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The Ingredients Based Tornado Parameter Matt Onderlinde

The Ingredients Based Tornado Parameter Matt Onderlinde

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Page 1: The Ingredients Based Tornado Parameter Matt Onderlinde

The Ingredients Based Tornado Parameter

Matt Onderlinde

Page 2: The Ingredients Based Tornado Parameter Matt Onderlinde

Motivation

• At least 550 fatalities due to tornadoes in the US in 2011

http://www.noaanews.noaa.gov/2011_tornado_information.html

• SPC maintains an extensive tornado database which can be compared to NCEP model analyses

• I attempt to derive statistical relationships between tornadoes and model variables

Page 3: The Ingredients Based Tornado Parameter Matt Onderlinde

Hypothesis

• Existing metrics for tornado parameters exist. Would the consideration of additional environmental factors improve these parameters?

• Can we use the SPC tornado reports database and model analyses to derive a parameter directly?

Page 4: The Ingredients Based Tornado Parameter Matt Onderlinde

Study DomainAll tornado reports and RUC analyses data are regridded to the grid shown here. The IBTP is calculated on this grid along with the SPC’s significant tornado parameter (STP) for comparison.

Page 5: The Ingredients Based Tornado Parameter Matt Onderlinde

Variables to consider• CAPE• CIN• 0-6 km vector wind shear• 0-1 km vector wind shear• 2 m temperature• 2m dew point• LCL height

• 0-1 km SRH• 0-3 km SRH• 1000-850 mb mean RH• 850-600 mb lapse rate• 850-700 mb lapse rate• Surface moisture

convergence

Variables considered by STP• CAPE• CIN• Effective Bulk Shear

• Effective SRH• LCL Height

STP = (mlCAPE/1500 J kg-1) * ((2000-mlLCL)/1000 m) * (ESRH/150 m2 s-2) * (EBWD/20 m s-1) * ((200+mlCIN)/150 J kg-1)

Plus if-statements….

Page 6: The Ingredients Based Tornado Parameter Matt Onderlinde

Methodology

• Calculate each model variable from the previous slide on our grid for the time of all tornadoes in the Plains (2005 – 2009)- Note, 2010 will be used for independent verification

• RUC analyses are used• Correlate all variables with each other and

check for inter-correlations• Correlate all variables with tornado occurrence

Page 7: The Ingredients Based Tornado Parameter Matt Onderlinde

Methodology

• Normalize each variable according to how frequently specific ranges of that variable occur (example in a minute)

• Make histograms of our normalized variables and then fit functions to the height of the bins

• Use these functions to scale each variable between 0 and 1 so we can use each variable as a predictor

Page 8: The Ingredients Based Tornado Parameter Matt Onderlinde

Methodology

• Multiply each scaled variable (now ranging between 0 and 1) together to get a “tornado potential value” between 0 and 1– This allows us to effectively deal with “necessary

but insufficient” atmospheric variables

Page 9: The Ingredients Based Tornado Parameter Matt Onderlinde

Scaled variable histogram

2 m dew point (F)

Normalization process draws out the true relationship between dew point and tornadoes

Page 10: The Ingredients Based Tornado Parameter Matt Onderlinde

Scaled variable histograms (examples)

Generally accept the red curve, however there are exceptions, like CAPE

So when the IBTP is calculated, each variable is scaled based on the red curves

Page 11: The Ingredients Based Tornado Parameter Matt Onderlinde

Results and VerificationCorrelation with Tornadoes

There are high inter-correlations between some variables. For example the 2 lapse rates are highly correlated with each other.

The final variables chosen for the IBTP were : 1) CONVECTIVE AVAILABLE POTENTIAL ENERGY (CAPE)2) LOW LEVEL RELATIVE HUMIDITY3) 0-1 KM STORM RELATIVE HELICITY4) 850-700 MB LAPSE RATE5) 2 M DEW POINT6) 2 M TEMPERATURE7) LCL HEIGHT8) MOISTURE CONVERGENCE9) 0-6 KM VECTOR WIND SHEAR

Page 12: The Ingredients Based Tornado Parameter Matt Onderlinde

Results and Verification

• IBTP correlates slightly better than STP for Plains tornadoes in 2010

• IBTP and STP values on the Plains grid are compared directly with the number of tornadoes that occur in the grid box during the forecast hour

Page 13: The Ingredients Based Tornado Parameter Matt Onderlinde

Specifics of Verification Correlations

• Clearly there are thousands of grid points where no tornadoes occur… (532 tornadoes in 2010, versus 198,188 null points)

• So if the parameter just forecasted 0 for all points at all times, it would correlate well with the gridded tornado reports

• To get a sense of actual skill, I randomly select 532 null grid points and include them in the correlation calculation... So correct negative forecasts count equally as much as correct positive forecasts

• I repeat this process 2000 times in a loop and average the correlation coefficients

Page 14: The Ingredients Based Tornado Parameter Matt Onderlinde

Example Case – May 10, 2010

Both IBTP and STP nicely capture the spatial extent of the tornadoes. Note that the 2 parameters are snapshots at 21 UTC whereas the SPC reports are for the entire day.

Case studies are good but comprehensive statistical verification is desired to determine which parameter best predicts tornado likelihood.

Page 15: The Ingredients Based Tornado Parameter Matt Onderlinde

Example 2 – May 19, 2010

Page 16: The Ingredients Based Tornado Parameter Matt Onderlinde

Future Work

• Double, Triple check that I’ve calculated these correlations accurately

• Add 2011 into the independent verification• Publish?

Page 17: The Ingredients Based Tornado Parameter Matt Onderlinde

Example 3 – June 8, 2010