Kesten C. Green Business and Economic Forecasting Unit

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Presentation transcript:

Validity of climate change forecasting for public policy decision making Kesten C. Green Business and Economic Forecasting Unit Monash University J. Scott Armstrong The Wharton School University of Pennsylvania 9 March, 2009 1

Characteristics of temperature series Temperature varies over time, but No persistent trend Apparent short and long trends Of varied length That reverse without warning 2

Antarctic temperature changes 3

More temperature history Second, a shorter global approximation from thermometer data… 4

Hadley annual temperature 1850-2008

Conditions favor conservatism Many opinions by experts, but no evidence that the climate is different now 6

No-change benchmark model Tempyear+1,2,…100 = Tempyear Consistent with the viewpoint of a weather-dominated climate system 7

Forecasting methodology Structuring the forecasting problem Auditing the forecasting process Selecting a forecasting method Validation tests 8

Test of the benchmark Used HadCRUt3 “best estimate” of global mean temperatures from 1850 to 2007 Each year’s temperature a forecast for up to 100 subsequent years 157 one-year-ahead forecasts… 58 hundred-year-ahead forecasts 10,750 forecasts across all horizons Absolute errors calculated vs HadCRUt3 9

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Validity of IPCC projection 1992 IPCC Report projected 0.03oC/year linear Test vs benchmark for 1992 to 2008 1851 to 1975 1992 to 2008; ex ante 1851 to 1975; analogous exponential CO2 growth 12

IPCC performance 1992-2008 (short-range ex ante) CumRAE IPCC/Benchmark* Hadley UAH n From 1991 0.98 1.82 17 Rolling 0.84 0.95 136 * CumRAE < 1 means forecast errors smaller than benchmark errors 13

Mean errors 1992-2008 Using UAH data and rolling forecasts, Averaging the mean absolute errors for all 17 horizons… Benchmark 0.215 oC IPCC projection 0.203 oC Difference 0.012 oC 14

IPCC performance 1851-1975 (long range; ex post IPCC advantage) CumRAE of IPCC/Benchmark Hadley n From 1850 10.1 125 Rolling (1-100 years) 7.7 7,550 1-10 years 1.5 1,205 41-50 years 6.8 805 91-100 years 12.6 305 * CumRAE < 1 means forecast errors smaller than benchmark errors 15

Armstrong-Gore bet expectations Based on the Hadley data for 1850 through 2008*… Armstrong has a probability of wining bets against the 0.03oC/year linear trend of 0.54 for forecasts one-year-ahead; n=158 0.68 for ten-year-ahead forecasts; n=149 * which, as we know, was a warming period 16

Antarctic temperatures revisited 17

Forecasting methodology Structuring the forecasting problem Auditing the forecasting process Selecting a forecasting method Validation tests 18

Alternatives to the benchmark Predictions from outcomes of analogies Causal model with atmospheric CO2 Policy implications? Rival causal variables? 19

Why Structured Analogies? Analogies commonly used to “sell” forecasts. They do not aid accuracy when used in this way. Structured analogies produce better forecasts by overcoming biases. They help learning from history and thereby improve accuracy. (Green & Armstrong 2007) 20

Structured analogies procedures Ask heterogeneous group* of experts to individually describe as many analogies as they can for the current AGW situation. Experts then rate analogies for similarity to the AGW situation. Mechanical summary: Forecasts based on the set of “most similar” analogies. * Recruit warmers, skeptics, and others. 21

List all analogies that have the following features Popular movements that were endorsed by scientists and politicians. Include all (i.e., those that proved to be justified by events as well as those that weren’t) Expert, lobby group, and media interest high Supported by some scientists Accompanied by calls for government action Outcomes now known and agreed upon Please use the sign up sheets if you are willing to participate. Thank you! 22

Causal model testing procedures Data: Global mean temperature: Hadley 1850- 2008 CO2: Total global atmospheric concentration, NASA Models: First differences; levels Estimated initially using 1850-1899 data Forecasts: Annual Rolling forecasts for up to 100 years Updated estimate of relationship each roll Conditional on knowing CO2 Accuracy: CumRAE, or cumulative relative absolute error; Sum forecast errors, ignoring signs, and divide by the equivalent sum of benchmark model errors [Please write suggestions on the page we circulated]

Causal models Forecast temperature using CO2 concentration versus alternatives explanations Over the period 1850 to 2008 Forecasts conditional on knowing future atmospheric CO2 CumRAE for annual forecasts with 1-100 year horizon (CumRAE is the absolute error vs. the benchmark error) Model: Please rank in terms of forecast accuracy ___ 1. Policy: CO2 causes warming; (t; t+1) ___ 2. Effect not cause: Warming causes CO2; (t; t-1) 24

Causal model Direction 1. CO2 policy – 2. CO2 effect not cause + Tentative results: conditional forecasts Signs on coefficients for 1diff lagged models Causal model Direction 1. CO2 policy – 2. CO2 effect not cause +

Causal model CumRAE 1. CO2 policy 0.83 2. CO2 effect not cause n/a Tentative results: conditional forecasts (based on 5,950+ forecasts from levels models) Causal model CumRAE 1. CO2 policy 0.83 2. CO2 effect not cause n/a

CO2 policy implications? Or not? Assume that if Manmade CO2 emissions contribute a net 0.3ppm/year to the atmosphere Policies could reduce that by 20% to 0.24ppm/year …and sustain that reduced rate for 100 years Then, our tentative first round results suggest: First difference model suggests that net 6ppm not contributed to atmosphere would result in a global mean temperature 0.02oC higher in 100 years. Levels model suggests the mean temperature would be 0.05oC lower in 100 years. Alternatively, stopping human emissions altogether would increase mean temperature by 0.40oC, or decrease it by 0.24oC, over 100 years

Might CO2 be spurious? Some scientists believe the hypothesized strong CO2–temperature relationship to be spurious. Moreover, relatively smaller forecast errors produced by a model of temperature changes causing subsequent CO2 changes. 28

Summary Policy decisions require scientific long term forecasts of temperature and effects of policies Such forecasts do not exist Climate data and knowledge are uncertain, and climate is complex The situation calls for simple methods and conservative forecasts The no-change benchmark performs well IPCC projections do not compare well Do causal policy models with CO2 lack credibility? What do analogies imply for the future of AGW? Scientific forecasting suggests appropriate policy decision is “don’t just do something, stand there!”

Handouts for Armstrong & Green talks References for papers cited in our talks / WWF solicitation based on False advertising? Boxer vs.Armstrong Charity Wager Gore vs. Armstrong Prediction Market. Suggestions on what to do? • Analogies study • WWF action steps • CO2 policy forecasting “Climate Change Forecasts are Useless for Policy Making”

References for the Armstrong and Green talks [Papers available at http://publicpolicyforecasting.com unless otherwise indicated] Armstrong, J. S., Green, K. C., & Soon, W. (2008). Polar Bear Population Forecasts: A Public-Policy Forecasting Audit. Interfaces, 38, 5, 382–405. (includes commentary & response). Graefe, A., Armstrong, J. S., & Green, K. C. (2009). Using Prediction Markets to Solve Complex Problems: An Application to the ‘Climate Bet’. Working paper available at http://kestencgreen.com/cbpm.pdf Green, K.C., & Armstrong, J. S. (2007). Global Warming: Forecasts by Scientists versus Scientific Forecasts. Energy and Environment, 18, No. 7+8, 995-1019. Green, K.C., & Armstrong, J. S. (2007). Structured Analogies in Forecasting. International Journal of Forecasting, 23, 365-376. Green, K.C., Armstrong, J. S., & Soon, W. (2009). Validity of Climate Change Forecasting for Public Policy Decision Making. International Journal of Forecasting, Forthcoming. Tetlock, P. E. (2005). Expert Political Judgment: How Good Is It? How Can We Know? Princeton University Press, Princeton, NJ. Gore-Armstrong prediction market at http://tinyurl.com/gore-armstrong-bet Details on Gore-Armstrong bet at http://theclimatebet.com