julia h. keller¹, sarah c. jones¹ and patrick a. harr² · julia h. keller¹, sarah c. jones¹...

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High Impact Weather

The Eddy Kinetic Energy Budget for Several Forecast Scenarios of the Extratropical

Transition of two Tropical Cyclones

Julia H. Keller¹, Sarah C. Jones¹ and Patrick A. Harr²¹ Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany Current affiliation: Deutscher Wetterdienst (DWD), Offenbach, Germany2 Naval Postgraduate School, Monterey, CA, USA

Fourth International Workshopon Extratropical Transition

Mont Gabriel Lodge, Quebec, Canada24 May 2012

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High Impact Weather Motivation

Eddy kinetic energy and energy flux for TY Nabi 2005 (Harr & Dea, 2009)

TC

Impact on mid-latitudes

ET event may strongly influence midlatitude flow

Harr & Dea (2009) examined the impact of several TCs on the midlatitude flow in an eddy kinetic energy frame work

Waves and Cyclones: Maxima of Ke

Downstream propagation: Steered by Ke fluxes(Downstream baroclinic development,

Orlanski&Sheldon, 1995)

Transitioning TC may act as additional source of Ke, enforcing an amplification of the midlatitude wave pattern

Eddy kinetic energy (Ke): Deviations from monthly mean

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High Impact Weather Motivation

Here: Apply analysis method to members from ECMWF EPS

Examine several forecast scenarios for same ET event

Recent studies of ET using Ke were based on analysis data

Only hypothesize about other possible developments

Investigate different development scenarios for the same transitioning TC

Identify processes that cause the distinct developments

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High Impact Weather Analysis Technique

Investigate Tendencies for Eddy Kinetic Energy (Ke)

(Orlanski & Sheldon, 1995)

Vertically integrated Ke budget highlights downstream propagation

Ke maxima at trough and ridge flanks Budget terms indicate accumulation or dispersion of Ke

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Transitioning storm can provide additional Ke

to sustain upstream maxima


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Vertically integrated Ke budget is affected by:

Ke Tendency Convergence of ageostrophic

geopotential flux


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Convergence of the ageostrophic geopotential flux

ageostrophic wind va' :

upstream in trough

downstream in ridge

perturbation of geopotential Φ' :

negative in trough

positive in ridge

Acceleration towards lower heights: Gain of Ke

Deceleration towards higher heights: Loss of Ke

Downstream propagation of wave by group velocity

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Vertically integrated Ke budget is affected by:

Ke Tendency Convergence of ageostrophic

geopotential flux

Baroclinicconversion

Convergenceof advective flux


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Baroclinic conversion

Convergence of advective Ke flux

Generation of Ke:

Ascending warm air

Descending cold air

Advection of Ke :Downstream propagationof maxima byphase velocity

Loss of Ke

Accumulation of Ke

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High Impact Weather Ke budget during ET

Extract scenarios from ECMWF EPS forecast using EOF-/cluster analysis (Keller et al., 2011)

Determine representative members for interesting scenarios

Investigate Ke budget to identify differences during ET

Investigate different forecast scenarios for same ET event

Two different scenarios for Hurricane Hanna (2008)

Four different scenarios for Typhoon Choi-Wan (2009)

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High Impact Weather Selected ensemble forecast

for Hurricane Hanna

ECMWF EPS forecast, initialized 5 Sep 2008, 00 UTC 54 h prior to ET

Forecast uncertainty downstream of transitioning Hanna

Standard deviation of 500 hPa geopotential height

Hanna in members

ET

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for Hurricane Hanna


Forecast uncertainty downstream of transitioning Hanna


Hanna in members

ETClustering Time

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High Impact Weather Two contrasting scenarios for

Hurricane Hanna

(Time relative to phase of ET not to forecast time)

Scenario II 12 UTC 7 Sep 08Scenario I 00 UTC 7 Sep 08

500 hPageopotential height

& mean slp

Ke(shaded, J/m²),

total flux (arrows)

& total gain of Ke (cont., a 50 W/m²)

Ke(shaded, J/m²),

& baroclinic conversion of Ke

(cont., a 50 W/m²)

*105

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Hurricane Hanna




& mean slp

Ke(shaded, J/m²),

total flux (arrows)


Ke(shaded, J/m²),


(cont., a 50 W/m²)

*105

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High Impact Weather Scenarios for Hurricane Hanna

- Summary -Scenario I, ave. 40-60°N Scenario II, ave. 40-60°N

Tim

eKe(shaded, J/m²)

baroclinic conversion(cont., a 50 W/m²)

Meridional velocity, 500 hPa (m/s)

southward

northward

Ke(shaded, J/m²)

ageo. geopot. flux(cont., a 50 W/m²)

Storm < 40°NStorm > 40°N

20

10

30

40

50

*105

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High Impact Weather Scenarios for Hurricane Hanna

- Summary -Scenario I, ave. 40-60°N Scenario II, ave. 40-60°N

Tim

eKe(shaded, J/m²)


Ke(shaded, J/m²)

ageo. geopot. flux(cont., a 50 W/m²)

Ongoingbaroclinic

conversion

Similardivergence

Storm > 40°NStorm < 40°N


southward

northward

20

10

30

40

50

*105

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High Impact Weather Results

Hurricane Hanna

Duration of baroclinic conversion during ET process crucial for amplification of shortwave trough and downstream wave pattern

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for Typhoon Choi-Wan


Strong increase in forecast uncertainty downstream of Choi-Wan


Choi-Wan in members

ET

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for Typhoon Choi-Wan


Strong increase in forecast uncertainty downstream of Choi-Wan


Choi-Wan in members

ETClustering Time

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Typhoon Choi-Wan



500 hPageopotential height &

mean sea level pressure

Ke(shaded, J/m²),

total flux (arrows)


Ke(shaded, J/m²),


(cont., a 50 W/m²)

*105

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Typhoon Choi-Wan





Ke(shaded, J/m²),

total flux (arrows)


Ke(shaded, J/m²),


(cont., a 50 W/m²)

*105

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Typhoon Choi-Wan



*105



Ke(shaded, J/m²),

total flux (arrows)


Ke(shaded, J/m²),


(cont., a 50 W/m²)

*105

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Typhoon Choi-Wan


Scenario I 00 UTC 22 Sep 09

*105

Scenario II 00 UTC 22 Sep 09



Ke(shaded, J/m²),

total flux (arrows)


Ke(shaded, J/m²),


(cont., a 50 W/m²)

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High Impact Weather Scenarios for Typhoon Choi-Wan

- Summary -

Tim

eKe(shaded, J/m²)


Ke(shaded, J/m²)

Ageo. Geopot flux.(cont., a 50 W/m²)

Scenario II, ave. 30-60°NScenario I, ave. 30-60°N

Storm > 30°NStorm < 30°NExtratropicalx


southward

northward

20

10

30

40

50

*105

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- Summary -

Tim

eKe(shaded, J/m²)


Ke(shaded, J/m²)


Scenario II, ave. 30-60°NScenario I, ave. 30-60°N

Downstreamdispersion


20

10

30

40

50

*105


southward

northward

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- Summary -

Tim

eKe(shaded, J/m²)


Ke(shaded, J/m²)


Scenario IV, ave. 30-60°NScenario III, ave. 30-60°N



southward

northward

20

10

30

40

50

*105

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High Impact Weather

Hurricane Hanna

Duration of baroclinic conversion during ET was crucial for amplification of shortwave trough and downstream wave pattern

Typhoon Choi-Wan

Phasing with midlatitude flow and merging with preexisting extratropical cyclone influenced impact on midlatitudes

Sensitivity of midlatitude flow to interaction with a TC seems to be restricted to a short period of time (~ 2 days)

Summary

+12 hrs

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High Impact Weather

Sensitivity experiments

Apply ensemble sensitivity analysis (Hakim&Torn, 2008) to identify correlation, i.e. between amplification of downstream trough and energy flux emanating the transitioning TC

Outlook

First Example: Correlation between 500 hPa geopotential height fieldand Ke, averaged over box around storm

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High Impact Weather

Explore characteristics of TIGGE in representing forecast uncertainty during ET events:

Increased forecast variability in multimodel approach?

Broader range of possible development scenarios

Characteristic contributions from individual constituent EPS to overall variability?

Forecasting ET events with TIGGE

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High Impact Weather

Analysis Approach

Multimodel forecasts, containing eight of ten TIGGE EPS Application of EOF- and Cluster-Analysis to ten forecasts for

five ET cases in 2008 Compare TIGGE, ECMWF and TIGGE w/o EC

Main Outcome of the Study

Constituing TIGGE EPS contribute differently to forecast variability and hence also to the several extracted development scenarios (clusters)

TIGGE and ECMWF often show distinct patterns of dominant variability Typical groupings of the EPS in the clusters could be identified

TIGGE contains broader variations and thus offers more possible development scenarios, but ECMWF is necessary to obtain full scope of variations

?


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PANDOWAE

High Impact Weather

Analysis Approach

Multimodel forecasts, containing eight of ten TIGGE EPS Application of EOF- and Cluster-Analysis to ten forecasts for

five ET cases in 2008 Compare TIGGE, ECMWF and TIGGE w/o EC

Main Outcome of the Study

Constituing TIGGE EPS contribute differently to forecast variability and hence also to the several extracted development scenarios (clusters)

TIGGE and ECMWF often show distinct patterns of dominant variability Typical groupings of the EPS in the clusters could be identified

TIGGE contains broader variations and thus offers more possible development scenarios, but ECMWF is necessary to obtain full scope of variations

?


Keller, J. H., S. C. Jones, J. L. Evans, and P. A. Harr (2011):

Characteristics of the TIGGE multimodel ensemble prediction system in representing forecast variability associated with extratropical transition

Geophys. Res. Lett., 38, L12802

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High Impact Weather

Picture taken during T-PARC

THANK YOU FOR YOUR ATTENTION!

Contact: [email protected]

Thanks to Jay Cordiera and HeatherArchambault for valuable discussions

julia h. keller¹, sarah c. jones¹ and patrick a. harr² · julia h. keller¹, sarah c. jones¹...

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