks. Math. Meth. Oper Res . 65 , in press .

[CIT0011] Vickery , P. J. , Lin , J. , Skerlj , P. F. , Twisdale , L. A. and Huang , K. 2006 . HAZUS-MH hurricane model methodology. I: hurricane hazard, terrain, and wind load modeling . Natural Hazards Re v . 7 , 82 – 93 .

[CIT0012] Vickery , P. J. , Skerlj , P. F. and Twisdale , L. A. 2000 . Simulation of hurricane risk in the US using an empirical track model . J. StrucL Engin . 126 , 1222 – 1237 .

[CIT0013] Webster , P. J. , Holland , G. J. , Curry , J. A. and Chang , H.-R. 2005 . Changes in tropical cyclone number, duration, and intensity in a warming environment . Science 309 , 1844 – 1846 .

Reading: Statistical modelling of North Atlantic tropical cyclone tracks

Original Research Papers

Statistical modelling of North Atlantic tropical cyclone tracks

Authors:

Timothy M. Hall ,

NASA GISS, New York, NY, US

X close

Stephen Jewson

Risk Management Solutions, London, GB

X close

Abstract

References