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Bruce Wielicki, David Young, Marty Mlynczak , Rosemary Baize NASA Langley Roger Cooke

What is the Economic Value of Climate Science?. Bruce Wielicki, David Young, Marty Mlynczak , Rosemary Baize NASA Langley Roger Cooke Resources for the Future April 12, 2012. Economic Value of Climate Science. We have traceable estimates of the economic value of weather prediction

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Bruce Wielicki, David Young, Marty Mlynczak , Rosemary Baize NASA Langley Roger Cooke

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  1. What is the Economic Value of Climate Science? Bruce Wielicki, David Young, Marty Mlynczak, Rosemary Baize NASA Langley Roger Cooke Resources for the Future April 12, 2012

  2. Economic Value of Climate Science • We have traceable estimates of the economic value of weather prediction • Climate: “Will impact societal decisions with trillion dollar impacts” • But is this statement verified and traceable in any way, or is it just a vague qualitative statement? • How could we quantify an economic value to climate science? • Climate change science value exists decades into the future • That value has to be treated as a risk/benefit economic analysis • Investment perspective vs insurance perspective • Rigorous analysis must take into account the uncertainties in both climate science, economic impacts, policy • Needs to be sufficiently rigorous to be published in both economic and scientific journals • Potential to change the dynamic of the discussion on climate change science from “threat” to “economic investment”. Requires a combination of climate science and economics expertise

  3. CLARREO Science ValueClimateForcing, Response, Feedback Blue = CLARREO Solar Reflected Spectra Science Red = CLARREO IR spectra & GNSS-RO Science - Temperature - Water Vapor - Clouds - Radiation - Snow/Ice Cover Earth's Climate • Greenhouse Gases • Surface Albedo Cloud Feedback Water Vapor/Lapse Rate Feedback Snow/Ice Albedo Feedback Roe and Baker, 2007 50% of CLARREO Science Value is in Reflected Solar Spectra 50% of CLARREO Science Value is in Infrared Spectra & GNSS-RO 100% of CLARREO Science Value is in the Accuracy of the Data

  4. Climate Sensitivity uncertainty isdriven by uncertain Feedbacks: Factor of 3 uncertainty in response to doubled CO2 Relative uncertainty known Climate Change Response: Temperature Profile, Water Vapor Profile, Cloud Properties, Surface albedo (snow, sea-ice, land cover) Radiative Forcings: Verify greenhouse gas infrared radiation effects Aerosols advances by GLORY APS and NRC ACE missions. Science Impact 0.26 0.24 0.09 0.05 Effective Climate Forcings (W/m2): 1750-2000

  5. Climate Trend Accuracy & Calibration: IR • Example for Temperature Trends • CLARREO accuracy goals are optimal cost/value • High confidence critical for policy decisions • CLARREO accuracy designed to provide that confidence. • Uncertainty includes orbit sampling, instrument noise • CLARREO is within 20% of a perfect observing system Climate Change Accuracy is Critical to Making Difficult Policy Decisions

  6. Climate Trend Accuracy &Calibration: RS • Example for decadal change in • cloud feedback: changing SW Cloud Radiative Forcing • All major error sources included:- absolute accuracy assumes gaps occur,- orbit sampling (90 deg), - instrument noise, - reference intercalibration uncertainty (CERES) • CLARREO trend accuracy is within 20% of a perfect observing system. Climate Change Accuracy is Critical to Making Difficult Policy Decisions

  7. How does this fit with economics? • Roger Cooke at Resources for the Future • IPCC impacts chapter lead author • Mathematician/Risk Analysis Theory • Participated in recent workshop on socioeconomic benefits of earth science • Run and modify Integrated Economic Assessment (IAM) models • Expertise in “fat tails” analysis of economic impacts of statistically rare events • Was attracted to CLARREO by our accuracy requirements development and science value matrix concept: and especially the previous 2 figures. • Economic Model • Dynamic Integrated model of Climate and the Economy (DICE 2007), Nordhaus, 2008. • Includes uncertainties in climate sensitivity, economics • Can vary discount rates assumed: 1.5% (Stern), 3% (moderate), 5.5% (Nordhaus) • Interagency Memo on the Social Cost of Carbon (IMSCC, 2010) • Policy options: Business as Usual (BAU), DICE Optimal, Aggressive Emission Reductions (AER), Stern, 2007. • Climate change economic impacts scale with square of temperature change Climate Sensitivity and Discount Rates Dominate Economic Impacts

  8. Sample Economic Calculation • Cooke Initial Example Calculation • Assume world continues on "Business as Usual" policy track • Calculate economic impact costs through 2115. • Assume actual climate sensitivity is 5.8C for doubled CO2 (high end) • Assume that in 2055 we finally realize that climate sensitivity is high and we switch from BAU to the Aggressive Emissions Reductions policy track • Now imagine that science advances allow us to discover we were on a high sensitivity track by 2035 instead of 2055. • What is the economic value in todays dollars of society of discovering this 20 years earlier (i.e. the present value in economic terms). • Assume discount rate is 3%: above Stern but below Nordhaus • In this case, value to society of 20 year advance knowledge is $3.6 Trillion in 2012 dollars! • What is the cost of a full climate observing system? Roughly $10B/yr more than we currently spend (U.S.: $2B/yr, International: $2B/yr). If we started a crash course in 2013 to 2035: 22 years or $220B. But put in todays dollars it would be less because of the 3% discount rate. $200 Billion investment to save $3.6 Trillion?

  9. Caveats on Initial Calculation • Worst case scenario: i.e. biggest cost savings • A higher discount rate will drop the value, a lower discount rate raises it. • At 5.5% discount rate value drops to $600B (from $3,600B) • At 1.5% discount rate the value increases to $10,800B (from $3,600B) • Appropriate discount rates remain a huge debate in the economic community • A distribution of climate sensitivity will drop the value • Quadratic dependence of economic impacts on climate sensitivity • Use a back of the envelope spreadsheet climate sensitivity distribution roughly like IPCC • At 1.5% discount rate: economic value today is $3,800B • At 3% discount rate: economic value today is $1,300B • At 5.5% discount rate: economic value is $210B We understand where the key uncertainties are

  10. Next Steps • Wielicki/Young/Cooke proposal accepted for initial $60K Science Innovation Fund study to flesh out the concept by Sept 2012 • Instead of a step function for decision: use a narrowing uncertainty in climate sensitivity with time. • Compare the science value with/without CLARREO • Compare science value with different start dates for CLARREO • Compare temperature trend estimation of climate sensitivity vs cloud feedback (cloud radiative forcing) estimation • Temperature trends: high sensitivity have slower response • Cloud feedback: response depends on fast vs slow feedback • Present as value of entire climate observing system • CLARREO is used as the key example • Point out need independent confirmation of ocean heat storage, sea level rise, ice sheet mass loss, carbon cycle feedbacks, ecosystem impacts, etc • Point out value of more rapid verification of the impacts of policy shifts on carbon emissions • Publish in both science and economics literature to start discussion (e.g. EOS, BAMS, economics journals) Add rigor to first back of the envelope calculation

  11. Long Term Development • Vary fast (< 1yr) vs slow (wait for ocean warming) cloud feedbacks • Use multiple Integrated Economic Assessment models (FUND, PAGE) • Consider narrowing uncertainties in other feedbacks as well • Vary uncertainty in aerosol radiative forcing • Add nonlinear climate change trends with nonlinear forcing build up • Vary emissions/policy decisions beyond the 3 in DICE 2007 • Add LW and net cloud radiative forcing (initial is SW CRF: low clouds) • Consider the effect of adding "fat tails": abrupt climate change that is unlikely but a very large impact: e.g. much larger sea level rise than expected, carbon feedbacks from tundra and ocean bottom methane • Bring in uncertainties and value of other components of the climate observing system • Publish results in both climate science and economic journals • Search for next step funding: doesn't fit any normal ROSES or other science competition in NASA/NOAA/NSF/DOE: need to get very creative. • Once we get the discussion going, should drive further innovation in this area We have a longer term view of how to evolve

  12. Impact on Climate Change Discussions • Change the discussion from fear or concern about climate change to a more constructive discussion of economic investment strategy • Provide a more rigorous justification for the economic value of science • Provide a methodology broadly useful to understanding the economic value of climate science Help communicate the value of CLARREO and climate science overall

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