Societal Benefits of Winds Mission

Ken Miller

Mitretek Systems

February 8, 2007

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National Research Council Vision Statement 1

“A healthy, secure, prosperous and sustainable society for all people on Earth”

“Understanding the … planet …, how it supports life, and how human activities affect its ability to do so … is one of the greatest intellectual challenges facing humanity...”

NRC (April 2005)

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Societal Benefits from Improved Weather Forecasts Using Lidar Winds

Improved Operational Weather Forecasts

Civilian Military

Hurricane Track Forecast Ground, air & sea operationsAgriculture Weapons DeliveryTransportation Satellite launchEnergy Aerial Refueling Homeland Security Dispersion Forecasts for Air Quality Forecast Nuclear, Biological,Recreation & Chemical Release

Science

Climate Change IssuesCirculationH20, trace gases, aerosol, heat transportCarbon cycle Energy cycle

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Recent estimates for Decadal Survey, ESTO study, Lidar Winds white paper

Based on 1995, 1998 estimates (Cordes)2,3

– Key assumptions • Seem conservative • Hard to validate

Purpose – Update estimates – Added a benefit area– Increased from $228 M to $807 M / yr – Compared with estimates from other programs

Quantifiable Economic Benefits

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Findings

Benefits greater than in 1995– Fuel costs– Coastal population – Property values– GDP growth – Inflation– Added offshore drilling rig benefits

Magnitudes in line with other case studiesAdditional benefits could be includedRecommend more study of assumptions

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US Economy Affected by Weather

2005 GDP ~ $12.5 TrillionPercent of GDP affected by weather17

– Nearly 30% directly or indirectly ($3.75 Trillion)

– About 10% directly ($1.25 Trillion)Mission benefits large vs. cost

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Benefits Reviewed

Cordes Study2,3

– Quantified $• Reduce hurricane over-warnings• Reduce hurricane preventable damage and

business interruption • Save aviation fuel using wind in routing• General forecast improvement

– Not $ - Loss of life and limbConsidine et al Study12

– Off-shore drilling rig decision optimization

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Hurricanes: Loss of Life and Limb11

Not quantified hereBefore Katrina, Red Cross estimated 25K to 100K

deaths in a New Orleans worst caseDeath rate for hurricanes with > $1 B property

damage (20 yr avg to 2005)– All 128 / yr– Excluding Katrina, Andrew 34 / yr

“…late 20th century forecasting prevents 90% of hurricane-related mortality that would occur with techniques used in the 1950s”

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Hurricane Over-Warning Savings10,11

Evacuation cost: popular estimate $1 M / mileRegional dependence

– Could exceed $50M / mile in some areas– Much less in other areas

Hurricane Floyd (1999) evacuation cost rivaled damage cost 9

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Statistics 1995 2 2005 11

– Typical warning 341 miles300- 400– Affected coast 124 miles 100– Overwarning 217 miles200- 300

Benefits– Cost / mile $145 K $ 1 M– Over-warn cost / landfall $ 32 M – Reduce over-warning/landfall $ 5.4 M (17%*) $50 M

(50 miles)– x 2 landfalls / yr $ 11 M 100 M**

– Or scale 1995 to $1M / mile $ 75 M

Reduce Hurricane Overwarning

* Storm climatology and simulations for global 3D winds in NWP** Ref 11, better forecasts, not necessarily wind measurement alone

2005 Evacuation Avoidance: $75 to 100 M/yr

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Direct Hurricane Property Damage 11

Much not preventableHard to demonstrate reduction

– Probably improves over time– Growth & property values increase

losses– “…no discernable trend from better

forecasts or more effective mitigation measures”

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Direct Property Damage Savings (1995)2

13 yr to 1995 avg damage– Selected “typical” storms w/o Andrew = $1.2 B / yr

Assumed – 15% preventable with sufficient warning– 17% forecast improvement with winds vs. 1995 24

hr– Total 15% x 17% = 2.5%

Reduction, typical hurricanes = $30 M / yr

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Update Direct Damage

For > $B storms20 yr avg to 2005 (2005 $)

– About 1 landfall / yr > $1B– $7.1 B / yr less Andrew, Katrina– $15.7 B / yr counting Andrew, Katrina

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Update Direct Damage (concluded)

Using the lower number– $7.1 B / yr without Andrew, Katrina– Account for lesser hurricanes 22

• Divide by .83• Total = $8.5 B / yr

Reduce preventable losses 2.5% 2

2005 Savings Estimate = $212 M / yr

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Not in Cordes studyGulf Rigs 12

– Need hurricane track/intensity

– Optimize operating decisions: continue, evacuate, stop production

– Estimated value of 24 hour forecast• Perfect $239 M / yr• Imperfect $ 10 M / yr

Assume 17% improvement2 x ($239 M-$10 M)Benefit = $39 M / yr

Off-shore Drilling Rigs

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General Forecasting

Winds improve accuracy and lead timesForecasts impact the economyHow much?

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Some Industries Affected by Weather16, 18

Industry $BAgriculture 80 - 109Air Transportation 88Construction 373 - 528Elecricity Generation 220Fisheries 4Heating / cooling 7Outdoor recreation 100Storm mitigation & repair 17Total 889

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Chapman study 20 – Estimated gains from maximum

forecast improvement from NWS modernization

– $1.2 B / year in 1992 Cordes2

– Assumed winds provide 5% of max – $60 M / yr ($1992)

General Forecasting (1995)2

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Scale 1995 General Forecasting Estimate by GDP

1992 – GDP = 5.6 Trillion 1992$– Benefit was $60M– 0.0011 % of GDP

2005 GDP estimate = $12.5 Trillion2005 benefit scales to > $137 M / yr

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Forecast Improvements Example 1: Households

Household benefit estimates for better forecasts

• $1.7 B / yr (2003) 13 • $1.87 B / yr (2005) 14

This doesn’t include industry benefits

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Forecast BenefitsExample 2: ENSO 17

El Nino Southern Oscillation (ENSO) savings estimate– U.S. agriculture $200-300 M – U.S. corn storage $ 10- 25 M– NW US salmon fishery $

1 MTotal $211-326

MCan winds help?

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Forecast Benefits Example 3:Est. Marginal GOES-R Benefits15

$M / yrAgriculture

– Avoided irrigation costs15 41 – Orchard frost mitigation 9

Transportation– Flight delays 41 – Trucking 28 – 56

Recreational Boating 86 - 130 Energy Utilities 486 - 507 Total of Case Studies 691 - 784

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Conclusions from General Forecasting Examples

Big benefits: examples = $1191 to 1428 M / yr

Is our $137 M “in the ballpark” or low?Can add important benefits to list

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U.S. Airlines Fuel Savings

User preferred routing– Critical capability for FAA Next Generation

Air Transportation System (NGATS)– Wind optimal routing can save fuel

Benefits: economic, environmental, energy security

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U.S. Airlines Fuel: 1995 Estimate 2

Background– Fuel consumption effects

• 50 knot wind ~ 11% fuel impact (FAA, early 1980s)• Haul extra fuel for unknown wind conditions

– Real time vs. NWS forecast winds cut flight time 4.2% (simulation early 1980s)

Cordes2 lidar fuel savings estimates– 0.5% domestic – 1.0% international, less wind information available

2006 Savings = $107 M / yr (1994$)

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2006 (annualized Jan - Nov data)5

– 19.3 billion gallons @ average $1.972 / gal = $38 B– 72% for domestic flight, 28% international

Estimated savings with wind data– Domestic $137 M– International $106 M

Update U.S. Airlines Fuel

2006 US Airlines Savings Estimate= $243 M

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U.S. Military Aviation Fuel for 2006 (Cordes 1998)3

Military Aviation Savings ~ $20 M (1994$)

Military Aviation FuelAF Navy Total

Cost (1994 $B) 1.854 0.554 2.408% of Total Used 77 23Savings Rate 0.75% 1% 0.81%Savings (1994 $M) 13.9 5.5 19.4Savings (2006 $M) 18.9 7.5 26.4

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Military Aviation – More Recent Numbers21

AF jet fuel usage 2.6 B gallons / year53% over continental USCost

– ~ $2.40 / gal – vs. $0.63 in 1995 study– Transport to plane $1.30 / gal

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Military Aviation Update*

* Basis is 2.6 B gallons / yr for AF, $2.40 / gal for fuel, $1.30 / gal for transport to plane, estimated Navy usage using ratio from Ref 3.

Recent Military Aviation Fuel AF Navy* Total

Quantity (B gal) 2.6 0.78 3.38

% of Total Used3

77 23Cost / gal 2.40Transport cost / gal 1.30Total cost @ plane ($B) 12.49Savings Rate 0.81%Savings (2006 $M) 101

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2006 Annual Benefits Estimates ($M)

1995 Est 2006 EstHurricane Overwarning 11 75Direct Hurricane Damage 30 212Off Shore Drilling 0 39General Forecasting 60 137Airline Aviation Fuel 107 243Military Aviation Fuel 20 101Total 228 807

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Conclusions

Dollar benefit estimates have increased– Fuel costs– Increased coastal population and property

values– Growing GDP– Added offshore drilling rig benefits

Magnitudes seem in line with other weather case studies

Assumptions should be reviewedSignificant benefit areas may not be included yet

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References

1. National Academy of Science, Earth Science and Applications from Space, Briefing of Decadal Survey Findings, AMS Town Hall, 1/15/07 http://www.nap.edu/catalog/11820.html

2. Cordes, J. J., “Economic Benefits and Costs of Developing and Deploying A Space-Based Wind Lidar,” GWU, NOAA Contract 43AANW400233, March 1995

3. Cordes, J. J., Memorandum to W. Baker, “Projected Benefits in Military Fuel Savings from Lidar,” June, 1998

4. Kakar, R., et al, “An Advanced Earth Science Mission Concept Study for GLOBAL WIND OBSERVING SOUNDER,” NASA HQ, December 2006.

5. Air Transport Association, Jan thru Nov 2006, average airline paid price and consumption: http://www.airlines.org/economics/energy/MonthlyJetFuel.htm

6. http://fermat.nap.edu/books/0309087155/html/9.html reference to Zeiger and Smith, 1998

7. http://www.oilendgame.com/pdfs/MediaKit/MediaWtOEg_MilFacts.pdf8. NOAA National Climatic Data Center, www.ncdc.noaa.gov/oa/reports/billionz.html9. WeatherZine No. 18, October 1999,

http://sciencepolicy.colorado.edu/zine/archives/1-29/txt/zine18.txt10.UCAR Quarterly, Spring 1999,

http://www.ucar.edu/communications/quarterly/spring99/USWRP.html11. H. Willoughby, E. Rappaport, F. Marks, “Hurricane forecasting, the state of the art,”

Hurricane Socioeconomic Working Group, Feb 16-18, 2005, http://www.sip.ucar.edu/pdf/01_Hurricane_Forecasting_the_State_of theArt.1.pdf

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References

12. T. Considine et al, “The value of hurricane forecasts to oil and gas producers in the Gulf of Mexico”, Journal of Applied Meteorology, 43, 1270-1281. http://www.isse.ucar.edu/HP_rick/energy.html

13. “The Economic Value of Current and Improved Weather Forecasts to U.S. Households”, NOAA Magazine, 2003 http://www.magazine.noaa.gov/stories/mag99.htm

14. J. Lazo, NCAR, “What are Weather Forecasts Worth?” CANSEE, October 28, 2005 15. Williamson, Hertzfeld, Cordes, “The Socio-Economic Value of Improved Weather and

Climate Information”, GWU, 2002 http://www.gwu.edu/~spi/Socio-EconomicBenefitsFinalREPORT2.pdf

16. “Methodologies for the Assessment of Costs and Benefits of Meteorological Services,” http://www.wmo.ch/web/spla/R&Op-II(02)APPENDIX_D.doc

17. Weiher et al, “Valuing Weather Forecasts”, 2003 http://www.economics.noaa.gov/librarly/documents/social_science_initiative/workshop_briefing_book-ww.pdf

18. Teisberg, “Valuing Weather Forecasts: Methods, Examples, Next Steps,” http://www.economics.noaa.gov/librarly/documents/social_science_initiative/workshop_briefing_book-ww.pdf

19.”Inventory of Estimates of Value of Weather Information and References” http://www.economics.noaa.gov/librarly/documents/social_science_initiative/workshop_briefing_book-ww.pdf

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References

20. R. Chapman, “Benefit-Cost analysis for the modernization and associated restructuring of the National Weather Service,” NISTIR 4867. Report to NIST, 1992

21. M. Babcock, USAF, memoranda to K. Miller, January 2007 22. R. Pielke and Landsea, “Normalized Hurricane Damages in the United States:1925-

1995,” Weather and Forecasting, 13:621-631 http://www.aoml.noaa.gov/hrd/Landsea/USdmg/

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Backup Charts

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Weather in Economic Decision Making 2

Simple Decision ModelP = Probability of adverse weather eventL = Loss from adverse weather eventS = Savings by preventive action (given adverse

event)C = Cost of actionCost = 0 if no adverse event

Then:Expected loss without action = PLExpected loss with action = P(L-S) + C

If PS > C, it is rational to act

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Better Forecasts MakeBetter Decisions

P is the weather forecast (neglecting the complexities) If less uncertainty in P

– People use it more– Better economic decisions

Evacuation decisions will be conservative since loss of life is a factor