By: Michael Kevin Hernandez Key JTWC ET onset JTWC Post ET  Fig. 1: JTWC best track data on TC Sinlaku (2008). ECMWF analysis ET completion ECMWF analysis ET onset

Two primary reasons for studying Extratropical Transitions (ET) Societal Relevance Post Hurricane Noel caused floods and wind damage to Maryland and Eastern Quebec & Labrador Scientific Relevance ET can modulate the baroclinic zone, enhancing midlatitude cyclogenesis and associated high-impact weather (Danielsen 2004; Harr et al. 2008)

Literature review Veiga et al. (2008) used kinetic energy to calculate energetics of Hurricane Catarina (2004) Explored Kinetic Energy (KE) – use KE as a diagnostic here Kuo et al. (1990) used the NCAR/PSU MM5 model to explore the impact of diabatic processes on the development of a midlatitude cyclone Two different runs (regular and fake dry physics) – will also use this approach here

High resolution initial conditions Infrared satellite imagery 325K Ertel PV 500 hPa KE and geopotential height Fig. 2: Observed storm (left), 25 x 25km ECMWF resolution diagnostics (below) which will be fed into the model.

Model formulation for the simulations analyzed here Resolution: 9km (740 x 370), 3km (331 x 331) vortex following LW radiation: RRTM scheme SW radiation: Goddard scheme PBL physics: YSU scheme Surface layer: MM5 similarity Microphysics: WSM 5-class scheme Full physics Surface fluxes included Cumulus physics: Kain–Fritsch scheme (9km only) Fake dry Surface fluxes included no convection or grid scale precipitation

Diagnostics Kinetic Energy at 500mb Kinetic Energy at 500mb Other Parameters: MSLP, accumulated precip, ω, vertical wind shear, T v, θ e, θ e anomaly, RH, vorticity, Ertel PV etc. Other Parameters: MSLP, accumulated precip, ω, vertical wind shear, T v, θ e, θ e anomaly, RH, vorticity, Ertel PV etc.

Difference between the two model forecasts Fig. 3: Observed (black), full physics (pink) and fake dry (blue) simulated tracks for Typhoon Sinlaku.

Numerical Difference Table 1: Error metrics of distance [km] for each simulation of TC Sinlaku compared to the JTWC best track. Forecast time full physics fake dry n/a HR full physics fake dry n/a Table 2: Error metrics of minimum central pressure [hPa] for each simulation of TC Sinlaku compared to the JTWC best track.

Fig. 4: KE analyses from the ECMWF Analysis, Full Physics and Fake Dry runs at the 500 mb. The red dots show the storm and the black line shows the trough axis. Fake Dry Full Physics IR imagery ECMWF. Reanalysis. 500 hPa KE Forecast lead time 48 hr 24 hr 00 hr

Fig. 5: KE analyses from the ECMWF Analysis, Full Physics and Fake Dry runs at the 500 mb. The red dots show the storm and the black line shows the trough axis. IR imagery ECMWF Full Fake. Reanalysis Physics Dry 500 hPa KE Forecast lead time 96 hr 72 hr 48 hr

In the full physics run, the TC underwent ET ET completion time consistent with ECMWF analyses Trough to north of TC at 24h (simulation and analyses) Simulated trough moved eastwards much faster in subsequent 24h (transition phase) than analyzed (model fast) Model TC moved NNE (rather than NE) in this period, leading to significantly different wind structure Model TC moved due east from h (rather than ENE) giving smaller track errors at 72h than 48h Analyzed trough stronger and further east than full physics simulation at 72h (model slower) Very different evolution of trough in simulation than analyses Take home message from full physics simulation

In the fake dry run TC Sinlaku could no longer be tracked by 72 hours into the simulation Without latent heat continuously feeding the TC, it became shallower and died Advected northwards by the low-level steering current TC west of trough axis by 24h and there was no interaction of the trough with the storm Subtropical high became much stronger than in the full physics Take home message from fake dry simulation

Cloud permitting simulations of the ET of Typhoon Sinlaku initializing with high resolution ECMWF reanalysis focused on the 500 hPa trough with and without latent heating with the storm filtered out QG diagnostics to evaluate the impact of diabatic heating on ET Future work

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