1. 2013 Hurricane Season Predictions
Brandon Sherman
Vinicius Taguchi
Kehao Zhu

2. Purpose
Analysis
Methods
Model Selection
Results
Conclusion

3. Purpose
To accurately predict the number of hurricanes that will impact the United States during the 2013 hurricane season
Days Before Landfall
Error in miles 5
350 4
290 3
230 2
160 1
100
Damage from Hurricane Katrina in 2005
NOAA Data, 2004

4. Methods: Initial Model
Averaged 12 months covariates from January of previous year to December of previous year
e.g. Jan Dec to predict hurricane season
Started with all the covariates in the poisson regression model
Ignore any covariates which have NA values

5. Methods: Model Selection
BIC backward/forward(both) selections
AIC backward/forward(both) selections
Physical Model

6. Methods: Physical Model
MDRSST - MDR Sea Surface Temperature
MDRSLP - MDR Sea Level Pressure
MDRVWS - MDR Vertical Wind Shear
NINO4,NINO12 - El Niño/La Niña
AMO - Atlantic Multi-Decadal Oscillation
QBO - Quasi-Biennial Oscillation
AMM - Atlantic Meridional Mode
TSA,TNA,DM,GGST,NGST,SGST
- Global/Hemispheric Surface Temperatures

7. Methods: Cross-Validation
5-fold cross-validation for:
null model
full model
"BIC"-selected model
"AIC"-selected model
physical model

8. Results: Statistics

9. Results: Model Selection
Number of covariates
AIC
Error rates from 5-folds cross-validation
Null model
316.84
Full model 30
311.59
"BIC" selected model 6
307.98
"AIC" selected model 14
285.73
Physical Model 13
301.51

10. Conclusions BIC model most preferred Most parsimonious
Lowest cross-validation error
Atlantic Dipole Mode is the difference between TSA and TNA, so it appears the Atlantic Dipole Mode itself is sufficient for the model

11. Final Model Prediction for 2013: 7.458387 Landfalls Coefficients
Estimates
Intercept
Atlantic Multi-Decadal Oscillation
Atlantic Dipole Mode
El Niño - Region 4
Quasi-Biennial Oscillation
Prediction for 2013: Landfalls

13. Discussion Strength: Weakness:
relative simple model, easy to interpret
Weakness:
the method of averaging the covariates is arbitrary

14. Thank You For Listening

15. Works Cited Post-Katrina. N.d. Photograph. Design
Intentions. Web. 16 May 2013.
Samost, Aubrey. "Predicting Hurricanes: A Not
So Exact Science." Predicting Hurricanes.
Massachusetts Institute of Technology, n.d.
Web. 16 May 2013.
Satellite Image of Hurricane Fran. N.d.
Photograph. NASA. Geology.com. Web. 16
May 2013.