Cluster Analysis of Tropical Cyclone Tracks and ENSO Suzana J. Camargo, Andrew W. Robertson, International Research Institute for Climate Prediction, Columbia.

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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 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 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 –North Atlantic – NHC –Eastern North Pacific – NHC 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. 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.A. Harr and R.L. Elsberry, Mon. Wea. Rev. 123, (1985). – J.B. Elsner and K.B. Liu, Climate Research 25, (2003); North Atlantic: –J.B. Elsner, Bull. Amer. Meteor. Soc. 84, (2003); J.B. Elsner et al., J. Climate 13, (2000). Eastern North Pacific (TC precursors): –J.B. Mozer and J.A. Zehnder, J. Geophys. Res. – Atmos. 99, (1994).

Western North Pacific Tropical Cyclones Cluster Analysis Results

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.

MEAN REGRESSION TRAJECTORIES TRACKS TRACKS TROPICAL CYCLONES Western North Pacific

Number of TCs per Cluster

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

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

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

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

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

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

Mean NTC and ACE per cluster and ENSO A A E E G G

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

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

Anomalous Low Level Wind Composites

Wind Shear Composites Magnitude of the total wind shear between 200hPa and 850hPa

North Atlantic Tropical Cyclones Cluster Analysis Results

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

Number of TCs per cluster

ENSO Relationship NTC correlations ACE correlations

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

Named Tropical Cyclones:

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

Wind shear composites Magnitude of the total wind shear between 200hPa and 850hPa. NCEP Reanalysis and TC data for composites:

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

Number of Major Hurricanes per cluster

SST anomalies composite SST composites: 11/ /2003

Eastern North Pacific Tropical Cyclones Cluster Analysis Results

Mean Regression Trajectories and Tracks

ENSO Relationship

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

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.