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Hurricane Track Effects on Supply Distribtuion

Hurricane Track Effects on Supply Distribtuion. Student Author - Anonymous MEA 593—Term Project May 9, 2013. Background. Emergency supply distribution sector Corporations: Stock up on emergency supplies Wal-Mart, Kmart, Costco, etc. Disaster relief agencies: First aid personnel

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Hurricane Track Effects on Supply Distribtuion

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  1. Hurricane Track Effects on Supply Distribtuion Student Author - Anonymous MEA 593—Term Project May 9, 2013

  2. Background • Emergency supply distribution sector • Corporations: • Stock up on emergency supplies • Wal-Mart, Kmart, Costco, etc. • Disaster relief agencies: • First aid personnel • American Red Cross, Salvation Army, etc.

  3. Background • Main targets for hurricane landfall in US: • Gulf Coast • Atlantic Coast • What determines where hurricanes make landfall? • How will tracks change in future climate? • How will corporations and disaster relief agencies need to adapt?

  4. Current Policies • Weather response vs. seasonal preparation • Issues: timing, cost • Focusing on bulk number rather than distribution • Issues: not representative of what to expect • Example: 1990 • Handling individually • Issues: no uniformity

  5. Current Policies

  6. Indices • El-Nino Southern Oscillation (ENSO) • North Atlantic Oscillation (NAO) • Atlantic SST Dipole Mode (DM) • Difference between tropical North Atlantic SST and tropical South Atlantic SST

  7. Evidence of Relationship • From Xie et al. (2005): • Negative ENSO = Atlantic trend • Negative NAO = Atlantic trend • Positive DM = Atlantic trend • Positive NAO = out to sea trend

  8. Data and Methods • Hurricane data • National Hurricane Center Data Archives • List of land-falling hurricanes • Month, location (Gulf of Mexico/Atlantic Coast) • Categorize seasons • Gulf Coast, Atlantic Coast, Out to Sea • Active (>12 named storms) • Neutral (10, 11, 12 named storms) • Inactive (<10 named storms)

  9. Data and Methods Activity Index Trend Index

  10. Data and Methods

  11. Data and Methods • Collected NAO and ENSO from Climate Prediction Center • Collected TNA and TSA from ESRL to calculate DM • Calculated yearly averages and hurricane season averages • Compared with hurricane data in a series of time series

  12. Analysis—ENSO

  13. Analysis—ENSO

  14. Analysis—ENSO • ENSO and Trend Index: • Strictly Gulf = negative/neutral ENSO • Atlantic = negative ENSO • ENSO and Landfalling Hurricanes: • No distinct trend • Suggest ENSO better for trend not activity

  15. Analysis—NAO

  16. Analysis—NAO

  17. Analysis—NAO • NAO and Trend Index: • Strong negative years = Atlantic • Year average and hurricane average with opposite sign = out to sea • Neutral = Gulf • Positive = Gulf/out to sea • NAO and Landfalling Hurricanes: • No noticeable trend • NAO better at trend rather than activity

  18. Analysis—DM

  19. Analysis—DM

  20. Analysis—DM • DM and Trend Index: • Positive = Atlantic • Negative = Gulf • Neutral = out to sea • DM and Landfalling Hurricanes: • No distinguishable trend • DM also better and trend versus activity

  21. Analysis • Consistent with Dr. Xie for the Atlantic Coast • Seems to be distinguishable between Gulf and Atlantic trends • Further analysis needs to be done to test significance

  22. Indices and Climate Models • El-Nino Southern Oscillation (ENSO) • Current confidence: • Steady progress in simulation and prediction • Still significant errors in simulated mean climate and natural variability • Many issues to overcome, but progress is being made

  23. Indices and Climate Models • El-Nino Southern Oscillation (ENSO) • Future projections • Need proper simulation of mean state and air-sea coupling under current climate conditions • Wide range of projections with no statistical significance • Clear that ENSO will continue, but uncertain about how it will change • Hopefully better prediction in the future

  24. Indices and Climate Models • North Atlantic Oscillation (NAO) • Current confidence: • Difficult to document past NAO variations • Solar and volcanic forcing associated with warming and positive NAO index • Need reliable projections of tropical SST and/or changes in meridional SST gradient

  25. Indices and Climate Models • North Atlantic Oscillation (NAO) • Future projections: • Used multi-model ensemble with increased CO2 • Shows positive trend, but magnitude small and model dependent • Large variations between models, so high uncertainty • Projected northward shift in NAO center, but does not affect this application

  26. Indices and Climate Models • Atlantic SST Dipole Mode (DM) • Current confidence: • Low confidence in air-sea interactions, heat transfer, etc. • Future projections: • Not much information could be found

  27. Implications • Large uncertainties • Potential positive trend in NAO could lead to less hurricanes reaching the Atlantic Coast • For now, speculate • Propose ways to include index information in policies

  28. Recommendations • Seasonal preparation vs. weather response • Benefits: • No rush • Steps: • 1) Put together list of instructions • 2) Monitor climate indices and look for trends • 3) Use trends and cost/benefit analyses • 4) Carry out seasonal preparation • OR 5) Continue with weather response

  29. Recommendations • Focus on distribution rather than bulk number • Benefits: more accurate idea of what to expect • Main step: include more scientific analysis in decision making

  30. Recommendations • Handle more uniformly • Benefits: everyone on same page • Steps: • 1) Organize a team of scientists to operate at the corporate level • 2) Analyze climate index data • 3) Distribute to local areas • 4) Have local areas make decisions • All or none • All suggestions tied in together

  31. Conclusions • Climate indices are a decent indicator of Atlantic Basin tropical system trends (not activity) • Incorporate more science into decisions • Changes in policy need to happen • Limitations • Uncertainty in climate indices • No policy will be 100% error free

  32. References References Climate Prediction Center Internet Team. (2005a, December). National Weather Service: Climate Prediciton Center. Retrieved from Arctic Oscillation (AO): http://www.cpc.ncep.noaa.gov/products/precip/CWlink/daily_ao_index/ao.shtml Climate Prediction Center Internet Team. (2005b, December). National Weather Service: Climate Prediciton Center. Retrieved from El Nino-Southern Oscillation (ENSO): http://www.cpc.ncep.noaa.gov/products/precip/CWlink/MJO/enso.shtml Climate Prediction Center Internet Team. (2010, January). National Weather Service: Climate Prediction Center. Retrieved from North Atlantic Oscillation (NAO): http://www.cpc.ncep.noaa.gov/data/teledoc/nao.shtml Class Notes. Corporation for National Service. (n.d.). The Disaster Center. Retrieved from Disaster Relief Agencies: http://www.disastercenter.com/agency.htm Enfield, D.B., A.M. Mestas, D.A. Mayer, and L. Cid-Serrano, 1999: How ubiquitous is the dipole relationship in tropical Atlantic sea surface temperatures? JGR-O, 104, 7841-7848.AOMLand PSD Jansen, E., J. Overpeck, K.R. Briffa, J.-C. Duplessy, F. Joos, V. Masson-Delmotte, D. Olago, B. Otto-Bliesner, W.R. Peltier, S. Rahmstorf, R. Ramesh, D. Raynaud, D. Rind, O. Solomina, R. Villalba and D. Zhang, 2007: Palaeoclimate. In: Climate Change 2007: The Physical Science Basis. Contribution on Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA Keith, E., & Xie, L. (2009). Predicting Atlantic Tropical Cyclone Seasonal Activity in April. Weather and Forecasting, 24, 436-255. Meehl, G.A., T.F. Stocker, W.D. Collins, P. Friedlingstein, A.T. Gaye, J.M. Gregory, A. Kitoh, R. Knutti, J.M. Murphy, A. Noda, S.C.B. Raper, I.G. Watterson, A.J. Weaver and Z.-C. Zhao, 2007: Global Climate Projections. In: Climate Change 2007: The Physical Scienve Bases. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA

  33. References (..cont.) National Hurricane Center. (2013, April). National Weather Service: National Hurricane Center. Retrieved from NHC Data Archive: http://www.nhc.noaa.gov/pastall.shtml#hurdat National Weather Service. (n.d.). Retrieved from Arctic Oscillation: http://forecast.weather.gov/glossary.php?word=ARCTIC%20OSCILLATION NOAA National Climatic Data Center, State of the Climate: Hurricanes & Tropical Storms for Annual 2012, published online December 2012, retrieved on May 6, 2013 from http://www.ncdc.noaa.gov/sotc/tropical-cyclones/. Randall, D.A., R.A. Wood, S. Bony, R. Colman, T. Fichefet, J. Fyfe, V. Kattsov, A. Pitman, J. Shukla, J. Srinivasan, R.J. Stouffer, A. Sumi, and K.E. Taylor, 2007: Climate Models and Their Evaluation. In: Climate Report of the Intergovernmental Panel on Climate Change [Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA Visbeck, M. H., Hurrell, J. W., Palvani, L., & Cullen, H. M. (2001). The North Atlantic Oscillation: Past, present, and future. PNAS, 98 (23), 12876-12877. Wikimedia Foundation, Inc. (2013, February). Wikipedia: The Free Encyclopdia. Retrieved from Tropical Atlantic SST Dipole: http://en.wikipedia.org/wiki/Tropical_Atlantic_SST_Dipole Xie, L., Yan, T., Pietrafesa, L. J., Morrison, J. M., & Karl, T. (2005). Climatology and Interannual Variability of North Atlantic Hurricane Tracks. Journal of Climate, 18, 5370-5381.

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