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Caribbean/Central American Hurricane Landfall Probabilities Phil Klotzbach

Caribbean/Central American Hurricane Landfall Probabilities Phil Klotzbach Department of Atmospheric Science Colorado State University Climate Diagnostics and Prediction Workshop October 27, 2009. Basic Premise:

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Caribbean/Central American Hurricane Landfall Probabilities Phil Klotzbach

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  1. Caribbean/Central American Hurricane Landfall Probabilities Phil Klotzbach Department of Atmospheric Science Colorado State University Climate Diagnostics and Prediction Workshop October 27, 2009

  2. Basic Premise: Caribbean and Central American hurricane activity is related to Atlantic basin seasonal hurricane forecasts. More active tropical cyclone seasons as predicted by the Tropical Meteorology Project (CSU) tend to have more landfalling hurricanes.

  3. 49.75 Hurricane Days Top 10 August Hindcasts (1900-2005) HURRICANE TRACKS 1.75 Hurricane Days Bottom 10 August Hindcasts (1900-2005) HURRICANE TRACKS

  4. 28.25 Hurricane Days Top 5 June Forecasts (1984-2008) Bottom 5 June Forecasts (1984-2008) 3.25 Hurricane Days

  5. Caribbean/Central America Probabilities • Climatological and current-year probabilities of a named storm, hurricane and major hurricane within 50 miles and 100 miles of each island or landmass • 50-Year Probabilities

  6. Historical Probability Calculation Steps - Select all tropical cyclones that tracked within 50 and 100 miles of each island or landmass during the 20th century Assign the maximum intensity of the tropical cyclone that was reached within 50 or 100 miles of the landmass - Calculate climatological probabilities using the Poisson distribution (e.g., EP = px/epx!) where EP = Expected Probability p = Annual average number of tropical cyclones that have occurred in the 20th century x = Number of storms expected in the upcoming year based on the Poisson formula - For Barbados, 26 named storms tracked within 50 miles of Barbados during the 20th century, and therefore, the Poisson distribution gives the climatological probability of one or more named storms making landfall as 23%

  7. 50 Miles 100 Miles

  8. Current-Year Probability Calculations 50-Year Probability Calculations Multiply the historical number of storms that occurred over the 20th century by predicted Net Tropical Cyclone activity (where 100% is defined to be an average season) For example, for Barbados, if 26 named storms formed during the 20th century and the predicted NTC was 150%, the current-year probability would be calculated based on 39 named storms (32%) Apply the Poisson distribution to this new number of storms • Apply the binomial distribution to the annual-average probabilities (e.g., 50-Year Prob. = 1 - (1 - One-Year Prob.)50 • For example, if the individual-year probability is 2%, the 50-year probability would be: 50-Year Prob. = 1 - (1 – 0.02)50 = 63%

  9. Current Year and Climatological Probabilities (1900-2000) Climatological probabilities are in parentheses

  10. 50-Year Probabilities

  11. Caribbean Activity – Ranked by Observed NTC (1900-2007)

  12. Caribbean Activity – Based on August Hindcast NTC (1900-2007)

  13. Caribbean Probability – Based on Poisson Distribution

  14. ? 1860 1900 1940 1980 2020 Goldenberg et al. (2001)

  15. 86 Major Hurricane Days POSITIVE AMO ATLANTIC THC STRONG 79 Years CAT 3-4-5 TRACKS 30 Major Hurricane Days NEGATIVEAMO ATLANTIC THC WEAK 78 Years CAT 3-4-5 TRACKS

  16. Positive AMO Negative AMO

  17. Positive AMO Negative AMO

  18. TEN COLDEST ASO NINO 3.4 (1900-2008) 56.75 Hurricane Days TEN WARMEST ASO NINO 3.4 (1900-2008) 5.5 Hurricane Days

  19. TWENTY COLDEST ASO NINO 3.4 (1900-2008) 105.5 Hurricane Days TWENTY WARMEST ASO NINO 3.4 (1900-2008) 28.5 Hurricane Days

  20. Caribbean Activity – Based on ASO Nino 3.4 (1900-2007)

  21. Future Work • Investigate precursor steering current patterns for Caribbean/Central American landfall • Create shorter period user-selected probabilities for landfall using climatological storm frequency in the Caribbean/Central America

  22. Arago’s Admonition: “Never, no matter what may be the progress of science, will honest scientific men who have regard for their reputations venture to predict the weather.”

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