Causes of the Global Warming Observed since the 19th Century

Measurements show that the Earth’s global-average near-surface temperature has increased by about 0.8℃ since the 19th century. It is critically important to determine whether this global warming is due to natural causes, as contended by climate contrarians, or by human activities, as argued by the Intergovernmental Panel on Climate Change. This study updates our earlier calculations which showed that the observed global warming was predominantly human-caused. Two independent methods are used to analyze the temperature measurements: Singular Spectrum Analysis and Climate Model Simulation. The concurrence of the results of the two methods, each using 13 additional years of temperature measurements from 1998 through 2010, shows that it is humanity, not nature, that has increased the Earth’s global temperature since the 19th century. Humanity is also responsible for the most recent period of warming from 1976 to 2010. Internal climate variability is primarily responsible for the early 20th century warming from 1904 to 1944 and the subsequent cooling from 1944 to 1976. It is also found that the equilibrium climate sensitivity is on the low side of the range given in the IPCC Fourth Assessment Report.

A Fair Plan to Safeguard Earth’s Climate. 3: Outlook for Global Temperature Change throughout the 21st Century

We apply Singular Spectrum Analysis to four datasets of observed global-mean near-surface temperature from start year to through 2012: HadCRU (to = 1850), NOAA (to = 1880), NASA (to = 1880), and JMA (to = 1891). For each dataset, SSA reveals a trend of increasing temperature and several quasi-periodic oscillations (QPOs). QPOs 1, 2 and 3 are predictable on a year-by-year basis by sine waves with periods/amplitudes of: 1) 62.4 years/0.11°C;2) 20.1 to 21.4 years/0.04°C to 0.05°C;and 3) 9.1 to 9.2 years/0.03°C to 0.04°C. The remainder of the natur°l variability is not predictable on a year-by-year basis. We represent this noise by its 90 percent confidence interval. We combine the predictable and unpredictable natural variability with the temperature changes caused by the 11-year solar cycle and humanity, the latter for both the Reference and Revised-Fair-Plan scenarios for future emissions of greenhouse gases. The resulting temperature departures show that we have moved from the first phase of learning—Ignorance—through the second phase—Uncertainty—and are now entering the third phase—Resolution—when the human-caused signal is much larger than the natural variability. Accordingly, it is now time to transition to the post-fossil-fuel age by phasing out fossil-fuel emissions from 2020 through 2100.

A Revised Fair Plan to Safeguard Earth’s Climate

In our original study we crafted trajectories for developed and developing countries that phased-out greenhouse gas emissions during 2015-2065 such that the maximum global warming does not exceed the 2℃ threshold adopted by the UN Framework Convention on Climate Change, and the cumulative emissions for developed and developing countries are identical. Here we examine the effects of increasing the start year from 2015 to 2030 in 5-year intervals, and the phase-out period from 50 to 100 years in 10-year intervals. We find that phase-out during 2020-2100 is optimal. This phase-out increases the year of peak emission from 2015 to 2030 for developed countries and from 2042 to 2053 for developing countries. It also increases the time from peak emissions to zero emissions from 50 to 70 years for developed countries and from 23 to 47 years for developing countries. Both outcomes should facilitate agreement of the Revised Fair Plan by the UNFCCC.

A Fair Plan to Safeguard Earth’s Climate

A maximum global-mean warming of 2°C above preindustrial temperatures has been adopted by the United Nations Framework Convention on Climate Change to “prevent dangerous anthropogenic interference with the climate system”. Attempts to find agreements on emissions reductions have proved highly intractable because industrialized countries are responsible for most of the historical emissions, while developing countries will produce most of the future emissions. Here we present a Fair Plan for reducing global greenhouse-gas emissions. Under the Plan, all countries begin mitigation in 2015 and reduce greenhouse-gas emissions to zero in 2065. Developing countries are required to follow a mitigation trajectory that is less aggressive in the early years of the Plan than the mitigation trajectory for developed countries. The trajectories are chosen such that the cumulative emissions of the Kyoto Protocol’s Annex B (developed) and non-Annex B (developing) countries are equal. Under this Fair Plan the global-mean warming above preindustrial temperatures is held below 2°C.

Fair Plan 4: Safeguarding the Climate of “This Island Earth”

Earth is the only habitable planet in the solar system and beyond in interstellar space for a distance that would take us at least 80,000 years to traverse at the speed of Voyager 1. Thus our home planet is “This Island Earth”. Here we use our Simple (engineering-type) Climate Model to calculate the change in global-mean near-surface air temperature from 1765 through the third millennium for historical emissions and two scenarios of future emissions of greenhouse gases: (1) a Reference scenario of unabated emissions, and (2) our Fair Plan scenario wherein emissions are phased out to zero from 2020 to 2100. The temperature change for the Reference cases increases to 5.2°C (9.4°F) in 2225 and remains there for at least 40 human generations. By design, the temperature change for the Fair Plan increases only to 2°C (3.6°F)—the limit adopted by the UN Framework Convention on Climate Change “to prevent dangerous anthropogenic interference with the climate system”—in 2082 and thereafter decreases through the remainder of the millennium. Accordingly, we need to adopt the Fair Plan to safeguard the climate of “This Island Earth”.

A Simple Deconstruction of the HadCRU Global-Mean Near-Surface Temperature Observations

Previously we have used Singular Spectrum Analysis (SSA) to deconstruct the global-mean near-surface temperature observations of the Hadley Centre—Climate Research Unit that extend from 1850 through 2012. While SSA is a very powerful tool, it is rather like a statistical “black box” that gives little intuition about its results. Accordingly, here we use the simplest statistical tool to provide such intuition, the Simple Moving Average (SMA). Firstly we use a 21-year SMA. This reveals a nonlinear trend and an oscillation of about 60 years' length. Secondly we use a 61-year SMA on the raw observations. This yields a nonlinear trend. We subtract this trend from the raw observations and apply a 21-year SMA. This yields a Quasi-periodic Oscillation (QPO) with a period and amplitude of about 62.4 years and 0.11°C. This is the QPO we discovered in our 1994 Nature paper, which has come to be called the Atlantic Multidecadal Oscillation. We then subtract QPO-1 from the detrended observations and apply an 11-year SMA. This yields QPO-2 with a period and amplitude of about 21.0 years and 0.04°C. We subtract QPO-2 from the detrended observations minus QPO-1 and apply a 3-year SMA. This yields QPO-3 with a period and amplitude of about 9.1 years and 0.03°C. QPOs 1, 2 and 3 are sufficiently regular in period and amplitude that we fit them by sine waves, thereby yielding the above periods and amplitudes. We then subtract QPO-3 from the detrended observations minus QPOs 1 and 2. The result is too irregular in period and amplitude to be fit by a sine wave. Accordingly we represent this unpredictable part of the temperature observations by a Gaussian probability distribution (GPD) with a mean of zero and standard deviation of 0.08°C. The sum of QPOs 1, 2 and 3 plus the GPD can be used to project the natural variability of the global-mean near-surface temperature to add to, and be compared with, the continuing temperature trend caused predominantly by humanity’s continuing combustion of fossil fuels.

Bayesian Learning of Climate Sensitivity I: Synthetic Observations

The instrumental temperature records are affected by both external climate forcings—in particular, the increase of long-lived greenhouse gas emissions—and natural, internal variability. Estimates of the value of equilibrium climate sensitivity—the change in global-mean equilibrium near-surface temperature due to a doubling of the pre-industrial CO2 concentration—and other climate parameters using these observational records are affected by the presence of the internal variability. A different realization of the natural variability will result in different estimates of the values of these climate parameters. In this study we apply Bayesian estimation to simulated temperature and ocean heat-uptake records generated by our Climate Research Group’s Simple Climate Model for known values of equilibrium climate sensitivity, T2x direct sulfate aerosol forcing in reference year 2000, FASA, and oceanic heat diffusivity, ΔT2x. We choose the simulated records for one choice of values of the climate parameters to serve as the synthetic observations. To each of the simulated temperature records we add a number of draws of the quasi-periodic oscillations and stochastic noise, determined from the observed temperature record. For cases considering only values of ΔT2x and/or κ, the Bayesian estimation converges to the value(s) of ΔT2x and/or κ used to generate the synthetic observations. However, for cases studying FASA, the Bayesian analysis does not converge to the “true” value used to generate the synthetic observations. We show that this is a problem of low signal-to-noise ratio: by substituting an artificial, continuously increasing sulfate record, we greatly improve the value obtained through Bayesian estimation. Our results indicate Bayesian learning techniques will be useful tools in constraining the values of ΔT2x and κ but not FASA In our Group’s future work we will extend the methods used here to the observed, instrumental records of global-mean temperature increase and ocean heat uptake.