Previous studies have estimated global available potential energy (APE) and global APE generation, but no study has focused on the geographic distribution of contributions to global APE and APE generation. To obtain the information needed for this analysis, simulations were performed using the NCAR CESM1.0.4 climate model. Based on these simulation results, maps of the spatial and seasonal distribution of APE contributions and APE generation in the atmosphere were obtained from the analysis. APE is generated by processes that cool relatively cool areas or warm relatively warm areas. It was found that there are two regions of the mid-to upper troposphere that contribute primarily to APE generation: 1) the tropics, especially the western tropical Pacific, owing largely to latent heat released in the intertropical convergence zone, and 2) the polar regions, especially in the relatively cold polar night, where longwave cooling is not offset by shortwave warming. It was also found that these qualitative results are largely insensitive to the assumptions examined regarding the treatment of topography in the atmosphere. Further, the analysis was extended to calculate how APE and APE generation is changed in a 4 x CO2 climate relative to a 1 x CO2 climate. It was found that in the high-CO2 climate, APE decreased by 7.0% and APE generation decreased by 10.1%. This is consistent with expectations based on decreased equator-to-pole temperature gradients in warmer climates. The methods, results, and analysis presented here should prove useful in helping to build a better understanding of controls on atmospheric kinetic energy.

Integrated assessment models are commonly used to generate optimal carbon prices based on an objective function that maximizes social welfare. Such models typically project an initially low carbon price that increases with time. This framework does not reflect the incentives of decision makers who are responsible for generating tax revenue. If a rising carbon price is to result in near-zero emissions, it must ultimately result in near-zero carbon tax revenue. That means that at some point, policy makers will be asked to increase the tax rate on carbon emissions to such an extent that carbon tax revenue will fall. Therefore, there is a risk that the use of a carbon tax to generate revenue could eventually create a perverse incentive to continue carbon emissions in order to provide a continued stream of carbon tax revenue. Using the Dynamic Integrated Climate Economy (DICE) model, we provide evidence that this risk is not a concern for the immediate future but that a revenue-generating carbon tax could create this perverse incentive as time goes on. This incentive becomes perverse at about year 2085 under the default configuration of DICE, but the timing depends on a range of factors including the cost of climate damages and the cost of decarbonizing the global energy system. While our study is based on a schematic model, it highlights the importance of considering a broader spectrum of incentives in studies using more comprehensive integrated assessment models. Our study demonstrates that the use of a carbon tax for revenue generation could potentially motivate implementation of such a tax today, but this source of revenue generation risks motivating continued carbon emissions far into the future.

Adaptation is the process of adjusting to climate change in order to moderate harm or exploit beneficial opportunities associated with it. Most adaptation strategies are designed to adjust to a new climate state. However, despite our best efforts to curtail greenhouse gas emissions, climate is likely to continue changing far into the future. Here, we show how considering rates of change affects the projected optimal adaptation strategy. We ground our discussion with an example of optimal investment in the face of continued sea-level rise, presenting a quantitative model that illustrates the interplay among physical and economic factors governing coastal development decisions such as rate of sea-level rise, land slope, discount rate, and depreciation rate. This model shows that the determination of optimal investment strategies depends on taking into account future rates of sea-level rise, as well as social and political constraints. This general approach also applies to the development of improved strategies to adapt to ongoing trends in temperature, precipitation, and other climate variables. Adaptation to some amount of change instead of adaptation to ongoing rates of change may produce inaccurate estimates of damages to the social systems and their ability to respond to external pressures.

A number of analyses, meta-analyses, and assessments, including those performed by the Intergovernmental Panel on Climate Change, the National Oceanic and Atmospheric Administration, the National Renewable Energy Laboratory, and the International Energy Agency, have concluded that deployment of a diverse portfolio of clean energy technologies makes a transition to a low-carbon-emission energy system both more feasible and less costly than other pathways. In contrast, Jacobson et al. [Jacobson MZ, Delucchi MA, Cameron MA, Frew BA (2015) Proc Natl Acad Sci USA 112(49): 15060-15065] argue that it is feasible to provide "low-cost solutions to the grid reliability problem with 100% penetration of WWS [wind, water and solar power] across all energy sectors in the continental United States between 2050 and 2055", with only electricity and hydrogen as energy carriers. In this paper, we evaluate that study and find significant shortcomings in the analysis. In particular, we point out that this work used invalid modeling tools, contained modeling errors, and made implausible and inadequately supported assumptions. Policy makers should treat with caution any visions of a rapid, reliable, and low-cost transition to entire energy systems that relies almost exclusively on wind, solar, and hydroelectric power.

Clean energy technologies that cost more than fossil fuel technologies require support through research and development (R & D). Learning-by-doing relates historical cost decreases to accumulation of experience. A learning investment is the amount of subsidy that is required to reach cost parity between a new technology and a conventional technology. We use learning investments to compare the relative impacts of two stylized types of R & D. We define curve-following R & D to be R & D that lowers costs by producing knowledge that would have otherwise been gained through learning-by-doing. We define curve-shifting R & D to be R & D that lowers costs by producing innovations that would not have occurred through learning-by-doing. We show that if an equal investment in curve-following or curve-shifting R & D would produce the same reduction in cost, the curve shifting R & D would be more effective at reducing the learning investment needed to make the technology competitive. The relative benefit of curve-shifting over curve-following R & D is greater with a high starting cost and low learning rate. Our analysis suggests that, other things equal, investments in curve-shifting R & D have large benefits relative to curve-following R & D. In setting research policy, governments should consider the greater benefits of cost reductions brought about by transformational rather than incremental change.

Wind turbines continuously remove kinetic energy from the lower troposphere, thereby reducing the wind speed near hub height. The rate of electricity generation in large wind farms containing multiple wind arrays is, therefore, constrained by the rate of kinetic energy replenishment from the atmosphere above. In recent years, a growing body of research argues that the rate of generated power is limited to around 1.5 W m(-2) within large wind farms. However, in this study, we show that considerably higher power generation rates may be sustainable over some open ocean areas. In particular, the North Atlantic is identified as a region where the downward transport of kinetic energy may sustain extraction rates of 6 W m(-2) and above over large areas in the annual mean. Furthermore, our results indicate that the surface heat flux from the oceans to the atmosphere may play an important role in creating regions where sustained high rates of downward transport of kinetic energy and thus, high rates of kinetic energy extraction may be geophysical possible. While no commercial-scale deep water wind farms yet exist, our results suggest that such technologies, if they became technically and economically feasible, could potentially provide civilizationscale power.

Climate models provide the principal means of projecting global warming over the remainder of the twenty-first century but modelled estimates of warming vary by a factor of approximately two even under the same radiative forcing scenarios. Across-model relationships between currently observable attributes of the climate system and the simulated magnitude of future warming have the potential to inform projections. Here we show that robust across-model relationships exist between the global spatial patterns of several fundamental attributes of Earth's top-of-atmosphere energy budget and the magnitude of projected global warming. When we constrain the model projections with observations, we obtain greater means and narrower ranges of future global warming across the major radiative forcing scenarios, in general. In particular, we find that the observationally informed warming projection for the end of the twenty-first century for the steepest radiative forcing scenario is about 15 per cent warmer (+0.5 degrees Celsius) with a reduction of about a third in the two-standard-deviation spread (-1.2 degrees Celsius) relative to the raw model projections reported by the Intergovernmental Panel on Climate Change. Our results suggest that achieving any given global temperature stabilization target will require steeper greenhouse gas emissions reductions than previously calculated.

The six largest known impact craters of the last 250 Myr (>= 70 km in diameter), which are capable of causing significant environmental damage, coincide with four times of recognized extinction events at 36 (with 2 craters), 66, and 145 Myr ago, and possibly with two provisional extinction events at 168 and 215 Myr ago. These impact cratering events are accompanied by layers in the geologic record interpreted as impact ejecta. Chance occurrences of impacts and extinctions can be rejected at confidence levels of 99.96% (for 4 impact/extinctions) to 99.99% (for 6 impact/extinctions). These results argue that several extinction events over the last 250 Myr may be related to the effects of large-body impacts. (C) 2017, China University of Geosciences (Beijing) and Peking University. Production and hosting by Elsevier B.V.

Solar geoengineering has been proposed as a backup plan to offset some aspects of anthropogenic climate change if timely CO2 emission reductions fail to materialize. Modeling studies have shown that there are trade-offs between changes in temperature and hydrological cycle in response to solar geoengineering. Here we investigate the possibility of stabilizing both global mean temperature and precipitation simultaneously by combining two geoengineering approaches: stratospheric sulfate aerosol increase (SAI) that deflects sunlight to space and cirrus cloud thinning (CCT) that enables more longwave radiation to escape to space. Using the slab ocean configuration of National Center for Atmospheric Research Community Earth System Model, we simulate SAI by uniformly adding sulfate aerosol in the upper stratosphere and CCT by uniformly increasing cirrus cloud ice particle falling speed. Under an idealized warming scenario of abrupt quadrupling of atmospheric CO2, we show that by combining appropriate amounts of SAI and CCT geoengineering, global mean (or land mean) temperature and precipitation can be restored simultaneously to preindustrial levels. However, compared to SAI, cocktail geoengineering by mixing SAI and CCT does not markedly improve the overall similarity between geoengineered climate and preindustrial climate on regional scales. Some optimal spatially nonuniform mixture of SAI with CCT might have the potential to better mitigate climate change at both the global and regional scales.

Correction for Geophysical constraints on the reliability of solar and wind power in the United States' by Matthew R. Shaner et al., Energy Environ. Sci., 2018, DOI: ; 10.1039/c7ee03029k.