Climate Sensitivity: Uncertainties & Learning Workshop on GHG Stabilization Scenarios Tsukuba, Japan, 23 January 2004 Michael Schlesinger and Natasha Andronova Climate Research Group Department of Atmospheric Sciences University of Illinois at Urbana-Champaign Introduction • Climate sensitivity, ∆T2x: The change in global-average near-surface temperature resulting from a doubling of the preindustrial carbon dioxide concentration. • If ∆T2x is small, then the problem of human-induced climate change may not be acute. If ∆T2x is large, then human-induced climate change may be one of the most severe problems of the 21st century. Outline • Primer on Climate Sensitivity, ∆T2x • Estimates of Climate Sensitivity, ∆T2x • Uncertainty in ∆T2x due to uncertainty in the radiative forcing • Causes of temperature changes from 1856 to present • Learning ∆T2x over time dH ()t ΔT() t = − + F() t dt λ • F(t): Radiative Forcing – The change in the net downward radiative flux at some level in the atmosphere, usually the tropopause, caused by some “external” factor, such as changed solar insolation or GHGs. • Instantaneous Radiative Forcing – Radiative forcing before any temperature changes. • Adjusted Radiative Forcing – Radiative forcing after temperatures above the tropopause change, with tropospheric temperatures held constant. dH ()t ΔT() t = − + F() t dt λ • dH(t)/dt – The change in heat storage of the climate system; on earth, essentially the heat taken up or lost by the ocean. • λ – Climate Sensitivity • Equilibrium Climate Sensitivity , λeq – F(t) = constant and sufficient time elapsed for dH/dt = 0. ∆T = ∆Teq. – λ = λeq = ∆Teq/F ; e.g., λeq = ∆T2x/F2x. 2 F2x = 3.71 W/m . ∆T2x taken as a synonym for λeq. ∆T2x Simulated By The UIUC Stratosphere/Troposphere General Circulation Model 3.5 3.5 3 3 WO PCHEM 2.5 2.5 2 2 1.5 W PCHEM 1.5 1 1 0.5 y = m1*(1-exp(-0.5*M0/m1)) y = m1*(1-exp(-0.5*M0/m1)) 0.5 Value Error Value Error m1 2.2227 0.01223 m1 2.3625 0.011291 0 Chisq 14.79 NA Chisq 23.68 NA 0 R2 0.82407 NA R2 0.76598 NA -0.5 -0.5 2xCO2 – 1xCO2 surface air temperature (°C) 0 10 20 30 40 50 60 Time (years) Outline • Primer on Climate Sensitivity, ∆T2x • Estimates of Climate Sensitivity, ∆T2x • Uncertainty in ∆T2x due to uncertainty in the radiative forcing • Causes of temperature changes from 1856 to present • Learning ∆T2x over time 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 Cumulative distribution function 0.2 0.1 0 Arrhenius Range-0.1 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 Climate sensitivity, ∆T2x (°C) 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 Cumulative distribution function 0.2 0.1 0 EBM Arrhenius Range-0.1 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 Climate sensitivity, ∆T2x (°C) 1 0.9 0.8 RCM 0.7 0.6 0.5 0.4 0.3 Cumulative distribution function 0.2 0.1 0 Range EBM Arrhenius -0.1 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 Climate sensitivity, ∆T2x (°C) 1 0.9 0.8 RCM 0.7 GCM 0.6 0.5 0.4 0.3 Cumulative distribution function 0.2 0.1 0 EBM Arrhenius Range-0.1 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 Climate sensitivity, ∆T2x (°C) 1 0.9 Paleo 0.8 RCM 0.7 0.6 GCM 0.5 0.4 0.3 Cumulative distribution function 0.2 0.1 0 Arrhenius Range-0.1 EBM -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 Climate sensitivity, ∆T2x (°C) • U.S. National Research Council study chaired by Jule Charney wrote: "We estimate the most probable global warming for a doubling of CO2 to be near 3°C with a probable error of ±1.5°C". • The Intergovernmental Panel on Climate Change interpreted the findings of the Charney report to mean that 1.5°C ≤ ∆T2x ≤ 4.5°C. • We assert that this interpretation is incorrect and that the correct interpretation is that there is only a 50% likelihood that ∆T2x lies within 1.5° to 4.5°C. 1 0.9 Paleo 0.8 RCM 0.7 NRC 9779 0.6 0.5 0.4 0.3 Cumulative distribution function 0.2 GCM 0.1 0 Range Arrhenius -0.1 EBM -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 Climate sensitivity, ∆T2x (°C) 1 0.9 Paleo 0.8 RCM 0.7 NRC 9779 0.6 0.5 0.4 0.3 Cumulative distribution function 0.2 GCM 0.1 0 IPCC Range Arrhenius -0.1 EBM -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 Climate sensitivity, ∆T2x (°C) 1 0.9 0.8 0.7 "Expert" opinion NRC 7997 0.6 0.5 0.4 0.3 Cumulative distribution function 0.2 0.1 0 IPCC Range Arrhenius -0.1 EBM -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 Climate sensitivity, ∆T2x (°C) 1 0.9 Expert Forest et al 0.8 Expert 0.7 Wigley & Raper Tol & de Vos 0.6 0.5 0.4 "Expert" 0.3 opinion Cumulative distribution function 0.2 0.1 0 IPCC NRC 97 Range 79 Arrhenius -0.1 EBM -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 Climate sensitivity, ∆T2x (°C) 1 0.9 Andronova & Schlesinger 0.8 0.7 0.6 Uniform 0.5 Uniform ForestForest et et al al GregoryGregory et et al al 0.4 0.3 Cumulative distribution function 0.2 Knutti et al 0.1 Knutti et al 0 IPCC NRC 79 Arrhenius Range-0.1 EBM -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 Climate sensitivity, ∆T2x (°C) 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 Cumulative distribution function 0.2 0.1 0 IPCC Arrhenius Range-0.1 EBM -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 Climate sensitivity, ∆T2x (°C) Arrhenius (1896) GCM Expert Gregory et al. Knutti et al. EBM Paleo Uniform Forrest et al. Andronova & Schlesinger Tol & de Vos RCM IPCC Expert Forrest et al. Expert Wigley & Raper NRC 79 Outline • Primer on Climate Sensitivity, ∆T2x • Estimates of Climate Sensitivity, ∆T2x • Uncertainty in ∆T2x due to uncertainty in the radiative forcing • Causes of temperature changes from 1856 to present • Learning ∆T2x over time Simple climate/ocean model λ ΔF ΔF oi Li λ Atmosphere k N Atmosphere β a . over Ocean over Land k S λ Na,o λ Sa,o λa , L βo Mixed Layer Interior Ocean Land Bottom Ocean σo , i σL , i λ ΔF ΔF oN oS λ NH Atmosphere βa SH Atmosphere over Ocean over Ocean λ Na,o λ Sa,o NH Mixed Layer SH Mixed Layer κ κ W βo W SH Polar Ocean NH Interior Ocean SH Interior Ocean κ κ W W NH Polar Ocean βo W κ κ W NH Bottom βo SH Bottom Ocean Ocean σo, N σo, S 2) Radiative Forcing 2.5 2 GHG Sulphate aerosol 1.5 Tropospheric ozone 1 Total anthropogenic Anthropogenic forcing0.5 (W/m 0 -0.5 -1 -1.5 (A) 1750 1800 1850 1900 1950 2000 2) 1 0 -1 -2 Volcanic forcing-3 (W/m -4 -5 -6 (B) 1750 1800 1850 1900 1950 2000 2) 1369 1368 1367 Solar irradiance 1366 (W/m 1365 1364 LN (C) HS 1363 1750 1800 1850 1900 1950 2000 Year 0.6 (A) (NH+SH)/2 C o 0.4 Obs 0.2 Air 0 -0.2 -0.4 Temperature Departure, -0.6 1850 1880 1910 1940 1970 2000 0.6 (B) (NH–SH) C o 0.4 Obs 0.2 0 emperature Changes Observed Surface T -0.2 Temperature Departure, -0.4 1850 1880 1910 1940 1970 2000 Simulated Vs. Observed Surface Air Temperature Change 0.6 0.6 (A) (NH+SH)/2 (B) (NH–SH) C C o 0.4 o 0.4 Obs Obs 0.2 0.2 0 0 -0.2 -0.2 -0.4 Sim(GTAS) Temperature Departure, Sim(GTAS) Temperature Departure, -0.6 -0.4 1850 1880 1910 1940 1970 2000 1850 1880 1910 1940 1970 2000 0.4 (C) (NH+SH)/2 0.3 (D) NH–SH C) 0.3 C) o o 0.2 0.2 0.1 0.1 0 0 -0.1 -0.1 -0.2 -0.2 Res = Obs – Sim(GTAS) Obs – sim temperature ( Obs – sim temperature ( -0.3 Res = Obs – Sim(GTAS) -0.3 -0.4 1850 1880 1910 1940 1970 2000 1850 1880 1910 1940 1970 2000 Schlesinger & Ramankutty (1994) 100 0.08 IPCC 92 (1858-1992) N = 135, M = 40 0.06 0.04 ∧ 10 X 0.02 1 0 ∧ X -0.02 2 / Total Variance x 100 (%) 1 k λ Mode Time Series (°C) -0.04 -0.06 A -0.08 C Eigenvalues 0 5 10 15 20 25 30 35 40 1850 1870 1890 1910 1930 1950 1970 1990 Mode Year 0.3 0.4 0.3 ∧ ∧ X + X 0.2 1 2 0.2 C) ρ o 1 0.1 0.1 0.0 0 -0.1 -0.1 ρ 2 -0.2 Eigenvectors (EOFs, -0.2 -0.3 IPCC Obs B Detrended Temperature Anomaly (°C) D -0.3 -0.4 0 5 10 15 20 25 30 35 40 1850 1870 1890 1910 1930 1950 1970 1990 i (years) Year Schlesinger & Ramankutty (1994) 180 120W 60W 0 60E 120E 180 90N 90N 60N 60N 1 5 2 3 5 30N 30N 4 0 8 10 0 7 6 11 30S 30S 9 9 60S 60S 90S 90S 180 120W 60W 0 60E 120E 180 ∆T2x Versus Radiative Forcing 5 4 3 (°C) 2x T IPCC Range ∆ 2 1 0 GT GTA GTAV1 GTAS GTASV1 GTASV2 Radiative forcing model Conclusion 1 • To reduce the uncertainty in climate sensitivity requires reducing the uncertainty in the radiative forcing, not only by aerosols, but also by the Sun and volcanoes.