Tropical Transition Climatology R. McTaggart-Cowan, L. F. Bosart, C. A. Davis and G. Deane.

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Tropical Transition

Climatology

R. McTaggart-Cowan, L. F. Bosart, C. A. Davis and G. Deane

Outline

Review of TT:– Role of midlatitude trough

– SEC vs. WEC precursors

Data and methodology:– Motivation for climatology

– Selection of metrics

and groups (LCA)

Results from TT climatology:– Group membership and physical properties

Hurricane Michael (18 October

2000) – Category 1. NOAA

SeaWiFS imagery.

Review of TT

Components of TT:– Low latitude trough

– Lower/midlevel vortex

Low latitude trough– Related to TUTT– Provides downshear QG ascent forcing– Reduces column stability– Cyclonic relative vorticity > local f

Review of TT

Lower vortex - SEC– Wind >10 m/s - WISHE– Elevates near-surface equivalent potential

temperature– Redistributes PV and momentum through

convection to reduce shear

Review of TT

Lower vortex - WEC– Wind <10 m/s– Weak baroclinic or remnant MCV– Couples with trough forcing to focus ascent– Stretching increases intensity (WISHE)

Review of TT

The Question

Do TCs initiated by TT events have different fundamental characteristcs that those whose genesis follows a more traditional “tropical”

pathway?

Genesis frequencyPeak intensityStorm longevityLikelihood of ET... ?

Data and MethodologyDefine objective indicators of TT:

– Upper level Q-vector convergence

– Lower level thermal asymmetry

Both are indicators of key components of the Davis and Bosart (2004) TT conceptual model

Data and MethodologyDefine objective indicators of TT:

– Upper level Q-vector convergence

– Lower level thermal asymmetry

Q-vector convergence represents:

– Trough-induced synoptic scale ascent

– Mid-level moistening (reduces downdrafts)

Data and MethodologyDefine storm-centred objective indicators of

TT:– Upper level Q-vector convergence

– Lower level thermal asymmetry Thermal asymmetry represents:

– Baroclinicity of percursor vortex– Focusing mechanism for ascent– Discriminates between baroclinic and MCV

precursors in WEC cases

Data and MethodologyDatasets (1948-2004)

– NCEP/NCAR Reanalysis

– NHC Best Track

Compute linear back-trajectories for storm centre locations from T-0h (NHC tracking) to T-36h

– NHC Best Track

Data and MethodologyCompute storm-

centered diagnostics at 6- hourly intervals along the back- trajectory

Sample T-12h diagnostic plots for

Hurricane Diana (1984). Top left: DT

potential temperature and winds. Top

right: 1000-700 hPa thickness and winds.

Bottom left: 850-700 hPa relative

vorticity and nondivergent winds. Bottom

right: Q-vectors, Q-vector divergence and

relative humidity (contoured). Plots from

T-72h to T+24h are available at http://www.atmos.albany.edu/facstaff/rmctc/ttclim/indexd.php

Data and MethodologyCompute storm-

centered diagnostics at 6- hourly intervals along the back- trajectory

Sample T-12h diagnostic plots for

Hurricane Diana (1984). Top left: DT

potential temperature and winds. Top

right: 1000-700 hPa thickness and winds.

Bottom left: 850-700 hPa relative

vorticity and nondivergent winds. Bottom

right: Q-vectors, Q-vector divergence and

relative humidity (contoured). Plots from

T-72h to T+24h are available at http://www.atmos.albany.edu/facstaff/rmctc/ttclim/indexd.php

Data and Methodology

Q-vector for:

Time series of Q-vector metric for Hurricane Diana (1984)

Q-vector for:

Genesis events categorized by the T-36h to T-0h trajectories of the metrics– Latent Class Analysis (LCA)

– Both the magnitude and the shape of the metric series is considered during grouping

TT is based on the structural evolution of the trough and lower level vortex

Although events A and C have nearly identical means, the LCA will group A with B because of their similar trajectories– Provides physically consistent groupings

The metrics are conditioned against each other for the final set of groups

Results - ClassificationThe optimal division of the dataset is:

3 Thickness Groups 7 Q-vector Groups

Time Time

T-36h T-00hT-36hT-36h T-00h

Results - ClassificationPhysically based synthesis of the groups

yields 6 basic categories:

Results - ClassificationTotal 591 storms in the NHC Atlantic archive:

Strong TT

Weak TT

Trough Induced

Perturbed

Wave Induced

Tropical Development

Genesis Category Events

% Total

Results – Genesis Locations

Strong TT Weak TT Tr Induced

TropicalWave InducedPerturbed

Results – Track Density

Results – Maximum Intensity

Summary

Objective method for identifying tropical / midlatitude interactions during genesis– Based on TT conceptual model:

Q-vector convergence Lower/midlevel thickness asymmetry

– Groupings based on evolution as well as magnitude of the metrics

Identified 6 genesis modes in 591 cases

Conclusions

TT accounts for ~30% of genesis events in the Atlantic Basin

TT events are localized in space near the North American continent

Storms that form from TT tend to be weaker and to have shorter tracks and lifetimes

Strong TT cases are more likely to undergo ET

Lots more analysis to be done ...http://www.atmos.albany.edu/facstaff/rmctc/ttclim/indexd.php

Review of TT

Lower/midlevel vortex - SEC– Near-surface windspeed > 10 m/s (WISHE)

– Elevates near-surface equivalent potential temperature

– Redistributes PV and momentum through convection to reduce shear

Review of TT

Lower/midlevel vortex - WEC– Near-surface windspeed < 10 m/s

– Weak baroclinic or remnant MCV

– Couples with trough forcing to focus ascent

– Stretching increases intensity (WISHE)

Review of TT

Tropical Transition Climatology R. McTaggart-Cowan, L. F. Bosart, C. A. Davis and G. Deane.

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