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FIGURE 1: ATMOSPHERIC METHANE CONCENTRATION 1983-201401

 

FIGURE 2: ANNUAL INCREASE IN METHANE CONCENTRATION02

 

FIGURE 3: ANNUAL COAL PRODUCTION03

 

FIGURE 4: ANNUAL NATURAL GAS PRODUCTION04

 

FIGURE 5: ANNUAL OIL PRODUCTION05

 

FIGURE 6: ANNUAL HYDRO-POWER GENERATION06

 

FIGURE 7: ANNUAL INDEX OF ENTERIC FERMENTATION ACTIVITY07

 

FIGURE 8: ANNUAL METHANE EMISSIONS FROM RICE CULTIVATION08

 

FIGURE 9: MULTI-COLLINEARITY 09

 

FIGURE 10: DETRENDED CORRELATION: COAL AND NATURAL GAS10

 

FIGURE 11: DETRENDED CORRELATION: OIL AND HYDROPOWER11

 

FIGURE 12: DETRENDED CORRELATION: ENTERIC FERMENTATION & RICE12

 

FIGURE 13: DETRENDED CORRELATION AT DIFFERENT METHANE LIFETIMES13

 

 

 

 

[LIST OF POSTS ON THIS SITE]

 

 

  1. The so called greenhouse effect of atmospheric carbon dioxide is based on the theory that solar irradiance reaches the surface of the earth relatively unhindered but the longer wavelength radiation by the warmed surface does not escape to outer space unhindered but is absorbed by carbon dioxide and re-radiated such that much of it is returned to the surface causing the surface temperature to be higher than it would have been without this absorption effect (Anderson, 2016) (Arrhenius, 1896) (Callendar, 1938) (Tyndall, 1861). The modern version of the theory of anthropogenic global warming (AGW) holds that atmospheric CO2 is “the control knob” that determines surface temperature at an annual time scale such that there is a direct logarithmic relationship between atmospheric CO2 and surface temperature that can be expressed in the form of an Equilibrium Climate Sensitivity or ECS to compute the rise in temperature expected for a doubling of atmospheric CO2 concentration (Charney, 1979) (Hansen-Lacis, 1984) (IPCC, 2013) (Lacis, 2010) (Manabe, 1975).
  2. It has been speculated since the 1930s that man’s use of fossil fuels in the industrial economy has introduced an extraneous and unnatural source of carbon dioxide that acts as a perturbation of the current account of the carbon cycle that sustains life and the climate system on the surface of the earth (Callendar, 1938) (Revelle, 1957). When consistent, accurate, and continual measurements of atmospheric CO2 uncontaminated by local conditions became available at the remote Mauna Loa station, the observed persistent and sustained increase in atmospheric CO2 year after year was interpreted as an alarming and unprecedented trend caused by man’s use of fossil fuels (Revelle, 1983) (Keeling, 1977) (Hansen, 1981) (Hansen, 1988).
  3. A compound feedback relationship between atmospheric CO2 and temperature was solved with computer climate models and it is claimed that the overall ocean-atmosphere climatology is driven completely by the greenhouse effect of CO2 on surface temperature to the point that atmospheric CO2 acts as the control knob that determines surface temperature (Lacis, Atmospheric CO2: Principal Control Knob Governing Earth’s Temperature, 2010). The greater greenhouse effect of water vapor depends directly on the amount of warming created by CO2 which does not condense out and is therefore “long lived” in the atmosphere (Lacis, 1974) (Lacis, The role of long lived greenhouse gases, 2013) (IPCC, 2014).
  4. In theory, the concern in “human cause” of global warming (Anthropogenic Global Warming or AGW) is that in the industrial economy, considered to have started in the late nineteenth century, humans were 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 therefore an artificial and unnatural perturbation of the carbon cycle and therefore of the climate system by way of the GHG effect of atmospheric CO2. However, this narrow definition later became extended to all human activity to include land use, agriculture, deforestation, and other activities such that the initial argument about the perturbation of the current account of the carbon cycle with external carbon no longer applied so that any carbon emission that can be ascribed to humans were considered “external”. Here we argue that this extension of AGW theory about the impact of the “industrial economy” on climate to human activities that predate the Industrial Revolution is arbitrary and capricious and that the perturbation of the current account of the carbon cycle by “external carbon” can only be assessed in terms of non-surface phenomena that are peculiar to the industrial economy.
  5. Two non-industrial human activities identified as additional causes of global warming are rice farming and enteric fermentation of farm animals because these activities are known to be sources of methane emissions. Methane (CH4) is considered to be a powerful greenhouse gas more potent than CO2. It has been suggested that the rate of global warming can be moderated by restricting human activities known to be sources of methane emission. A significant body of research exists on the subject of human-induced CH4 emissions from land use changes, rice farming, and cattle ranching (Conrad, 1996) (Johnson K. , 1995) (Sass, 1991) (Lamb, 1994) as well as emissions from the extraction and transportation of hydrocarbons (Harrison, 1996) (EPA, 2015) (Warmuzinski, 2008) (Allen, 2013) (Howarth, 2011). Recently, the generation of hydroelectric power, ordinarily thought to be a green energy source, has been found to be a source of anthropogenic methane because its production involves converting flowing river water into still water in reservoirs that retain the vast quantities of vegetation that were flooded when the reservoir was formed. Such bog-like conditions are known to favor methane emissions and these emissions have been documented (Fearnside, 2015) (Giles, 2006) (Magill, 2014) (Santos, 2006) (Delsontro, 2010). However, the IPCC does not yet recognize hydropower production as a source of anthropogenic methane. The IPCC identifies large flows of methane from natural sources (IPCC, 2007) (IPCC, 2014) that include mud volcanoes (Etiope, 2005), geothermal vents (Etiope G. , 2007), marine and terrestrial hydrocarbon seepage (Cline, 1977) (Geyer, 1973) (NASA/Goddard Space Flight Center, 2000) (Kvenvolden, 2003), termites (Sanderson, 1996), incomplete combustion in peat bog fires and coal seam fires (Stracher, 2004) (Kuenzer, 2007), and the wetlands of the northern hemisphere (Christensen, 2003) (Aselmann, 1989) (Ortiz-Llorente, 2012) (Bousquet, 2006). That natural sources of geological carbon are not trivial can be seen in the Pliocene-Eocene Thermal Maximum  (PETM) event when a global and catastrophic devastation is thought to have been caused by natural geological sources of methane [LINK] . A source of bias in the environmental sciences is the tendency to assume a human cause for all observed trends. 
  6. Although it is common to ascribe changes in atmospheric methane to human causes under study (Smith 2010), these natural flows make that attribution problematic. An added complexity in the study of atmospheric methane is that methane is unstable in the presence of oxygen and spontaneously oxidizes to carbon dioxide and water releasing the heat of reaction into the atmosphere. Methane emissions into the atmosphere thus deplete naturally with a half life of ≈5 to 6 years. In that sense methane is not a “long-lived” greenhouse gas.
  7. Care must be taken in the attribution of observed changes in atmospheric methane so that the attribution is supported by responsiveness at an annual time scale. Direct measurements of atmospheric CH4 are available from the NOAA Mauna Loa (MLO) measuring station from 1983 denominated as parts per billion by volume on a dry basis (PPBV) (NOAA, 2015). Monthly mean values of “flask” measurements of CH4 are downloaded and converted into annual means as the average of the monthly values for all 12 months of each calendar year. Annual changes in atmospheric methane are computed from 1984 to 2013 by subtracting the previous year’s annual mean adjusted for oxidation decay from the annual mean value of the current year. For the base case, we assume that each year 1/12th of the atmospheric methane decays by oxidation. Two alternate cases are also studied – one at a higher decay rate of 1/9th per year and one at a lower decay rate of 1/15th per year. These decay rates are based on a mean lifetime of methane in the atmosphere of 12±3 years. These differences give us 30 years of changes in mean annual atmospheric CH4. This time series is the object of our study and the dependent variable in our detrended correlation model.
  8. Methane measurements have been made at MLO using the “in-situ” method since 1988 (NOAA, 2015). These values are somewhat different. The flask measurements are used in this study because they offer a longer time series and a larger sample size. In the common period 1988-2014, the two series do not differ in a way that would affect our analysis. A comprehensive dataset of global greenhouse gas emissions from agricultural activities is available from the FAOSTAT data services of the Food and Agriculture Organization of the United Nations (FAO, 2015). The data are reported as “CO2-equivalent” emissions in Gigagrams per year. These figures are used only as a proxy for year to year changes in the size of agricultural activities and processes that are known to be sources of methane emission. Agricultural activities included in this study are enteric fermentation and rice cultivation.
  9. Figure 1 shows the atmospheric CH4 data used in this study. These data are used to compute annual change in atmospheric CH4 net of oxidation decay shown in the left panel of Figure 2.  The changes are computed as δCH4 = CH4i – CH4i-1 * (λ-1)/λ where λ is the mean lifetime of methane in the atmosphere and i is the year for which the change is computed. The difference δCH4 represents the additional methane that was added to the atmosphere from surface sources during the year. In the base  case presented here, the value of λ is set to λ=12 years. Possible values of λ at either end of the range  are also included in this study with λ=9 years and λ=15 years.
  10. The values of δCH4 are detrended by subtracting the trend line from the observed values. The detrended series is shown in the right panel of Figure 2. These values are the object of our study. They represent the year to year changes in atmospheric CH4 net of long term trends. We proceed now to investigate whether these changes correlate with indexes of six human activities that have been identified as anthropogenic sources of atmospheric methane. The observed data and their detrended values for coal production, natural gas production, oil production, hydropower generation, enteric fermentation, and rice cultivation are presented graphically in Figure 3 to Figure 8. An important feature of the six detrended series presented here is that, with the exception of oil production, the explanatory variables are correlated with each other to a degree that makes it difficult to test their individual effects in the same model (Draper&Smith, 1998). The correlation coefficients among the six anthropogenic emission factors are tabulated in Figure 9. The multi-collinearity among the anthropogenic emission rates may imply that methane emissions attributed to these anthropogenic sources may derive from a common natural source source and that their attribution is arbitrary and capricious.
  11. In detrended correlation analysis, we look at the correlation of each of the detrended sources of emission individually with the detrended δCh4 series. The six correlations are shown graphically in Figure 10 to Figure 12. The correlations shown in these figures are based on a mean methane lifetime in the atmosphere of λ= 12 years and the assumption that 1/12th of the atmospheric methane is removed by oxidation each year. Figure 13 shows the correlations at two additional decay rates with λ=9 and λ=15. We note in Figure 13 that higher values of λ and the corresponding lower rates of decay of atmospheric methane yield higher correlations. All eighteen values of detrended correlations are tabulated in Figure 13. The correlations for enteric fermentation and coal production are higher than the correlations for the other emission factors but in all eighteen hypothesis tests the p-value > α and we fail to reject the null H0: ρ≤0. The data do not provide evidence that any of the six sources of anthropogenic methane emission are correlated with changes in atmospheric methane at an annual time scale net of long term trends. The data do not provide evidence that changes in atmospheric methane concentration can be explained in terms of the six anthropogenic causes investigated. Rather their multi-collinearity suggests that changes in methane derive from a common source possibly the geological sources listed by the IPCC and arbitrarily ascribed to human activities.
  12. Using a conversion rate of 2.78 megatons per ppbv of methane in the atmosphere we estimate that annual changes in atmospheric methane in the sample period corresponded with 320-360 MTY for a lifetime of λ=15 years, 400-440 MTY for λ=12 years, and 540-585 MTY for λ=9 years. The IPCC estimates natural flows as 254-502 MTY and anthropogenic flows as 278-239 MTY. The detrended correlation of annual changes in atmospheric methane with anthropogenic sources were highest at λ=15 years when they are least needed and lowest at λ=9 years when they are most needed to achieve a methane balance. The apparent paradox provides further support for the non-significance and spuriousness of the observed sample correlations. The role of anthropogenic sources in observed changes in atmospheric methane will likely not be understood until we have gained a far better precision in the measurement of natural flows (Bousquet, 2006) (Talbot, 2014).
  13. We conclude from these findings that anthropogenic activities do not contribute to the observed rise in atmospheric methane in a measurable way and that therefore proposed climate action initiatives of eating less meat, the banning of fracking for natural gas production, and proposed changes in rice cultivation are unnecessary because there is no evidence that these initiatives will change the rate of increase in atmospheric methane. It  is far more likely that the observed rising trend in atmospheric methane is natural and geological in origin with no scope for human intervention for its attenuation. 

 

 

 

 

BIBLIOGRAPHY

CATTLE, MEAT EATING, METHANE, AND CLIMATE CHANGE

 

 

  1. 1991: Fung, Inez, et al. “Three‐dimensional model synthesis of the global methane cycle.” Journal of Geophysical Research: Atmospheres 96.D7 (1991): 13033-13065. The geographic and seasonal emission distributions of the major sources and sinks of atmospheric methane were compiled using methane flux measurements and energy and agricultural statistics in conjunction with global digital data bases of land surface characteristics and anthropogenic activities. Chemical destruction of methane in the atmosphere was calculated using three‐dimensional OH fields every 5 days taken from Spivakovsky et al. (1990a, b). The signatures of each of the sources and sinks in the atmosphere were simulated using a global three‐dimensional tracer transport model. Candidate methane budget scenarios were constructed according to mass balance of methane and its carbon isotopes. The verisimilitude of the scenarios was tested by their ability to reproduce the meridional gradient and seasonal variations of methane observed in the atmosphere. Constraints imposed by all the atmospheric observations are satisfied simultaneously by several budget scenarios. A preferred budget comprises annual destruction rates of 450 Tg by OH oxidation and 10 Tg by soil absorption and annual emissions of 80 Tg from fossil sources, 80 Tg from domestic animals, and 35 Tg from wetlands and tundra poleward of 50°N. Emissions from landfills, tropical swamps, rice fields, biomass burning, and termites total 295 Tg; however, the individual contributions of these terms cannot be determined uniquely because of the lack of measurements of direct fluxes and of atmospheric methane variations in regions where these sources are concentrated.
  2. 1997: Hein, Ralf, Paul J. Crutzen, and Martin Heimann. “An inverse modeling approach to investigate the global atmospheric methane cycle.” Global Biogeochemical Cycles 11.1 (1997): 43-76. Estimates of the global magnitude of atmospheric methane sources are currently mainly based on direct flux measurements in source regions. Their extrapolation to the entire globe often involves large uncertainties. In this paper, we present an inverse modeling approach which can be used to deduce information on methane sources and sinks from the temporal and spatial variations of atmospheric methane mixing ratios. Our approach is based on a three‐dimensional atmospheric transport model which, combined with a tropospheric background chemistry module, is also employed to calculate the global distribution of OH radicals which provide the main sink for atmospheric methane. The global mean concentration of OH radicals is validated with methyl chloroform (CH3CCl3) observations. The inverse modeling method optimizes the agreement between model‐calculated and observed methane mixing ratios by adjusting the magnitudes of the various methane sources and sinks. The adjustment is constrained by specified a priori estimates and uncertainties of the source and sink magnitudes. We also include data on the 13C/12C isotope ratio of atmospheric methane and its sources in the model. Focusing on the 1980s, two scenarios of global methane sources are constructed which reproduce the main features seen in the National Oceanic and Atmospheric Administration’s Climate Monitoring and Diagnostics Laboratory (NOAA/CMDL) methane observations. Differences between these two scenarios may probably be attributed to underestimated a priori uncertainties of wetland emissions. Applying the inverse model, the average uncertainty of methane source magnitudes could be reduced by at least one third. We also examined the decrease in the atmospheric methane growth rate during the early 1990s but could not associate it with changes in specific sources.   [FULL TEXT PDF]
  3. 1998: Dlugokencky, E. J., et al. “Continuing decline in the growth rate of the atmospheric methane burden.” Nature 393.6684 (1998): 447. The global atmospheric methane burden has more than doubled since pre-industrial times1,2, and this increase is responsible for about 20% of the estimated change in direct radiative forcing due to anthropogenic greenhouse-gas emissions. Research into future climate change and the development of remedial environmental policies therefore require a reliable assessment of the long-term growth rate in the atmospheric methane load. Measurements have revealed that although the global atmospheric methane burden continues to increase2 with significant interannual variability3,4, the overall rate of increase has slowed2,5. Here we present an analysis of methane measurements from a global air sampling network that suggests that, assuming constant OH concentration, global annual methane emissions have remained nearly constant during the period 1984–96, and that the decreasing growth rate in atmospheric methane reflects the approach to a steady state on a timescale comparable to methane’s atmospheric lifetime. If the global methane sources and OH concentration continue to remain constant, we expect average methane mixing ratios to increase slowly from today’s 1,730 nmol mol−1 to 1,800 nmol mol−1, with little change in the contribution of methane to the greenhouse effect.
  4. 1998: Etheridge, David M., et al. “Atmospheric methane between 1000 AD and present: Evidence of anthropogenic emissions and climatic variability.” Journal of Geophysical Research: Atmospheres 103.D13 (1998): 15979-15993. Atmospheric methane mixing ratios from 1000 A.D. to present are measured in three Antarctic ice cores, two Greenland ice cores, the Antarctic firn layer, and archived air from Tasmania, Australia. The record is unified by using the same measurement procedure and calibration scale for all samples and by ensuring high age resolution and accuracy of the ice core and firn air. In this way, methane mixing ratios, growth rates, and interpolar differences are accurately determined. From 1000 to 1800 A.D. the global mean methane mixing ratio averaged 695 ppb and varied about 40 ppb, contemporaneous with climatic variations. Interpolar (N‐S) differences varied between 24 and 58 ppb. The industrial period is marked by high methane growth rates from 1945 to 1990, peaking at about 17 ppb yr−1 in 1981 and decreasing significantly since. We calculate an average total methane source of 250 Tg yr−1 for 1000–1800 A.D., reaching near stabilization at about 560 Tg yr−1 in the 1980s and 1990s. The isotopic ratio, δ13CH4, measured in the archived air and firn air, increased since 1978 but the rate of increase slowed in the mid‐1980s. The combined CH4 and δ13CH4 trends support the stabilization of the total CH4 source.  [FULL TEXT PDF]
  5. 1998: Lelieveld, J. O. S., Paul J. Crutzen, and Frank J. Dentener. “Changing concentration, lifetime and climate forcing of atmospheric methane.” Tellus B 50.2 (1998): 128-150. Previous studies on ice core analyses and recent in situ measurements have shown that CH4 has increased from about 0.75–1.73 μmol/mol during the past 150 years. Here, we review sources and sink estimates and we present global 3D model calculations, showing that the main features of the global CH4 distribution are well represented. The model has been used to derive the total CH4 emission source, being about 600 Tg yr‐1. Based on published results of isotope measurements the total contribution of fossil fuel related CH4 emissions has been estimated to be about 110 Tg yr‐1. However, the individual coal, natural gas and oil associated CH4 emissions can not be accurately quantified. In particular natural gas and oil associated emissions remain speculative. Since the total anthropogenic CH4 source is about 410 Tg yr‐1 (∼70% of the total source) and the mean recent atmospheric CH4 increase is ∼20 Tg yr‐1 an anthropogenic source reduction of 5% could stabilize the atmospheric CH4 level. We have calculated the indirect chemical effects of increasing CH4 on climate forcing on the basis of global 3D chemistry‐transport and radiative transfer calculations. These indicate an enhancement of the direct radiative effect by about 30%, in agreement with previous work. The contribution of CH4 (direct and indirect effects) to climate forcing during the past 150 years is 0.57W m−2 (direct 0.44W m−2, indirect 0.13 W m−2). This is about 35% of the climate forcing by CO2 (1.6W m−2) and about 22% of the forcing by all long‐lived greenhouse gases (2.6 W m−2). Scenario calculations (IPCC‐IS92a) indicate that the CH4 lifetime in the atmosphere increased by about 25–30%during the past 150 years to a current value of 7.9 years. Future lifetime changes are expected to be much smaller, about 6%, mostly due to the expected increase of tropospheric O3 (→OH) in the tropics. The global mean concentration of CH4 may increase to about 2.55 μmol/mol, its lifetime is expected to increase to 8.4 years in the year 2050. Further, we have calculated a CH4 global warming potential (GWP) of 21 (kgCH4/kgCO2) over a time horizon of 100 years, in agreement with IPCC (1996). Scenario calculations indicate that the importance of the climate forcing by CH4 (including indirect effects) relative to that of CO2 will decrease in future; currently this is about 35%, while this is expected to decrease to about 15% in the year 2050. [FULL TEXT PDF]  
  6. 1999: Houweling, Sander, et al. “Inverse modeling of methane sources and sinks using the adjoint of a global transport model.” Journal of Geophysical Research: Atmospheres104.D21 (1999): 26137-26160. An inverse modeling method is presented to evaluate the sources and sinks of atmospheric methane. An adjoint version of a global transport model has been used to estimate these fluxes at a relatively high spatial and temporal resolution. Measurements from 34 monitoring stations and 11 locations along two ship cruises by the National Oceanographic and Atmospheric Administration have been used as input. Recent estimates of methane sources, including a number of minor ones, have been used as a priori constraints. For the target period 1993–1995 our inversion reduces the a priori assumed global methane emissions of 528 to 505 Tg(CH4) yr−1 a posteriori. Further, the relative contribution of the Northern Hemispheric sources decreases from 77% a priori to 67% a posteriori. In addition to making the emission estimate more consistent with the measurements, the inversion helps to reduce the uncertainties in the sources. Uncertainty reductions vary from 75% on the global scale to ∼1% on the grid‐scale (8° × 10°), indicating that the grid scale variability is not resolved by the measurements. Large scale features such as the inter-hemispheric methane concentration gradient are relatively well resolved and therefore impose strong constraints on the estimated fluxes. The capability of the model to reproduce this gradient is critically dependent on the accuracy at which the inter-hemispheric tracer exchange and the large‐scale hydroxyl radical distribution are represented. As a consequence, the inversion‐derived emission estimates are sensitive to errors in the transport model and the calculated hydroxyl radical distribution. In fact, a considerable contribution of these model errors cannot be ignored. This underscores that source quantification by inverse modeling is limited by the extent to which the rate of interhemispheric transport and the hydroxyl radical distribution can be validated. We show that the use of temporal and spatial correlations of emissions may significantly improve our results; however, at present the experimental support for such correlations is lacking. Our results further indicate that uncertainty reductions reported in previous inverse studies of methane have been overestimated.  [FULL TEXT PDF] 
  7. 2003: Dlugokencky, E. J., et al. “Atmospheric methane levels off: Temporary pause or a new steady‐state?.” Geophysical Research Letters 30.19 (2003).  The globally‐averaged atmospheric methane abundance determined from an extensive network of surface air sampling sites was constant at ∼1751 ppb from 1999 through 2002. Assuming that the methane lifetime has been constant, this implies that during this 4‐year period the global methane budget has been at steady state. We also observed a significant decrease in the difference between northern and southern polar zonal annual averages of CH4 from 1991 to 1992. Using a 3‐D transport model, we show that this change is consistent with a decrease in CH4 emissions of ∼10 Tg CH4 from north of 50°N in the early‐1990s. This decrease in emissions may have accelerated the global methane budget towards steady state. Based on current knowledge of the global methane budget and how it has changed with time, it is not possible to tell if the atmospheric methane burden has peaked, or if we are only observing a persistent, but temporary pause in its increase.  [FULL TEXT]
  8. 2010: Smith, Pete, David Reay, and Andre Van Amstel, eds. Methane and climate change. Routledge, 2010.  It is necessary to minimize our environmental impacts and carbon footprint through reducing waste, recycling and offsetting our methane emissions. During the 1990s and the first few years of the 21st century the growth rate of CH4 concentrations in the atmosphere slowed to almost zero, but during 2007 and 2008 concentrations increased once again. Recent studies have attributed to enhanced emissions of CH4 in the Arctic as a result of high temperatures in 2007, and to greater rainfall in the tropics in 2008. The former response represents a snapshot of a potentially very large positive climate change feedback, with the higher temperatures projected at high latitudes for the 21st century increasing CH4 emissions from wetlands, permafrost and CH4 hydrates. It is to this and the myriad of other natural and anthropogenic determinants of CH4 flux to the atmosphere that this book is directed. [FULL TEXT PDF]
  9. 2010: Popp, Alexander, Hermann Lotze-Campen, and Benjamin Bodirsky. “Food consumption, diet shifts and associated non-CO2 greenhouse gases from agricultural production.” Global Environmental Change 20.3 (2010): 451-462. Today, the agricultural sector accounts for approximately 15% of total global anthropogenic emissions, mainly methane and nitrous oxide. Projecting the future development of agricultural non-CO2 greenhouse gas (GHG) emissions is important to assess their impacts on the climate system but poses many problems as future demand of agricultural products is highly uncertain. We developed a global land use model (MAgPIE) that is suited to assess future anthropogenic agricultural non-CO2 GHG emissions from various agricultural activities by combining socio-economic information on population, income, food demand, and production costs with spatially explicit environmental data on potential crop yields. In this article we describe how agricultural non-CO2 GHG emissions are implemented within MAgPIE and compare our simulation results with other studies. Furthermore, we apply the model up to 2055 to assess the impact of future changes in food consumption and diet shifts, but also of technological mitigation options on agricultural non-CO2 GHG emissions. As a result, we found that global agricultural non-CO2 emissions increase significantly until 2055 if food energy consumption and diet preferences remain constant at the level of 1995. Non-CO2 GHG emissions will rise even more if increasing food energy consumption and changing dietary preferences towards higher value foods, like meat and milk, with increasing income are taken into account. In contrast, under a scenario of reduced meat consumption, non-CO2GHG emissions would decrease even compared to 1995. Technological mitigation options in the agricultural sector have also the capability of decreasing non-CO2 GHG emissions significantly. However, these technological mitigation options are not as effective as changes in food consumption. Highest reduction potentials will be achieved by a combination of both approaches.  [FULL TEXT PDF]
  10. 2011: Wirsenius, Stefan, Fredrik Hedenus, and Kristina Mohlin. “Greenhouse gas taxes on animal food products: rationale, tax scheme and climate mitigation effects.” Climatic change108.1-2 (2011): 159-184. Agriculture is responsible for 25–30% of global anthropogenic greenhouse gas (GHG) emissions but has thus far been largely exempted from climate policies. Because of high monitoring costs and comparatively low technical potential for emission reductions in the agricultural sector, output taxes on emission-intensive agricultural goods may be an efficient policy instrument to deal with agricultural GHG emissions. In this study we assess the emission mitigation potential of GHG weighted consumption taxes on animal food products in the EU. We also estimate the decrease in agricultural land area through the related changes in food production and the additional mitigation potential in devoting this land to bioenergy production. Estimates are based on a model of food consumption and the related land use and GHG emissions in the EU. Results indicate that agricultural emissions in the EU27 can be reduced by approximately 32 million tons of CO2-eq with a GHG weighted tax on animal food products corresponding to €60 per ton CO2-eq. The effect of the tax is estimated to be six times higher if lignocellulosic crops are grown on the land made available and used to substitute for coal in power generation. Most of the effect of a GHG weighted tax on animal food can be captured by taxing the consumption of ruminant meat alone.
  11. 2013: Ripple, William J., et al. “Ruminants, climate change and climate policy.” Nature Climate Change 4.1 (2013): 2. Greenhouse gas emissions from ruminant meat production are significant. Reductions in global ruminant numbers could make a substantial contribution to climate change mitigation goals and yield important social and environmental co-benefits.International climate negotiators can take steps to reduce greenhouse gas emissions from livestock as well as from the burning of fossil fuels. So far, global climate policy instruments have mainly focused on engineering improved industrial processes, energy efficiency and investments in alternative energy generation technologies, because sustainability has been predominantly interpreted as technological progress rather than changed patterns of human behaviour. Continued growth of ruminant meat consumption will represent a major obstacle for reaching ambitious climate change targets. The substantial environmental and climate costs of increased meat consumption have been recognized by the United Nations Food and Agriculture Organization. However, mitigation of greenhouse gas emissions from ruminants has not received adequate attention in negotiations under the United Nations Framework Convention on Climate Change. Meeting documents show that activities to reduce emissions from ruminants and agriculture in general, and in negotiations on land use, land-use change and forestry and reducing emission from deforestation and forest degradation have been disproportionately slow. The land-use accounting under the Kyoto Protocol provides insufficient coverage of land-based emissions considering their large contributions to greenhouse gas fluxes. The Kyoto Protocol also only covers industrialized countries, so it misses some of the largest emerging ruminant producers. Further, under Articles 3.3 and 3.4 of the Kyoto Protocol, emission reduction commitments for cropland and grazing land management are optional in many situations. The above-presented evidence calls for a more comprehensive approach to accounting in the Agriculture, Forestry and Other Land Use sector, following the lead of those countries requesting mandatory accounting for land-based emissions, including cropland and grazing land sectors. Progress would be facilitated if emissions resulting from ruminant livestock production are placed on the agenda of forthcoming global climate meetings such as the annual sessions of the Conference of the Parties. Current national policies on mitigating climate change could also be revised to curtail emissions from ruminant livestock in both developed and developing countries. Because the Earth’s climate may be near tipping points to major change, the need to act is increasingly pressing. Lowering peak climate forcing quickly with ruminant and CH4 reductions would lessen the likelihood of irreversibly crossing such tipping points into a new climatic state. Reducing the numbers of ruminants will be a difficult and complex task, both politically and socially. However, decreasing ruminants should be considered alongside our grand challenge of significantly reducing the world’s reliance on fossil fuel combustion. Only with the recognition of the urgency of this issue and the political will to commit resources to comprehensively mitigate both CO2 and non-CO2 greenhouse gas emissions will meaningful progress be made on climate change. For an effective and rapid response, we need to increase awareness among the public and policymakers that what we choose to eat has important consequences for climate change.   [FULL TEXT PDF]
  12. 2013: Edjabou, Louise Dyhr, and Sinne Smed. “The effect of using consumption taxes on foods to promote climate friendly diets–The case of Denmark.” Food policy 39 (2013): 84-96. Agriculture is responsible for 17–35% of global anthropogenic greenhouse gas emissions with livestock production contributing by approximately 18–22% of global emissions. Due to high monitoring costs and low technical potential for emission reductions, a tax on consumption may be a more efficient policy instrument to decrease emissions from agriculture than a tax based directly on emissions from production. In this study, we look at the effect of internalising the social costs of greenhouse gas emissions through a tax based on CO2equivalents for 23 different foods. Furthermore, we compare the loss in consumer surplus and the changed dietary composition for different taxation scenarios. In the most efficient scenario, we find a decrease in the carbon footprint from foods for an average household of 2.3–8.8% at a cost of 0.15–1.73 DKK per kg CO2 equivalent whereas the most effective scenario led to a decrease in the carbon footprint of 10.4–19.4%, but at a cost of 3.53–6.90 DKK per kg CO2 equivalent. The derived consequences for health show that scenarios where consumers are not compensated for the increase in taxation level lead to a decrease in the total daily amount of kJ consumed, whereas scenarios where the consumers are compensated lead to an increase. Most scenarios lead to a decrease in the consumption of saturated fat. Compensated scenarios leads to an increase in the consumption of added sugar, whereas uncompensated scenarios lead to almost no change or a decrease. Generally, the results show a low cost potential for using consumption taxes to promote climate friendly diets. HIGHLIGHTS: Effect of a consumption tax based on CO2 equivalents for 23 different foods. Calculated changes in consumption based on systems of demand elasticities, The most efficient scenario decreases CO2 emission with 2.3–8.8% at a cost of 0.15–1.73 DKK/kilo, Health effects in terms of changes in the intake of calories, saturated fat and sugar. CONCLUSION: Taxes are a low cost way of promoting climate friendly diets without large adverse health effects[FULL TEXT PDF]
    • 2014: Hedenus, Fredrik, Stefan Wirsenius, and Daniel JA Johansson. “The importance of reduced meat and dairy consumption for meeting stringent climate change targets.” Climatic change 124.1-2 (2014): 79-91. For agriculture, there are three major options for mitigating greenhouse gas (GHG) emissions: 1) productivity improvements, particularly in the livestock sector; 2) dedicated technical mitigation measures; and 3) human dietary changes. The aim of the paper is to estimate long-term agricultural GHG emissions, under different mitigation scenarios, and to relate them to the emissions space compatible with the 2 °C temperature target. Our estimates include emissions up to 2070 from agricultural soils, manure management, enteric fermentation and paddy rice fields, and are based on IPCC Tier 2 methodology. We find that baseline agricultural CO2-equivalent emissions (using Global Warming Potentials with a 100 year time horizon) will be approximately 13 Gton CO2eq/year in 2070, compared to 7.1 Gton CO2eq/year 2000. However, if faster growth in livestock productivity is combined with dedicated technical mitigation measures, emissions may be kept to 7.7 Gton CO2eq/year in 2070. If structural changes in human diets are included, emissions may be reduced further, to 3–5 Gton CO2eq/year in 2070. The total annual emissions for meeting the 2 °C target with a chance above 50 % is in the order of 13 Gton CO2eq/year or less in 2070, for all sectors combined. We conclude that reduced ruminant meat and dairy consumption will be indispensable for reaching the 2 °C target with a high probability, unless unprecedented advances in technology take place.
    • 2014: Caulton, Dana R., et al. “Toward a better understanding and quantification of methane emissions from shale gas development.” Proceedings of the National Academy of Sciences (2014): 201316546. The identification and quantification of methane emissions from natural gas production has become increasingly important owing to the increase in the natural gas component of the energy sector. An instrumented aircraft platform was used to identify large sources of methane and quantify emission rates in southwestern PA in June 2012. A large regional flux, 2.0–14 g CH4 s−1 km−2, was quantified for a ∼2,800-km2 area, which did not differ statistically from a bottom-up inventory, 2.3–4.6 g CH4 s−1 km−2. Large emissions averaging 34 g CH4/s per well were observed from seven well pads determined to be in the drilling phase, 2 to 3 orders of magnitude greater than US Environmental Protection Agency estimates for this operational phase. The emissions from these well pads, representing ∼1% of the total number of wells, account for 4–30% of the observed regional flux. More work is needed to determine all of the sources of methane emissions from natural gas production, to ascertain why these emissions occur and to evaluate their climate and atmospheric chemistry impacts.
    • 2014: Bajželj, Bojana, et al. “Importance of food-demand management for climate mitigation.” Nature Climate Change4.10 (2014): 924. Recent studies show that current trends in yield improvement will not be sufficient to meet projected global food demand in 2050, and suggest that a further expansion of agricultural area will be required. However, agriculture is the main driver of losses of biodiversity and a major contributor to climate change and pollution, and so further expansion is undesirable. The usual proposed alternative—intensification with increased resource use—also has negative effects. It is therefore imperative to find ways to achieve global food security without expanding crop or pastureland and without increasing greenhouse gas emissions. Some authors have emphasized a role for sustainable intensification in closing global ‘yield gaps’ between the currently realized and potentially achievable yields. However, in this paper we use a transparent, data-driven model, to show that even if yield gaps are closed, the projected demand will drive further agricultural expansion. There are, however, options for reduction on the demand side that are rarely considered. In the second part of this paper we quantify the potential for demand-side mitigation options, and show that improved diets and decreases in food waste are essential to deliver emissions reductions, and to provide global food security in 2050. [FULL TEXT PDF]
    • 2014: Westhoek, Henk, et al. “Food choices, health and environment: effects of cutting Europe’s meat and dairy intake.” Global Environmental Change 26 (2014): 196-205. Western diets are characterised by a high intake of meat, dairy products and eggs, causing an intake of saturated fat and red meat in quantities that exceed dietary recommendations. The associated livestock production requires large areas of land and lead to high nitrogen and greenhouse gas emission levels. Although several studies have examined the potential impact of dietary changes on greenhouse gas emissions and land use, those on health, the agricultural system and other environmental aspects (such as nitrogen emissions) have only been studied to a limited extent. By using biophysical models and methods, we examined the large-scale consequences in the European Union of replacing 25–50% of animal-derived foods with plant-based foods on a dietary energy basis, assuming corresponding changes in production. We tested the effects of these alternative diets and found that halving the consumption of meat, dairy products and eggs in the European Union would achieve a 40% reduction in nitrogen emissions, 25–40% reduction in greenhouse gas emissions and 23% per capita less use of cropland for food production. In addition, the dietary changes would also lower health risks. The European Union would become a net exporter of cereals, while the use of soymeal would be reduced by 75%. The nitrogen use efficiency (NUE) of the food system would increase from the current 18% to between 41% and 47%, depending on choices made regarding land use. As agriculture is the major source of nitrogen pollution, this is expected to result in a significant improvement in both air and water quality in the EU. The resulting 40% reduction in the intake of saturated fat would lead to a reduction in cardiovascular mortality. These diet-led changes in food production patterns would have a large economic impact on livestock farmers and associated supply-chain actors, such as the feed industry and meat-processing sector.
    • 2014: Scarborough, Peter, et al. “Dietary greenhouse gas emissions of meat-eaters, fish-eaters, vegetarians and vegans in the UK.” Climatic change 125.2 (2014): 179-192. The production of animal-based foods is associated with higher greenhouse gas (GHG) emissions than plant-based foods. The objective of this study was to estimate the difference in dietary GHG emissions between self-selected meat-eaters, fish-eaters, vegetarians and vegans in the UK. Subjects were participants in the EPIC-Oxford cohort study. The diets of 2,041 vegans, 15,751 vegetarians, 8,123 fish-eaters and 29,589 meat-eaters aged 20–79 were assessed using a validated food frequency questionnaire. Comparable GHG emissions parameters were developed for the underlying food codes using a dataset of GHG emissions for 94 food commodities in the UK, with a weighting for the global warming potential of each component gas. The average GHG emissions associated with a standard 2,000 kcal diet were estimated for all subjects. ANOVA was used to estimate average dietary GHG emissions by diet group adjusted for sex and age. The age-and-sex-adjusted mean (95 % confidence interval) GHG emissions in kilograms of carbon dioxide equivalents per day (kgCO2e/day) were 7.19 (7.16, 7.22) for high meat-eaters ( > = 100 g/d), 5.63 (5.61, 5.65) for medium meat-eaters (50-99 g/d), 4.67 (4.65, 4.70) for low meat-eaters ( < 50 g/d), 3.91 (3.88, 3.94) for fish-eaters, 3.81 (3.79, 3.83) for vegetarians and 2.89 (2.83, 2.94) for vegans. In conclusion, dietary GHG emissions in self-selected meat-eaters are approximately twice as high as those in vegans. It is likely that reductions in meat consumption would lead to reductions in dietary GHG emissions.
    • 2016: Bryngelsson, David, et al. “How can the EU climate targets be met? A combined analysis of technological and demand-side changes in food and agriculture.” Food Policy 59 (2016): 152-164. To meet the 2 °C climate target, deep cuts in greenhouse gas (GHG) emissions will be required for carbon dioxide from fossil fuels but, most likely, also for methane and nitrous oxide from agriculture and other sources. However, relatively little is known about the GHG mitigation potential in agriculture, in particular with respect to the combined effects of technological advancements and dietary changes. Here, we estimate the extent to which changes in technology and demand can reduce Swedish food-related GHG emissions necessary for meeting EU climate targets. This analysis is based on a detailed representation of the food and agriculture system, using 30 different food items. We find that food-related methane and nitrous oxide emissions can be reduced enough to meet the EU 2050 climate targets. Technologically, agriculture can improve in productivity and through implementation of specific mitigation measures. Under optimistic assumptions, these developments could cut current food-related methane and nitrous oxide emissions by nearly 50%. However, also dietary changes will almost certainly be necessary. Large reductions, by 50% or more, in ruminant meat (beef and mutton) consumption are, most likely, unavoidable if the EU targets are to be met. In contrast, continued high per-capita consumption of pork and poultry meat or dairy products might be accommodated within the climate targets. High dairy consumption, however, is only compatible with the targets if there are substantial advances in technology. Reducing food waste plays a minor role for meeting the climate targets, lowering emissions only by an additional 1–3%. [FULL TEXT]
    • 2016: Springmann, Marco, et al. “Analysis and valuation of the health and climate change cobenefits of dietary change.” Proceedings of the National Academy of Sciences 113.15 (2016): 4146-4151. What we eat greatly influences our personal health and the environment we all share. Recent analyses have highlighted the likely dual health and environmental benefits of reducing the fraction of animal-sourced foods in our diets. Here, we couple for the first time, to our knowledge, a region-specific global health model based on dietary and weight-related risk factors with emissions accounting and economic valuation modules to quantify the linked health and environmental consequences of dietary changes. We find that the impacts of dietary changes toward less meat and more plant-based diets vary greatly among regions. The largest absolute environmental and health benefits result from diet shifts in developing countries whereas Western high-income and middle-income countries gain most in per capita terms. Transitioning toward more plant-based diets that are in line with standard dietary guidelines could reduce global mortality by 6–10% and food-related greenhouse gas emissions by 29–70% compared with a reference scenario in 2050. We find that the monetized value of the improvements in health would be comparable with, or exceed, the value of the environmental benefits although the exact valuation method used considerably affects the estimated amounts. Overall, we estimate the economic benefits of improving diets to be 1–31 trillion US dollars, which is equivalent to 0.4–13% of global gross domestic product (GDP) in 2050. However, significant changes in the global food system would be necessary for regional diets to match the dietary patterns studied here.  The food system is responsible for more than a quarter of all greenhouse gas emissions while unhealthy diets and high body weight are among the greatest contributors to premature mortality. Our study provides a comparative analysis of the health and climate change benefits of global dietary changes for all major world regions. We project that health and climate change benefits will both be greater the lower the fraction of animal-sourced foods in our diets. Three quarters of all benefits occur in developing countries although the per capita impacts of dietary change would be greatest in developed countries. The monetized value of health improvements could be comparable with, and possibly larger than, the environmental benefits of the avoided damages from climate change. [FULL TEXT]
    • 2018: Tweet thread by Frederic Leroy @fleroy1974 on Twitter : https://twitter.com/fleroy1974/status/1074111080052482053

     

     

     

    REFERENCES TO METHANE GHG

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    [LIST OF POSTS ON THIS SITE]

     

     

    FIGURE 1A: RCP8.5 WITH TIME SCALE = 10 YEARSrcp10chart

     

    FIGURE 1B: HADCRUT4 WITH TIME SCALE = 10 YEARShad10chart

     

    FIGURE 2A: RCP8.5 WITH TIME SCALE = 15 YEARSrcp15chart

     

    FIGURE 2B: HADCRUT4 WITH TIME SCALE = 15 YEARShad15chart

     

    FIGURE 3A: RCP8.5 WITH TIME SCALE = 20 YEARSrcp20chart

     

    FIGURE 3B: HACRUT4 WITH TIME SCALE = 20 YEARShad20chart

     

    FIGURE 4A: RCP8.5 WITH TIME SCALE = 25 YEARSrcp25chart

     

    FIGURE 4B: HADCRUT4 WITH TIME SCALE = 25 YEARShad25chart

     

    FIGURE 5A: RCP8.5 WITH TIME SCALE = 30 YEARSrcp30chart

     

    FIGURE 5B: HADCRUT4 WITH TIME SCALE = 30 YEARShad30chart

     

    FIGURE 6: CORRELATION, DETRENDED CORRELATION, & SURVIVAL RATECORR-DETCOR-SURVIVAL

     

    FIGURE 7: HYPOTHESIS TEST FOR DETRENDED CORRELATIONTSTAT-PVALUE

     

    FIGURE 8: SUMMARY TABLESUMMARY-TABLE

     

     

     

    [LIST OF POSTS ON THIS SITE]

     

     

    1. The essential feature of climate science, and its activism for climate action in the form of reductions in fossil fuel emissions, is a causal relationship between emissions and the rate of warming with the implication that emission reduction will reduce the rate of warming. This relationship is found in the Transient Climate Response to Cumulative Emissions or TCRE based on a near perfect proportionality between cumulative emissions and surface temperature. Accordingly, the TCRE not only serves as the rationale for climate action but also as the tool for the construction of so called “carbon budgets” that define the maximum amount of emissions for a given target rate of global warming.
    2. However, it has been shown in two related posts  [LINK]  [LINK] that there is a fatal statistical flaw in the TCRE methodology. Correlations between cumulative values of time series data are spurious because the effective sample size of the cumulative value series is EFFN=2 leaving it with neither time scale nor degrees of freedom.  The details of this analysis are presented in related works at SSRN [LINK] [LINK] . This weakness of the TCRE is demonstrated with correlations between random numbers in the two related posts described above [LINK]  [LINK]
    3. This work addresses these shortcomings of the TCRE by defining finite time scales shorter than the full span of the time series so that the effective sample size will be greater than two (EFFN>2) and thus yield positive degrees of freedom so that a hypothesis test can be constructed to determine the statistical significance of the correlation. The effective sample size procedure is described in a related SSRN paper [LINK] . Data for fossil fuel emissions in millions of tons of carbon equivalent are provided by the Carbon Dioxide Information Analysis Center of the Oak Ridge National Laboratories (CDIAC, 2017). Two surface temperature datasets for the study peruid 1861 to 2016 are used for the analysis. They are the RCP8.5 theoretical temperature forecasts from climate models with CMIP5 forcings (hereafter referred to as RCP), and the HadCRUT4 global mean temperature reconstruction (hereafter referred to as HAD) provided by the Hadley Centre of the Climate Research Unit of the UK Met Office. The comparison between these temperature datasets are made in the context that the RCP8.5 represents the theory of Anthropogenic Global Warming by way of fossil fuel emissions (AGW) because it was created by climate models that contain the causal relationship between the rate of emissions and the rate of warming. The HadCRUT4 reconstruction represents observational data although they are not direct observations but reconstructions from observations.
    4. To insert a time scale and finite degrees of freedom into the TCRE model, we use five different time scales for this analysis from 10 years to 30 years at 5 year increments. For each time scale we compute the cumulative emissions in the duration of the time scale and the rate of warming within the time scale. The time scale window then moves across the full span of the data one year at a time. For example, in the 10-year time scale, cumulative emissions is computed as the total emissions in a moving 10-year window that moves one year at a time through the full span of the data. Likewise, the rate of warming is computed within a moving 10-year window that moves through the full span of the data one year at a time. We then compute the detrended correlation between warming and emissions net of the contribution to source data correlation by shared long term trends. The rationale for detrended analysis is described in a related post [LINK]
    5. Figure 1A to Figure 5B above show the data for both RCP and HAD against the cumulative emissions in moving windows of 10, 15, 20, 25, and 30 years along with a graphical display of the correlations and detrended correlations. The results are summarized in Figure 6 and Figure 7. Both temperature datasets show that source data correlation (CORR) rises as the time scale is increased from 10-years to 30-years but more rapidly at the lower time scales than at higher time scales. The theoretical model predictions (RCP) show much stronger source data correlations (CORR=0.5 to 0.8) than the observational data (HAD) with source data correlations of (CORR=0.27 to 0.65). When the spurious effect of long term trends is removed from the source data correlation, lower correlations are seen in the detrended data (DETCOR) with values of (DETCOR=0.3 to 0.56) in the RCP climate model prediction and much lower values of (DETCOR=0.1 to 0.2) in the HAD observational data. We also note that a much larger portion of the model prediction RCP source correlation CORR survives into the detrended series DETCOR (56% to 68%) than in the observational data HAD (29% to 35%) indicating a much stronger relationship between emissions and warming in climate models than in observational data. It is also noted that the behavior of the detrended correlation curve and the percent survival curve are different in the HAD data series than in the RCP climate model series.
    6. The rising value of correlations with increasing values of the time scale from 10-years to 30-years comes at a price because higher time scales reduce the effective value of the sample size (EFFN) and therefore of the degrees of freedom (DF). (see reference paper at SSRN [LINK] . In Figure 8 we see that as the time scale is increased from 10-years to 30-years, the effective sample size drops from 16.6 to 6.4 and takes down the degrees of freedom with it computed as DF=EFFN-2. There is a price to be paid for the higher correlations in longer time scales. The standard deviation of the correlation coefficient is estimated using Bowley’s procedure (Bowley, 1928). To test for positive values of the correlation coefficient, the null hypothesis is set to H0: ρ≤0 with the alternate HA: ρ>0. Hypothesis tests for correlation are carried out at a maximum false positive error rate of α=0.001 per comparison in keeping with “Revised Standards for Statistical Evidence” published by the NAS (Johnson, 2013) as a way of addressing an unacceptably high rate of irreproducible results in published research (Siegfried, 2010).
    7. In these tests we find that the four time scales greater than ten years (15, 20, 25, and 30 years) show statistically significant detrended correlations for the climate model series RCP8.5. No statistically significant detrended correlation is found in the observational data HadCRUT4. These results show that though the causal relationship between emissions and warming, assumed in the motivation for costly climate action, is found in the RCP8.5 generated by climate models, it is not found in the data. This result is consistent with the finding in the TCRE post [LINK]  that the correlation seen between temperature and cumulative emissions is spurious and that in fact there is no evidence that the correlation between emissions and warming found in climate models exists in the data.
    8. The Transient Climate Response to Cumulative Emissions (TCRE) does show that the rate of warming is responsive to emissions in the observational data but that metric contains a fatal statistical flaw. It is based on a spurious correlation and contains neither time scale nor degrees of freedom as shown in a related post at this site [LINK] .
    9. We conclude from these results that no empirical evidence exists to support the rationale for costly climate action that assumes a causal relationship between the rate of emissions and the rate of warming. The evidence does not show that reducing emissions will lower the rate of warming.   

     

     

     

    CITATIONS

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    CLIMATE ACTION PARIS AGREEMENT BIBLIOGRAPHY

    1. 2016: 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.
    2. 2016: Hale, Thomas. ““All hands on deck”: The Paris agreement and nonstate climate action.” Global Environmental Politics 16.3 (2016): 12-22. The 2015 Paris Climate summit consolidated the transition of the climate regime from a “regulatory” to a “catalytic and facilitative” model. A key component of this shift was the intergovernmental regime’s embrace of climate action by sub- and nonstate actors. Although a groundswell of transnational climate action has been growing over time, the Paris Agreement seeks to bring this phenomenon into the heart of the new climate regime. This forum article describes that transition and considers its implications.
    3. 2016: Falkner, Robert. “The Paris Agreement and the new logic of international climate politics.” International Affairs 92.5 (2016): 1107-1125. This article reviews and assesses the outcome of the 21st Conference of the Parties (COP-21) to the United Nations Framework Convention on Climate Change (UNFCCC), held in Paris in December 2015. It argues that the Paris Agreement breaks new ground in international climate policy, by acknowledging the primacy of domestic politics in climate change and allowing countries to set their own level of ambition for climate change mitigation. It creates a framework for making voluntary pledges that can be compared and reviewed internationally, in the hope that global ambition can be increased through a process of ‘naming and shaming’. By sidestepping distributional conflicts, the Paris Agreement manages to remove one of the biggest barriers to international climate cooperation. It recognizes that none of the major powers can be forced into drastic emissions cuts. However, instead of leaving mitigation efforts to an entirely bottom-up logic, it embeds country pledges in an international system of climate accountability and a ‘ratchet mechanism’, thus offering the chance of more durable international cooperation. At the same time, it is far from clear whether the treaty can actually deliver on the urgent need to de-carbonize the global economy. The past record of climate policies suggests that governments have a tendency to express lofty aspirations but avoid tough decisions. For the Paris Agreement to make a difference, the new logic of ‘pledge and review’ will need to mobilize international and domestic pressure and generate political momentum behind more substantial climate policies worldwide. It matters, therefore, whether the Paris Agreement’s new approach can be made to work.
    4. 2016: Bodansky, Daniel. “The Paris climate change agreement: a new hope?.” American Journal of International Law 110.2 (2016): 288-319.  Know your limits. This familiar adage is not an inspirational rallying cry or a recipe for bold action. It serves better as the motto for the tortoise than the hare. But, after many false starts over the past twenty years, states were well advised to heed it when negotiating the Paris Agreement. While it is still far too early to say whether the Agreement will be a success, its comparatively modest approach provides a firmer foundation on which to build than its more ambitious predecessor, the Kyoto Protocol.
    5. 2016: Schleussner, Carl-Friedrich, et al. “Science and policy characteristics of the Paris Agreement temperature goal.” Nature Climate Change 6.9 (2016): 827.  The Paris Agreement sets a long-term temperature goal of holding the global average temperature increase to well below 2 °C, and pursuing efforts to limit this to 1.5 °C above pre-industrial levels. Here, we present an overview of science and policy aspects related to this goal and analyse the implications for mitigation pathways. We show examples of discernible differences in impacts between 1.5 °C and 2 °C warming. At the same time, most available low emission scenarios at least temporarily exceed the 1.5 °C limit before 2100. The legacy of temperature overshoots and the feasibility of limiting warming to 1.5 °C, or below, thus become central elements of a post-Paris science agenda. The near-term mitigation targets set by countries for the 2020–2030 period are insufficient to secure the achievement of the temperature goal. An increase in mitigation ambition for this period will determine the Agreement’s effectiveness in achieving its temperature goal.
    6. 2016: Dimitrov, Radoslav S. “The Paris agreement on climate change: Behind closed doors.” Global Environmental Politics16.3 (2016): 1-11. The Paris Agreement constitutes a political success in climate negotiations and traditional state diplomacy, and offers important implications for academic research. Based on participatory research, the article examines the political dynamics in Paris and highlights feature2016s of the process that help us understand the outcome. It describes battles on key contentious issues behind closed doors, provides a summary and evaluation of the new agreement, identifies political winners and losers, and offers theoretical explanations of the outcome. The analysis emphasizes process variables and underscores the role of persuasion, argumentation, and organizational strategy. Climate diplomacy succeeded because the international conversation during negotiations induced cognitive change. Persuasive arguments about the economic benefits of climate action altered preferences in favor of policy commitments at both national and international levels.
    7. 2016: Van Asselt, Harro. “The role of non-state actors in reviewing ambition, implementation, and compliance under the Paris agreement.” Climate Law 6.1-2 (2016): 91-108. Non-state actors will play a unique and crucial role in the implementation of the Paris Agreement. Although much of the focus in the lead-up to Paris was on the mitigation commitments and actions of non-state actors, this essay focuses on another valuable contribution they can make: to hold the parties to their obligations under the Paris Agreement. I argue that, while the formal avenues for non-state-actor participation in review processes—encompassing the review of implementation, compliance, and effectiveness—remain limited, there are several other ways in which non-state actors can be, and already have been, influential
    8. 2017: Höhne, Niklas, et al. “The Paris Agreement: resolving the inconsistency between global goals and national contributions.” Climate Policy 17.1 (2017): 16-32. he adoption of the Paris Agreement in December 2015 moved the world a step closer to avoiding dangerous climate change. The aggregated individual intended nationally determined contributions (INDCs) are not yet sufficient to be consistent with the long-term goals of the agreement of ‘holding the increase in global average temperature to well below 2°C’ and ‘pursuing efforts’ towards 1.5°C. However, the Paris Agreement gives hope that this inconsistency can be resolved. We find that many of the contributions are conservative and in some cases may be overachieved. We also find that the preparation of the INDCs has advanced national climate policy-making, notably in developing countries. Moreover, provisions in the Paris Agreement require countries to regularly review, update and strengthen these actions. In addition, the significant number of non-state actions launched in recent years is not yet adequately captured in the INDCs. Finally, we discuss decarbonization, which has happened faster in some sectors than expected, giving hope that such a transition can also be accomplished in other sectors. Taken together, there is reason to be optimistic that eventually national action to reduce emissions will be more consistent with the agreed global temperature limits.
    9. 2017: Rogelj, Joeri, et al. “Understanding the origin of Paris Agreement emission uncertainties.” Nature Communications 8 (2017): 15748. The UN Paris Agreement puts in place a legally binding mechanism to increase mitigation action over time. Countries put forward pledges called nationally determined contributions (NDC) whose impact is assessed in global stocktaking exercises. Subsequently, actions can then be strengthened in light of the Paris climate objective: limiting global mean temperature increase to well below 2 °C and pursuing efforts to limit it further to 1.5 °C. However, pledged actions are currently described ambiguously and this complicates the global stocktaking exercise. Here, we systematically explore possible interpretations of NDC assumptions, and show that this results in estimated emissions for 2030 ranging from 47 to 63 GtCO2e yr−1. We show that this uncertainty has critical implications for the feasibility and cost to limit warming well below 2 °C and further to 1.5 °C. Countries are currently working towards clarifying the modalities of future NDCs. We identify salient avenues to reduce the overall uncertainty by about 10 percentage points through simple, technical clarifications regarding energy accounting rules. Remaining uncertainties depend to a large extent on politically valid choices about how NDCs are expressed, and therefore raise the importance of a thorough and robust process that keeps track of where emissions are heading over time.

     

     

     

     

    [LIST OF POSTS ON THIS SITE]

     

     

    1. Millions of years ago (MYA), in the Triassic and Jurassic geological periods, reptiles and dinosaurs ruled the world. The Triassic Period started with the mass extinction that ended the Permian Period 250 MYA and ended with the mass extinction 200 MYA that marks the boundary between the Triassic and Jurassic periods. The mass extinction that ended the Triassic and that marks the beginning of the Jurassic is called the “End Triassic Extinction” or ETE for short. It is one of the most extreme and horrific mass extinctions in the paleo record.
    2. This post is a literature review of paleoclimate evidence and expert interpretations of the data to surmise what happened in that horrific mass extinction that changed the Triassic age of reptiles and small dinosaurs into the Jurassic, the age of the dominance of giant dinosaurs.
    3. The paleo data show that about 200MYA the geochemical evidence indicate a sequential eruption of the Central Atlantic Magmatic Province (CAMP) with a contemporaneous disappearance of a large number of land and oceanic life forms.
    4. This summary of the End Triassic Extinction event is provided by Hames (2003):  “A singular event in Earth’s history occurred roughly 200 million years ago, as rifting of the largest and most recent supercontinent was joined by basaltic volcanism that formed the most extensive large igneous province (LIP) known. A profound and widespread mass extinction of terrestrial and marine genera occurred at about the same time, suggesting a causal link between the biological transitions of the Triassic-Jurassic boundary and massive volcanism. A series of stratigraphic, geochronologic, petrologic, tectonic, and geophysical studies have led to the identification of the dispersed remnants of this Central Atlantic Magmatic Province (CAMP) on the rifted margins of four continents. Current discoveries are generally interpreted to indicate that CAMP magmatism occurred in a relative and absolute interval of geologic time that was brief, and point to mechanisms of origin and global environmental effects. Because many of these discoveries have occurred within the past several years, in this monograph we summarize new observations and provide an up-to-date review of the province.
    5. A bibliography of research in this field is presented below.

     

     

    BIBLIOGRAPHY

    JESSICA WHITESIDE, JEAN GUEX, ANDREA MARZOLI, BLAIR SCHOENE

     

    1. 1992: Hodych, J. P., and G. R. Dunning. “Did the Manicouagan impact trigger end-of-Triassic mass extinction?.” Geology 20.1 (1992): 51-54.  We use U-Pb zircon dating to test whether the bolide impact that created the Manicouagan crater of Quebec also triggered mass extinction at the Triassic/Jurassic boundary. The age of the impact is provided by zircons from the impact melt rock on the crater floor; we show that the zircons yield a U-Pb age of 214 ±1 Ma. The age of the Triassic/Jurassic boundary is provided by zircons from the North Mountain Basalt of the Newark Supergroup of Nova Scotia; the zircons yield a U-Pb age of 202 ±1 Ma. This should be the age of the end-of-Triassic mass extinction that paleontology and sedimentation rates suggest occurred less than 1 m.y. before extrusion of the North Mountain Basalt. Although the Manicouagan impact could thus not have triggered the mass extinction at the Triassic/Jurassic boundary (impact likely having preceded extinction by 12 ±2 m.y.), the impact may possibly have triggered an earlier mass extinction at the Carnian/Norian boundary in the Late Triassic.  [FULL TEXT]
    2. 1999: Marzoli, Andrea, et al. “Extensive 200-million-year-old continental flood basalts of the Central Atlantic Magmatic Province.” Science 284.5414 (1999): 616-618. The Central Atlantic Magmatic Province (CAMP) is defined by tholeiitic basalts that crop out in once-contiguous parts of North America, Europe, Africa, and South America and is associated with the breakup of Pangea. 40Ar/39Ar and paleomagnetic data indicate that CAMP magmatism extended over an area of 2.5 million square kilometers in north and central Brazil, and the total aerial extent of the magmatism exceeded 7 million square kilometers in a few million years, with peak activity at 200 million years ago. The magmatism coincided closely in time with a major mass extinction at the Triassic-Jurassic boundary[FULL TEXT]
    3. 2000: Pálfy, József, et al. “Timing the end-Triassic mass extinction: First on land, then in the sea?.” Geology 28.1 (2000): 39-42. The end-Triassic marks one of the five biggest mass extinctions, but current geologic time scales are inadequate for understanding its dynamics. A tuff layer in marine sedimentary rocks encompassing the Triassic-Jurassic transition yielded a U-Pb zircon age of 199.6 ± 0.3 Ma. The dated level is immediately below a prominent change in radiolarian faunas and the last occurrence of conodonts. Additional recently obtained U-Pb ages integrated with ammonoid biochronology confirm that the Triassic Period ended ca. 200 Ma, several million years later than suggested by previous time scales. Published dating of continental sections suggests that the extinction peak of terrestrial plants and vertebrates occurred before 200.6 Ma. The end-Triassic biotic crisis on land therefore appears to have preceded that in the sea by at least several hundred thousand years[FULL TEXT]
    4. 2002: Hesselbo, Stephen P., et al. “Terrestrial and marine extinction at the Triassic-Jurassic boundary synchronized with major carbon-cycle perturbation: A link to initiation of massive volcanism?.” Geology 30.3 (2002): 251-254. Mass extinction at the Triassic-Jurassic (Tr-J) boundary occurred about the same time (200 Ma) as one of the largest volcanic eruptive events known, that which characterized the Central Atlantic magmatic province. Organic carbon isotope data from the UK and Greenland demonstrate that changes in flora and fauna from terrestrial and marine environments occurred synchronously with a light carbon isotope excursion, and that this happened earlier than the Tr-J boundary marked by ammonites in the UK. The results also point toward synchronicity between extinctions and eruption of the first Central Atlantic magmatic province lavas, suggesting a causal link between loss of taxa and the very earliest eruptive phases. The initial isotopic excursion potentially provides a widely correlatable marker for the base of the Jurassic. A temporary return to heavier values followed, but relatively light carbon dominated the shallow oceanic and atmospheric reservoirs for at least 600 k.y.
    5. 2002: Hallam, Anthony. “How catastrophic was the end‐Triassic mass extinction?.” Lethaia 35.2 (2002): 147-157. A review of marine and terrestrial animal and plant fossils fails to reveal convincing evidence of a global catastrophe at the Triassic‐Jurassic boundary, although this time marked the final disappearance of ceratite ammonites and conodonts, together with the extinction of most calcareous demosponges; important groups of bivalves and brachiopods went extinct. Because of facies problems, however, there is no stratigraphic section that reveals a clear‐cut disappearance over a short distance. Other marine animal groups except perhaps the radiolarians fail to reveal a notable extinction of global extent immediately across the boundary. On the other hand, there was a substantially higher extinction rate among marine animals in the Rhaetian as compared with the previous stage. On the land, the record is equivocal. Dramatic changes across the T‐J boundary have been claimed for plants in particular areas, such as eastern North America and East Greenland, but only gradual change has been recognized elsewhere. Similarly, claims of a T‐J boundary vertebrate mass extinction have not been supported by others. For the Rhaetian as a whole, however, the turnover rate of reptiles was high. Although much remains to be learned, it seems evident that the fossil record of the latest Triassic is more consistent with a gradual scenario extended over time than a ‘geologically instantaneous’ impact catastrophe.
    6. Hames, Willis, et al. “The Central Atlantic magmatic province: Insights from fragments of Pangea.” Washington DC American Geophysical Union Geophysical Monograph Series 136 (2003).  A singular event in Earth’s history occurred roughly 200 million years ago, as rifting of the largest and most recent supercontinent was joined by basaltic volcanism that formed the most extensive large igneous province (LIP) known. A profound and widespread mass extinction of terrestrial and marine genera occurred at about the same time, suggesting a causal link between the biological transitions of the Triassic-Jurassic boundary and massive volcanism. A series of stratigraphic, geochronologic, petrologic, tectonic, and geophysical studies have led to the identification of the dispersed remnants of this Central Atlantic Magmatic Province (CAMP) on the rifted margins of four continents. Current discoveries are generally interpreted to indicate that CAMP magmatism occurred in a relative and absolute interval of geologic time that was brief, and point to mechanisms of origin and global environmental effects. Because many of these discoveries have occurred within the past several years, in this monograph we summarize new observations and provide an up-to-date review of the province
    7. 2004: Guex, Jean, et al. “High-resolution ammonite and carbon isotope stratigraphy across the Triassic–Jurassic boundary at New York Canyon (Nevada).” Earth and Planetary Science Letters 225.1-2 (2004): 29-41.The Triassic–Jurassic boundary is generally considered as one of the major extinctions in the history of Phanerozoic. The high-resolution ammonite correlations and carbon isotope marine record in the New York Canyon area allow to distinguish two negative carbon excursions across this boundary with different paleoenvironmental meanings. The Late Rhaetian negative excursion is related to the extinction and regressive phase. The Early Hettangian  δ13Corg negative excursion is associated with a major floristic turnover and major ammonite and radiolarian radiation. The end-Triassic extinction–Early Jurassic recovery is fully compatible with a volcanism-triggered crisis, probably related to the Central Atlantic Magmatic Province. The main environmental stress might have been generated by repeated release of SO2 gas, heavy metals emissions, darkening, and subsequent cooling. This phase was followed by a major long-term CO2accumulation during the Early Hettangian with development of nutrient-rich marine waters favouring the recovery of productivity and deposition of black shales
    8. 2004: Marzoli, Andrea, et al. “Synchrony of the Central Atlantic magmatic province and the Triassic-Jurassic boundary climatic and biotic crisis.” Geology 32.11 (2004): 973-976. The evolution of life on Earth is marked by catastrophic extinction events, one of which occurred ca. 200 Ma at the transition from the Triassic Period to the Jurassic Period (Tr-J boundary), apparently contemporaneous with the eruption of the world’s largest known continental igneous province, the Central Atlantic magmatic province. The temporal relationship of the Tr-J boundary and the province’s volcanism is clarified by new multidisciplinary (stratigraphic, palynologic, geochronologic, paleomagnetic, geochemical) data that demonstrate that development of the Central Atlantic magmatic province straddled the Tr-J boundary and thus may have had a causal relationship with the climatic crisis and biotic turnover demarcating the boundary.
    9. 2004: Hautmann, Michael. “Effect of end-Triassic CO 2 maximum on carbonate sedimentation and marine mass extinction.” Facies50.2 (2004): 257-261. Correlation of stratigraphic sections from different continents suggests a worldwide interruption of carbonate sedimentation at the Triassic–Jurassic boundary, which coincided with one of the most catastrophic mass extinctions in the Phanerozoic. Both events are linked by a vulcanogenic maximum of carbon dioxide, which led to a temporary undersaturation of sea water with respect to aragonite and calcite and a corresponding suppression of carbonate sedimentation including non-preservation of calcareous skeletons. Besides the frequently cited climatic effect of enhanced carbon dioxide, lowering the saturation state of sea water with respect to calcium carbonate was an additional driving force of the end-Triassic mass extinction, which chiefly affected organisms with thick aragonitic or high-magnesium calcitic skeletons. Replacement of aragonite by calcite, as found in the shells of epifaunal bivalves, was an evolutionary response to this condition.
    10. 2004: Knight, K. B., et al. “The Central Atlantic Magmatic Province at the Triassic–Jurassic boundary: paleomagnetic and 40 Ar/39 Ar evidence from Morocco for brief, episodic volcanism.” Earth and Planetary Science Letters 228.1 (2004): 143-160. The Central Atlantic Magmatic Province (CAMP), one of the largest known flood basalt provinces formed in the Phanerozoic, is associated with the pre-rift stage of the Atlantic Ocean at the Triassic–Jurassic boundary ca. 200 Ma. Paleomagnetic sampling targeted packages of CAMP lava flows in Morocco’s High Atlas divided into four basic units (the lower, intermediate, upper, and recurrent units) from sections identified on the basis of field observations and geochemistry. Oriented cores were demagnetized using both alternating field (AF) and thermal techniques. Paleomagnetic results reveal wholly normal polarity interrupted by at least one brief reversed chron located in the intermediate unit, and reveal distinct pulses of volcanic activity identified by discrete changes in declination and inclination. These variations in magnetic direction are interpreted as a record of secular variation, and they may provide an additional correlative tool for identification of spatially separated CAMP lava flows within Morocco. 40Ar/39Ar analyses of Moroccan CAMP lavas yield plateau ages indistinguishable within 2σ error limits, sharing a weighted mean age of 199.9±0.5 Ma (2σ), reinforcing the short-lived nature of these eruptions despite the presence of sedimentary horizons between them. Correlation of our sections with the E23n, E23r, E24 sequence reported in the Newark basin terrestrial section and St. Audrie’s Bay marine section is suggested. Brief volcanism in sudden pulses is a potential mechanism for volcanic-induced climatic changes and biotic disruption at the Triassic–Jurassic boundary. Combination of our directional group (DG) poles yields an African paleomagnetic pole at 200 Ma of λ(°N)=73.0°, ϕ(°E)=241.3° (Dp=5.0°, Dm=18.5°).
    11. 2007: Nomade, S., et al. “Chronology of the Central Atlantic Magmatic Province: implications for the Central Atlantic rifting processes and the Triassic–Jurassic biotic crisis.” Palaeogeography, Palaeoclimatology, Palaeoecology 244.1-4 (2007): 326-344. The Central Atlantic Magmatic Province (CAMP) is among the largest igneous provinces on Earth, emplaced synchronously with or just prior to the Triassic–Jurassic (T–J) boundary ca. 200 Ma. In great part due to the controversial connection between the occurrence of CAMP and the events of the T–J boundary, the demand for better constraints on the duration and eruptive chronology of this province has increased. More than 100 new 40Ar/39Ar ages have been published in the last 15 years, with more than half of these in the last 3 years. A careful review and selection of available ages, as well as the publication of 16 new ages from the Carolinas, Newark Basin (USA), French Guyana and Morocco are presented. Judicious selection yields a total of 58 accepted age determinations for CAMP magmatism, ranging from 202 to 190 Ma covering every part of the CAMP. A more complete picture develops with intrusive CAMP magmatism commencing as early as 202 Ma. Extrusive activity initiated abruptly ∼ 200 Ma, reaching peak volume and intensity around 199 Ma on the African margin. The main period of CAMP magmatism is confirmed as brief, but is suggested to consist of at least two phases over ∼ 1.5 Ma, with magmatism commencing along the Africa–North American margins and slightly later along the South American margin. Two volumetrically minor, but distinctive magmatic peaks centered at 195 and 192 Ma are mirrored in data from all three continents and highlighted by our statistical approach. Models describing rifting and thermal input and magma production on these timescales are explored. Despite significant advances in our understanding of the chronology of CAMP, more data of better quality and broader geographical coverage are needed to completely characterize the evolution of the CAMP and infer its geodynamic origin. In addition, lack of a well-defined T–J boundary age, as well as the absence of a relevant basis for comparison between U/Pb and 40Ar/39Ar data for this time period remain limiting factors to unambiguously linking CAMP in time with the events of the T–J boundary.
    12. 2008: Schaltegger, Urs, et al. “Precise U–Pb age constraints for end-Triassic mass extinction, its correlation to volcanism and Hettangian post-extinction recovery.” Earth and Planetary Science Letters 267.1-2 (2008): 266-275. New precise zircon U–Pb ages are proposed for the Triassic–Jurassic (Rhetian–Hettangian) and the Hettangian–Sinemurian boundaries. The ages were obtained by ID-TIMS dating of single chemical-abraded zircons from volcanic ash layers within the Pucara Group, Aramachay Formation in the Utcubamba valley, northern Peru. Ash layers situated between last and first occurrences of boundary-defining ammonites yielded 206Pb/238U ages of 201.58 ± 0.17/0.28 Ma (95% c.l., uncertainties without/with decay constant errors, respectively) for the Triassic–Jurassic and of 199.53 ± 0.19 / 0.29 Ma for the Hettangian–Sinemurian boundaries. The former is established on a tuff located 1 m above the last local occurrence of the topmost Triassic genus Choristoceras, and 5 m below the Hettangian genus Psiloceras. The latter sample was obtained from a tuff collected within the Badouxia canadensis beds. Our new ages document total duration of the Hettagian of no more than c. 2 m.y., which has fundamental implications for the interpretation and significance of the ammonite recovery after the topmost Triassic extinction.The U–Pb age is about 0.8 ± 0.5% older than 40Ar–39Ar dates determined on flood basalts of the Central Atlantic Magmatic Province (CAMP). Given the widely accepted hypothesis that inaccuracies in the 40K decay constants or physical constants create a similar bias between the two dating methods, our new U–Pb zircon age determination for the T/J boundary corroborates the hypothesis that the CAMP was emplaced at the same time and may be responsible for a major climatic turnover and mass extinction. The zircon 206Pb/238U age for the T/J boundary is marginally older than the North Mountain Basalt (Newark Supergroup, Nova Scotia, Canada), which has been dated at 201.27 ± 0.06 Ma [Schoene et al., 2006. Geochim. Cosmochim. Acta 70, 426–445]. It will be important to look for older eruptions of the CAMP and date them precisely by U–Pb techniques while addressing all sources of systematic uncertainty to further test the hypothesis of volcanic induced climate change leading to extinction. Such high-precision, high-accuracy data will be instrumental for constraining the contemporaneity of geological events at a 100 kyr level.
    13. 2009: Cirilli, S., et al. “Latest Triassic onset of the Central Atlantic magmatic province (CAMP) volcanism in the Fundy basin (Nova Scotia): new stratigraphic constraints.” Earth and Planetary Science Letters 286.3-4 (2009): 514-525. In this paper we investigate the stratigraphic relationship between the emplacement of the CAMP basalts and the Triassic–Jurassic (Tr–J) boundary in the Fundy Basin (Nova Scotia, Canada). This is one of the best exposed of the synrift basins of eastern North America (ENA) formed as a consequence of the rifting that led to the formation of the Atlantic Ocean. The Triassic palynological assemblages found in the sedimentary rocks below (uppermost Blomidon Formation) and just above the North Mountain Basalt (Scots Bay Member of the McCoy Brook Formation) indicate that CAMP volcanism, at least in Nova Scotia, is entirely of Triassic age, occurred in a very short time span, and may have triggered the T–J boundary biotic and environmental crisis. The palynological assemblage from the Blomidon Formation is characterised by the dominance of the Circumpolles group (e.g. Gliscopollis meyeriana, Corollina murphyae, Classopollis torosus) which crosses the previously established Tr–J boundary. The Triassic species Patinasporites densus disappears several centimetres below the base of the North Mountain basalt, near the previously interpreted Tr–J boundary. The lower strata of the Scots Bay Member yielded a palynological assemblage dominated by Triassic bisaccate pollens (e.g Lunatisporites acutus, L. rhaeticus Lueckisporites sp., Alisporites parvus) with minor specimens of the Circumpolles group. Examination of the state of preservation and thermal alteration of organic matter associated with the microfloral assemblages precludes the possibility of recycling of the Triassic sporomorphs from the older strata. Our data argue against the previous definition of the Tr–J boundary in the ENA basins, which was based mainly on the last occurrence of P. densus. Consequently, it follows that the late Triassic magnetostratigraphic correlations should be revised considering that chron E23r, which is correlated with the last occurrence of P. densus in the Newark basin, does not occur at the Tr–J boundary but marks rather a late Triassic (probably Rhaetian) reversal.
    14. 2010: Schoene, Blair, et al. “Correlating the end-Triassic mass extinction and flood basalt volcanism at the 100 ka level.” Geology 38.5 (2010): 387-390.  New high-precision U/Pb geochronology from volcanic ashes shows that the Triassic-Jurassic boundary and end-Triassic biological crisis from two independent marine stratigraphic sections correlate with the onset of terrestrial flood volcanism in the Central Atlantic Magmatic Province to <150 ka. This narrows the correlation between volcanism and mass extinction by an order of magnitude for any such catastrophe in Earth history. We also show that a concomitant drop and rise in sea level and negative δ13C spike in the very latest Triassic occurred locally in <290 ka. Such rapid sea-level fluctuations on a global scale require that global cooling and glaciation were closely associated with the end-Triassic extinction and potentially driven by Central Atlantic Magmatic Province volcanism.  [FULL TEXT]
    15. 2010: Whiteside, Jessica H., et al. “Compound-specific carbon isotopes from Earth’s largest flood basalt eruptions directly linked to the end-Triassic mass extinction.” Proceedings of the National Academy of Sciences 107.15 (2010): 6721-6725. A leading hypothesis explaining Phanerozoic mass extinctions and associated carbon isotopic anomalies is the emission of greenhouse, other gases, and aerosols caused by eruptions of continental flood basalt provinces. However, the necessary serial relationship between these eruptions, isotopic excursions, and extinctions has never been tested in geological sections preserving all three records. The end-Triassic extinction (ETE) at 201.4 Ma is among the largest of these extinctions and is tied to a large negative carbon isotope excursion, reflecting perturbations of the carbon cycle including a transient increase in CO2. The cause of the ETE has been inferred to be the eruption of the giant Central Atlantic magmatic province (CAMP). Here, we show that carbon isotopes of leaf wax derived lipids (n-alkanes), wood, and total organic carbon from two orbitally paced lacustrine sections interbedded with the CAMP in eastern North America show similar excursions to those seen in the mostly marine St. Audrie’s Bay section in England. Based on these results, the ETE began synchronously in marine and terrestrial environments slightly before the oldest basalts in eastern North America but simultaneous with the eruption of the oldest flows in Morocco, a CO2 super greenhouse, and marine biocalcification crisis. Because the temporal relationship between CAMP eruptions, mass extinction, and the carbon isotopic excursions are shown in the same place, this is the strongest case for a volcanic cause of a mass extinction to date.
    16. 2010: Deenen, Martijn HL, et al. “A new chronology for the end-Triassic mass extinction.” Earth and Planetary Science Letters291.1-4 (2010): 113-125. The transition from the Triassic to Jurassic Period, initiating the ‘Age of the dinosaurs’, approximately 200 Ma, is marked by a profound mass extinction with more than 50% genus loss in both marine and continental realms. This event closely coincides with a period of extensive volcanism in the Central Atlantic Magmatic Province (CAMP) associated with the initial break-up of Pangaea but a causal relationship is still debated. The Triassic–Jurassic (T–J) boundary is recently proposed in the marine record at the first occurrence datum of Jurassic ammonites, post-dating the extinction interval that concurs with two distinct perturbations in the carbon isotope record. The continental record shows a major palynological turnover together with a prominent change in tetrapod taxa, but a direct link to the marine events is still equivocal. Here we develop an accurate chronostratigraphic framework for the T–J boundary interval and establish detailed trans-Atlantic and marine–continental correlations by integrating astrochronology, paleomagnetism, basalt geochemistry and geobiology. We show that the oldest CAMP basalts are diachronous by 20 kyr across the Atlantic Ocean, and that these two volcanic pulses coincide with the end-Triassic extinction interval in the marine realm. Our results support the hypotheses of Phanerozoic mass extinctions resulting from emplacement of Large Igneous Provinces (LIPs) and provide crucial time constraints for numerical modelling of Triassic–Jurassic climate change and global carbon-cycle perturbations.  [FULL TEXT]
    17. 2011: Schaller, Morgan F., James D. Wright, and Dennis V. Kent. “Atmospheric pCO2 perturbations associated with the Central Atlantic magmatic province.” Science 331.6023 (2011): 1404-1409. The effects of a large igneous province on the concentration of atmospheric carbon dioxide (PCO2) are mostly unknown. In this study, we estimate PCO2 from stable isotopic values of pedogenic carbonates interbedded with volcanics of the Central Atlantic Magmatic Province (CAMP) in the Newark Basin, eastern North America. We find pre-CAMP PCO2 values of ~2000 parts per million (ppm), increasing to ~4400 ppm immediately after the first volcanic unit, followed by a steady decrease toward pre-eruptive levels over the subsequent 300 thousand years, a pattern that is repeated after the second and third flow units. We interpret each PCO2 increase as a direct response to magmatic activity (primary outgassing or contact metamorphism). The systematic decreases in PCO2 after each magmatic episode probably reflect consumption of atmospheric CO2 by weathering of silicates, stimulated by fresh CAMP volcanics.
    18. 2011: Ruhl, Micha, et al. “Atmospheric carbon injection linked to end-Triassic mass extinction.” Science 333.6041 (2011): 430-434. The end-Triassic mass extinction (~201.4 million years ago), marked by terrestrial ecosystem turnover and up to ~50% loss in marine biodiversity, has been attributed to intensified volcanic activity during the break-up of Pangaea. Here, we present compound-specific carbon-isotope data of long-chain n-alkanes derived from waxes of land plants, showing a ~8.5 per mil negative excursion, coincident with the extinction interval. These data indicate strong carbon-13 depletion of the end-Triassic atmosphere, within only 10,000 to 20,000 years. The magnitude and rate of this carbon-cycle disruption can be explained by the injection of at least ~12 × 103 gigatons of isotopically depleted carbon as methane into the atmosphere. Concurrent vegetation changes reflect strong warming and an enhanced hydrological cycle. Hence, end-Triassic events are robustly linked to methane-derived massive carbon release and associated climate change[FULL TEXT]
    19. 2013: Blackburn, Terrence J., et al. “Zircon U-Pb geochronology links the end-Triassic extinction with the Central Atlantic Magmatic Province.” Science 340.6135 (2013): 941-945. Correlating a specific triggering event, such as an asteroid impact or massive volcanism, to mass extinction events is clouded by the difficulty in precisely timing their occurrence in the geologic record. Based on rock samples collected in North America and Morocco, Blackburn et al. (p. 941, published online 21 March) acquired accurate ages for events surrounding the mass extinction that occurred ∼201 million years ago, between the Triassic and Jurassic Periods. The timing of the disappearance of marine and land fossils and geochemical evidence of the sequential eruption of the Central Atlantic Magmatic Province imply a strong causal relationship[FULL TEXT]

     

     

     

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    FIGURE 1: LIST OF SEA LEVEL RISE DATA SOURCES01

     

    FIGURE 2: FOSSIL FUEL EMISSIONS 1814-201402

     

    FIGURE 3: RESULTS FOR JEVREJEVA GMSL 1807-201003a03b

     

    FIGURE 4: RESULTS FOR KEY BISCAYNE 1913-201404a04b

     

    FIGURE 5: RESULTS FOR PORTLAND, MAINE 1910-201405a05b

     

    FIGURE 6: RESULTS FOR ATLANTIC CITY, NJ 1911-201406a06b

     

    FIGURE 7: RESULTS FOR CRISTOBAL 1907-201407a07b

     

    FIGURE 8: RESULTS FOR HALIFAX, NOVA SCOTIA 1919-201408a08b

     

    FIGURE 9: RESULTS FOR GALVESTON, TX 1904-201409a09b

     

    FIGURE 10: RESULTS FOR BREST, FRANCE 1846-201410a10b

     

    FIGURE 11: RESULTS FOR MARSEILLE FRANCE 1885-201411a11b

     

    FIGURE 12: RESULTS FOR GEDSER DENMARK 1891-201412a12b

     

    FIGURE 13: RESULTS FOR HORNBAEK, DENMARK 1891-201413a13b

     

    FIGURE 14: RESULTS FOR HONOLULU, HI 1905-201414a14b

     

    FIGURE 15: RESULTS FOR BALBOA 1907-201415a15b

     

    FIGURE 16: RESULTS FOR PRINCE RUPERT, BC 1909-201416a16b

     

    FIGURE 17: RESULTS FOR VICTORIA BC 1909-201417a17b

     

    FIGURE 18: RESULTS FOR SAN FRANCISCO, CA 1897-201418a18b

     

    FIGURE 19: RESULTS FOR SAN DIEGO, CA 1906-201419a19b

     

    FIGURE 20: SUMMARY OF ALL 16 STATIONS: FULL SPAN20A20B

     

    FIGURE 21: SUMMARY OF ALL 16 STATIONS: FIRST HALF21A21B

     

    FIGURE 22: SUMMARY OF ALL 16 STATIONS: SECOND HALF22A22B

     

     

     

     

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    1. The anthropogenic global warming (AGW) hypothesis holds that fossil fuel emissions since the Industrial Revolution have created an unnatural warming of the climate and thereby caused an unnatural sea level rise at an accelerated rate. The UNFCCC’s international agreement to limit fossil fuel emissions is derived from this theory of causation and proposes that dangerous anthropogenic sea level rise can be moderated by reducing emissions. This work is an empirical test of the causal relationship between emissions and sea level rise on which the UNFCCC emission reduction plan is based. A necessary condition for the effectiveness of the proposed intervention to attenuate sea level rise is that the rate of sea level rise and the rate of emissions must be correlated and that the correlation must be positive and must be statistically significant at the appropriate time scale. Here we test sea level data for the evidence of responsiveness of sea the rate of sea level rise to the rate of fossil fuel emissions at nine different time scales ranging from 20 years to 60 years using both a global mean sea level reconstruction for the period 1807 to 2010 (Jevrejeva, 2014) and observational data from sixteen Northern Hemisphere sea level measurement stations in the Pacific and Atlantic oceans. Figure 1 is a list of all sea level data sources and their time spans. Figure 2 displays the emissions data used in the study.
    2. A  consideration in the study of sea level rise is the complexity of ocean dynamics that creates spatial and temporal differences that are natural and therefore have no interpretation in terms of an external or artificial cause. Therefore care must be taken to identify the changes that can be attributed to AGW forcing (Sallenger, 2012). As described in the Sallenger paper, “Climate warming does not force sea-level rise (SLR) at the same rate everywhere. Rather, there are spatial variations of SLR superimposed on a global average rise. These variations are forced by dynamic processes arising from circulation and variations in temperature and/or salinity, and by static equilibrium processes arising from mass redistributions, changing gravity, and the Earth’s rotation and shape. These sea level variations form unique spatial and temporal patterns that are hard to predict” (Landerer, 2007) (Levermann, 2005) (Schleussner, 2011). Differences among the stations are understood in this context but long term differences in time in the same dataset cannot be explained in terms of the natural phenomena described by Sallenger.
      These issues are addressed in this study in several ways. First, only very long continuous time series of a century or more are used. Second, multiple measurement stations are selected over a wide geographical area and latitude span. Nine different time scales are used ranging from two to six decades for assessing the anthropogenic forcing of sea level change. The smaller time scales, less than 35 years, are likely to contain some noise from known multi-decadal cycles in ocean dynamics but the longer time scales of 40, 45, 50, 55, and 60 years are expected to detect an anthropogenic forcing if it exists. The reliability of the correlation between SLR and emissions is checked using a procedure patterned after the Cronbach split-half test. The two halves of the time series, overlapping in most cases, are compared and the reliability of the full span correlation is judged based on their consistency (Cronbach, 1947). The standard deviation of the correlation coefficient is estimated using Bowley’s procedure (Bowley, 1928) and degrees of freedom are adjusted for multiplicity of data use in moving windows (Munshi, Illusory Statistical Power in Time Series Analysis, 2016).
    3. The proposition that the rate of sea level rise can be moderated by reducing fossil fuel emissions is tested with detrended correlation analysis. Correlations between time series may derive from effects other than those at the time scale of interest particularly from an incidental common drift in time that is unrelated to the theory of causation at the proposed time scale (Shumway, 2011) (Prodobnik,2008) (Munshi, Spurious Correlations in Time Series Data, 2016) (Munshi, 2017). It is therefore necessary to separate the time scale effect from the common drift effect. In the hypothesis test for correlation, the alternate hypothesis is HA: ρ>0 and the corresponding null hypothesis is H0: ρ≤0. Here ρ represents the correlation in the underlying phenomenon that generated the time series sample data being studied. The sixteen correlations from the sixteen stations for each of the three time spans and for each time scale are assumed to be manifestations of the same underlying phenomenon but with natural geographical variability among stations and their average is taken “as a more accurate estimate of the population correlation” (Corey, 1998).
    4. The results of detrended correlation analysis for the Jevrejeva global mean sea level reconstruction 1807-2010 are presented in Figure 3. No positive relationship between rate of emissions and the rate of sea level rise is found at any of nine time scales from 20 years to 60 years in the full span of the data 1807-2010 or in the most recent half-span 1909-2010. Some high positive correlations between r=0.628 to r=0.829 are found for time scales of 45 to 55 years are found in the early half-span of the data 1807-1908. This result is considered spurious in light of the complete absence of positive correlations in the full span and particularly in the recent half-span when fossil fuel emissions were an order of magnitude greater than in the early half-span. Total fossil fuel emissions 1807-1908 were 18.1 GTC (gigatons of carbon equivalent) while in the recent half-span 1909-2010 emissions were 345.7 GTC. If forcing by emissions drive the rate of sea level rise it should be more apparent in the recent half-span than in the early half-span. Thus, the results in Figure 3 do not present credible evidence that the proposed climate action intervention to attenuate sea level rise will be effective. It is noted that correlation is a necessary though not sufficient condition for causation.
    5. The corresponding results for observational data from the sixteen measuring stations are presented in Figure 4 to Figure 19. As in the global mean sea level reconstruction, detrended correlation analysis is carried out for the full span as well as for the early half and the recent half of the available full span data series. The full span results for all sixteen stations are summarized in Figure 20 and the results for the early half and recent half are summarized in Figure 21 and Figure 22 respectively. Differences in the observed correlation among time scales in each of these Figures 20,21,&22 are expected but for any given time scale the sources of variance are assumed to be natural regional variation. In such cases “the correlation coefficient can be a highly variable statistic” (Corey, 1998). Although the time spans among stations don’t exactly correspond, we assume that the sixteen correlations from the sixteen stations for each of the three time spans and for each time scale are the manifestations of the same underlying phenomenon but with natural geographical variability among stations. Accordingly, we take their average as a better estimate of the population correlation (Corey, 1998). The average is shown in the bottom of each of the Figures 20,21,&22. For statistical significance, the standardized value of the average correlation would have to be much greater than unity. However, as seen in the charts in Figures 20,21,&22, the maximum standardized average correlation, found at time scales of 30 to 40 years, is tmax=0.1 for the full span (Figure 20), tmax=0.4 for the early time span (Figure 21), and tmax=0.53 for the recent time span (Figure 22). These results are consistent with the results for the 204-year sea level reconstruction data (Figure 3). We conclude that the data presented in Figures 20,21,&22 do not provide credible evidence that the rate of sea level rise can be moderated by reducing fossil fuel emissions as claimed by various authors (Hansen, 2016).
    6. The (Clark 2018) paper that showed a correlation between cumulative sea level rise and cumulative emissions is discussed in a related post [LINK] . There we show that the correlation between cumulative  values is spurious because time series of the cumulative values of another time series contains neither time scale nor degrees of freedom (See also [TCRE] ). In our work this issue is addressed by using finite time scales less than the full span to insert both time scale and degrees of freedom in the correlation statistics and find that when the spuriousness of the correlation between cumulative values is removed, no correlation is found.

     

     

     

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    CITATIONS 

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    FIGURE 1: CUMULATIVE UFO SIGHTINGS AND CUMULATIVE GLOBAL WARMING01

     

    FIGURE 2: TCRU: TRANSIENT CLIMATE RESPONSE TO CUMULATIVE UFO SIGHTINGSGLOBAL-CHART

     

    FIGURE 3: TCRU VALUES BY CALENDAR MONTHGLOBAL-TABLE

     

     

    FIGURE 4: TCRU ESTIMATES FOR REGIONAL TEMPERATURE RECONSTRUCTIONS0203040506

     

     

     

    [LIST OF POSTS ON THIS SITE]

     

     

    1. The TCRE (Transient Climate Response to Cumulative Emissions) serves a crucial role in climate science. First, it provides a direct causal link between emissions and warming in support of the two key elements of climate change theory theory that (i) the observed warming since the LIA is driven by fossil fuel emissions, and (ii) that the rate of warming can be moderated by climate action in the form of emission reduction. Even more important, the TCRE provides climate science with a metric for estimating the so called “carbon budget” used by climate action policy makers to determine the maximum total emissions possible to meet total warming targets such as the IPCC 1.5ºC and 2.0ºC targets. For more information about the TCRE and its applications in climate science, please see [2018: Matthews, Damon, “Focus on cumulative emissions, global carbon budgets and the implications for climate mitigation targets.” Environmental Research Letters 13.1 (2018)].
    2. The Environmental Research Letters focus issue on ‘Cumulative Emissions, Global Carbon Budgets and the Implications for Climate Mitigation Targets‘ was launched in 2015 to highlight the emerging science of the climate response to cumulative emissions, and how this can inform efforts to decrease emissions fast enough to avoid dangerous climate impacts. There is also a related post on the TCRE at this site [LINK] where it is argued and demonstrated that the observed proportionality between temperature and cumulative emissions is spurious and that therefore, the TCRE metric and carbon budgets derived from it are specious because the correlation derives from a fortuitous sign pattern in the data where annual emissions are always positive and, in an era of global warming, the amount of warming each year is mostly positive.
    3. This work is a parody of the TCRE that further demonstrates the speciousness of the TCRE metric showing that any variable that matches the sign convention offered by cumulative emissions creates just as good a proportionality as emissions. The variable chosen for this parody demonstration is UFO sightings. Like emissions, UFO sightings each year are either zero or positive but never negative. UFO activity data are available from numerous sources for different regions and periods of time (Bader, 2017) (Donderi, 2013) (Hopkins, 1987) (Picknett, 2001) (Sheaffer, 1998) (Spencer, 1993) (UFO-Info, 2017). A convenient summary is also provided by Wikipedia (Wikipedia, 2018). The data are cross checked against the Wikipedia compilation for completeness.
    4. The sightings data are available as individual sightings and complied into total number of UFO sightings worldwide for each year 1910-2015. It is noted that individual sightings are usually for a number of different spaceships that vary from sighting to sighting and in different reports of the same sighting. For the purpose of this study, UFO activity is defined in terms of sightings without consideration for the number of ships per sighting. The annual sightings data are sparse in the first half of the study period with most years containing no sightings. The data are compiled into a cumulative values series along the lines of the CCR/TCRE procedure in climate science (Allen, 2009) (Matthews, 2009) (Matthews/Solomon, 2012) (Munshi, 2018). The proportionality π between cumulative sightings and surface temperature is computed both as a linear regression coefficient and also as a correlation coefficient and tested for statistical significance. The null hypothesis H0: π=0 is tested against the alternate HA: π>0 in a one-tailed test. Here π represents proportionality estimated as a combination of the strength of the linear regression coefficient and the correlation coefficient.
    5. Global surface temperature reconstructions for the period 1910-2015 are provided by the Hadley Centre of the Met Office of the Government of the UK (Morice, 2012). The data are available as monthly mean temperatures for each calendar month in four distinct region and surface combinations. They are Land in the Northern Hemisphere, Sea in the Northern Hemisphere, Land in the Southern Hemisphere, and Sea in the Southern Hemisphere. Data for each calendar month in each of four distinct surface and region specifications are studied for a total of forty eight different statistical tests of the hypothesis that surface temperature in the study period 1910-2015 is driven by UFO activity. The beginning of the study period of 1910-2015 is constrained by the availability of UFO data and the end is constrained by the data availability at the time the study was carried out.
    6. Figure 1 is a graphical display of the UFO sightings and temperature data used in this work. The results of the analysis of these data using the TCRE methodology is displayed in Figure 2 and tabulated in Figure 3. The left frame of Figure 2 is a graphical display of the correlation between annual mean global temperature and cumulative UFO sightings. The right frame is a presentation of the results for monthly mean temperatures. The numbers 1 to 12 along the coordinate represent the twelve calendar months from January to December. There are two ordinate parameters. The TCRU coefficients for the calendar months, computed as the regression coefficient of monthly mean global temperature against cumulative UFO sightings is shown in blue. The corresponding correlation that supports the validity of the regression coefficient is shown in red. The numerical values for both the TCRU and corresponding correlation are tabulated in Figure 3. Details of the month by month analysis are shown in Figure 4.
    7. the empirical test with available UFO sighting data and surface temperature reconstructions 1910-2015 presented in Figure 1, Figure 2, and Figure 3 shows a strong statistically significant proportionality between temperature and cumulative UFO sightings. We conclude that the data are consistent with the proposition that the observed warming since 1910 can be explained as an effect of UFO sightings perhaps by way of their unnatural perturbation of earth’s gravitational and magnetic fields as suggested by various authors.
    8. It has been proposed that UFO spacecraft contain no mechanism for flying known to man. The consensus among scientists is that the method of flight employed by these craft involve interactions with the earth’s own gravitational and geomagnetic system. Analysis of artifacts retrieved from crashed UFOs as well as the study of the intensification of the Aurora Borealis in the presence of UFOs reveal details of UFO propulsion dynamics that imply a massive and intense interference in the earth’s gravitational and magnetic fields (Potter, 2016) (Mike, 2011) (Ensley, 2013) (LaViolette, 2008) (Sarg, 2009). These electromagnetic and gravitational effects alter the way the earth interacts with its sun (Potter, 2009). Based on these effects of UFOs on the atmosphere and the results of our analysis presented above, we propose that the observed warming since 1910 is related to atmospheric perturbations of UFO activity.

     

     

    INTENSIFICATION OF NORTHERN LIGHTS BY UFOsnorthernLights

     

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    CITATIONS

    1. Allen, M. (2009). Warming caused by cumulative carbon emissions towards the trillionth tonne. Nature, 458.7242 (2009): 1163.
    2. Bader, C. (2017). Paranormal America: Ghost encounters, UFO sightings, bigfoot hunts, and other curiosities in religion and culture. NY: NYU Press, 2017.
    3. Box, G. (1994). Time series analysis: forecasting and control. . Englewood Cliffs, NJ: : Prentice Hall.
    4. Donderi, D. (2013). UFOs, ETs, and Alien Abductions: A Scientist Looks at the Evidence. Hampton Roads Publishing (2013).
    5. Draper&Smith. (1998). Applied Regression Analysis. . Wiley.
      Ensley, H. (2013). Alien technology. CreateSpace Independent Publishing Platform.
    6. Holm, S. (1979). A simple sequentially rejective multiple test procedure. Scandinavian Journal of Statistics, 6:2:65-70.
    7. Hopkins, B. (1987). Intruders: The Incredible Visitations at Copley Woods. New York: Random House, 1987.
    8. IPCC. (2007). IPCC AR4 The Physical Science Basis. Retrieved 2017, from IPCC: https://www.ipcc.ch/report/ar4/wg1/
    9. IPCC. (2013). AR5 The Physical Science Basis. Retrieved 2017, from IPCC: http://www.ipcc.ch/report/ar5/wg1/
    10. Johnson, V. (2013). Revised standards for statistical evidence. Proceedings of the National Academy of Sciences, 110.48 (2013): 19313-19317.
    11. Kriebel, D. (2001). The precautionary principle in environmental science.” . Environmental health perspectives , 109.9 (2001): 871.
    12. LaViolette, P. (2008). Secrets of Antigravity Propulsion: Tesla, UFOs, and Classified Aerospace Technology. Bear & Company.
    13. Matthews, H. (2009). The proportionality of global warming to cumulative carbon emissions. Nature, 459.7248 (2009): 829.
    14. Matthews/Solomon. (2012). Cumulative carbon as a policy framework for achieving climate stabilization. Phil. Trans. R. Soc. A, 370.1974 (2012): 4365-4379.
    15. Mike, J. (2011). The anatomy of a flying saucer. CreateSpace Independent Publishing Platform.
    16. Morice, e. (2012). Quantifying uncertainties in global and regional temperature change using an ensemble of observational estimates: The HadCRUT4 dataset. J.Geophys. Res.,, 117.
    17. Munshi, J. (2017). Limitations of the TCRE: Transient Climate Response to Cumulative Emissions. SSRN, https://ssrn.com/abstract=3000932 or http://dx.doi.org/10.2139/ssrn.3000932.
    18. Munshi, J. (2017). OLS Trend Analysis of CET Daily Mean Temperatures 1772-2016. SSRN.
    19. Munshi, J. (2018). From Equilibrium Climate Sensitivity to Carbon Climate Response. SSRN, https://ssrn.com/abstract=3142525.
    20. Picknett, L. (2001). The Mammoth Book of UFOs. Consteble & Robinson Ltd, 2001.
    21. Potter, P. (2009). Physics of UFO gravity manipulation. Retrieved from Physics of UFO gravity manipulation: http://www.zamandayolculuk.com/html-2/ufogravity.htm
    22. Potter, P. (2016). Anti-Gravity Propulsion Dynamics: UFOs and Gravitational Manipulation. Adventures Unlimited Press.
    23. Prodobnik. (2008). Detrended cross correlation analysis. Physical Review Letters, 100: 084102.
    24. Sarg, S. (2009). Field Propulsion by Control of Gravity: Theory and Experiments. CreateSpace Independent Publishing Platform.
    25. Sheaffer, R. (1998). UFO sightings: The evidence. Prometheus Books, 1998.
    26. Spencer, J. (1993). The UFO Encyclopedia. . New York: Avon Books, New York.
    27. UFO-Info. (2017). UFO Info. Retrieved from UFO Info: http://www.ufoinfo.com
    28. Von-Storch, H. (1999). Misuses of statistical analysis in climate research. Analysis of Climate Variability. Springer, Berlin, Heidelberg, , 1999. 11-26.
    29. Wikipedia. (2018). UFO Sightings. Retrieved from Wikipedia: https://en.wikipedia.org/wiki/List_of_reported_UFO_sightings

     

     

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    FIGURE 1: THE 6 BASINS AND 7 DECADES OF THE TEST

     

     

    FIGURE 2: REGRESSION RESULTS FOR ALL BASINS

     

     

    FIGURE 3: TEST FOR DIFFERENCES

     

     

    FIGURE 4: EASTERN PACIFIC BASIN

     

     

    FIGURE 5: NORTH ATLANTIC BASIN

     

    FIGURE 6: NORTH INDIAN BASIN

     

     

    FIGURE 7: SOUTH INDIAN BASIN

     

     

    FIGURE 8: SOUTH PACIFIC BASIN

     

     

    FIGURE 9: WEST PACIFIC BASIN

     

     

    FIGURE 10: SUMMARY OF RESULTS FOR INDIVIDUAL BASINS

    BASIN-SUMMARY

     

    [LIST OF POSTS ON THIS SITE]

     

     

    1. SUMMARY: In a general linear model for global mean annual Accumulated Cyclone Energy (ACE) in six basins and seven decades from 1945 to 2014 we find some evidence of a rising trend in tropical cyclone activity in the early part of the study period prior to the decade D03 [1965-1974]. No global trends are found after this decade. The same pattern is found in three of the six cyclone basins studied, namely, EP [Eastern Pacific], SI [South Indian], and SP [South Pacific]; with each basin showing a rising trend relative to the decades prior to D03 and none since D03. No trends could be detected in the other three cyclone basins in the study, namely, NA [North Atlantic], NI [North Indian], and WP [Western Pacific]. The global model found significant differences in mean overall ACE index among the six basins. The Western Pacific Basin was the most active and the North Indian Basin was the least active. Not much separates the other four basins except that the South Indian Basin was more active than the South Pacific Basin.
    2. BACKGROUND: Sea surface temperature (SST) is the link that connects climate change research with tropical cyclone research. Rising SST is observed (Hadley Centre, 2017) and thought to be an effect of Anthropogenic global warming or AGW (Hansen, 2005) . At the same time, the theory of tropical cyclones holds that cyclone formation, and particularly cyclone intensification are related to SST (Vecchi, 2007) (Knutson, 2010). Testable implications of the theory for empirical research are derived from climate model simulations (Knutson, 2010) and also from sedimentary evidence of land-falling hurricanes over a 1500-year period (Mann, 2009). These studies suggest some guidelines and testable implications for empirical tests of the theory that AGW affects tropical cyclone activity (Knutson, 2010).
    3. These guidelines are as follows: 1. Globally averaged intensity of tropical cyclones will rise as AGW increases SST. Models predict globally averaged intensity increase of 2% to 11% by 2100. 2. Models predict falling globally averaged frequency of tropical cyclones with frequency decreasing 6%-34% by 2100. 3. The globally averaged frequency of “most intense tropical cyclones” should increase as a result of AGW. The intensity of tropical cyclones is measured as the ACE (Accumulated Cyclone Energy). 4. Models predict increase in precipitation within a 100 km radius of the storm center. A precipitation rise of 20% is projected for the year 2100.
    4. Complications of empirical tests in this line of research are (Knutson, 2010): 1. Extremely high variance in tropical cyclone data at an annual time scale suggests longer, perhaps a decadal time scale which in turn greatly reduces statistical power. 2. Limited data availability and poor data quality present barriers to research. 3. Limited theoretical understanding of natural variability makes it difficult to ascertain whether the variability observed in the data is in excess of natural variability. 4. Model projections for individual cyclone basins show large differences and conflicting results. Thus, no testable implication can be derived for studies of individual basins. It is necessary that empirical studies have a global geographical span. 5. Advances in data collection activity, methods, and technology create trends in the data that must be separated from climate change effects (Landsea, 2007) (Landsea, 2010). A high level of interest in tropical cyclones derives from an unusually active hurricane season in 2004 when more than 14 tropical cyclones formed in the North Atlantic basin . Four of these storms intensified to Category 4 or greater and made landfall in the USA causing considerable damage. The even more dramatic 2005 season followed in its heels with more than thirty depressions. Four of them intensified to Category 5 and three made landfall. The most intense was Hurricane Wilma but the most spectacular was Hurricane Katrina which made landfall in Florida and again in Louisiana. Its devastation was facilitated by a breach in the levee system that was unrelated to AGW but its dramatic consequences made it an icon of the possible extreme weather impacts of AGW.
    5. DATA: The “best track” cyclone data were used as received from the NCDC without corrections, adjustments, additions, or deletions with the exception that the years 1848-1944 were not used because they did not contain data for all six basins. It is generally assumed that these data may contain a measurement bias over time and across basins because of differences in data collection methods and procedures (Kossin, 2013). Although aircraft reconnaissance of tropical cyclones in selected basins began as early as the 1940s, these data did not reach a level of coverage and sophistication until the C-130 was deployed in the 1960s. Satellite data gathering for tropical cyclones began in the 1970s.  The undercount bias in the oldest data explains why a rising trend in cyclone activity is found only against the early part of the study period. The findings presented here are entirely empirical and their utility depends on the validity of the ACE index as a measure of tropical cyclone activity. All data and computational details are available in the online data archive for this paper [LINK] . The full text of the source paper for this post may be downloaded from [SSRN.COM] or [ACADEMIA.EDU] .
    6. THEORY: The effect of rising atmospheric carbon dioxide and sea surface temperature (SST) in the climate change era on the formation and intensification of tropical cyclones is not well understood (Walsh, 2014). The conventional theory is that rising SST under the right atmospheric conditions will increase both the formation and intensification of tropical cyclones (Gray W. , 1967) (McBride, 1995) (Emanuel K. , The dependence of hurricane intensity on climate, 1987) (Gray W. , 1979). However, historical tropical cyclone data in a warming world as well as future tropical cyclone conditions generated by general circulation climate models imply that the relationship between the warming trend in the climate change era and tropical cyclone formation and intensification may be more complicated (Hodges, 2007) (Kozar, 2013) (Lin, 2015) (Walsh, 2014). Perhaps it has to do with the amount and extent of rainfall associated with tropical cyclones with higher SST producing more rain (Scoccimarro, 2014) and localized SST relatively higher than surrounding waters producing a greater extent of the rainfall area (Lin, 2015). It is also possible that a complex relationship exists between SST and the frequency2 and intensity of tropical cyclones with rising temperatures implying fewer but more intense storms (Hodges, 2007). On the other hand, a simulation on a millennial time scale by Kozar, Mann, Emanuel, and others suggests that warming will increase the decadal frequency of North Atlantic hurricanes and proportionately, the decadal frequency of hurricanes that make landfall (Kozar, 2013). An extensive study by the US CLIVAR hurricane working group3 (HWG) with multiple general circulation climate models found that warming may cause the frequency of tropical cyclones to decline in the long term and that rising CO2 may have its own independent effect on hurricane activity (Walsh, 2014) (Held, 2011) (Royer, 1998). The authors of the Walsh study included the disclaimer that the effect of climate change on tropical cyclones is “uncertain” and the sobering implication that we don’t really know the relationship between climate change and tropical cyclones. At the root of the tropical cyclone conundrum is the extreme inter-annual variation in the number and maximum intensity of tropical cyclones and the seemingly independent and unrelated behavior of the six major tropical cyclone basins (Hodges, 2007) (Frank, 2007) (Mann, 2007) (Zhao M. , Simulations of global hurricane climatology, interannual variability, and reponse to global warming, 2009) (Zhao H. , 2011) (Eric, 2012) (Chan, Interannual and interdecadal variations of tropical cyclone activity over the western North Pacific, 2005). Although apparent patterns may be visualized in decadal and multi-decadal means, their differences can be interpreted only within the low statistical power imposed by the high variance at the annual level, and their utility is constrained by the limited historical reach of the data along with a measurement bias imposed on the time series by changing measurement technology (Kozar, 2013) (Mann, Evidence of a modest undercount bias in early historical Atlantic tropical cyclone counts, 2007) (Landsea, 2007).
    7. DATA ANALYSIS: There are six tropical and sub-tropical oceanic regions where tropical cyclones form from an isolated patch of relatively higher sea surface temperature. They are, alphabetically, The East Pacific, North Atlantic, North Indian, South Indian, South Pacific, and West Pacific. North Atlantic tropical cyclones are called Hurricanes and those in the West Pacific are called Typhoons. In the other basins they are called cyclones. Figure 1 shows their relative locations of the six tropical cyclone basins as well as the General Linear Model used used to combine them at a decadal time scale in this study of long term trends in global tropical cyclone activity in six basins and seven decades.
    8. RESULTS: The results of the general linear model analysis of global mean ACE for all six tropical cyclone zones at a decadal time scale [as suggested by (Knutson 2010)], are displayed in Figure 2. The left panel is a tabulation of the regression coefficients and their statistical significance. The right panel is a plot across time of the derived global decadal mean ACE for each of the seven decades in the study period 1945-2015. The 21 possible differences in global mean ACE among the seven decades are tested for statistical significance in Figure 3. In these tests, only 2 of the 21 hypothesis tests show statistically significant differences. It shows that decade#5 (1985-1994) and decade#6 (1995-2004) had higher mean global ACE than decade#1 (1955-1964). No other statistically significant difference is found.
    9. The general linear model depicted in Figures 1&2 is also used to compare tropical cyclone activity among the six cyclone basins net of the variation among the seven decades. The mean annual ACE index in each basin for the entire study period 1945-2014 is shown in Figure 3 where the six basins are compared graphically. Hypothesis tests for all pairwise comparisons of the six basins are listed in Figure 3. They show that the Western Pacific (WP) is the most active basin and that North Indian (NI) is the least active. No difference among the other four basins is found except that the South Indian basin (SI) is more active than the South Pacific (SP). Interestingly, the North Atlantic (NA) basin that gets a great deal of attention from researchers due its proximity and relevance to the USA, is not a particularly active basin in the global context. It is more active than only one  basin – the least active North Indian (NI) basin. Tropical cyclone research is therefore biased by a lopsided attention to the North Atlantic basin such that many of the conclusions drawn may not be relevant in a global context, the only context for tests of the effect of global warming on tropical cyclone activity (Knutson 2010). 
    10. The trends for each basin are studied in Figure 4 to Figure 9 alphabetically from EP to WP. Some trends are found in the Eastern Pacific (EP), South Indian (SI), and the South Pacific (SP) basins relative to the earliest decades. No trends are found in the other three basins. In particular, no trend is found in the most active basin WP or in the most popular research basin NA. Cyclonic activity in the EP basin in the twenty-year period 1975-1994 was greater than in the decade 1945-1954 and greater in the decade 1985-1994 than in the decade 1955-1964. No overall trend is found. In particular, there is no evidence that tropical cyclone activity has increased in subsequent decades since the decade D03 [1965-1974]. That in the SI basin is found to be higher in 1965-2004 than in the decade 1945-1954 and higher in the decade1995-2004 than in the decade 1955-1964. However, no sustained trend is found in the sample period 1945-2014 and in particular we find no evidence of an increase in cyclonic activity since the decade D03 [1965-1974]. In the SP basin, cyclonic activity shows a difference between the period 1975-2004 and the decade 1945-1954. However, no sustained trend in cyclonic activity is found. In particular, there is no evidence that cyclonic activity has increased since the decade D02 [1955-1964].
    11. In CONCLUSION, 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 undercount bias in the data in the earliest decades; and not in terms of the theory of anthropogenic global warming and climate change.
    12.  The full text of this work may be downloaded from [ACADEMIA.EDU] or [SSRN.COM] .

     

     

    [LIST OF POSTS ON THIS SITE]

     

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    Figure 1: Annual homicides in England and Wales: Full Span 1898-2003figure01figure02

     

    Figure 2: Annual homicides in England and Wales: 1stHalf 1898-1950FIGURE04FIGURE05

     

    Figure 3: Annual homicides in England and Wales: 2ndHalf 1951-2003FIGURE06FIGURE07

     

    Figure 4: HACRUT4 global mean temperature anomaly: Full span 1898-2003hadcru-fullspanhadcru-fullspan-det

    Figure 5: HACRUT4 global mean temperature anomaly: 1st Half 1898-1950hadcru1sthalfhadcru-1sthalf-det

     

    Figure 6: HACRUT4 global mean temperature anomaly: 2nd Half 1951-2003hadcru-2ndhalfhadcru-2ndhalf-det

     

    Figure 7: Summary Tables for Figure 1 to Figure 6FIGURE03hadcru-summary

     

     

    [LIST OF POSTS ON THIS SITE]

     

     

    1. The theory that fossil fuel emissions since the Industrial Revolution have caused global warming is based on the proposition that such emissions increase atmospheric carbon dioxide concentration which in turn increases surface temperature according to a heat trapping effect first proposed by Arrhenius in a failed attempt to explain ice ages. A testable implication of the theory is the Charney Climate Sensitivity equal to the increase in surface temperature for a doubling of atmospheric CO2 and based on the proportionality of surface temperature with the logarithm of atmospheric CO2. This proportionality is described in terms of a linear regression coefficient based on an assumed statistically significant correlation between the two variables.  [RELATED POST ON ECS]
    2. However, the large body of empirical research in climate sensitivity has not produced an orderly accumulation of knowledge but instead created confusion and mistrust of the climate sensitivity parameter by virtue of an unacceptably large range of empirical sensitivity values. The frustration of climate science with this so called “uncertainty issue in climate sensitivity” has motivated proposals to abandon the climate sensitivity approach in favor of the “Climate Response to Cumulative Emissions or TCRE (Transient Climate Response to Cumulative Emissions) (Knutti, 2017) (Matthews, 2009).  [RELATED POST ON TCRE]
    3. This state of affairs in climate sensitivity research is likely the result of insufficient statistical rigor in the research methodologies applied. This work demonstrates spurious proportionalities in time series data that can yield specious climate sensitivities that have no interpretation. A parody of the Charney sensitivity with data for homicides in England and Wales 1898-2003 is used for the demonstration. The homicide parody is compared with a parallel analysis of global mean temperature reconstructions for the same period.
    4. The analysis demonstrates that such spurious results are more likely to be taken seriously when they occur under conditions where they are more likely to be accepted at face value. The results imply that the large number of climate sensitivities reported in the literature are likely to be mostly spurious and without an interpretation in terms of the Charney climate sensitivity. Sufficient statistical discipline is likely to settle the Charney climate sensitivity issue one way or the other, either to determine its hitherto elusive value or to demonstrate that the assumed relationships do not exist in the data.
    5. Homicides in England and Wales 1898-2003 are studied against the atmospheric carbon dioxide data for the same period. The Charney Equilibrium Sensitivity of Homicides is found to be λ=1.7 thousands of additional annual homicides for each doubling of atmospheric CO2. The sensitivity estimate is supported by a strong correlation of ρ=0.95 and detrended correlation of ρ=0.86. The analysis illustrates and demonstrates that spurious proportionalities in time series data derived from inadequate statistical rigor in the interpretation of the data has led to a theory of human caused global warming since the Little Ice Age that is unlikely to survive a review with sufficient statistical rigor.  [RELATED POST ON THE LIA] .
    6. The full text of this work is available for download from [ACADEMIA.EDU] or from [SSRN.COM] . This blog post is a brief presentation of the work and its findings. The discussion consists of a presentation of the seven charts and tables shown above in sequence from Figure 1 to Figure 7.
    7. Figure 1, Figure 2, and Figure 3 present the data for the annual number of homicides in England and Wales for the 106-year period from 1889 to 2003. Each Figure contains two panels (upper and lower) and three frames (left, middle, and right). The upper panel is a presentation of the proportionality between homicides and log(CO2) seen in the source data as received. The lower panel tests that proportionality for responsiveness at an annual time scale with detrended correlation analysis [DESCRIBED IN A RELATED POST] . Each panel consists of three frames. The left frame presents the log(CO2) data, the middle frame presents object data, either homicides or temperature, and the right frame displays their proportionality.
    8. Figure 1: Full Span of the homicide data (1898-2003): The top panel displays the source data with the right frame showing a strong observed correlation in the sample of ρ=0.945 between log(CO2) and the number of homicides per year (in thousands) in the 106-year sample period 1898-2003. This correlation appears to validate the proportionality and in particular, the OLS linear regression coefficient of β=2.45 that represents the homicide sensitivity of to atmospheric CO2. To restate the sensitivity homicides to carbon dioxide in the Charney/Manabe format in terms of a doubling of atmospheric CO2 concentration, we multiply by Ln(2) = 0.694 to find that λ=1.70 thousand additional homicides for each doubling of atmospheric CO2. The 95% confidence interval for the Charney Sensitivity is 95%CI=[1.58<λ<1.81].Thus we find strong empirical support for the proportionality of homicides to atmospheric carbon dioxide concentration that would support a theory that atmospheric CO2 causes homicides.
    9. However, it is known that correlations in time series data are often spurious in this context because these correlations can be driven by shared long term trends with little or no responsiveness information for a finite time scale of interest that is shorter than the full span of the data being studied. Therefore it is necessary to study correlation in time series data net of the trend as a way of extracting the responsiveness information [DESCRIBED IN A RELATED POST] . The lower panel of Figure 1 presents this analysis. The left and middle frames show the detrended series for log(CO2) and thousands of homicides per year. In the detrended series, the OLS linear regression line has been subtracted from the data. The right frame shows the proportionality between the detrended series. What we expect is that some of the correlation seen in the source data is attributable to long term trends but some may remain and if the portion of the correlation that survives into the detrended series is statistically significant, then responsiveness at the time scale of the detrending procedure is implied. In this case, of the source data correlation of r=0.945, a statistically significant ρ=0.859 survives into the detrended series at an annual time scale. The result implies that homicides are responsive to atmospheric CO2 at an annual time scale. Therefore, the source data correlation is not an artifact of shared trends but a result of responsiveness at an annual time scale and can be interpreted in terms of sensitivity of homicides to atmospheric CO2.
    10. Yet another aspect of time series data that must be taken into consideration is the assumption implicit in the full span analysis that the behavior of the data derived from full span analysis is more or less homogeneous across the full span of the data. This condition is imposed by OLS linear regression assumptions. A common method of carrying out the test is the “split-half” test in which the first half and second half of the full span are compared. If they are found to be very different then full span homogeneity cannot be assumed. Figure 2 presents the analysis for the first 53 years of the homicide data 1898-1950. The corresponding analysis for the second half, 1951-2003, is presented in Figure 3. A comparison of these results shows somewhat different sensitivity values particularly in the first half with the Charney Sensitivity λ=[1.70, 0.60, 2.1] thousand additional homicides for each doubling of atmospheric CO2 in the full span, 1st half, and 2nd half of the time series. The detrended correlation supporting the interpretation of these sensitivities at an annual time scale are  ρ=[0.86, 0.28, 0.30]. The strong detrended correlation supporting the regression coefficient seen in the full span is not found in either half of the span and that explains the instability of the regression coefficient in this analysis.
    11. The corresponding analysis of annual HADCRUT4 global mean temperature anomaly data from the Hadley Centre for the same sample period 1898-2003 is presented in Figure 4, Figure 5, and Figure 6. These temperature data are available for q longer period but the sample period studied is that which corresponds with the homicide data so that the same set of CO2 data are used in each case for a common comparison basis. Figure 4 is a graphical display of the analysis for the full span of the data and it shows a regression coefficient of β=3.1 which implies a climate sensitivity of λ=2.15ºC of warming for each doubling of atmospheric CO2. However, the OLS linear regression coefficient is not supported by a sufficient correlation. The full span correlation in the source data is ρ=0.85. However, unlike the homicide data where almost all of the source data correlation survived into the detrended series, almost all of this strong correlation is attributed to the common trend and only ρ=0.27 survives into the detrended series. Thus, although a sensitivity of λ=2.15 can be computed from the data, the existence of sensitivity at an annual time scale is not supported by the data.
    12. The split half analysis of the temperature anomaly data shows a further weakness in the computed climate sensitivity with a dramatic difference between the two halves. The 1st half 1898-1950 shows a very high regression coefficient of β=8.14 that implies an impossibly high climate sensitivity of λ=5.64ºC of warming for each doubling of atmospheric CO2 but no support for the regression is found in the correlation. The significant source data correlation of ρ=0.80 in the source data derives entirely from shared trends and vanishes when detrended leaving a detrended correlation of ρ=0.04 with no statistical significance. The large and anomalous values the regression coefficient and climate sensitivity are likely to be artifacts of violations of OLS assumptions without any interpretation in terms of a relationship between atmospheric CO2 concentration and surface temperature.
    13. Very different results are seen for the 2nd half of the temperature anomaly data 1951-2003 where strong support for climate sensitivity is found. The regression coefficient β=2.77 implies a climate sensitivity of λ=1.92ºC of warming for each doubling of atmospheric CO2 very close to the full span sensitivity of λ=2.15ºC . The sensitivity is supported by a strong and significant source data correlation of ρ=0.81 almost all of which survives into the detrended series with ρ=0.66 . Thus neither the detrended correlation in the full span of the temperature data nor the split half analysis supports the existence of a climate sensitivity parameter in the temperature anomaly data 1898-2003.
    14. Conclusion#1: It is found that the data show stronger support for the parody research question of the sensitivity of homicides to atmospheric CO2 than for the real research question about the sensitivity of surface temperature anomalies to atmospheric CO2. Yet, though there is an overall acceptance of climate sensitivity as being true and proven by data, no one would of course subscribe to the idea of homicide sensitivity. This kind of interpretation of data is a well known property of human cognition called confirmation bias described more fully in a related post [LINK] .
    15. This anomalous result reveals real and possibly serious issues and weaknesses in empirical sensitivity research in climate science in terms of statistics.The weaknesses likely have to do with overlooked OLS linear regression assumptions as well as flawed interpretation of source data correlation in time series data without consideration for the the effect of shared trends on correlation. This consideration is necessary before source data correlation in time series field data are interpreted in terms of causation at a finite time scale. The uncertainty problem in empirical climate sensitivity research likely arises from inadequate attention to whether regression coefficients are supported by correlation at the time scale of interest. Without such support, though regression coefficients may be computed from the data, they have no interpretation in terms of causal relationships. This issue is discussed in detail in related posts [LINK] [LINK]
    16. Conclusion#2: The relationship between correlation in field data and a theory of causation is that correlation at the correct time scale is a necessary but not sufficient condition for causation. This means that that without correlation at the time scale of interest, no causation theory is possible; but it does not mean that correlation at the time scale of interest implies causation. A dramatic demonstration of this principle is provided by the data presented in this work where we find that the homicide parody shows stronger correlation than the climate sensitivity data.
    17. Conclusion#3: The general state of uncertainty and confusion in empirical climate sensitivity research outside of climate models and in the world of observational data may imply that the hypothesized warming effect of atmospheric CO2 concentration, though programmed into climate models, is not supported by observational data and that therefore there is no empirical support for this theory. This conclusion is supported by related posts at this site that may be found at the links that follow: [LINK#1]  ,  [LINK#2]   [LINK#3] [LINK#4]The source paper for this post may be downloaded from [ACADEMIA.EDU] or from [SSRN.COM] 

     

     

     

     

    ECS Bibliography

    1. 1963: Möller, Fritz. “On the influence of changes in the CO2 concentration in air on the radiation balance of the earth’s surface and on the climate.” Journal of Geophysical Research68.13 (1963): 3877-3886. The numerical value of a temperature change under the influence of a CO2 change as calculated by Plass is valid only for a dry atmosphere. Overlapping of the absorption bands of CO2 and H2O in the range around 15 μ essentially diminishes the temperature changes. New calculations give ΔT = + 1.5° when the CO2 content increases from 300 to 600 ppm. Cloudiness diminishes the radiation effects but not the temperature changes because under cloudy skies larger temperature changes are needed in order to compensate for an equal change in the downward long‐wave radiation. The increase in the water vapor content of the atmosphere with rising temperature causes a self‐amplification effect which results in almost arbitrary temperature changes, e.g. for constant relative humidity ΔT = +10° in the above mentioned case. It is shown, however, that the changed radiation conditions are not necessarily compensated for by a temperature change. The effect of an increase in CO2 from 300 to 330 ppm can be compensated for completely by a change in the water vapor content of 3 per cent or by a change in the cloudiness of 1 per cent of its value without the occurrence of temperature changes at all. Thus the theory that climatic variations are effected by variations in the CO2 content becomes very questionable.
    2. 1964: Manabe, Syukuro, and Robert F. Strickler. “Thermal equilibrium of the atmosphere with a convective adjustment.” Journal of the Atmospheric Sciences 21.4 (1964): 361-385. The states of thermal equilibrium (incorporating an adjustment of super-adiabatic stratification) as well as that of pure radiative equilibrium of the atmosphere are computed as the asymptotic steady state approached in an initial value problem. Recent measurements of absorptivities obtained for a wide range of pressure are used, and the scheme of computation is sufficiently general to include the effect of several layers of clouds. The atmosphere in thermal equilibrium has an isothermal lower stratosphere and an inversion in the upper stratosphere which are features observed in middle latitudes. The role of various gaseous absorbers (i.e., water vapor, carbon dioxide, and ozone), as well as the role of the clouds, is investigated by computing thermal equilibrium with and without one or two of these elements. The existence of ozone has very little effect on the equilibrium temperature of the earth’s surface but a very important effect on the temperature throughout the stratosphere; the absorption of solar radiation by ozone in the upper and middle stratosphere, in addition to maintaining the warm temperature in that region, appears also to be necessary for the maintenance of the isothermal layer or slight inversion just above the tropopause. The thermal equilibrium state in the absence of solar insulation is computed by setting the temperature of the earth’s surface at the observed polar value. In this case, the stratospheric temperature decreases monotonically with increasing altitude, whereas the corresponding state of pure radiative equilibrium has an inversion just above the level of the tropopause. A series of thermal equilibriums is computed for the distributions of absorbers typical of different latitudes. According to these results, the latitudinal variation of the distributions of ozone and water vapor may be partly responsible for the latitudinal variation of the thickness of the isothermal part of the stratosphere. Finally, the state of local radiative equilibrium of the stratosphere overlying a troposphere with the observed distribution of temperature is computed for each season and latitude. In the upper stratosphere of the winter hemisphere, a large latitudinal temperature gradient appears at the latitude of the polar-night jet stream, while in the upper statosphere of the summer hemisphere, the equilibrium temperature varies little with latitude. These features are consistent with the observed atmosphere. However, the computations predict an extremely cold polar night temperature in the upper stratosphere and a latitudinal decrease (toward the cold pole) of equilibrium temperature in the middle or lower stratosphere for winter and fall. This disagrees with observation, and suggests that explicit introduction of the dynamics of large scale motion is necessary.
    3. 1967: Manabe, Syukuro, and Richard T. Wetherald. “Thermal equilibrium of the atmosphere with a given distribution of relative humidity.” Journal of the Atmospheric Sciences 24.3 (1967): 241-259. [ECS=2]bandicam 2018-09-21 13-24-28-297
    4. 1969: Budyko, Mikhail I. “The effect of solar radiation variations on the climate of the earth.” tellus 21.5 (1969): 611-619. It follows from the analysis of observation data that the secular variation of the mean temperature of the Earth can be explained by the variation of short-wave radiation, arriving at the surface of the Earth. In connection with this, the influence of long-term changes of radiation, caused by variations of atmospheric transparency on the thermal regime is being studied. Taking into account the influence of changes of planetary albedo of the Earth under the development of glaciations on the thermal regime, it is found that comparatively small variations of atmospheric transparency could be sufficient for the development of quaternary glaciations.
    5. 1969: Sellers, William D. “A global climatic model based on the energy balance of the earth-atmosphere system.” Journal of Applied Meteorology 8.3 (1969): 392-400. A relatively simple numerical model of the energy balance of the earth-atmosphere is set up and applied. The dependent variable is the average annual sea level temperature in 10° latitude belts. This is expressed basically as a function of the solar constant, the planetary albedo, the transparency of the atmosphere to infrared radiation, and the turbulent exchange coefficients for the atmosphere and the oceans. The major conclusions of the analysis are that removing the arctic ice cap would increase annual average polar temperatures by no more than 7C, that a decrease of the solar constant by 2–5% might be sufficient to initiate another ice age, and that man’s increasing industrial activities may eventually lead to a global climate much warmer than today.
    6. 1971: Rasool, S. Ichtiaque, and Stephen H. Schneider. “Atmospheric carbon dioxide and aerosols: Effects of large increases on global climate.” Science 173.3992 (1971): 138-141. Effects on the global temperature of large increases in carbon dioxide and aerosol densities in the atmosphere of Earth have been computed. It is found that, although the addition of carbon dioxide in the atmosphere does increase the surface temperature, the rate of temperature increase diminishes with increasing carbon dioxide in the atmosphere. For aerosols, however, the net effect of increase in density is to reduce the surface temperature of Earth. Because of the exponential dependence of the backscattering, the rate of temperature decrease is augmented with increasing aerosol content. An increase by only a factor of 4 in global aerosol background concentration may be sufficient to reduce the surface temperature by as much as 3.5 ° K. If sustained over a period of several years, such a temperature decrease over the whole globe is believed to be sufficient to trigger an ice age.
    7. 1975: Manabe, Syukuro, and Richard T. Wetherald. “The effects of doubling the CO2 concentration on the climate of a general circulation model.” Journal of the Atmospheric Sciences 32.1 (1975): 3-15. An attempt is made to estimate the temperature changes resulting from doubling the present CO2 concentration by the use of a simplified three-dimensional general circulation model. This model contains the following simplifications: a limited computational domain, an idealized topography, no beat transport by ocean currents, and fixed cloudiness. Despite these limitations, the results from this computation yield some indication of how the increase of CO2 concentration may affect the distribution of temperature in the atmosphere. It is shown that the CO2 increase raises the temperature of the model troposphere, whereas it lowers that of the model stratosphere. The tropospheric warming is somewhat larger than that expected from a radiative-convective equilibrium model. In particular, the increase of surface temperature in higher latitudes is magnified due to the recession of the snow boundary and the thermal stability of the lower troposphere which limits convective beating to the lowest layer. It is also shown that the doubling of carbon dioxide significantly increases the intensity of the hydrologic cycle of the model. bandicam 2018-09-21 15-17-14-922
    8. 1976: Cess, Robert D. “Climate change: An appraisal of atmospheric feedback mechanisms employing zonal climatology.” Journal of the Atmospheric Sciences 33.10 (1976): 1831-1843. The sensitivity of the earth’s surface temperature to factors which can induce long-term climate change, such as a variation in solar constant, is estimated by employing two readily observable climate changes. One is the latitudinal change in annual mean climate, for which an interpretation of climatological data suggests that cloud amount is not a significant climate feedback mechanism, irrespective of how cloud amount might depend upon surface temperature, since there are compensating changes in both the solar and infrared optical properties of the atmosphere. It is further indicated that all other atmospheric feedback mechanisms, resulting, for example, from temperature-induced changes in water vapor amount, cloud altitude and lapse rate, collectively double the sensitivity of global surface temperature to a change in solar constant. The same conclusion is reached by considering a second type of climate change, that associated with seasonal variations for a given latitude zone. The seasonal interpretation further suggests that cloud amount feedback is unimportant zonally as well as globally. Application of the seasonal data required a correction for what appears to be an important seasonal feedback mechanism. This is attributed to a variability in cloud albedo due to seasonal changes in solar zenith angle. No attempt was made to individually interpret the collective feedback mechanisms which contribute to the doubling in surface temperature sensitivity. It is suggested, however, that the conventional assumption of fixed relative humidity for describing feedback due to water vapor amount might not be as applicable as is generally believed. Climate models which additionally include ice-albedo feedback are discussed within the framework of the present results.
    9. 1978: Ramanathan, V., and J. A. Coakley. “Climate modeling through radiative‐convective models.” Reviews of geophysics16.4 (1978): 465-489. We present a review of the radiative‐convective models that have been used in studies pertaining to the earth’s climate. After familiarizing the reader with the theoretical background, modeling methodology, and techniques for solving the radiative transfer equation the review focuses on the published model studies concerning global climate and global climate change. Radiative‐convective models compute the globally and seasonally averaged surface and atmospheric temperatures. The computed temperatures are in good agreement with the observed temperatures. The models include the important climatic feedback mechanism between surface temperature and H2O amount in the atmosphere. The principal weakness of the current models is their inability to simulate the feedback mechanism between surface temperature and cloud cover. It is shown that the value of the critical lapse rate adopted in radiative‐convective models for convective adjustment is significantly larger than the observed globally averaged tropospheric lapse rate. The review also summarizes radiative‐convective model results for the sensitivity of surface temperature to perturbations in (1) the concentrations of the major and minor optically active trace constituents, (2) aerosols, and (3) cloud amount. A simple analytical model is presented to demonstrate how the surface temperature in a radiative‐convective model responds to perturbations.
    10. 1985: Wigley, Thomas ML, and Michael E. Schlesinger. “Analytical solution for the effect of increasing CO2 on global mean temperature.” Nature 315.6021 (1985): 649. Increasing atmospheric carbon dioxide concentration is expected to cause substantial changes in climate. Recent model studies suggest that the equilibrium warming for a CO2 doubling (Δ T2×) is about 3–4°C. Observational data show that the globe has warmed by about 0.5°C over the past 100 years. Are these two results compatible? To answer this question due account must be taken of oceanic thermal inertia effects, which can significantly slow the response of the climate system to external forcing. The main controlling parameters are the effective diffusivity of the ocean below the upper mixed layer (κ) and the climate sensitivity (defined by Δ T2×). Previous analyses of this problem have considered only limited ranges of these parameters. Here we present a more general analysis of two cases, forcing by a step function change in CO2 concentration and by a steady CO2 increase. The former case may be characterized by a response time which we show is strongly dependent on both κ and Δ T2×. In the latter case the damped response means that, at any given time, the climate system may be quite far removed from its equilibrium with the prevailing CO2 level. In earlier work this equilibrium has been expressed as a lag time, but we show this to be misleading because of the sensitivity of the lag to the history of past CO2 variations. Since both the lag and the degree of disequilibrium are strongly dependent on κ and Δ T2×, and because of uncertainties in the pre-industrial CO2 level, the observed global warming over the past 100 years can be shown to be compatible with a wide range of CO2-doubling temperature changes.
    11. 1991: Lawlor, D. W., and R. A. C. Mitchell. “The effects of increasing CO2 on crop photosynthesis and productivity: a review of field studies.” Plant, Cell & Environment 14.8 (1991): 807-818. Only a small proportion of elevated CO2 studies on crops have taken place in the field. They generally confirm results obtained in controlled environments: CO2increases photosynthesis, dry matter production and yield, substantially in C3 species, but less in C4, it decreases stomatal conductance and transpiration in C3 and C4 species and greatly improves water‐use efficiency in all plants. The increased productivity of crops with CO2 enrichment is also related to the greater leaf area produced. Stimulation of yield is due more to an increase in the number of yield‐forming structures than in their size. There is little evidence of a consistent effect of CO2 on partitioning of dry matter between organs or on their chemical composition, except for tubers. Work has concentrated on a few crops (largely soybean) and more is needed on crops for which there are few data (e.g. rice). Field studies on the effects of elevated CO2 in combination with temperature, water and nutrition are essential; they should be related to the development and improvement of mechanistic crop models, and designed to test their predictions.
    12. 2009: Danabasoglu, Gokhan, and Peter R. Gent. “Equilibrium climate sensitivity: Is it accurate to use a slab ocean model?.” Journal of Climate 22.9 (2009): 2494-2499. The equilibrium climate sensitivity of a climate model is usually defined as the globally averaged equilibrium surface temperature response to a doubling of carbon dioxide. This is virtually always estimated in a version with a slab model for the upper ocean. The question is whether this estimate is accurate for the full climate model version, which includes a full-depth ocean component. This question has been answered for the low-resolution version of the Community Climate System Model, version 3 (CCSM3). The answer is that the equilibrium climate sensitivity using the full-depth ocean model is 0.14°C higher than that using the slab ocean model, which is a small increase. In addition, these sensitivity estimates have a standard deviation of nearly 0.1°C because of interannual variability. These results indicate that the standard practice of using a slab ocean model does give a good estimate of the equilibrium climate sensitivity of the full CCSM3. Another question addressed is whether the effective climate sensitivity is an accurate estimate of the equilibrium climate sensitivity. Again the answer is yes, provided that at least 150 yr of data from the doubled carbon dioxide run are used.
    13. 2010: Connell, Sean D., and Bayden D. Russell. “The direct effects of increasing CO2 and temperature on non-calcifying organisms: increasing the potential for phase shifts in kelp forests.” Proceedings of the Royal Society of London B: Biological Sciences (2010): rspb20092069. Predictions about the ecological consequences of oceanic uptake of CO2 have been preoccupied with the effects of ocean acidification on calcifying organisms, particularly those critical to the formation of habitats (e.g. coral reefs) or their maintenance (e.g. grazing echinoderms). This focus overlooks the direct effects of CO2 on non-calcareous taxa, particularly those that play critical roles in ecosystem shifts. We used two experiments to investigate whether increased CO2 could exacerbate kelp loss by facilitating non-calcareous algae that, we hypothesized, (i) inhibit the recovery of kelp forests on an urbanized coast, and (ii) form more extensive covers and greater biomass under moderate future CO2 and associated temperature increases. Our experimental removal of turfs from a phase-shifted system (i.e. kelp- to turf-dominated) revealed that the number of kelp recruits increased, thereby indicating that turfs can inhibit kelp recruitment. Future CO2 and temperature interacted synergistically to have a positive effect on the abundance of algal turfs, whereby they had twice the biomass and occupied over four times more available space than under current conditions. We suggest that the current preoccupation with the negative effects of ocean acidification on marine calcifiers overlooks potentially profound effects of increasing CO2and temperature on non-calcifying organisms.
    14. 2011: Schmittner, Andreas, et al. “Climate sensitivity estimated from temperature reconstructions of the Last Glacial Maximum.” Science 334.6061 (2011): 1385-1388. Assessing the impact of future anthropogenic carbon emissions is currently impeded by uncertainties in our knowledge of equilibrium climate sensitivity to atmospheric carbon dioxide doubling. Previous studies suggest 3 kelvin (K) as the best estimate, 2 to 4.5 K as the 66% probability range, and nonzero probabilities for much higher values, the latter implying a small chance of high-impact climate changes that would be difficult to avoid. Here, combining extensive sea and land surface temperature reconstructions from the Last Glacial Maximum with climate model simulations, we estimate a lower median (2.3 K) and reduced uncertainty (1.7 to 2.6 K as the 66% probability range, which can be widened using alternate assumptions or data subsets). Assuming that paleoclimatic constraints apply to the future, as predicted by our model, these results imply a lower probability of imminent extreme climatic change than previously thought.
    15. 2012: Fasullo, John T., and Kevin E. Trenberth. “A less cloudy future: The role of subtropical subsidence in climate sensitivity.” science 338.6108 (2012): 792-794. An observable constraint on climate sensitivity, based on variations in mid-tropospheric relative humidity (RH) and their impact on clouds, is proposed. We show that the tropics and subtropics are linked by teleconnections that induce seasonal RH variations that relate strongly to albedo (via clouds), and that this covariability is mimicked in a warming climate. A present-day analog for future trends is thus identified whereby the intensity of subtropical dry zones in models associated with the boreal monsoon is strongly linked to projected cloud trends, reflected solar radiation, and model sensitivity. Many models, particularly those with low climate sensitivity, fail to adequately resolve these teleconnections and hence are identifiably biased. Improving model fidelity in matching observed variations provides a viable path forward for better predicting future climate.
    16. 2012: Andrews, Timothy, et al. “Forcing, feedbacks and climate sensitivity in CMIP5 coupled atmosphere‐ocean climate models.” Geophysical Research Letters 39.9 (2012). We quantify forcing and feedbacks across available CMIP5 coupled atmosphere‐ocean general circulation models (AOGCMs) by analysing simulations forced by an abrupt quadrupling of atmospheric carbon dioxide concentration. This is the first application of the linear forcing‐feedback regression analysis of Gregory et al. (2004) to an ensemble of AOGCMs. The range of equilibrium climate sensitivity is 2.1–4.7 K. Differences in cloud feedbacks continue to be important contributors to this range. Some models show small deviations from a linear dependence of top‐of‐atmosphere radiative fluxes on global surface temperature change. We show that this phenomenon largely arises from shortwave cloud radiative effects over the ocean and is consistent with independent estimates of forcing using fixed sea‐surface temperature methods. We suggest that future research should focus more on understanding transient climate change, including any time‐scale dependence of the forcing and/or feedback, rather than on the equilibrium response to large instantaneous forcing.
    17. 2012: Bitz, Cecilia M., et al. “Climate sensitivity of the community climate system model, version 4.” Journal of Climate 25.9 (2012): 3053-3070.Equilibrium climate sensitivity of the Community Climate System Model, version 4 (CCSM4) is 3.20°C for 1° horizontal resolution in each component. This is about a half degree Celsius higher than in the previous version (CCSM3). The transient climate sensitivity of CCSM4 at 1° resolution is 1.72°C, which is about 0.2°C higher than in CCSM3. These higher climate sensitivities in CCSM4 cannot be explained by the change to a preindustrial baseline climate. This study uses the radiative kernel technique to show that, from CCSM3 to CCSM4, the global mean lapse-rate feedback declines in magnitude and the shortwave cloud feedback increases. These two warming effects are partially canceled by cooling because of slight decreases in the global mean water vapor feedback and longwave cloud feedback from CCSM3 to CCSM4. A new formulation of the mixed layer, slab-ocean model in CCSM4 attempts to reproduce the SST and sea ice climatology from an integration with a full-depth ocean, and it is integrated with a dynamic sea ice model. These new features allow an isolation of the influence of ocean dynamical changes on the climate response when comparing integrations with the slab ocean and full-depth ocean. The transient climate response of the full-depth ocean version is 0.54 of the equilibrium climate sensitivity when estimated with the new slab-ocean model version for both CCSM3 and CCSM4. The authors argue the ratio is the same in both versions because they have about the same zonal mean pattern of change in ocean surface heat flux, which broadly resembles the zonal mean pattern of net feedback strength.
    18. 2012: Rogelj, Joeri, Malte Meinshausen, and Reto Knutti. “Global warming under old and new scenarios using IPCC climate sensitivity range estimates.” Nature climate change 2.4 (2012): 248. Climate projections for the fourth assessment report1 (AR4) of the Intergovernmental Panel on Climate Change (IPCC) were based on scenarios from the Special Report on Emissions Scenarios2 (SRES) and simulations of the third phase of the Coupled Model Intercomparison Project3 (CMIP3). Since then, a new set of four scenarios (the representative concentration pathways or RCPs) was designed4. Climate projections in the IPCC fifth assessment report (AR5) will be based on the fifth phase of the Coupled Model Intercomparison Project5 (CMIP5), which incorporates the latest versions of climate models and focuses on RCPs. This implies that by AR5 both models and scenarios will have changed, making a comparison with earlier literature challenging. To facilitate this comparison, we provide probabilistic climate projections of both SRES scenarios and RCPs in a single consistent framework. These estimates are based on a model set-up that probabilistically takes into account the overall consensus understanding of climate sensitivity uncertainty, synthesizes the understanding of climate system and carbon-cycle behaviour, and is at the same time constrained by the observed historical warming.
    19. 2014: Sherwood, Steven C., Sandrine Bony, and Jean-Louis Dufresne. “Spread in model climate sensitivity traced to atmospheric convective mixing.” Nature 505.7481 (2014): 37. Equilibrium climate sensitivity refers to the ultimate change in global mean temperature in response to a change in external forcing. Despite decades of research attempting to narrow uncertainties, equilibrium climate sensitivity estimates from climate models still span roughly 1.5 to 5 degrees Celsius for a doubling of atmospheric carbon dioxide concentration, precluding accurate projections of future climate. The spread arises largely from differences in the feedback from low clouds, for reasons not yet understood. Here we show that differences in the simulated strength of convective mixing between the lower and middle tropical troposphere explain about half of the variance in climate sensitivity estimated by 43 climate models. The apparent mechanism is that such mixing dehydrates the low-cloud layer at a rate that increases as the climate warms, and this rate of increase depends on the initial mixing strength, linking the mixing to cloud feedback. The mixing inferred from observations appears to be sufficiently strong to imply a climate sensitivity of more than 3 degrees for a doubling of carbon dioxide. This is significantly higher than the currently accepted lower bound of 1.5 degrees, thereby constraining model projections towards relatively severe future warming.
    20. 2015: Mauritsen, Thorsten, and Bjorn Stevens. “Missing iris effect as a possible cause of muted hydrological change and high climate sensitivity in models.” Nature Geoscience 8.5 (2015): 346. Equilibrium climate sensitivity to a doubling of CO2 falls between 2.0 and 4.6 K in current climate models, and they suggest a weak increase in global mean precipitation. Inferences from the observational record, however, place climate sensitivity near the lower end of this range and indicate that models underestimate some of the changes in the hydrological cycle. These discrepancies raise the possibility that important feedbacks are missing from the models. A controversial hypothesis suggests that the dry and clear regions of the tropical atmosphere expand in a warming climate and thereby allow more infrared radiation to escape to space. This so-called iris effect could constitute a negative feedback that is not included in climate models. We find that inclusion of such an effect in a climate model moves the simulated responses of both temperature and the hydrological cycle to rising atmospheric greenhouse gas concentrations closer to observations. Alternative suggestions for shortcomings of models — such as aerosol cooling, volcanic eruptions or insufficient ocean heat uptake — may explain a slow observed transient warming relative to models, but not the observed enhancement of the hydrological cycle. We propose that, if precipitating convective clouds are more likely to cluster into larger clouds as temperatures rise, this process could constitute a plausible physical mechanism for an iris effect.
    21. 2015: Schimel, David, Britton B. Stephens, and Joshua B. Fisher. “Effect of increasing CO2 on the terrestrial carbon cycle.” Proceedings of the National Academy of Sciences 112.2 (2015): 436-441. Feedbacks from terrestrial ecosystems to atmospheric CO2 concentrations contribute the second-largest uncertainty to projections of future climate. These feedbacks, acting over huge regions and long periods of time, are extraordinarily difficult to observe and quantify directly. We evaluated in situ, atmospheric, and simulation estimates of the effect of CO2 on carbon storage, subject to mass balance constraints. Multiple lines of evidence suggest significant tropical uptake for CO2, approximately balancing net deforestation and confirming a substantial negative global feedback to atmospheric CO2 and climate. This reconciles two approaches that have previously produced contradictory results. We provide a consistent explanation of the impacts of CO2 on terrestrial carbon across the 12 orders of magnitude between plant stomata and the global carbon cycle.
    22. 2016: Tan, Ivy, Trude Storelvmo, and Mark D. Zelinka. “Observational constraints on mixed-phase clouds imply higher climate sensitivity.” Science 352.6282 (2016): 224-227. How much global average temperature eventually will rise depends on the Equilibrium Climate Sensitivity (ECS), which relates atmospheric CO2 concentration to atmospheric temperature. For decades, ECS has been estimated to be between 2.0° and 4.6°C, with much of that uncertainty owing to the difficulty of establishing the effects of clouds on Earth’s energy budget. Tan et al. used satellite observations to constrain the radiative impact of mixed phase clouds. They conclude that ECS could be between 5.0° and 5.3°C—higher than suggested by most global climate models.
    23. 2018: Watanabe, Masahiro, et al. “Low clouds link equilibrium climate sensitivity to hydrological sensitivity.” Nature Climate Change (2018): 1. Equilibrium climate sensitivity (ECS) and hydrological sensitivity describe the global mean surface temperature and precipitation responses to a doubling of atmospheric CO2. Despite their connection via the Earth’s energy budget, the physical linkage between these two metrics remains controversial. Here, using a global climate model with a perturbed mean hydrological cycle, we show that ECS and hydrological sensitivity per unit warming are anti-correlated owing to the low-cloud response to surface warming. When the amount of low clouds decreases, ECS is enhanced through reductions in the reflection of shortwave radiation. In contrast, hydrological sensitivity is suppressed through weakening of atmospheric longwave cooling, necessitating weakened condensational heating by precipitation. These compensating cloud effects are also robustly found in a multi-model ensemble, and further constrained using satellite observations. Our estimates, combined with an existing constraint to clear-sky shortwave absorption, suggest that hydrological sensitivity could be lower by 30% than raw estimates from global climate mode

     

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