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  1. Uncertainties in global mean temperature estimation and and implications for trend uncertainty are studied by comparing four different temperature datasets, three temperature reconstructions from the instrumental record and one set of satellite microwave radiometry. They are identified with 3-letter acronyms as HAD (Hadley Center HadCRUT4), GIS (Goddard Institute of Space Studies), BRK (Berkeley Earth Climate Research), and UAH (University of Alabama Satellite data).  The common time span 1979-2018 is used for all four data sources restricted by data availability for UAH. The temperatures are delivered as deseasonalized temperature anomalies that should have no seasonal cycle remaining in the data. The analysis is carried out for each calendar month separately. In related posts at this site it is shown that trend behavior of temperature varies significantly among the calendar months [LINK] . The uncertainties found in this analysis are compared with uncertainties in the HadCRUT4 temperature reconstructions reported by Colin Morice  (
  2. Morice, Colin P., et al. “Quantifying uncertainties in global and regional temperature change using an ensemble of observational estimates: The HadCRUT4 data set.” Journal of Geophysical Research: Atmospheres 117.D8 (2012).
  3. Figure 1 presents the four temperature series BRK, GIS, HAD, and UAH in a GIF format that cycles through the twelve calendar months. The animation appears to show differences among the four estimations of global mean temperature with some variance of these differences among the calendar months.
  4. Figure 2 is a graphical summary of the visual information in the GIF animation in Figure 1. The left panel is a graphical presentation of detrended correlations among the three global mean temperature reconstructions BRK, GIS, and HAD. The red line in left panel shows a near perfect correlation between BRK and GIS and the black and blue lines display the somewhat lower correlations of HAD against the two nearly identical datasets GIS and BRK. These correlations appear to differ among the calendar months. The right panel of Figure 2 displays a similar comparison of the three surface temperature reconstruction series (BRK GIS HAD) with the UAH satellite based microwave sounding measurements for the lower troposphere.
  5. Figure 3 and Figure 4 present the corresponding analysis of these four datasets (BRK GIS HAD UAH) for decadal trends computed as OLS linear trend values within a moving ten-year window that moves through the time series one year at a time. Figure 3 presents these trends for all four data sources graphically in a GIF animation that cycles through the calendar months and Figure 4 displays their correlations in a graphical format.
  6. Correlations among the four decadal trend series shown in Figure 3 are summarized in Figure 4. The left frame of Figure 4 presents correlations among the three surface reconstructions UAH, GIS, and BRK. The right frame shows the correlation of the three surface reconstructions with UAH satellite data.
  7. An extension of this uncertainty analysis is presented in Figure 5 and Figure 6 with the Morice uncertainties in the HadCRUT4 global mean temperature data. In 2012 the Hadley Centre completed their work on estimating the uncertainty in temperature in their reconstruction and published the results online [LINK] . The full text of Colin’s paper is available online [LINK ]. More detail on Colin Morice’s work is presented in a related post [LINK] . The Morice uncertainties are presented graphically as animation in the two brief video presentations in Figure 5. The top frame compares temperatures and the bottom frame compares their decadal trends. The data for these graphics are derived from the Morice variances in a Monte Carlo simulation that creates four different data series possible under the uncertainty described by the variance. The variance used in the Monte Carlo simulation is derived from the 95% confidence intervals reported by Colin Morice. Figure 6 is a graphical display of the correlations among the four Monte Carlo series for both temperature and decadal trends. The correlations displayed graphically in Figure 2, Figure 4, and Figure 6 are tabulated in Figure 7. The tabulation shows as follows:
  8. Figure 7 Item#1: A near perfect correlation is found between BRK and GIS in both the temperature and decadal trend time series. Item#2: The comparison of nearly identical series BRK and GIS with HAD reveals lower correlations of both BRK and GIS against HAD in both the temperature and decadal trend time series with significant seasonal differences. The correlations are low in summer and high in winter for both temperature and decadal trends. Item#3: Comparison of the three surface temperature reconstruction (BRK GUS HAD) with satellite data for lower troposphere temperature (UAH). Here the summer correlations for both temperature and decadal trends are lower than in Item#1 and Item#2 although the winter correlations are strong. Item#4: Correlations among the four different Monte Carlo simulations of HAD with the Morice uncertainties show weaker correlations than the comparison of different measurement methods.
  9. CONCLUSION: Differences among global mean temperature sources and whether surface reconstructions or satellite lower troposphere temperature measurements are within surface reconstruction uncertainty reported for the HAD by Morice. We therefore conclude that no significant difference is found among these four datasets that can be ascribed to measurement methods. An oddity of the findings of this study is the extreme correspondence between the BRK (Berkeley Earth) and GIS (Goddard Institute of Space Sciences) reconstructions.






The Reference Document (RD) for this post is from the Cicero Center for Climate Research in Norway. The chief researcher is Glen Peters who is also the author of the RD which Dr. Peters has made available online [LINK] . The IPCC Synthesis Report used as a reference is also available online [LINK] . The Millar etal 2015 paper used in this post is discussed in more detail in a related post [LINK] and Richard Millar‘s commentary on his paper’s findings is available online courtesy of Carbon Brief [LINK] .




  1. In a related post we present the case that the essence of the climate change movement is that it is a reincarnation of the 1960s movement against fossil fuels [LINK] . In that context the fear of global warming, in terms of sea level rise, extreme weather, mass extinctions, mass migrations, agricultural and economic devastation, rampant epidemics, and the collapse of civilization, serves as motivation for climate action because climate action is guaranteed to control climate change and thereby to relieve humanity of these horrific climate impacts. In other words, the goal of climate change activism is climate action.
  2. Thus, the essence of the climate change movement and the purpose of climate science is to push for climate action in the form of reducing and eventually eliminating the the use of fossil fuels as a way of reducing and eliminating the “external” and artificial carbon emissions of the industrial economy that act as a dangerous perturbation of nature’s balanced carbon cycle and climate system.
  3. In practical terms, climate action is described as reducing fossil fuel emissions to meet maximum warming targets beyond which unacceptable levels of climate impacts are expected. The maximum warming target (MWT) was set in the Paris Agreement which sets the MWT at 2C but with bureaucratic language that also refers to a target of 1.5C. In practical terms for climate science, the 1.5C target is used to formulate the needed climate action procedures.
  4. The usual procedure for a climate action plan is to compute what is known as a carbon budget. A carbon budget is the total amount of carbon that can be emitted from the present time to the target date (cumulative emissions) if the MWT is not to be exceeded. For example, suppose that the Paris Agreement MWT is 1.5C since pre-industrial times. Of that 1C has already been used up to the present and so the warming target from now to the target date is reduced to MWT=0.5C.
  5. The total amount of carbon that can be emitted in for this MWT is computed using the Transient Climate Response to Cumulative Emissions (TCRE) described in the Matthews 2009 paper included in the bibliography below.  This reference paper shows that there is a near perfect proportionality between cumulative emissions and temperature. The linear regression coefficient derived from this proportionality is the TCRE parameter which describes degrees Celsius of warming per unit of cumulative emissions. When emissions are denominated in gigatons, the TCRE is the degC of warming per gigaton of cumulative emissions. The total gigatons of emission possible within the MWT constraint is then computed using the TCRE. This amount of cumulative emissions is the carbon budget.
  6. For example, if our MWT is 0.5C and the TCRE is found to be 0.0025 degC/gigaton, the carbon budget is 0.5/0.0025 = 200 gigatons of carbon equivalent cumulative emissions. Sometimes the carbon budget is stated in carbon dioxide (molecular weight 44) instead of the carbon equivalent (molecular weight 12). In this case the equivalent carbon dioxide budget is 200*44/12 = 733 gigatons of carbon dioxide.
  7. The IPCC published such a carbon budget in 2015 for a 0.5C MWT. That IPCC carbon budget is 250 gigatons of carbon dioxide. This carbon budget is the subject of Peter Glen’s analysis for the CICERO climate research center cited above and with full text available online [LINK] . There, Professor Peters points out that at an average rate of 40 gigatons of carbon dioxide emissions per year, the 250 gigaton CO2 budget would  be gone in 250/40 = 6.25 years and that therefore the carbon budget implies an unrealistically high rate of warming of 0.5/6.25 = 0.08C/year since the current rate of warming is closer to 0.025C/year. Clearly something is not right with the IPCC carbon budget for 1.5C.
  8. At the more realistic rate of warming, the real carbon budget has to be 3.2 times larger or about 800 gigatons. And in fact that is exactly what we see in the Millar etal 2017 paper listed in the bibliography below. Glen Peters, a recognized authority on the issue of carbon budgets (alongside researchers like Joeri Rogelj cited below in the bibliography), then resolves this issue in his article cited above and in so doing presents several key issues in carbon budget mathematics that expose an underlying weakness in the science of climate science.
  9. Carbon budgets are computed with the TCRE proportionality between cumulative emissions and temperature (temperature is cumulative warming). However, it is found that the procedure leads to mysterious inconsistencies when the time span is changed or when the remaining carbon budget is to be computed. In  climate science these inconsistencies are interpreted in terms of theory and their resolution is carried out with climate models in terms of Earth System Models and non-CO2 forcings.
  10. These resolutions are by their very nature a form of circular reasoning because these variables are fine tuned until the carbon budget anomaly is resolved. However, they also yield very large uncertainties. For example, the Millar 2017 paper uses a “climate-carbon-cycle” model to find that that the carbon budget for 1.5C is 920 to 1,980 gigatons of carbon dioxide for the period 2016 to 2100. In any other science discipline an uncertainty this large would imply that “we don’t know” but the climate science conclusion is that a budget of 920 gigatons give us “a 66% likelihood of staying below the 1.5C target“.
  11. However these mysterious complexities of the carbon budget including for example the mystery of the “remaining carbon budget” [LINK] have a much simpler and more rational explanation in terms of statistics. The underlying issue is that climate science is dealing with a spurious statistic and attempting to explain the random variations of the spurious statistic in terms of the science of climate change and with the help of climate models and earth system models of increasing complexity.
  12. The essential carbon budget issue is that the proportionality between temperature and cumulative emissions is spurious and illusory and its use in carbon budget construction is not a science but an error in statistics. The statistical issues with the TCRE are explained in related posts [LINK] [LINK] . The issues that this statistics error creates in carbon budgets are discussed in these related posts [LINK] [LINK] [TCRE] .




  1. Matthews, H. Damon, et al. “The proportionality of global warming to cumulative carbon emissions.” Nature 459.7248 (2009): 829.  The global temperature response to increasing atmospheric CO2 is often quantified by metrics such as equilibrium climate sensitivity and transient climate response1. These approaches, however, do not account for carbon cycle feedbacks and therefore do not fully represent the net response of the Earth system to anthropogenic CO2 emissions. Climate–carbon modelling experiments have shown that: (1) the warming per unit CO2 emitted does not depend on the background CO2 concentration2; (2) the total allowable emissions for climate stabilization do not depend on the timing of those emissions3,4,5; and (3) the temperature response to a pulse of CO2 is approximately constant on timescales of decades to centuries3,6,7,8. Here we generalize these results and show that the carbon–climate response (CCR), defined as the ratio of temperature change to cumulative carbon emissions, is approximately independent of both the atmospheric CO2 concentration and its rate of change on these timescales. From observational constraints, we estimate CCR to be in the range 1.0–2.1 °C per trillion tonnes of carbon (Tt C) emitted (5th to 95th percentiles), consistent with twenty-first-century CCR values simulated by climate–carbon models. Uncertainty in land-use CO2 emissions and aerosol forcing, however, means that higher observationally constrained values cannot be excluded. The CCR, when evaluated from climate–carbon models under idealized conditions, represents a simple yet robust metric for comparing models, which aggregates both climate feedbacks and carbon cycle feedbacks. CCR is also likely to be a useful concept for climate change mitigation and policy; by combining the uncertainties associated with climate sensitivity, carbon sinks and climate–carbon feedbacks into a single quantity, the CCR allows CO2-induced global mean temperature change to be inferred directly from cumulative carbon emissions.
  2. Allen, Myles R., et al. “Warming caused by cumulative carbon emissions towards the trillionth tonne.” Nature 458.7242 (2009): 1163.  Global efforts to mitigate climate change are guided by projections of future temperatures1. But the eventual equilibrium global mean temperature associated with a given stabilization level of atmospheric greenhouse gas concentrations remains uncertain1,2,3, complicating the setting of stabilization targets to avoid potentially dangerous levels of global warming4,5,6,7,8. Similar problems apply to the carbon cycle: observations currently provide only a weak constraint on the response to future emissions9,10,11. Here we use ensemble simulations of simple climate-carbon-cycle models constrained by observations and projections from more comprehensive models to simulate the temperature response to a broad range of carbon dioxide emission pathways. We find that the peak warming caused by a given cumulative carbon dioxide emission is better constrained than the warming response to a stabilization scenario. Furthermore, the relationship between cumulative emissions and peak warming is remarkably insensitive to the emission pathway (timing of emissions or peak emission rate). Hence policy targets based on limiting cumulative emissions of carbon dioxide are likely to be more robust to scientific uncertainty than emission-rate or concentration targets. Total anthropogenic emissions of one trillion tonnes of carbon (3.67 trillion tonnes of CO2), about half of which has already been emitted since industrialization began, results in a most likely peak carbon-dioxide-induced warming of 2 °C above pre-industrial temperatures, with a 5–95% confidence interval of 1.3–3.9 °C.
  3. Mackey, Brendan, et al. “Untangling the confusion around land carbon science and climate change mitigation policy.” Nature climate change 3.6 (2013): 552.  Depletion of ecosystem carbon stocks is a significant source of atmospheric CO2 and reducing land-based emissions and maintaining land carbon stocks contributes to climate change mitigation. We summarize current understanding about human perturbation of the global carbon cycle, examine three scientific issues and consider implications for the interpretation of international climate change policy decisions, concluding that considering carbon storage on land as a means to ‘offset’ CO2 emissions from burning fossil fuels (an idea with wide currency) is scientifically flawed. The capacity of terrestrial ecosystems to store carbon is finite and the current sequestration potential primarily reflects depletion due to past land use. Avoiding emissions from land carbon stocks and refilling depleted stocks reduces atmospheric CO2concentration, but the maximum amount of this reduction is equivalent to only a small fraction of potential fossil fuel emissions.
  4. Gignac, Renaud, and H. Damon Matthews. “Allocating a 2 C cumulative carbon budget to countries.” Environmental Research Letters 10.7 (2015): 075004.  Recent estimates of the global carbon budget, or allowable cumulative CO2 emissions consistent with a given level of climate warming, have the potential to inform climate mitigation policy discussions aimed at maintaining global temperatures below 2 °C. This raises difficult questions, however, about how best to share this carbon budget amongst nations in a way that both respects the need for a finite cap on total allowable emissions, and also addresses the fundamental disparities amongst nations with respect to their historical and potential future emissions. Here we show how the contraction and convergence (C&C) framework can be applied to the division of a global carbon budget among nations, in a manner that both maintains total emissions below a level consistent with 2 °C, and also adheres to the principle of attaining equal per capita CO2emissions within the coming decades. We show further that historical differences in responsibility for climate warming can be quantified via a cumulative carbon debt (or credit), which represents the amount by which a given country’s historical emissions have exceeded (or fallen short of) the emissions that would have been consistent with their share of world population over time. This carbon debt/credit calculation enhances the potential utility of C&C, therefore providing a simple method to frame national climate mitigation targets in a way that both accounts for historical responsibility, and also respects the principle of international equity in determining future emissions allowances.
  5. Rogelj, Joeri, et al. “Mitigation choices impact carbon budget size compatible with low temperature goals.” Environmental Research Letters 10.7 (2015): 075003.  Global-mean temperature increase is roughly proportional to cumulative emissions of carbon-dioxide (CO2). Limiting global warming to any level thus implies a finite CO2 budget. Due to geophysical uncertainties, the size of such budgets can only be expressed in probabilistic terms and is further influenced by non-CO2 emissions. We here explore how societal choices related to energy demand and specific mitigation options influence the size of carbon budgets for meeting a given temperature objective. We find that choices that exclude specific CO2mitigation technologies (like Carbon Capture and Storage) result in greater costs, smaller compatible CO2 budgets until 2050, but larger CO2 budgets until 2100. Vice versa, choices that lead to a larger CO2 mitigation potential result in CO2 budgets until 2100 that are smaller but can be met at lower costs. In most cases, these budget variations can be explained by the amount of non-CO2 mitigation that is carried out in conjunction with CO2, and associated global carbon prices that also drive mitigation of non-CO2 gases. Budget variations are of the order of 10% around their central value. In all cases, limiting warming to below 2 °C thus still implies that CO2 emissions need to be reduced rapidly in the coming decades.
  6. Riahi, Keywan, et al. “Locked into Copenhagen pledges—implications of short-term emission targets for the cost and feasibility of long-term climate goals.” Technological Forecasting and Social Change 90 (2015): 8-23.  This paper provides an overview of the AMPERE modeling comparison project with focus on the implications of near-term policies for the costs and attainability of long-term climate objectives. Nine modeling teams participated in the project to explore the consequences of global emissions following the proposed policy stringency of the national pledges from the Copenhagen Accord and Cancún Agreements to 2030. Specific features compared to earlier assessments are the explicit consideration of near-term 2030 emission targets as well as the systematic sensitivity analysis for the availability and potential of mitigation technologies. Our estimates show that a 2030 mitigation effort comparable to the pledges would result in a further “lock-in” of the energy system into fossil fuels and thus impede the required energy transformation to reach low greenhouse-gas stabilization levels (450 ppm CO2e). Major implications include significant increases in mitigation costs, increased risk that low stabilization targets become unattainable, and reduced chances of staying below the proposed temperature change target of 2 °C in case of overshoot. With respect to technologies, we find that following the pledge pathways to 2030 would narrow policy choices, and increases the risks that some currently optional technologies, such as carbon capture and storage (CCS) or the large-scale deployment of bioenergy, will become “a must” by 2030.
  7. Rogelj, Joeri, et al. “Differences between carbon budget estimates unravelled.” Nature Climate Change 6.3 (2016): 245.  Several methods exist to estimate the cumulative carbon emissions that would keep global warming to below a given temperature limit. Here we review estimates reported by the IPCC and the recent literature, and discuss the reasons underlying their differences. The most scientifically robust number — the carbon budget for CO2-induced warming only — is also the least relevant for real-world policy. Including all greenhouse gases and using methods based on scenarios that avoid instead of exceed a given temperature limit results in lower carbon budgets. For a >66% chance of limiting warming below the internationally agreed temperature limit of 2 °C relative to pre-industrial levels, the most appropriate carbon budget estimate is 590–1,240 GtCO2 from 2015 onwards. Variations within this range depend on the probability of staying below 2 °C and on end-of-century non-CO2 warming. Current CO2 emissions are about 40 GtCO2 yr−1, and global CO2 emissions thus have to be reduced urgently to keep within a 2 °C-compatible budget.
  8. Rogelj, Joeri, et al. “Paris Agreement climate proposals need a boost to keep warming well below 2 C.” Nature 534.7609 (2016): 631.  The Paris climate agreement aims at holding global warming to well below 2 degrees Celsius and to “pursue efforts” to limit it to 1.5 degrees Celsius. To accomplish this, countries have submitted Intended Nationally Determined Contributions (INDCs) outlining their post-2020 climate action. Here we assess the effect of current INDCs on reducing aggregate greenhouse gas emissions, its implications for achieving the temperature objective of the Paris climate agreement, and potential options for overachievement. The INDCs collectively lower greenhouse gas emissions compared to where current policies stand, but still imply a median warming of 2.6–3.1 degrees Celsius by 2100. More can be achieved, because the agreement stipulates that targets for reducing greenhouse gas emissions are strengthened over time, both in ambition and scope. Substantial enhancement or over-delivery on current INDCs by additional national, sub-national and non-state actions is required to maintain a reasonable chance of meeting the target of keeping warming well below 2 degrees Celsius.
  9. Anderson, Kevin, and Glen Peters. “The trouble with negative emissions.” Science 354.6309 (2016): 182-183.  In December 2015, member states of the United Nations Framework Convention on Climate Change (UNFCCC) adopted the Paris Agreement, which aims to hold the increase in the global average temperature to below 2°C and to pursue efforts to limit the temperature increase to 1.5°C. The Paris Agreement requires that anthropogenic greenhouse gas emission sources and sinks are balanced by the second half of this century. Because some nonzero sources are unavoidable, this leads to the abstract concept of “negative emissions,” the removal of carbon dioxide (CO2) from the atmosphere through technical means. The Integrated Assessment Models (IAMs) informing policy-makers assume the large-scale use of negative-emission technologies. If we rely on these and they are not deployed or are unsuccessful at removing CO2from the atmosphere at the levels assumed, society will be locked into a high-temperature pathway.
  10. Pfeiffer, Alexander, et al. “The ‘2 C capital stock’for electricity generation: Committed cumulative carbon emissions from the electricity generation sector and the transition to a green economy.” Applied Energy 179 (2016): 1395-1408.  This paper defines the ‘2°C capital stock’ as the global stock of infrastructure which, if operated to the end of its normal economic life, implies global mean temperature increases of 2°C or more (with 50% probability). Using IPCC carbon budgets and the IPCC’s AR5 scenario database, and assuming future emissions from other sectors are compatible with a 2°C pathway, we calculate that the 2°C capital stock for electricity will be reached by 2017 based on current trends. In other words, even under the very optimistic assumption that other sectors reduce emissions in line with a 2°C target, no new emitting electricity infrastructure can be built after 2017 for this target to be met, unless other electricity infrastructure is retired early or retrofitted with carbon capture technologies. Policymakers and investors should question the economics of new long-lived energy infrastructure involving positive net emissions.
  11. Peters, Glen P., et al. “Key indicators to track current progress and future ambition of the Paris Agreement.” Nature Climate Change 7.2 (2017): 118.  Current emission pledges to the Paris Agreement appear insufficient to hold the global average temperature increase to well below 2 °C above pre-industrial levels1. Yet, details are missing on how to track progress towards the ‘Paris goal’, inform the five-yearly ‘global stocktake’, and increase the ambition of Nationally Determined Contributions (NDCs). We develop a nested structure of key indicators to track progress through time. Global emissions2,3 track aggregated progress1, country-level decompositions track emerging trends4,5,6 that link directly to NDCs7, and technology diffusion8,9,10 indicates future reductions. We find the recent slowdown in global emissions growth11 is due to reduced growth in coal use since 2011, primarily in China and secondarily in the United States12. The slowdown is projected to continue in 2016, with global CO2 emissions from fossil fuels and industry similar to the 2015 level of 36 GtCO2. Explosive and policy-driven growth in wind and solar has contributed to the global emissions slowdown, but has been less important than economic factors and energy efficiency. We show that many key indicators are currently broadly consistent with emission scenarios that keep temperatures below 2 °C, but the continued lack of large-scale carbon capture and storage13 threatens 2030 targets and the longer-term Paris ambition of net-zero emissions.
  12. Millar, Richard J., et al. “Emission budgets and pathways consistent with limiting warming to 1.5 C.” Nature Geoscience10.10 (2017): 741.  The Paris Agreement has opened debate on whether limiting warming to 1.5 °C is compatible with current emission pledges and warming of about 0.9 °C from the mid-nineteenth century to the present decade. We show that limiting cumulative post-2015 CO2 emissions to about 200 GtC would limit post-2015 warming to less than 0.6 °C in 66% of Earth system model members of the CMIP5 ensemble with no mitigation of other climate drivers. We combine a simple climate–carbon-cycle model with estimated ranges for key climate system properties from the IPCC Fifth Assessment Report. Assuming emissions peak and decline to below current levels by 2030, and continue thereafter on a much steeper decline, which would be historically unprecedented but consistent with a standard ambitious mitigation scenario (RCP2.6), results in a likely range of peak warming of 1.2–2.0 °C above the mid-nineteenth century. If CO2emissions are continuously adjusted over time to limit 2100 warming to 1.5 °C, with ambitious non-CO2 mitigation, net future cumulative CO2emissions are unlikely to prove less than 250 GtC and unlikely greater than 540 GtC. Hence, limiting warming to 1.5 °C is not yet a geophysical impossibility, but is likely to require delivery on strengthened pledges for 2030 followed by challengingly deep and rapid mitigation. Strengthening near-term emissions reductions would hedge against a high climate response or subsequent reduction rates proving economically, technically or politically unfeasible.






  1. Northeast Lua Response Cruise, May5-13,2009 [LINK]   – I had  conversations with Robert Embley, one of the scientists on this and subsequent cruises. In 2014, I became interested in underwater volcanic activity as a source of heat triggering El Ninos since it didn’t seem logical that CO2/GHGs could be triggering them. Although at the time he was unaware of heat emanating from the lower layers of the Pacific Ocean, he did give me a reference later on indicating heat in a lower layer [LINK] and enjoyed communicating with him until the government cut it off.
  2. Magma chamber grows beneath New Zealand, COSMOS Earth Sciences June 6, 2016. Ocean warming, not atmospheric temperature, may be main contributor to glacier retreat, Science/Environment, July14,2016.
  3. Three articles relating to the Earth’s magnetic field #1: Does an anomaly in the Earth’s magnetic field portend a coming pole reversal? [LINK] , #2: How Scientists Are Tracking a Dangerous Weakening of Earth’s Magnetic Field, [LINK] #3: Clay jars store clues to Earth’s magnetic field strength [LINK]
  4. Vast lake of molten carbon discovered under western US [LINK]  
  5. Two articles about the East Pacific Rise and Climate Change:  #1: [LINK]  #2: Kinematics and dynamics of the East Pacific Rise linked to a stable, deep-mantle upwelling,  Rowley et al. Sci. Adv. 2016; 2:e1601107 23 December 2016.
  6. The river of molten iron: river-discovered speeding beneath Russia and Canada [LINK]  
  7. Massive lake of molten carbon under the USA [LINK]
  8. A Lava Lamp inside the earth (a description of the mantle in plain language [LINK]
Hope you find this of some interest with respect to climate change.
  1. The Geology of Interglacials
  2. The Geology of ENSO
  3. About the Arctic
  4. About Antarctica






Climate Change and Land, an IPCC special report

  1. The IPCC is the world body for assessing the state of scientific knowledge related to climate change, its impacts and potential future risks, and possible response options. The Summary for Policymakers of the Special Report on Climate Change and Land (SRCCL) was approved by the world’s governments on Wednesday in Geneva. It will be a key scientific input into forthcoming climate and environment negotiations, such as the Conference of the Parties of the UN Convention to Combat Desertification (COP14) in New Delhi, India in September and the UN Framework Convention on Climate Change Conference (COP25) in Santiago, Chile, in December.
  2. Governments challenged the IPCC to take a comprehensive look at the whole land-climate system. The IPCC did this through many contributions from experts and governments worldwide. This is the first time in IPCC report history that a majority of authors – 53% – are from developing countries,” said Hoesung Lee, Chair of the IPCC. This report shows that better land management can contribute to tackling climate change, but is not the only solution. Reducing greenhouse gas emissions from all sectors is essential if global warming is to be kept to well below 2ºC, if not 1.5oC.  [Comment: “better land management can contribute to tackling climate change, but is not the only solution“. That “tackling climate change” is inserted in the sustainable land management context reveals that the real purpose of this document is to push the UN’s climate action program although no evidence has been submitted that such action in land management will reduce the rate of warming. Also one is left wondering what the reference is in the statement that “it is not the only solution“. If there are other solutions why are farmers being thus burdened in their sustainable land management practices. Clearly, the IPCC is not the appropriate UN agency for this job particularly since the UN has an agriculture agency called the Food and Agriculture Organization.]
  3. In 2015, governments backed the Paris Agreement goal of strengthening the global response to climate change by holding the increase in the global average temperature to well below 2ºC above pre-industrial levels and to pursue efforts to limit the increase to 1.5ºC.
  4. Biofuels & The Land Climate System: Land must remain productive to maintain food security as the population increases and the negative impacts of climate change on vegetation increase. Therefore, there are limits to the contribution of land to addressing climate change with cultivation of energy crops and afforestation. It takes time for trees and soils to store carbon effectively. Biofuel production needs to be managed to avoid risks to food security, biodiversity and land degradation. Desirable outcomes will depend on locally appropriate policies and governance systems. [Comment-1: The purpose of the document is to describe the role of land use by humans in the climate system but what is a “land climate system“. The invention and interjection of this phrase may help the UN’s bureaucratic needs but does not serve the purpose of clarity in communication. Perhaps this kind of language is used to create an air of elevated scientific reality, perhaps of some deep scientific knowledge yet unspecified, known by the IPCC, but with which the reader is not as familiar. Such bureaucratic tools have no place in clear science communication.]
    [Comment-2: [“Land must remain productive to maintain food security as the population increases and the negative impacts of climate change on vegetation increase. Therefore, there are limits to the contribution of land to addressing climate change with cultivation of energy crops and afforestation“. This is a bizarre and fraudulent way for the IPCC to acknowledge its gross and destructive error in the promotion of biofuel as a way of combating climate change. The error was pointed out early on by agricultural science as well as the FAO with reference to not only the allocation of land resources (mentioned by the IPCC in this document) but also, and more importantly, the allocation of critical and scarce resources such as phosphorus fertilizer (omitted in this IPCC document). It should be noted that at that time, many researchers along with the FAO had argued that the mis-allocation of phosphorus fertilizer to climate action would adversely affect food production and food security. An even bigger issue in Southeast Asia is that the push for biodiesel production from palm oil led to a devastating destruction by fire of tens of millions of hectares of forest particularly in Indonesia. The IPCC and its minions must take full responsibility for the destructive failure of their idea, even now promoted by the IPCC, that all the world’s problems can now be framed in terms of climate change and that their resolution is somehow tied in with climate action.] 
    Comment-3:  [The issue of food security and land use is an agricultural issue and the UN has an agriculture agency in the form of the Food and Agriculture Organization (FAO). That the UN and the world now depend on IPCC climate science experts for food and agriculture issues such as food security and land use, is a worrying sign of how distorted and dysfunctional the UN has become as a global body by having morphed into a one-issue creature that sees everything in terms of climate change and climate action.]
  5. Land is a critical resource: Sustainability in agriculture is needed to tackle climate change because land plays an important role in the climate system. Agriculture, forestry and other types of land use account for 23% of human greenhouse gas emissions. At the same time natural land processes absorb carbon dioxide equivalent to almost a third of carbon dioxide emissions from fossil fuels and industry. Therefore, management of land resources sustainably helps to address climate change.  Comment: [Here, the IPCC having admitted that it had gone wrong when it had redefined land as a climate action device in terms of biofuel production, instead of defining land as a critical food and agriculture asset, now goes back to that same flawed position that got them into the biofuel blunder. Thus, once again, the climate priority of the UN and the IPCC redefines the role of land in terms of climate change and climate action having paid lip service to its food and agriculture function.]
  6. Land already in use could feed the world in a changing climate and provide biomass for renewable energy, but early, far-reaching action across several areas is required. The conservation and restoration of ecosystems and biodiversity is necessary.
  7. Desertification and land degradation: When land is degraded, it becomes less productive, restricting what can be grown and reducing the soil’s ability to absorb carbon. This exacerbates climate change, while climate change in turn exacerbates land degradation in many ways. The solution is sustainable land management. The choices we make about sustainable land management can help reduce and in some cases reverse these adverse impacts. Comment: [Sustainable land management in the traditional sense (see bibliography below) has to do with maintaining its productivity over a longer life span. Here, the IPCC uses the same word to mean something entirely different. While appearing to present “sustainable land management as a tool to help farmers, it appears that the real purpose of this verbiage is to sell its climate agenda in terms of using land to absorb carbon. In this context it should be noted that the “human cause” argument in global warming is that in the industrial economy humans started bringing up fossil fuels from under the ground, where they had been sequestered from the carbon cycle for millions of years, and injecting that carbon into the current account of the carbon cycle. This injection of carbon is taken as an artificial and unnatural perturbation of the carbon cycle and therefore of the climate system by way of the GHG effect of atmospheric CO2. This extension of AGW theory from the impact of the “industrial economy” on climate to all human activities, even those that predate the Industrial Revolution, is arbitrary and capricious. The perturbation of the current account of the carbon cycle with “external carbon” can only be assessed in terms of non-surface carbon that is peculiar to the industrial economy][LINK] .
  8. In a future with more intensive rainfall the risk of soil erosion on croplands increases, and sustainable land management is a way to protect communities from the detrimental impacts of this soil erosion and landslides but there are limits to the ability of sustainable land management to control soil erosion. There are land areas known to experience desertification. These lands are vulnerable to climate change extreme events including drought, heatwaves, and dust storms, with an increasing global population providing further pressure. Comment: [ So what? What on earth is the point of this item in the context of this report? Has climate change shown that global warming has caused soil erosion, landslides, or desertification? or is it some inane bureaucratic climate verbiage derived from the UN’s standard climate fear mongering database? That you need to stick things like that in a report about sustainable land management exposes your hidden agenda.]
  9. We propose options to tackle land degradation, and prevent or adapt to further climate change. It also examines potential impacts from different levels of global warming. New knowledge shows an increase in risks from dryland water scarcity, fire damage, permafrost degradation and food system instability, even for global warming of around 1.5°C. Very high risks related to permafrost degradation and food system instability are identified at 2°C of global warming. Comment: [Sadly, this laundry list of standard and unproven climate impacts is neither new nor knowledge. In fact the invention of scary climate impacts to sell climate action propositions is standard operating procedure of the UN, the IPCC, and the whole of the climate movement that you have organized. Please see [LINK] . 
  10. Food security: Coordinated climate action can simultaneously improve land, food security and nutrition, and help to end hunger. The report highlights that climate change is affecting all four pillars of food security: availability (yield and production), access (prices and ability to obtain food), utilization (nutrition and cooking), and stability (disruptions to availability). Food security will be increasingly affected by future climate change through yield declines especially in the tropics increased prices, reduced nutrient quality, and supply chain disruptions. Comment: [That “climate change is affecting all four pillars of food security” and that “food security will be increasingly affected by future climate change through yield declines” are utter and complete falsehoods with no evidence provided by the UN or by anyone else. That the UN is still holding that line after evidence to the contrary reveals that this document is not an information delivery vehicle but a vehicle for climate activism and fear mongering.  
  11.  We will see different effects in different countries, but there will be more drastic impacts on low-income countries in Africa, Asia, Latin America and the Caribbean. About 1/3 of food produced is lost or wasted. Causes of food loss and waste differ substantially between developed and developing countries, as well as between regions. Reducing this loss and waste would reduce greenhouse gas emissions and improve food security. Comment: [Yes there is food waste in third world poor shit-hole countries and that derives mostly from not having refrigerators, potable water, and inadequate protection from insects and rodents. These things are not climate impacts. Reducing greenhouse gs emissions is not a method of attaining food security. Giving these people fossil fuels, electricity, and refrigerators, and increasing their greenhouse gas emissions is the more rational response to their pitiful condition. Poverty is not an opportunity to sell climate snake oil. 
  12. Some dietary choices require more land and water, and cause more emissions of heat-trapping gases than others. Balanced diets featuring plant-based foods, such as coarse grains, legumes, fruits and vegetables, and animal-sourced food produced sustainably in low greenhouse gas emission systems, present major opportunities for adaptation to and limiting climate change. Comment: [The “human cause” argument in global warming is that in the industrial economy humans started bringing up fossil fuels from under the ground, where they had been sequestered from the carbon cycle for millions of years, and injecting that carbon into the current account of the carbon cycle. This injection of carbon is taken as an artificial and unnatural perturbation of the carbon cycle and therefore of the climate system by way of the GHG effect of atmospheric CO2. This extension of AGW theory from the impact of the “industrial economy” on climate to all human activities, even those that predate the Industrial Revolution, is arbitrary and capricious. The perturbation of the current account of the carbon cycle with “external carbon” can only be assessed in terms of non-surface carbon that is peculiar to the industrial economy][LINK]
  13. Risk management of food systems can enhance resilience to extreme events, which has an impact on food systems. This can be the result of dietary changes or ensuring a variety of crops to prevent further land degradation and increase resilience to extreme or varying weather. Reducing inequalities, improving incomes, and ensuring equitable access to food so that regions where land cannot provide adequate food are not disadvantaged, are other ways to adapt to the negative effects of climate change. There are also methods to manage and share risks, some of which are already available, such as early warning systems. Comment: [What are these negative effects of climate change and how were they causally linked to fossil fuel emissions? That “reducing inequalities, improving incomes, and ensuring equitable access to food” are not something we do and should aspire to anyway but that are something imposed on us by climate change adaptation is ignorant and narrow minded and likely derived from and obsession with climate change.]
  14. An overall focus on sustainability coupled with early action offers the best chances to tackle climate change. This would entail low population growth and reduced inequalities, improved nutrition and lower food waste. This could enable a more resilient food system and make more land available for bioenergy, while still protecting forests and natural ecosystems. However, without early action in these areas, more land would be required for bioenergy, leading to challenging decisions about future land-use and food security. Policies that support sustainable land management, ensure the supply of food for vulnerable populations, and keep carbon in the ground while reducing greenhouse gas emissions are important. Comment: [Here we come full circle back to biofuels. The obscene logic for sustainable land management is that (1) it will reduce net carbon emissions from soils and (2) it will increase efficiency of land use to make way once again for the biofuel push that the IPCC had once preached, then retreated, the apologized, and now is once again promoting with no mention of the phosphorous fertilizer issue. When the IPCC preaches sustainable land management it is a form of climate action that they are after, not land management and the welfare of farmers. 
  15. Policies that are outside the land and energy domains, such as on transport and environment, can also make a critical difference to tackling climate change. Acting early is more cost-effective as it avoids losses. We are using technologies and good practices, but they need to be scaled up and used in other suitable places that they are not being used in now. More sustainable land use and reduction in over-consumption and food-waste, eliminating the clearing and burning of forests, preventing over-harvesting of fuelwood, and reducing greenhouse gas emissions, thus helping to address land related climate change issues. Comment: [Now they return to to the core of the issue and that is climate action with all their apparent concerns about human welfare being derived from the need for climate action. And yet, no evidence has yet been presented by climate science that climate action will reduce the rate of warming except with things like the carbon budget that contain serious statistical flaws as described in these related posts: 





  1. Smyth, A. J., and Julian Dumanski. “A framework for evaluating sustainable land management.” Canadian Journal of Soil Science 75.4 (1995): 401-406.  Concerns for the effects of global environmental change, caused primarily by the interrelated issues of environmental degradation and population growth, have prompted a consortium of international and national agencies to develop a Framework for Evaluation of Sustainable Land Management (FESLM). The FESLM, based on logical pathway analyses, provides a systematic procedure for identification and development of indicators and thresholds of sustainability. An assessment of sustainability is achieved by comparing the performance of a given land use with the objectives of the five pillars of sustainable land management: productivity, security, protection, viability and acceptability. A classification for sustainability is proposed, and plans for future development of the FESLM are described.
  2. Droogers, P., and J. Bouma. “Soil survey input in exploratory modeling of sustainable soil management practices.” Soil Science Society of America Journal 61.6 (1997): 1704-1710.  Soil survey information combined with exploratory simulation modeling was used to define indicators for sustainable land management. In one soil series in the Netherlands (the genoform), three different phenoforms were formed as a result of different management practices. Locations were identified using a soil map and interviews with farmers. Organic matter, bulk densities, and porosities were significantly different for the three phenoforms: biodynamic management (Bio), conventional management (Conv), and permanent grassland (Perm). By applying a dynamic simulation model for water movement, crop growth and N dynamics, the three phenoforms were analyzed in terms of sustainability indicators by defining four scenarios based on productivity and N leaching to the groundwater: (i) potential production, (ii) water-limited production, (iii) current management, and (iv) the environmental scenario. The latter was divided into EnvA: never exceeding the N-leaching threshold of 11.3 mg L-1; EnvB: exceedance occurring in one out of 30 yr; and EnvC: exceedance occurring in three out of 30 yr. Biodynamic management obtained the lowest yield under current management, while yields for Perm were highest. EnvA could not be reached for Perm as a result of high mineralization rates. Obtainable yields for scenarios EnvA, EnvB, and EnvC differed substantially, illustrating the importance of selecting “acceptable” risks in environmental regulation. The presented methodology demonstrates the importance of pedological input in sustainability studies.
  3. Bindraban, P. S., et al. “Land quality indicators for sustainable land management: proposed method for yield gap and soil nutrient balance.” Agriculture, Ecosystems & Environment81.2 (2000): 103-112.  The required increase in agricultural production to meet future food demand will further increase pressure on land resources. Integrative indicators of the current status of the agricultural production capacity of land and their change over time are needed for promoting land management practices to maintain or improve land productivity and a sustainable use of natural resources. It is argued that such land quality indicators should be obtained with a holistic systems-oriented approach. Two land quality indicators are elaborated that deal with (1) yield gaps, i.e. the difference of actual yield and yield obtained under optimum management practices, or yields determined by the land-based natural resources, and (2) a soil nutrient balance, i.e. the rate with which soil fertility is changing. The yield gap is based on the calculation of land-based cereal productivity at three different levels in terms of potential, water limited, and nutrient limited production, considering weather, soil and crop characteristics. These modelled production levels do not incorporate socio-economic aspects, which may impede agricultural management in its effort to release stress because of inadequate soil fertility, water availability and/or occurrence of pests and diseases. Therefore, location specific actual yield levels are also considered. Besides an evaluation of the actual status of the land, it is important to consider the rate of change. The quantification of changes in soil nutrient stocks is crucial to identify problematic land use systems. The soil nutrient balance, i.e. the net difference between gross inputs and outputs of nutrients to the system, is used as measure for the changes. The indicator for the soil nutrient balance combines this rate of soil nutrient change and the soil nutrient stock. Indicators for yield gaps and soil nutrient balances are defined, procedures for their quantification are described and their general applicability is discussed.
  4. Herrick, Jeffrey E. “Soil quality: an indicator of sustainable land management?.” Applied soil ecology 15.1 (2000): 75-83.  Soil quality appears to be an ideal indicator of SLM. Soil is the foundation for nearly all land uses. Soil quality, definition: Soil Quality=capacity to sustain plant and animal productivity, maintain or enhance water and air quality, and promote plant and animal health. By reflecting the basic capacity of the soil to function, it integrates across many potential uses. Nonetheless, few land managers have adopted soil quality as an indicator of sustainable land management. There are a number of constraints to adoption. Most could be overcome through a concerted effort by the research community. Specifically, we need to address the following issues: (1) demonstrate causal relationships between soil quality and ecosystem functions, including biodiversity conservation, biomass production and conservation of soil and water resources. True calibration of soil quality requires more than merely comparing values across management systems; (2) increase the power of soil quality indicators to predict response to disturbance. Although there are many indicators that reflect the current capacity of a soil to function, there are few that can predict the capacity of the soil to continue to function under a range of disturbance regimes. Both resistance and resilience need to be considered; (3) Increase accessibility of monitoring systems to land managers. Many existing systems are too complex, too expensive, or both; (4) Integrate soil quality with other biophysical and socio-economic indicators. Effective early-warning monitoring systems will require not just the inclusion of both biophysical and socio-economic indicators, but also the development of models that incorporate feedbacks between soil quality and socio-economic conditions and trends and (5) Place soil quality in a landscape context. Most ecosystem functions depend on connections through time across different parts of the landscape. In conclusion, soil quality is a necessary but not sufficient indicator of sustainable land management. Its value will continue to increase as limitations are diminished through collaboration between scientists, land managers and policymakers.
  5. Holt-Giménez, Eric. “Measuring farmers’ agroecological resistance after Hurricane Mitch in Nicaragua: a case study in participatory, sustainable land management impact monitoring.” Agriculture, Ecosystems & Environment 93.1-3 (2002): 87-105.A study using a participatory research approach and simple field techniques found significant differences in agro-ecological resistance between plots on “conventional” and “sustainable” farms in Nicaragua after Hurricane Mitch. On average, agro-ecological plots on sustainable farms had more topsoil, higher field moisture, more vegetation, less erosion and lower economic losses after the hurricane than control plots on conventional farms. The differences in favor of agro-ecological plots tended to increase with increasing levels of storm intensity, increasing slope and years under agro-ecological practices, though the patterns of resistance suggested complex interactions and thresholds. For some indicators agro-ecological resistance collapsed under extreme stress. With the help of 19 non-governmental organizations (NGOs) and 45 farmer–technician teams, 833 farmers measured key agroecological indicators on 880 plots paired under the same topographical conditions. These paired observations covered 181 communities of smallholders from southern to northern Nicaragua. The broad geographical coverage took into account the diversity of ecological conditions, a variety of practices common to sustainable agriculture in Nicaragua, and moderate, high and extreme levels of hurricane impact. This coverage, and the massive mobilization of farmer–technician field research teams, was made possible by the existence of the Movimiento Campesino a Campesino (MCAC) (farmer-to-farmer movement), a widespread smallholders’ network for sustainable land management. An approach for measuring agroecological resistance is introduced, and it is suggested that comparatively higher levels of agroecological resistance are an indication of lower vulnerability and higher sustainability. However, the effectiveness of practices appears to be bounded by a combination of steep slopes, maintenance and design of soil conservation structures, and extremely high storm intensity. The study concludes that the participatory research can contribute significantly to the monitoring and development of sustainable land management systems (SLM) among smallholders, and recommends a sustainable, participatory approach to agricultural reconstruction following natural disasters.
  6. Bouma, Johan. “Land quality indicators of sustainable land management across scales.” Agriculture, Ecosystems & Environment 88.2 (2002): 129-136.  Existing definitions of “soil quality” and “sustainable land management” are analysed to derive a procedure for defining land quality (LQ) indicators of sustainable land management. Land rather than soil qualities are considered to reflect the impact of the climate on soil behaviour. LQ is different for different types of land use and attention is arbitrarily confined here to agriculture. Simulation modelling of crop growth and solute fluxes is used to define LQ as the ratio between a conditioned crop yield and potential yield×100. The actual agro-ecological condition and its potential, both expressed by LQ for a given piece of land, is considered here as independent input into broader land-use discussions which tend to be dominated by socio-economicand political considerations. Agro-ecological considerations should not be held hostage to socio-economic and political considerations which may change in the near future while the LQ has a much more permanent character. The proposed LQ reflects yields, risks of production as simulations are made for many years, and soil and water quality associated with the production process. The latter are expressed here in an exploratory manner for seven tropical soils and in more detail for Dutch conditions in terms of the probability that groundwater is polluted with nitrates, reflecting the most dominant current LQ problem. The proposed procedure requires the selection of acceptable production and pollution risks by the user before a LQ value can be obtained. Existing definitions implicitly emphasise the field and farmlevel. However, LQ is also important at the regional and higher level which, so far, has received little attention. Then, again, an agro-ecological approach is suggested when defining the LQ as input into the planning process, emphasising not only an independent assessment of the potential for agricultural production, but also of nature conservation.
  7. Fakoya, E. O., M. U. Agbonlahor, and A. O. Dipeolu. “Attitude of women farmers towards sustainable land management practices in South-Western Nigeria.” World journal of agricultural sciences 3.4 (2007): 536-542.  The knowledge of the fungibility (replacable) and renewability potential of natural resources are critical determinants of the attitude and management conservation measures adopted to achieve a sustainable use. Women farmers have taken dominant roles in primary agricultural production in Nigeria over last two decades. The study was carried out among women farmers in Ondo State, South-West Nigeria, to investigate their knowledge and attitude towards sustainable land management practices in arable food crop production. Multistage sampling technique was adopted in selecting a total of 160 women farmers drawn from 18 extension blocks in the state. Data was collected on socio-demographic characteristics, knowledge/attitude towards land management practices and measures adopted by the women. The data was then analysed using both descriptive and inferential statistics. The results revealed that the mean age of the women farmers in the state was 45.3 years, most of the farmers (about 58.77 percent) were married and that majority of the farmers presently cultivated personal land. Also, it was observed that most of the farm lands were inherited or family-owned. Mixed cropping is the most dominant cropping system and the women were mainly farmers though about 12 percent of them are also involved in off-farm processing. The correlation analysis revealed that there is a strong positive (r = 0.63; p< 0.05) correlation between the attitude score and land management practices adopted by the women farmers. The study recommends increase in awareness campaigns on land use fertility and management practices, also that women farmers, through appropriate policy of land tenure and ownership be given equal assess to land resources
  8. *Kassie, Menale, et al. “The economics of sustainable land management practices in the Ethiopian highlands.” Journal of agricultural economics 61.3 (2010): 605-627.  This article uses data from household‐ and plot‐level surveys conducted in the highlands of the Tigray and Amhara regions of Ethiopia. We examine the contribution of sustainable land management (SLM) practices to net value of agricultural production in areas with low vs. high agricultural potential. A combination of parametric and non‐parametric estimation techniques is used to check result robustness. Both techniques consistently predict that minimum tillage (MT) is superior to commercial fertilisers (CFs), as are farmers’ traditional practices (FTPs) without CFs, in enhancing crop productivity in the low agricultural potential areas. In the high agricultural potential areas, in contrast, use of CFs is superior to both MT and FTPs without CFs. The results are found to be insensitive to hidden bias. Our findings imply a need for careful agro‐ecological targeting when developing, promoting and scaling up SLM practices.













Future cumulative budgets from January 2015 for percentiles
of the distribution of RCP8.5 (LEFT) AND RCP2.6 (RIGHT)



Emission budgets and pathways consistent with limiting warming to 1.5 °C
Richard J. Millar, Jan S. Fuglestvedt, Pierre Friedlingstein, Joeri Rogelj, Michael J. Grubb, H. Damon Matthews, Ragnhild B. Skeie, Piers M. Forster, David J. Frame & Myles R. Allen
Nature Geoscience volume 10, pages 741–747 (2017)  LINK TO FULL TEXT PDF:  2017CARBON-BUDGET-PAPER-PDF 




The Paris Agreement has opened debate on whether limiting warming to 1.5 °C is compatible with current emission pledges and warming of about 0.9 °C from the mid-nineteenth century to the present decade. We show that limiting cumulative post-2015 CO2 emissions to about 200 GtC would limit post-2015 warming to less than 0.6 °C in 66% of Earth system model members of the CMIP5 ensemble with no mitigation of other climate drivers. We combine a simple climate–carbon-cycle model with estimated ranges for key climate system properties from the IPCC Fifth Assessment Report. Assuming emissions peak and decline to below current levels by 2030, and continue thereafter on a much steeper decline, which would be historically unprecedented but consistent with a standard ambitious mitigation scenario (RCP2.6), results in a likely range of peak warming of 1.2–2.0 °C above the mid-nineteenth century. If CO2 emissions are continuously adjusted over time to limit 2100 warming to 1.5 °C, with ambitious non-CO2 mitigation, net future cumulative CO2 emissions are unlikely to prove less than 250 GtC and unlikely greater than 540 GtC. Hence, limiting warming to 1.5 °C is not yet a geophysical impossibility, but is likely to require delivery on strengthened pledges for 2030 followed by challengingly deep and rapid mitigation. Strengthening near-term emissions reductions would hedge against a high climate response or subsequent reduction rates proving economically, technically or politically unfeasible.
















  1. Figure 5 is a split-half reliability test of the near perfect proportionality between surface temperature and cumulative emissions from which the TCRE and the carbon budget are derived. In this context, it is best to understand surface temperature as cumulative warming. Therefore the correlations we see in these charts are correlations between cumulative values – cumulative warming as a function of cumulative emissions.
  2. Three different datasets of mean global temperatures are used – two temperature reconstructions (HADCRUT & BERKELEY) and the RCP8.5 business as usual projection of CMIP5 forcings. The full span is restricted to 156 years as 1861-2016 constrained by the the RCP8.5 series. The split halves are therefore 78 years. What we see in Figure 5 is that both the correlation and the regression coefficient (TCRE) between cumulative warming and cumulative emissions show large differences among full span, first half, and second half values not only for the temperature reconstructions but also for the theoretical projections from climate models in thee RCP8.5 values. We conclude from the analysis in Figure 5 that the TCRE is an unreliable statistic because it fails the spit half test and is therefore likely to be spurious and illusory. A further conclusion is that since these differences are also seen in the theoretical RCP series, the problem with the TCRE proportionality is likely to be a structural issue and not unique to these data.
  3. The structural nature of the spuriousness of correlations between cumulative values of time series data is examined in Figure 6 and Figure 7 by studying the behavior of random numbers. It is noted that emissions data are always positive and the temperature data in a period of warming has a bias for positive differences from one year to the next and that therefore there is some bias for the sum of temperature changes from year to year to be positive. These sums for the three data sets used, RCP8.5, HadCRU, and Berkeley are 14.6, 14.5, and 18.6 respectively. The random numbers used in Figure 6 and Figure 7 are therefore studied with positive random values for emissions against random temperature values with and without a bias for positive changes.
  4. In the analysis of random numbers, Figure 6 shows the behavior of the data when no bias exists in year to year changes in temperature but with emissions restricted to positive numbers. The two GIF images display an animation of the data under this condition. The first video displays the randomness of the relationship between the simulated positive annual emissions and simulated annual warming data without a sign constraint. No relationship is evident in the video. The second video shows the relationship between the cumulative  values of the data presented in the first video. Although some random spurious correlations are seen both positive and negative, on the whole we see no evidence of a proportionality between cumulative warming and cumulative emissions.
  5. The corresponding videos with a positive bias in temperature changes appear in Figure 7. Here, though no relationship is seen in the source data, a strong proportionality is found in the cumulative values of random numbers, just as climate science had found in the actual data for emissions and temperature. It is on this basis that we propose that the TCRE proportionality in climate science (Matthews 2009) is indistinguishable from the same proportionality in random numbers. The data presented in the GIF animations of Figure 6 and Figure 7 are summarized in Figure 8. These charts make it clear that the strong proportionality between cumulative emissions and cumulative warming found by climate science is illusory and not real because it is a creation of the bias for positive temperature changes that can be recreated in random numbers. Therefore, though carbon budgets may be constructed on the basis of the Matthews 2009 proportionality, no conclusions can be drawn from such budgets because the correlation is spurious and illusory and has no interpretation in the real world.
  6. It is shown in a related post [LINK]  that in statistical procedures that use source data repeatedly, a loss in effective sample size (EFFN) is incurred due to multiplicity in the use of the data and that this loss in EFFN translates into a loss in degrees of freedom. An extreme case of such multiplicity in the use of source data is the construction of a time series of the cumulative values of another time series. It is shown in an online paper that the in all such cases the effective sample size of cumulative  values is EFFN=2 and that therefore the degrees of freedom is DF=0. It should also be noted that the time series of cumulative values has no time scale since the there is no moving window of fixed size that moves through the time series but the size of the window changes from TS=1 to TS=N-1. Thus the time series of the cumulative values of another time series contains neither degrees of freedom nor time scale.
  7. We conclude from the analysis presented above, that the TCRE is a spurious and illusory statistic that has no interpretation and that therefore, carbon budgets constructed from he TCRE are mathematical illusions. The Millar 2017 paper cited above shows that despite its statistical flaws, climate science makes use of the TCRE in its construction of carbon budgets. The authors write “the relationship between CO2-induced future warming compatible with cumulative emissions is broadly consistent with that expected from the IPCC-AR5 likely range of TCRE”. In a related post [LINK] , it is shown that the complexity of the Remaining Carbon Budget issue in climate science derives from the statistical flaw of the TCRE described in this work,
  8. CONCLUSION: The near perfect proportionality between cumulative warming and cumulative emissions described by Matthews and others in 2009  [LINK] is a creation of the transformation to cumulative values. That proportionality is also found in the cumulative values of random numbers. This correlation derives from a sign pattern wherein emissions are always positive, and in a time of global warming, changes in temperature have a positive bias. It is shown here that under the same conditions the same correlation is found in random numbers. Therefore although strong correlation and regression coefficients can be computed from the time series of cumulative values, these statistics have no interpretation because they are illusory. The presentation of climate action mathematics by climate science in the form of carbon budgets derived from the TCRE has no interpretation in the real world because the TCRE is a creation of a spurious correlation. The instability and unreliability of the TCRE demonstrated in this work, has been noted in climate science research [LINK][LINK], and in other posts on this site [LINK] . This work provides further evidence of instability along with a statistical basis for  instability in the TCRE.


















  1. The theory of AGW climate change since pre-industrial times; and the need for climate action against this trend (AGW-CC-CA) is based on a causation sequence as follows. First fossil fuel emissions of the industrial economy causes the atmospheric CO2 concentration to rise. Second the higher CO2 concentration of the atmosphere increases its GHG effect and causes warming. Third the warming is dangerous and possibly catastrophic in terms of sea level rise, extreme weather, mass extinctions, and effects on agriculture and health. Fourth the undesirable and dangerous changes being caused by AGW climate change can and must be attenuated by taking climate action in the form of a synchronized global emission reduction program. Climate action will work because emission reduction will reduce the rate of rise in atmospheric CO2 and at zero emissions, the rise will cease. Following that atmospheric CO2 can be reduced with carbon dioxide removal and sequestration technologies being developed [LINK] .
  2. Fossil fuel emissions and atmospheric composition Part-1: The AGW-CC-CA causation sequence begins with the assumption that the observed changes in atmospheric concentration since pre-industrial times are explained exclusively in terms of fossil fuel emissions. Two arguments are presented by climate as proof of this relationship. The first argument is the flow account of the carbon cycle with and without fossil fuel emissions. The flow accounting presented shows that the rise in atmospheric CO2 is explained in terms of fossil fuel emissions. There are two problems with the methodology in this argument. First, nature’s carbon cycle flows are not directly measurable but are results of gross estimations with large uncertainties. To balance this flow account, uncertainties are ignored and the much larger natural flows of the carbon cycle are inferred with the implicit assumption that the increase in atmospheric CO2 derives from fossil fuel emissions. The flow accounting thus achieved of course shows that changes in atmospheric CO2 are driven by fossil fuel emissions. However, when uncertainties in natural flows are taken into account, it is shown that fossil fuel emissions cannot even be detected in the context of these uncertainties. The relevant analysis is presented in the post Carbon Cycle Measurement Problems Solved with Circular Reasoning 
  3. Fossil fuel emissions and atmospheric composition Part-2: Yet another proof of the causal relationship between fossil fuel emissions and rising atmospheric CO2 concentration is the observation that atmospheric CO2 is rising during a time of continued fossil fuel emissions since the Industrial Revolution first noted in the Callendar 1938 paper and subsequently repeated in AGW studies that followed. And in fact, if we look at the correlation between the time series of source data we find a strong and apparently statistically significant positive correlation between rising atmospheric CO2 concentration and fossil fuel emissions. However, it is well known that correlations between the source data of time series often derive from shared trends and not necessarily from responsiveness of one to changes in the other at a finite time scale at which this causation should occur. This property of time series data has been extensively documented by Tyler Vigen [LINK] . To separate responsiveness at the time scale of interest from the spurious effect of shared trends it is necessary to remove the trends from the data in what is called detrended correlation analysis as explained by Alex Tolley in this lecture [LINK] .
  4. When this procedure is used, the correlation in the source time series vanishes and no detrended correlation is found at scales from 1 to 5 years. This result supports and strengthens the conclusion drawn in the carbon flow accounting analysis with the common conclusion that no evidence is found in the observational data that atmospheric CO2 concentration is responsive to fossil fuel emissions in a measurable way. Details of this work is presented in a related post on this site [LINK] . It is noted in that post the analysis presented by climate science contains circular reasoning because it is carried out strictly in the context of assumed causes and in the absence of natural flows particularly the known large geological flows of carbon from plate tectonics and volcanism both above ground and in the ocean floor particularly so in the East Pacific Rise and in the Pacific Ring of Fire, a region of intense geological activity.
  5. The 14C Dilution Argument: A further argument presented by climate science to support the attribution of the observed rise in atmospheric CO2 concentration to fossil fuel emissions is that of Carbon-14 dilution by fossil fuel emissions. Carbon-14 (14C) forms naturally in the atmosphere by the action of cosmic rays on nitrogen but it is radioactive and so, once formed, 14C decays exponentially with a half-life of about 5,700 years. Radioactive decay is balanced by new cosmogenic synthesis and at equilibrium roughly one part per trillion of atmospheric carbon dioxide is made with radiocarbon. All carbon life-forms contain the prevailing equilibrium ratio of atmospheric 14C as long as they are alive and their bodily carbon is being replenished. When they die, however, the radiocarbon fraction in their body begins an exponential decay.
  6. The relevance of these relationships in climate science derives from the idea that fossil fuels are dead remains of living things that has been dead for millions of years and that therefore all their 14C has decayed leaving them 14C-free. It is thus postulated that the release of fossil fuel emissions into the atmosphere reduces the radiocarbon portion of atmospheric carbon dioxide and that therefore the degree of such radiocarbon dilution serves as a measure of the contribution of fossil fuel emissions to the observed increase in atmospheric carbon dioxide.
  7. The primary evidence for such dilution is the Stuiver and Quay paper (SQ) based on tree ring analysis of Douglas Firs in the Pacific Northwest of the USA that grew during the period 1815 to 1975. Their data show a steady 14C ratio from 1820 to 1900 with perhaps a gradual decline of about 5% and then a steep decline of about 20% from 1900 to 1950. These data are generally accepted as empirical evidence that the observed increase in atmospheric CO2 since pre-industrial times is derived from fossil fuel emissions because of the dilution of atmospheric 14C with pure 12C carbon of fossil fuels.
  8. However the attribution of these changes to fossil fuels contains a fatal flaw. During the period of the SQ study, 1900-1950, total fossil fuel emissions were 50 gigatons of carbon equivalent or 180 gigatons of carbon dioxide. These flows could not have caused a 14C dilution of more than 8%. The dilution of 20% reported by SQ is therefore not evidence of the effect of fossil fuel emissions. It should be mentioned in this context that geological carbon emissions are also pure 12C free of 14C carbon isotopes. If anything, the SQ data point to the more plausible geological flow explanation of changes to atmospheric composition. The Stuiver and Quay post on this site may be found here [LINK] .
  9. Climate Action and the Carbon Budget. The essence of climate change activism is climate action, stated as reductions in fossil fuel emissions needed to limit AGW warming to an upper limit considered safe. The unspoken principle is reduction in the use of fossil fuels with eventual elimination of fossil fuels altogether from the global energy infrastructure but stated in terms of emissions. In that sense AGW theory and its claimed calamitous impacts serve as the rationale for the energy infrastructure changes sought.
  10. AGW theory holds that warming occurs in a two-step process without a well defined time scale. First, emissions cause atmospheric CO2 to rise and second the higher atmospheric CO2 level increases surface temperature so that relative to the lower CO2 concentration prior to the increase, a warming trend is created in which the rate warming is a function of the rate of emissions. This equation when formalized can be used in climate models to create pathways for different emission reduction plans and these pathways could then be used to design an emission reduction plan for a target rate of warming. The target rate is usually stated as the total amount of warming since pre-industrial times by at the target date as for example 1.5C of warming since pre-industrial times by the year 2100. The sum of all the emissions that can be made from the present to the target date to stay within the warming limit is called the carbon budget. The carbon budget has thus become the focal point of climate action design and evaluation.
  11. However because of inconvenient non-linearity and large uncertainties in climate model pathways, carbon budget mathematics are instead based on the TCRE (Transient Climate Response to Emissions) described in a related post [LINK] . The TCRE arises from the near perfect proportionality between cumulative warming and cumulative emissions first noticed by climate scientists in 2009. The corresponding regression coefficient in units of degC of cumulative warming per trillion tons of cumulative emissions is the TCRE. This relationship is supported byn a linear relationship with correlation > 90%.  The TCRE is simpler to compute and appears to be mathematically more precise and robust than emission pathway computations of climate models.
  12. The important contribution of the TCRE in climate science has been in the area of climate action. In its AGW theory, climate science forecasts what it thinks are the undesirable effects of AGW such as sea level rise and extreme weather, attributed to fossil fuel emissions of the industrial economy. In its climate action plan, climate science shows humanity the path to avoid these undesirable impacts of climate. Climate action refers to a globally coordinated effort to reduce fossil fuel emissions as a way of attenuating the rate of AGW and thus moderating its undesirable impacts.
  13. Globally coordinated climate action plans such as the Paris Agreement are designed according to a carbon budget. The carbon budget refers to the total amount of cumulative emissions that can be made to stay at or below a given target temperature. The carbon budget is derived from the TCRE. For example, after 1C of warming from pre-industrial times, the carbon budget for a target of 1.5C would be the cumulative emissions that correspond to cumulative warming of 0.5C. Thus cumulative emissions from now to the 1.5C target would be the 0.5C/TCRE where TCRE is denominated in degC/trillion tons of cumulative emissions. A typical v alue of the TCRE coefficient is TCRE=2 degC/trillion tons. Thus in this case, the carbon budget would be 0.5/2 or 2.5 trillion tons of cumulative emissions allowable to stay at or below 1.5C warming since pre-industrial.
  14. THE IMPOSSIBILITY OF A CARBON BUDGET: The carbon budget can be computed as shown in the previous two paragraphs, but in light of the absence of attribution of changes atmospheric CO2 concentration to fossil fuel emissions, the carbon budget is an anomaly. Although a carbon budget can be computed, and well developed procedures exist for its computation, the budget thus computed may not have a real interpretation. This intuition becomes evident when we examine the remaining carbon budget problem in the next section of this presentation.
  15. THE REMAINING CARBON BUDGET PROBLEM: The convenience in constructing carbon budgets offered by the TCRE comes with an apparently mysterious inconvenience discovered by climate scientists and described in a related post [LINK] . It turns out that partway into a carbon budgeted time span, the remaining budget cannot be estimated by subtraction. Instead the TCRE carbon budget computation must be done anew for the remaining portion of the time span. The reason for this, described in the same document linked above, is that the TCRE proportionality, though showing a strong near perfect correlation, does not survive the so called “split-half test” in which the time span of a time series is split into two halves and the correlation is tested in both halves. In the case of the TCRE proportionality, the value of the regression coefficient fails the split half test [LINK] in the sense that its value can change significantly when its time span is changed. The split-half instability implies that the remaining carbon budget must be computed according to the different regression coefficient in the remaining time span.
  16. FAILURE OF THE TCRE: Although the RCB computations can be carried out and the remaining carbon budget can be computed, the underlying weakness of the TCRE implied by this anomaly cannot be ignored. As shown in the TCRE post [LINK] , the real problem with the TCRE is that time series of cumulative values have neither time scale nor degrees of freedom. The effective N (sample size) of the cumulative values of a time series is EFFN=2 and therefore the degrees of freedom is DF=2-2=0. Therefore, although a TCRE coefficient can be computed it has no interpretation in the real world because both correlation and regression coefficient are spurious and illusory.
  17. FINITE TIME SCALES: Finite time scales can be created in this kind of computation if a finite time scale is used instead of using the full span. For example in a full span of 100 years, if a moving window of 20 years is used the time scale is now 20 years and the effective degrees of freedom is approximately 100/20 or 5. If the TCRE implies a real correlation between the rate of emissions and the rate of warming, we should be able to find it at finite time scales. This test is presented in a related post [LINK] where time scales of 10 to 30 years are tried. No statistically significant correlation is found. We can therefore conclude that the high correlations seen in the cumulative value time series is illusory and is not a real property of the data. AND THAT THEREFORE CARBON BUDGETS BASED ON THE TCRE ARE ILLUSORY. They can be computed but they have no interpretation in the real world.









  1. Climate change science has proposed a change in the energy infrastructure of the world away from fossil fuels because it has identified fossil fuel emissions as a cause of global warming since the Little Ice Age [LINK to Little Ice Age Post] . The undesirability of global warming and climate change has been described in terms of its proposed impacts that include sea level rise, floods, droughts, and extreme weather. A principal feature of the extreme weather impact of climate change is described in terms of more intense and more destructive tropical cyclones as described in a related post [Climate Change and Hurricanes] . In addition to the North Atlantic Tropical Cyclone Basin where tropical cyclones are called Hurricanes, there are five other basins where they form. In the East Pacific Basin they are called Typhoons. In the other four basins (North Indian, South Indian, West Pacific, and South Pacific, they are simply called “tropical cyclones”.
  2. The link between climate change and intensification of tropical cyclones is sea surface temperature (SST). Rising global surface temperature since the LIA in the climate change era, ascribed to fossil fuel emissions, includes an upward trend in SST. In theory, the higher the surface temperature is the more energy there will be in the tropical cyclone, and therefore the greater the potential for the Accumulated Cyclone Energy (ACE) of the tropical cyclone. Climate models indicate a causal link from fossil fuel emissions to sea surface temperature and thence to stronger, wetter, longer lasting, more intense, and more destructive hurricanes.
  3. EMPIRICAL WORK #1: Empirical evidence for the proposition that climate change increases the destructiveness of hurricanes is presented in a baseline paper by MIT climate scientist Kerry Emmanuel. The summary of this paper and its critical review is presented in a related post [LINK] . The critical review of the Emmanuel paper reveals serious statistical weaknesses in the methodology and analysis. These weaknesses make it impossible to accept its premise that climate change increases the destructiveness of hurricanes (or that of tropical cyclones in general).
  4. EMPIRICAL WORK #2: The proposed relationship between sea surface temperature and total energy (ACE) of tropical cyclones is tested in a related work posted on this site [LINK] . No evidence is found that the ACE of tropical cyclones is related to SST. This finding challenges a basic assumption about tropical cyclones that allows climate science theory to relate cyclone energy to global warming. The abstract of this work says: The proposed relationship between sea surface temperature (SST) and tropical cyclone activity is tested with data for global mean Accumulated Cyclone Energy (ACE) in all six basins and global mean SST in the study period 1945-2013. Three different time scales from annual to decadal are studied. Although some strong correlations are seen in the source time series, no correlation is found in the detrended data. A test with only Northern Hemisphere tropical cyclone basins and Northern Hemisphere SST also failed to find the needed correlation. We conclude that no evidence is found in these data to relate the ACE measure of tropical cyclone activity to mean SST.
  5. EMPIRICAL WORK #3:  The climate science proposition that climate change is causing tropical cyclones to become more intense implies that along with the global warming trend we should see a corresponding trend in total global ACE of all tropical cyclones in all basins. This hypothesis is tested in a related post on this site [LINK] . No trend is found that could support a global warming to total global ACE causation. This work is a further refutation of the claimed relationship between climate change and tropical cyclones. Abstract: In this work, the ACE index is used to compare decadal mean tropical cyclone activity worldwide in all six basins among seven decades from 1945 to 2014. Some increase in tropical cyclone activity is found relative to the earliest decades. No trend is found after the decade 1965-1974. A comparison of the six cyclone basins in the study shows that the Western Pacific Basin is the most active basin and the North Indian Basin the least. These findings are best understood in terms of the known under-count bias in the data in the earliest decades; and not in terms of the theory of anthropogenic global warming and climate change.
  6. EMPIRICAL WORK #4:  In a related work, a list of pre-industrial tropical cyclones is presented to demonstrate the existence of intense and destructive tropical cyclones that pre-date the climate change era and that might have been interpreted in terms of climate change if they had occurred in the climate change era. [LINK] .


CONCLUSION: No evidence is found in observational data to support the claim by climate science that fossil fuel emissions acting through global warming and climate change have caused tropical cyclones to become more intense and therefore more destructive. A list of pre-industrial tropical cyclones does not show that tropical cyclones were less intense in an era without fossil fuel emissions. The claim by climate science that fossil fuel emissions make tropical cyclones more destructive is likely a part of the anti fossil fuel activism of climate science meant to motivate a move of the global energy infrastructure away from fossil fuels. Activism in climate science is described in a related post [LINK] .