Cluster Analysis of Tropical Cyclone Tracks and ENSO

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Cluster Analysis of Tropical Cyclone Tracks and ENSO Suzana J. Camargo, Andrew W. Robertson,

Cluster Analysis of Tropical Cyclone Tracks and ENSO Suzana J. Camargo, Andrew W. Robertson, International Research Institute for Climate Prediction, Columbia Earth Institute, Palisades, NY Scott J. Gaffney and Padhraic Smyth Department of Information and Computer Science, University of California, Irvine, CA

Outline • • Introduction Clustering Technique Previous works on cluster analysis and tropical cyclones

Outline • • Introduction Clustering Technique Previous works on cluster analysis and tropical cyclones Western North Pacific Results – – – Mean Regression Trajectories Tracks Properties of main clusters ENSO Relationship: tracks, tracks density, NTC, ACE Composites: SST, SLP, winds, wind shear • North Atlantic Results – Mean Regression Trajectories and Tracks – ENSO relationship – Atlantic multi-decadal signal • Eastern North Pacific Results – Mean Regression Trajectories and Tracks – ENSO relationship • Summary

Introduction • Identify different track types, their seasonality and relation with large-scale circulation and

Introduction • Identify different track types, their seasonality and relation with large-scale circulation and ENSO. • Importance: different track types have higher incidence on some years and make landfall in different regions. • New clustering technique used. • Best track datasets: – Western North Pacific – JTWC 1950 -2002. – North Atlantic – NHC 1851 -2003. – Eastern North Pacific – NHC 1949 -2003. • Only tropical cyclones (TCs) with tropical storm or hurricane (typhoon) intensity (no tropical depressions).

Clustering Technique • Developed by S. J. Gaffney and P. Smyth: - S. J.

Clustering Technique • Developed by S. J. Gaffney and P. Smyth: - S. J. Gaffney (2004), Ph. D. thesis, University of California, Irvine. • Mixture of polynomial regression models (curves) to fit the geographical “shape” of the trajectories. • Extension of the standard multivariate finite mixture model to allow quadratic functions. • Enable highly non-Gaussian density functions to be expressed as a mixture of a few PDFs. • Fitting by maximizing the likelihood of the parameters. • Rigorous probabilistic context for clustering • Accommodate easily tropical cyclone tracks of different lengths.

Previous works on Cluster Analysis and Tropical Cyclones • Western North Pacific: – P.

Previous works on Cluster Analysis and Tropical Cyclones • Western North Pacific: – P. A. Harr and R. L. Elsberry, Mon. Wea. Rev. 123, 1225 -1246 (1985). – J. B. Elsner and K. B. Liu, Climate Research 25, 43 -54 (2003); • North Atlantic: – J. B. Elsner, Bull. Amer. Meteor. Soc. 84, 353 -356 (2003); J. B. Elsner et al. , J. Climate 13, 2293 -2305 (2000). • Eastern North Pacific (TC precursors): – J. B. Mozer and J. A. Zehnder, J. Geophys. Res. – Atmos. 99, 8085 -8093 (1994).

Western North Pacific Tropical Cyclones Cluster Analysis Results

Western North Pacific Tropical Cyclones Cluster Analysis Results

Mean Regression Trajectories • Appropriate number of clusters appears to be seven. • Quantitative

Mean Regression Trajectories • Appropriate number of clusters appears to be seven. • Quantitative (out of sample likelihood) and subjective analysis. • Two main trajectory-types: “straight-movers” and “recurvers”. • Additional clusters: detailed differences in shape among these types.

TRACKS MEAN REGRESSION TRAJECTORIES TRACKS TROPICAL CYCLONES Western North Pacific 1983 -2002

TRACKS MEAN REGRESSION TRAJECTORIES TRACKS TROPICAL CYCLONES Western North Pacific 1983 -2002

Number of TCs per Cluster

Number of TCs per Cluster

Cluster A TRACK DENSITY FIRST POSITION DENSITY NTC ANNUAL CYCLE Landfall 63% Regression Trajectory

Cluster A TRACK DENSITY FIRST POSITION DENSITY NTC ANNUAL CYCLE Landfall 63% Regression Trajectory • 67% reach typhoon intensity

Cluster B TRACK DENSITY FIRST POSITION DENSITY NTC ANNUAL CYCLE Landfall 61% Regression Trajectory

Cluster B TRACK DENSITY FIRST POSITION DENSITY NTC ANNUAL CYCLE Landfall 61% Regression Trajectory 50% only reach TS intensity.

Cluster C TRACK DENSITY FIRST POSITION DENSITY NTC ANNUAL CYCLE Landfall 7% Regression Trajectory

Cluster C TRACK DENSITY FIRST POSITION DENSITY NTC ANNUAL CYCLE Landfall 7% Regression Trajectory • 70% reach typhoon intensity

ENSO Relationship NTC- Number of Tropical Cyclones Total NTC per year is not significantly

ENSO Relationship NTC- Number of Tropical Cyclones Total NTC per year is not significantly correlated with ENSO (e. g. Wang & Chan, 2002). ACE – Accumulated Cyclone Energy Total ACE has a well known relationship with ENSO (Camargo & Sobel, 2004).

Tracks El Niño years Cluster A Cluster E Cluster G Tracks La Niña years

Tracks El Niño years Cluster A Cluster E Cluster G Tracks La Niña years

Track Density per year: Difference El Niño and La Niña years Full basin Cluster

Track Density per year: Difference El Niño and La Niña years Full basin Cluster A Cluster E Cluster G

Mean NTC and ACE per cluster and ENSO A E G

Mean NTC and ACE per cluster and ENSO A E G

SST Anomalies Composites TCs first positions SST and TC data for SST composites: 11/81

SST Anomalies Composites TCs first positions SST and TC data for SST composites: 11/81 – 12/02 Regression trajectory

Sea Level Pressure Anomalies Composites NCEP Reanalysis and TC data for composites: 1950 -2002

Sea Level Pressure Anomalies Composites NCEP Reanalysis and TC data for composites: 1950 -2002

Anomalous Low Level Wind Composites

Anomalous Low Level Wind Composites

Wind Shear Composites Magnitude of the total wind shear between 200 h. Pa and

Wind Shear Composites Magnitude of the total wind shear between 200 h. Pa and 850 h. Pa

North Atlantic Tropical Cyclones Cluster Analysis Results

North Atlantic Tropical Cyclones Cluster Analysis Results

Tracks and Regression Trajectories Mean Regression Trajectory TRACKS Tracks Atlantic named Tropical Cyclones 1970

Tracks and Regression Trajectories Mean Regression Trajectory TRACKS Tracks Atlantic named Tropical Cyclones 1970 -2003.

Number of TCs per cluster

Number of TCs per cluster

ENSO Relationship NTC correlations ACE correlations

ENSO Relationship NTC correlations ACE correlations

Tracks El Niño years Tracks La Niña years Cluster 1 Cluster 2 Cluster 3

Tracks El Niño years Tracks La Niña years Cluster 1 Cluster 2 Cluster 3 Named Tropical Cyclones in warm/cold ENSO years 1950 -2003

Named Tropical Cyclones: 1950 -2003

Named Tropical Cyclones: 1950 -2003

SST Anomalies Composites Main Development Region SST and TC data for SST composites: 11/81

SST Anomalies Composites Main Development Region SST and TC data for SST composites: 11/81 – 12/2003 TCs First Positions

Wind shear composites NCEP Reanalysis and TC data for composites: 1950 -2003. Magnitude of

Wind shear composites NCEP Reanalysis and TC data for composites: 1950 -2003. Magnitude of the total wind shear between 200 h. Pa and 850 h. Pa.

Atlantic Multi-Decadal Signal • S. B. Goldenberg, C. W. Landsea, A. M. Mesta-Nuñez and

Atlantic Multi-Decadal Signal • S. B. Goldenberg, C. W. Landsea, A. M. Mesta-Nuñez and W. M. Gray, Science 293, 474 -478 (2001).

Number of Major Hurricanes per cluster

Number of Major Hurricanes per cluster

SST anomalies composite SST composites: 11/1981 -12/2003

SST anomalies composite SST composites: 11/1981 -12/2003

Eastern North Pacific Tropical Cyclones Cluster Analysis Results

Eastern North Pacific Tropical Cyclones Cluster Analysis Results

Mean Regression Trajectories and Tracks

Mean Regression Trajectories and Tracks

ENSO Relationship

ENSO Relationship

Tracks El Niño years Cluster 1 Cluster 2 Cluster 3 Tracks La Niña years

Tracks El Niño years Cluster 1 Cluster 2 Cluster 3 Tracks La Niña years

Summary • New clustering technique applied to Northern Hemisphere TC tracks. • Clusters with

Summary • New clustering technique applied to Northern Hemisphere TC tracks. • Clusters with different properties: genesis and track regions, intensity, timing. • In all basins clusters strongly related to ENSO are identified. • Composites of large scale fields with different characteristics for each cluster identify the factors influencing the formation and movement of TCs in each cluster.