Evidence from the 100-most cited papers ever published in ERL indicates the disproportionately large scientific impact of small groups of authors. The median number of authors on these 100 most-cited papers was 3.5, and 72 out of the 100 most cited papers had 5 or fewer authors. This indicates that small groups of authors often produce the work with the greatest impact, even in an inter-disciplinary setting. This suggests that it may be wise to institute policy changes that discourage inflation of author lists and that encourage the funding of research conducted by single investigators and small groups of researchers.

Understanding the temporal dynamics of present thermal and pH exposure on coral reefs is crucial for elucidating reef response to future global change. Diel ranges in temperature and carbonate chemistry parameters coupled with seasonal changes in the mean conditions define periods during the year when a reef habitat is exposed to anomalous thermal and/or pH exposure. Anomalous conditions are defined as values that exceed an empirically estimated threshold for each variable. We present a 200-day time series from June through December 2010 of carbonate chemistry and environmental parameters measured on the Heron Island reef flat. These data reveal that aragonite saturation state, pH, and pCO(2) were primarily modulated by biologically-driven changes in dissolved organic carbon (DIC) and total alkalinity (TA), rather than salinity and temperature. The largest diel temperature ranges occurred in austral spring, in October (1.5 - 6.6 degrees C) and lowest diel ranges (0.9 - 3.2 degrees C) were observed in July, at the peak of winter. We observed large diel total pH variability, with a maximum range of 7.7 - 8.5 total pH units, with minimum diel average pH values occurring during spring and maximum during fall. As with many other reefs, the nighttime pH minima on the reef flat were far lower than pH values predicted for the open ocean by 2100. DIC and TA both increased from June (end of Fall) to December (end of Spring). Using this high-resolution dataset, we developed exposure metrics of pH and temperature individually for intensity, duration, and severity of low pH and high temperature events, as well as a combined metric. Periods of anomalous temperature and pH exposure were asynchronous on the Heron Island reef flat, which underlines the importance of understanding the dynamics of co-occurrence of multiple stressors on coastal ecosystems.

In most climate models, after an abrupt increase in radiative forcing the climate feedback parameter magnitude decreases with time. We demonstrate how the evolution of the pattern of ocean heat uptake-moving from a more homogeneous toward a heterogeneous and high-latitude-enhanced pattern-influences not only regional but also global climate feedbacks. We force a slab ocean model with scaled patterns of ocean heat uptake derived from a coupled ocean-atmosphere general circulation model. Steady state results from the slab ocean approximate transient results from the dynamic ocean configuration. Our results indicate that cloud radiative effects play an important role in decreasing the magnitude of the climate feedback parameter. The ocean strongly affects atmospheric temperatures through both heat uptake and through influencing atmospheric feedbacks. This highlights the challenges associated with reliably predicting transient or equilibrated climate system states from shorter-term climate simulations and observed climate variability.

Earth's Future invited "leading experts in the field of geoengineering research to contribute brief reflections (2-5 pages) on the development of the discussion over the past decade and to consider where it may be going in the next 10 years." Responding to this request, we offer the following text in the spirit of reflections that emphasize our personal roles and viewpoints. The primary focus of many of our comments is solar geoengineering and not carbon dioxide removal (CDR). Thus, this text is not intended to comprise a comprehensive review or set of carefully documented analyses. Our primary conclusion is that sustained progress in "geoengineering" research will depend on social and material support for experimental work that can provide the observational basis for improved modeling and analysis, and, potentially, development and deployment of systems that may help protect the environment and improve human well-being. Relevant issues, and potential future trajectories, for CDR technologies may differ dramatically from those for solar geoengineering technologies.

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.