Climate econometric models indicate solar geoengineering would reduce inter-country income inequality.

Exploring heterogeneity in the economic impacts of solar geoengineering is a fundamental step towards understanding the risk tradeoff associated with a geoengineering option. To evaluate impacts of solar geoengineering and greenhouse gas-driven climate change on equal terms, we apply macroeconomic impact models that have been widely applied to climate change impacts assessment. Combining historical evidence with climate simulations of mean annual temperature and precipitation, we project socio-economic outcomes under high anthropogenic emissions for stylized climate scenarios in which global temperatures are stabilized or over-cooled by blocking solar radiation. We find impacts of climate changes on global GDP-per-capita by the end of the century are temperature-driven, highly dispersed, and model dependent. Across all model specifications, however, income inequality between countries is lower with solar geoengineering. Consistent reduction in inter-country inequality can inform discussions of the distribution of impacts of solar geoengineering, a topic of concern in geoengineering ethics and governance debates.

Mission-driven research for stratospheric aerosol geoengineering.

The last decade has seen broad exploratory research into stratospheric aerosol (SA) geoengineering, motivated by concern that reducing greenhouse gas emissions may be insufficient to avoid significant impacts from climate change. Based on this research, it is plausible that a limited deployment of SA geoengineering, provided it is used in addition to cutting emissions, could reduce many climate risks for most people. However, "plausible" is an insufficient basis on which to support future decisions. Developing the necessary knowledge requires a transition toward mission-driven research that has the explicit goal of supporting informed decisions. We highlight two important observations that follow from considering such a comprehensive, prioritized natural-science research effort. First, while field experiments may eventually be needed to reduce some of the uncertainties, we expect that the next phase of research will continue to be primarily model-based, with one outcome being to assess and prioritize which uncertainties need to be reduced (and, as a corollary, which field experiments can reduce those uncertainties). Second, we anticipate a clear separation in scale and character between small-scale experimental research to resolve specific process uncertainties and global-scale activities. We argue that the latter, even if the radiative forcing is negligible, should more appropriately be considered after a decision regarding whether and how to deploy SA geoengineering, rather than within the scope of "research" activities.

Solar geoengineering as part of an overall strategy for meeting the 1.5°C Paris target.

Solar geoengineering refers to deliberately reducing net radiative forcing by reflecting some sunlight back to space, in order to reduce anthropogenic climate changes; a possible such approach would be adding aerosols to the stratosphere. If future mitigation proves insufficient to limit the rise in global mean temperature to less than 1.5°C above preindustrial, it is plausible that some additional and limited deployment of solar geoengineering could reduce climate damages. That is, these approaches could eventually be considered as part of an overall strategy to manage the risks of climate change, combining emissions reduction, net-negative emissions technologies and solar geoengineering to meet climate goals. We first provide a physical-science review of current research, research trends and some of the key gaps in knowledge that would need to be addressed to support informed decisions. Next, since few climate model simulations have considered these limited-deployment scenarios, we synthesize prior results to assess the projected response if solar geoengineering were used to limit global mean temperature to 1.5°C above preindustrial in an overshoot scenario that would otherwise peak near 3°C. While there are some important differences, the resulting climate is closer in many respects to a climate where the 1.5°C target is achieved through mitigation alone than either is to the 3°C climate with no geoengineering. This holds for both regional temperature and precipitation changes; indeed, there are no regions where a majority of models project that this moderate level of geoengineering would produce a statistically significant shift in precipitation further away from preindustrial levels.This article is part of the theme issue 'The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels'.

Field experiments on solar geoengineering: report of a workshop exploring a representative research portfolio.

We summarize a portfolio of possible field experiments on solar radiation management (SRM) and related technologies. The portfolio is intended to support analysis of potential field research related to SRM including discussions about the overall merit and risk of such research as well as mechanisms for governing such research and assessments of observational needs. The proposals were generated with contributions from leading researchers at a workshop held in March 2014 at which the proposals were critically reviewed. The proposed research dealt with three major classes of SRM proposals: marine cloud brightening, stratospheric aerosols and cirrus cloud manipulation. The proposals are summarized here along with an analysis exploring variables such as space and time scale, risk and radiative forcing. Possible gaps, biases and cross-cutting considerations are discussed. Finally, suggestions for plausible next steps in the development of a systematic research programme are presented.

Solar geoengineering to limit the rate of temperature change.

Solar geoengineering has been suggested as a tool that might reduce damage from anthropogenic climate change. Analysis often assumes that geoengineering would be used to maintain a constant global mean temperature. Under this scenario, geoengineering would be required either indefinitely (on societal time scales) or until atmospheric CO2 concentrations were sufficiently reduced. Impacts of climate change, however, are related to the rate of change as well as its magnitude. We thus describe an alternative scenario in which solar geoengineering is used only to constrain the rate of change of global mean temperature; this leads to a finite deployment period for any emissions pathway that stabilizes global mean temperature. The length of deployment and amount of geoengineering required depends on the emissions pathway and allowable rate of change, e.g. in our simulations, reducing the maximum approximately 0.3°C per decade rate of change in an RCP 4.5 pathway to 0.1°C per decade would require geoengineering for 160 years; under RCP 6.0, the required time nearly doubles. We demonstrate that feedback control can limit rates of change in a climate model. Finally, we note that a decision to terminate use of solar geoengineering does not automatically imply rapid temperature increases: feedback could be used to limit rates of change in a gradual phase-out.

Using transfer functions to quantify El Niño Southern Oscillation dynamics in data and models.

Transfer function tools commonly used in engineering control analysis can be used to better understand the dynamics of El Niño Southern Oscillation (ENSO), compare data with models and identify systematic model errors. The transfer function describes the frequency-dependent input-output relationship between any pair of causally related variables, and can be estimated from time series. This can be used first to assess whether the underlying relationship is or is not frequency dependent, and if so, to diagnose the underlying differential equations that relate the variables, and hence describe the dynamics of individual subsystem processes relevant to ENSO. Estimating process parameters allows the identification of compensating model errors that may lead to a seemingly realistic simulation in spite of incorrect model physics. This tool is applied here to the TAO array ocean data, the GFDL-CM2.1 and CCSM4 general circulation models, and to the Cane-Zebiak ENSO model. The delayed oscillator description is used to motivate a few relevant processes involved in the dynamics, although any other ENSO mechanism could be used instead. We identify several differences in the processes between the models and data that may be useful for model improvement. The transfer function methodology is also useful in understanding the dynamics and evaluating models of other climate processes.

Control and alignment of segmented-mirror telescopes: matrices, modes, and error propagation.

Starting from the successful Keck telescope design, we construct and analyze the control matrix for the active control system of the primary mirror of a generalized segmented-mirror telescope, with up to 1000 segments and including an alternative sensor geometry to the one used at Keck. In particular we examine the noise propagation of the matrix and its consequences for both seeing-limited and diffraction-limited observations. The associated problem of optical alignment of such a primary mirror is also analyzed in terms of the distinct but related matrices that govern this latter problem.

Measurement accuracy in control of segmented-mirror telescopes.

Design concepts for future large optical telescopes have highly segmented primary mirrors, with the out-of-plane degrees of freedom actively controlled. We estimate the contribution to errors in controlling the primary mirror that results from sensor noise and, in particular, compare mechanical measurements of relative segment motion with optical wave-front information. Data from the Keck telescopes are used to obtain realistic estimates of the achievable noise due to mechanical sensors. On the basis of these estimates, mechanical sensors will be more accurate than wave-front information for any of the telescope design concepts currently under consideration, and therefore supplemental wave-front sensors are not required for real-time figure control. Furthermore, control system errors due to sensor noise will not significantly degrade either seeing-limited or diffraction-limited observations.

Local, hierarchic, and iterative reconstructors for adaptive optics.

Adaptive optics systems for future large optical telescopes may require thousands of sensors and actuators. Optimal reconstruction of phase errors using relative measurements requires feedback from every sensor to each actuator, resulting in computational scaling for n actuators of n2. The optimum local reconstructor is investigated, wherein each actuator command depends only on sensor information in a neighboring region. The resulting performance degradation "global" modes is quantified analytically, and two approaches are considered for recovering global performance. Combining local and global estimators in a two-layer hierarchic architecture yields computations scaling with n(4/3); extending this approach to multiple layers yields linear scaling. An alternative approach that maintains a local structure is to allow actuator commands to depend on both local sensors and prior local estimates. This iterative approach is equivalent to a temporal low-pass filter on global information and gives a scaling of n(3/2). The algorithms are simulated by using data from the Palomar Observatory adaptive optics system. The analysis is general enough to also be applicable to active optics or other systems with many sensors and actuators.