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Modifying TC Energy Metrics: Using Wind Radii to Better Estimate TC Induced Heating Philippe Papin.

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Presentation on theme: "Modifying TC Energy Metrics: Using Wind Radii to Better Estimate TC Induced Heating Philippe Papin."— Presentation transcript:

1 Modifying TC Energy Metrics: Using Wind Radii to Better Estimate TC Induced Heating Philippe Papin

2 Namias (1955) – Correlation between TC activity and changes with general circulation Emanuel (2001) – Meridional overturning circulation (MOC) driven by global TC activity Sriver and Huber (2010) – Uses global climate model with QuickScat wind data to estimate general circulation impact due to TCs Main Message: TCs are important to climate and can have a major influence on oceanic and atmospheric circulations on large time scales. Thus its important to quantify TC energy in a given season to infer impact on general circulations. Meridional Overturning Circulation

3 Power Dissipation Index (PDI) V max = Max Sustained Winds Integrate over Lifespan of Storm Winds cubed to account for relationship of wind and kinetic energy dissipation rate due to friction Emanuel (1998) Values summed for each year Very similar energy metric compared to Accumulated Cyclone Energy (ACE) PDI preferred to ACE since cubing the wind has a given mathematical relationship with power dissipation Emanuel (2005) Bell et al. (2000)

4 Emanuel (2007) Villarini and Vecchi (2012) Emanuel (2007) applies a smoothing metric in order to reveal high correlation with sea surface temperatures (SSTs) RAW yearly Atlantic PDI calculated in Villarini and Vecchi (2012) Will Focus on 2004-2011 Period (highlighted) One thing PDI does not account for is wind field area of TC. Emanuel (2005): No dataset available for proper assessment

5 Revised Atlantic Hurricane Database (HURDAT2) Contains information about storm wind field (since 2004) at synoptic times (0000, 0600, 1200, 1800 UTC) Wind field divided up into four quadrants and three categories (see figure) 300 mi (555.6 km) 150 mi (277.8 km) 75 mi (138.9 km) 140 mi (259.3 km) 75 mi (138.9 km) 30mi (55.6 km) 80 mi (148.2 km) 30mi (55.6 km) 50 mi (92.6 km) 120 mi (222.2 km) 220 mi (407.4 km) 17.5 m s -1 25.7 m s -1 32.9 m s -1 TS Force HU Force Dataset allows for practical application of calculating wind area for PDI

6 Wind Field Power Dissipation Index (WF_PDI) VA tot = total wind field (winds x area) Each area bin must be calculated seperately Note that maximum sustained winds are not used just area averaged wind magintude

7 Good correlation (R=0.85) Some years don’t match up well (e.g. 2006, 2007) Relationship still shows even after normalization Note different units

8 Florence, Gordon, Helene Dominate total PDI and WF_PDI calculations Note that Florence experiences a large change in the total seasonal contribution going from PDI to WF_PDI Gordon experiences the opposite change What's going on here?

9 Hurricane FlorenceHurricane Gordon 17.5 m s -1 25.7 m s -1 32.9 m s -1 TS Force HU Force Florence is a much larger TC than Gordon, despite also being weaker PDI will be higher for Gordon (greater maximum sustained winds) WF_PDI will be higher for Florence (much larger areal extent of winds) TC areal statistics from Kimball and Mulekar (2004)

10 Average Heating Rate (in Watts) can be calculated by multiplying by the density of air (1 kg m -3 ) and dividing by the total number of times TCs were observed (in seconds) Note minima in heating rate don’t necessary correspond to maxima in PDI or WF_PDI Actually due to an error in my calculations. I need to divide by the entire season, not just when TCs are occurring

11 Modified Plot Should Match up very closely with WF_PDI but now units are in Watts Note no drag coefficient was applied to this calculation, so values of WF_PDI and Heating Rate are likely high by several orders of magnitude See Emanuel (1998)

12 TCs have impact on ocean and atmospheric general circulation on large time scales (seasons) PDI better metric to use than ACE given mathematical relationship with power dissipation HURDAT2 dataset allows for creation of new area-based PDI (WF_PDI) Differences between PDI and WF_PDI related to size of TCs (WF_PDI allows more accurate energy metric since it captures entire wind field!) Heating rate of TCs can then be calculated – Only an estimation and calculation not perfected yet! One Last Thought on importance on TC size on energy calculations 2010 TC Nicole (minimal TC) has a higher energy output than 2010 TC Karl (high end cat. 3)! Suggests that ACE and PDI metrics be modified to account for area extent in TCs to produce more accurate energy calculations!


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