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© Crown copyright Met Office
Translating science to action
Haiyan to Hagupit
Paul Davies, Chief Meteorologist
Typhoon Haiyan
© Crown copyright Met Office
WMO Fact Finding Mission :
summary and conclusions
Going the extra mile – can science deliver??
“I would rather die with my refrigerator than let it
be taken by a storm surge”
STAKEHOLDER MEETING, MANILA
2014
© Crown copyright Met Office
WMO Fact Finding Mission :
summary and conclusions
Why did many people stay in their homes and
did not move to safety?
Possible reasons:
• Did not know of the danger
• They knew about it but chose to ignore it
• Many people didn’t understand the science such as
what is meant by ‘storm surge’ or how far the water
would go
• Some people moved to evacuation centres which
turned out to be in the inundation area – some died
there
Typhoon -> Hazards
Typhoon -> Primary
Lightning
Typhoon -> Secondary
Storm Surge
Typhoon -> Secondary
Storm Surge
Typhoon -> Secondary
Flood inundation
Typhoon -> Tertiary
Health and increased vulnerability
© Crown copyright Met Office
Typhoon Hagupit:
(1) Observations
(3) Forecast winds, rainfall,
temperatures…
Big Data, Big Science
(2) Models
Each day the Met Office processes and stores 106 million observations,
completes 20 quadrillion (1015) calculations, archives 10 Tera (1012)
bytes of model data and produces 4 million forecasts per day
Big Data, Big Science
Each day the Met Office processes and stores 106 million observations,
completes 20 quadrillion (1015) calculations, archives 10 Tera (1012)
bytes of model data and produces 4 million forecasts per day
“…bridging the Valley of Death…through effective
translation and application of science”
The 4.4 km
Typhoon Hagupit
Global (deterministic) 4.4 km downscaler (from determinsitic)
4.4 domain
Typhoon Hagupit:
Ensembles
TWO scenarios
1. Landfall not until Tuesday or later. Main hazards: Heavy
rainfall, severe inland flooding and landslides.
Probability 70%
2. Landfall later Saturday or early Sunday. Main Hazards:
wind and storm surge. Probability 30%.
Coping with Hurricanes/Typhoons
Weather and
climate extremes
Weather analyses
& forecast data
Hurricane track,
size, & intensity
Implementation of
evacuation &
recovery plans
Reducing risk &
response
scenarios
Mitigation strategies
Affected population
& infrastructure,
disruption of services,
damages due to wind
& water, etc.
Impact
Estimation
Placing into
situational context
Storm surge, flooding,
inundated areas
Weather
Translation to
hazards
Extraction of
relevant information
to predict hazards
Holistic approach to impact
and risk
GEO-PHYSICAL
HAZARD
EXPOSURE
VULNERABILITY
Socio-Economic
IMPACT
QUANTIFYING
&
REDUCING RISK
WEATHER &
CLIMATE
EXTREMES
Major Uncertainty
Some progress, still a limiting factor
Considerable progress
Advice on impacts
DSD-INT 2015 - Translating science to action - Paul Davies
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DSD-INT 2015 - Translating science to action - Paul Davies

  • 1. © Crown copyright Met Office Translating science to action Haiyan to Hagupit Paul Davies, Chief Meteorologist
  • 3. © Crown copyright Met Office WMO Fact Finding Mission : summary and conclusions Going the extra mile – can science deliver?? “I would rather die with my refrigerator than let it be taken by a storm surge” STAKEHOLDER MEETING, MANILA 2014
  • 4. © Crown copyright Met Office WMO Fact Finding Mission : summary and conclusions Why did many people stay in their homes and did not move to safety? Possible reasons: • Did not know of the danger • They knew about it but chose to ignore it • Many people didn’t understand the science such as what is meant by ‘storm surge’ or how far the water would go • Some people moved to evacuation centres which turned out to be in the inundation area – some died there
  • 10. Typhoon -> Tertiary Health and increased vulnerability
  • 11. © Crown copyright Met Office Typhoon Hagupit:
  • 12. (1) Observations (3) Forecast winds, rainfall, temperatures… Big Data, Big Science (2) Models Each day the Met Office processes and stores 106 million observations, completes 20 quadrillion (1015) calculations, archives 10 Tera (1012) bytes of model data and produces 4 million forecasts per day
  • 13. Big Data, Big Science Each day the Met Office processes and stores 106 million observations, completes 20 quadrillion (1015) calculations, archives 10 Tera (1012) bytes of model data and produces 4 million forecasts per day
  • 14. “…bridging the Valley of Death…through effective translation and application of science”
  • 15. The 4.4 km Typhoon Hagupit Global (deterministic) 4.4 km downscaler (from determinsitic) 4.4 domain
  • 17. TWO scenarios 1. Landfall not until Tuesday or later. Main hazards: Heavy rainfall, severe inland flooding and landslides. Probability 70% 2. Landfall later Saturday or early Sunday. Main Hazards: wind and storm surge. Probability 30%.
  • 18. Coping with Hurricanes/Typhoons Weather and climate extremes Weather analyses & forecast data Hurricane track, size, & intensity Implementation of evacuation & recovery plans Reducing risk & response scenarios Mitigation strategies Affected population & infrastructure, disruption of services, damages due to wind & water, etc. Impact Estimation Placing into situational context Storm surge, flooding, inundated areas Weather Translation to hazards Extraction of relevant information to predict hazards
  • 19. Holistic approach to impact and risk GEO-PHYSICAL HAZARD EXPOSURE VULNERABILITY Socio-Economic IMPACT QUANTIFYING & REDUCING RISK WEATHER & CLIMATE EXTREMES Major Uncertainty Some progress, still a limiting factor Considerable progress