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Overview of lecture

Overview of lecture. The year so far?. Predictable?. Unpredictable?. Nov 2000 - Nov 2001. Predictable times?. Predictable impacts?. Predictable places?. Predictable times?. Short term annual patterns To make a hurricane take warm ocean - 27ºC upper atmosphere weather

hamish-hartman
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Overview of lecture

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  1. Overview of lecture The year so far? Predictable? Unpredictable? Nov 2000 - Nov 2001

  2. Predictable times? Predictable impacts? Predictable places?

  3. Predictable times? • Short term annual patterns • To make a hurricane take • warm ocean - 27ºC • upper atmosphere weather • a dash of Coriolis force - the spinning effect of the Earth’s rotation N.hemisphere - J F M A M J J A S O N D S.hemisphere - J F M A MJ J A S O N D

  4. Predictable times? • Medium term patterns • To make a hurricane take • warm ocean - 27ºC • upper atmosphere weather • a dash of Coriolis force El Niño / La Niña Antarctic circum-polar wave Pacific decadal oscillation

  5. Predictable impacts? Wind * Waves * Rain * Surge Saffir Simpson Scale - 1 2 3 4 5 mph 74 96 111 131 156+ (70m/s) Impacts on: Buildings: 20 15 10 5 0 Agriculture: Loss as % value Forestry: 0 20 40 60 80 SS4 SS5 Windspeed (m/s) Infrastructure: Source - Swiss Re Insurance publication Ecosystems:

  6. Predictable impacts? Wind * Waves * Rain * Surge

  7. Predictable impacts? Wind * Waves * Rain * Surge Eg Sept 99: Hurricane Floyd 14 inches (35cm) rain in 3 hrs. Rivers rising 10 - 15 feet (3 - 4.5 m) Oct 1998: Hurricane Mitch 25 inches rainfall (63cm) in 36 hours

  8. Predictable impacts? Wind * Waves * Rain * Surge Galveston (Texas) 8 Sep 1900. One of US most prosperous cities - built on island 2 - 3m above sea level. Hurricane surge = 5m. Combination of damage to wooden houses - * Wind damage * Flotation 8000-12000 deaths due to storm surge.

  9. Too cool Too little spin Too cool Predictable places? • Global scale patterns • To make a hurricane take • warm ocean - 27ºC • upper atmosphere divergence • a dash of Coriolis force 26 9 13 6 0 8 6 10

  10. Predictable places? River flood plain eg Cyclone Eline Feb 2000 Mozambique • Local scale patterns • To make a hazard take • A vulnerable location • Coastal plain / Barrier Island Island eg Floyd Sept 99 - USA

  11. Predictable places? • Micro scale patterns • To make a hazard take • A vulnerable location Sample result Where to avoid

  12. Enter the Unpredictables Speed of system The system moves at speeds determined by the energy supply. This depends principally on temperature of sea Hurricane Dennis - Sept 99 impacts on the Gulf Stream... A warm sea fuels the hurricane, cooler sea slows it. But the hurricane may move across warm currents, gaining energy OR may mix the water, altering its potency as a fuel.

  13. Accelerator brakes and steering (upper atmosphere weather patterns) Upper atmosphere weather Enter the Unpredictables See Flash movie Location of landfall Steering Accelerator (warm water) and brakes (cold water) US Weather Service accuracy at predicting landfall location 24 hours before landfall (km from actual landfall site): Date 1995 1996 1997 1998 Km error 134 130 145 140

  14. Enter the Unpredictables Behaviour of landscape - eg Hurricane Mitch Oct/Nov 1998 Relief Mountainous in region where Mitch stalled Slope stability Weak volcanic ash Drainage Steep, dense networks - 70% roads impassable in Nicaragua after Mitch Landscape Vegetation 80,000 hectares/yr tropical rainforest cleared in coastal Honduras

  15. Enter the Unpredictables Behaviour of people Decision makers Preparation, planning, warning systems, emergency shelters Communities Mitch - flooding in Tipitapa alerted by locals, first aid contacts via locals, refugee camp water pipe laid by locals People Individuals Stay to protect property? Attract aid? Avoid vulnerability?

  16. Enter the Unpredictables Events Hurricane Mitch - Casitas Volcano produces lahar due to crater lake collapse

  17. Conclusions: More predictable than they used to be; Galveston (Texas) 8 Sep 1900 with 8 - 12000 deaths due to a 5 metre surge at night with no warning wouldn’t happen today. But prediction does not equate to preparedness. Orissa Cyclone 1999 killed 20,000 people in India. There was a 10-15 metre surge and the cyclone stalled for 8 hours. But 100,000 people were evacuated before the cyclone hit. “the dead are mostly daily wage labourers, fishermen and women.” Poverty is the single biggest predictor of hurricane impact.

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