Julia H. Keller¹, Sarah C. Jones¹ and Patrick A. Harr²

Transcription

1 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. Harr² ¹ Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany Current affiliation: Deutscher Wetterdienst (DWD), Offenbach, Germany 2 Naval Postgraduate School, Monterey, CA, USA Fourth International Workshop on Extratropical Transition Mont Gabriel Lodge, Quebec, Canada 24 May 2012

2 Motivation 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 Eddy kinetic energy (Ke): Deviations from monthly mean on mid-latitudes Waves and Cyclones: Maxima of Ke Downstream propagation: Steered by Ke fluxes (Downstream baroclinic development, Orlanski&Sheldon, 1995) TC Transitioning TC may act as additional source of Ke, enforcing an amplification of the midlatitude wave pattern Eddy kinetic energy and energy flux for TY Nabi 2005 (Harr & Dea, 2009)

3 Motivation 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 Here: Apply analysis method to members from ECMWF EPS Investigate different development scenarios for the same transitioning TC Identify processes that cause the distinct developments

4 Analysis Technique Investigate Tendencies for Eddy Kinetic Energy (Ke) Vertically integrated Ke budget highlights downstream propagation Ke maxima at trough and ridge flanks Budget terms indicate accumulation or dispersion of Ke (Orlanski & Sheldon, 1995)

5 Analysis Technique Investigate Tendencies for Eddy Kinetic Energy (Ke) Vertically integrated Ke budget highlights downstream propagation Ke maxima at trough and ridge flanks Budget terms indicate accumulation or dispersion of Ke (Orlanski & Sheldon, 1995) Transitioning storm can provide additional Ke to sustain upstream maxima

6 Analysis Technique Investigate Tendencies for Eddy Kinetic Energy (Ke) Vertically integrated Ke budget highlights downstream propagation Ke maxima at trough and ridge flanks Budget terms indicate accumulation or dispersion of Ke (Orlanski & Sheldon, 1995) Transitioning storm can provide additional Ke to sustain upstream maxima Vertically integrated Ke budget is affected by: Ke Tendency Convergence of ageostrophic geopotential flux

7 Analysis Technique 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 Deceleration towards higher heights: Loss of Ke Downstream propagation of wave by group velocity Acceleration towards lower heights: Gain of Ke

8 Analysis Technique Investigate Tendencies for Eddy Kinetic Energy (Ke) Vertically integrated Ke budget highlights downstream propagation Ke maxima at trough and ridge flanks Budget terms indicate accumulation or dispersion of Ke (Orlanski & Sheldon, 1995) Transitioning storm can provide additional Ke to sustain upstream maxima Vertically integrated Ke budget is affected by: Ke Tendency Convergence of ageostrophic geopotential flux Baroclinic conversion Convergence of advective flux

9 Analysis Technique Baroclinic conversion Generation of Ke: Ascending warm air Descending cold air Convergence of advective Ke flux Loss of Ke Advection of Ke : Downstream propagation of maxima by phase velocity Accumulation of Ke

10 Ke budget during ET Investigate different forecast scenarios for same ET event 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 Two different scenarios for Hurricane Hanna (2008) Four different scenarios for Typhoon Choi-Wan (2009)

11 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

12 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 Clustering Time ET

13 Two contrasting scenarios for Hurricane Hanna Scenario I 00 UTC 7 Sep 08 Scenario II 12 UTC 7 Sep hpa geopotential height & mean slp total flux (arrows) & total gain of Ke & baroclinic conversion of Ke *105 (Time relative to phase of ET not to forecast time)

14 Two contrasting scenarios for Hurricane Hanna Scenario I 00 UTC 7 Sep 08 Scenario II 12 UTC 7 Sep hpa geopotential height & mean slp total flux (arrows) & total gain of Ke & baroclinic conversion of Ke *105 (Time relative to phase of ET not to forecast time)

15 Two contrasting scenarios for Hurricane Hanna Scenario I 00 UTC 8 Sep 08 Scenario II 12 UTC 8 Sep hpa geopotential height & mean slp total flux (arrows) & total gain of Ke & baroclinic conversion of Ke *105 (Time relative to phase of ET not to forecast time)

16 Two contrasting scenarios for Hurricane Hanna Scenario I 00 UTC 8 Sep 08 Scenario II 12 UTC 8 Sep hpa geopotential height & mean slp total flux (arrows) & total gain of Ke & baroclinic conversion of Ke *105 (Time relative to phase of ET not to forecast time)

17 Two contrasting scenarios for Hurricane Hanna Scenario I 00 UTC 10 Sep 08 Scenario II 12 UTC 10 Sep hpa geopotential height & mean slp total flux (arrows) & total gain of Ke & baroclinic conversion of Ke *105 (Time relative to phase of ET not to forecast time)

18 Scenarios for Hurricane Hanna - Summary - Meridional velocity, 500 hpa (m/s) Scenario I, ave N Scenario II, ave N south ward north ward Ke(shaded, J/m²) baroclinic conversion Time Storm < 40 N Storm > 40 N Ke(shaded, J/m²) *105 ageo. geopot. flux

19 Scenarios for Hurricane Hanna - Summary - Meridional velocity, 500 hpa (m/s) Scenario I, ave N Scenario II, ave N south ward north ward Ke(shaded, J/m²) baroclinic conversion Time Storm > 40 N Storm < 40 N Ongoing baroclinic conversion Ke(shaded, J/m²) ageo. geopot. flux *105 Similar divergence

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

21 Selected ensemble forecast for Typhoon Choi-Wan ECMWF EPS forecast, initialized 15 Sep 2009, 00 UTC 132 h prior to ET Strong increase in forecast uncertainty downstream of Choi-Wan Standard deviation of 500 hpa geopotential height Choi-Wan in members ET

22 Selected ensemble forecast for Typhoon Choi-Wan ECMWF EPS forecast, initialized 15 Sep 2009, 00 UTC 132 h prior to ET Strong increase in forecast uncertainty downstream of Choi-Wan Standard deviation of 500 hpa geopotential height Choi-Wan in members Clustering Time ET

23 Two contrasting scenarios for Typhoon Choi-Wan Scenario I 00 UTC 20 Sep 09 Scenario II 00 UTC 20 Sep hpa geopotential height & mean sea level pressure total flux (arrows) & total gain of Ke & baroclinic conversion of Ke *105 (Time relative to phase of ET not to forecast time)

24 Two contrasting scenarios for Typhoon Choi-Wan Scenario I 00 UTC 20 Sep 09 Scenario II 00 UTC 20 Sep hpa geopotential height & mean sea level pressure total flux (arrows) & total gain of Ke & baroclinic conversion of Ke *105 (Time relative to phase of ET not to forecast time)

25 Two contrasting scenarios for Typhoon Choi-Wan Scenario I 12 UTC 20 Sep 09 Scenario II 12 UTC 20 Sep hpa geopotential height & mean sea level pressure total flux (arrows) & total gain of Ke & baroclinic conversion of Ke *105 (Time relative to phase of ET not to forecast time)

26 Two contrasting scenarios for Typhoon Choi-Wan Scenario I 12 UTC 20 Sep 09 Scenario II 12 UTC 20 Sep hpa geopotential height & mean sea level pressure total flux (arrows) & total gain of Ke & baroclinic conversion of Ke *105 (Time relative to phase of ET not to forecast time)

27 Two contrasting scenarios for Typhoon Choi-Wan Scenario I 00 UTC 21 Sep 09 Scenario II 00 UTC 21 Sep hpa geopotential height & mean sea level pressure total flux (arrows) & total gain of Ke & baroclinic conversion of Ke *105 (Time relative to phase of ET not to forecast time)

28 Two contrasting scenarios for Typhoon Choi-Wan Scenario I 00 UTC 21 Sep 09 Scenario II 00 UTC 21 Sep hpa geopotential height & mean sea level pressure total flux (arrows) & total gain of Ke & baroclinic conversion of Ke *10 *105 5 (Time relative to phase of ET not to forecast time)

29 Two contrasting scenarios for Typhoon Choi-Wan Scenario I 00 UTC 22 Sep 09 Scenario II 00 UTC 22 Sep hpa geopotential height & mean sea level pressure total flux (arrows) & total gain of Ke & baroclinic conversion of Ke *105 (Time relative to phase of ET not to forecast time)

30 Scenarios for Typhoon Choi-Wan - Summary - Meridional velocity, 500 hpa (m/s) Scenario I, ave N Scenario II, ave N south ward north ward Ke(shaded, J/m²) baroclinic conversion Time Storm > 30 N Storm < 30 N x Extratropical Ke(shaded, J/m²) *105 Ageo. Geopot flux.

31 Scenarios for Typhoon Choi-Wan - Summary - Meridional velocity, 500 hpa (m/s) Scenario I, ave N Scenario II, ave N south ward north ward Ke(shaded, J/m²) baroclinic conversion Time Storm > 30 N Storm < 30 N x Extratropical Ke(shaded, J/m²) Ageo. Geopot flux. *105 Downstream dispersion

32 Scenarios for Typhoon Choi-Wan - Summary - Meridional velocity, 500 hpa (m/s) Scenario III, ave N Scenario IV, ave N south ward north ward Ke(shaded, J/m²) baroclinic conversion Time Storm > 30 N Storm < 30 N x Extratropical Ke(shaded, J/m²) *105 Ageo. Geopot flux.

33 Summary 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) +12 hrs

34 Outlook 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 First Example: Correlation between 500 hpa geopotential height field and Ke, averaged over box around storm

35 Forecasting ET events with TIGGE 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?

36 Forecasting ET events with TIGGE? 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

37 Forecasting ET events with TIGGE Analysis Approach Multimodel forecasts, containing eight of ten TIGGE EPS Application of EOF- and Cluster-Analysis to ten forecasts for Keller, J. H.,five S. C. J L. Evans, and P. A. Harr (2011): ETJones, cases in Compare TIGGE, ECMWF and TIGGE w/o EC Characteristics of the TIGGE multimodel ensemble prediction system in representing forecast variability associated with Main Outcome of the Study extratropical transition? Constituing EPS 38, contribute Geophys.TIGGE Res. Lett., L12802differently 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

38 THANK YOU FOR YOUR ATTENTION! Contact: Thanks to Jay Cordiera and Heather Archambault for valuable discussions Picture taken during T-PARC