| Literature DB >> 25404684 |
David W Keith1, Riley Duren2, Douglas G MacMartin3.
Abstract
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.Entities:
Keywords: experiment; solar geoengineering; solar radiation management
Year: 2014 PMID: 25404684 PMCID: PMC4240958 DOI: 10.1098/rsta.2014.0175
Source DB: PubMed Journal: Philos Trans A Math Phys Eng Sci ISSN: 1364-503X Impact factor: 4.226
Experiment types. Laboratory testing is included for context; however, the workshop and this analysis were focused primarily on field experiments.
| classification | goal | examples |
|---|---|---|
| laboratory | understanding efficacy and risks for processes or scales that are well represented by laboratory experiments or models | indoor experiments using climate models, small-scale engineering tests of deployment hardware, laboratory measurement of relevant quantities (e.g. chlorine activation chemistry) |
| technology development | test hardware and operations needed for deployment | outdoor tests of enabling technologies (e.g. sea spray hardware, hydrosol dispersal or aircraft platforms) |
| process studies | predictive understanding of the small-scale evolution of physical, chemical and radiative properties in the atmosphere | Controlled release experiments in the atmosphere to understand aerosol/cloud microphysics, chemistry, microscale dynamics, etc. (e.g. aerosol dynamics and O3 response to small sulfur release in stratosphere). Passive studies of cirrus clouds and observations of volcanic eruptions, ship tracks or other analogues |
| scaling tests | bridge gaps across multiple process scales to validate end-to-end model representation | atmospheric experiments to evaluate models across a range of scales including gaps between model domains (e.g. marine cloud brightening test spanning microphysics, large eddy simulation and mesoscale models) |
| climate response tests | incremental evaluation of climate response to radiative forcing to assess risk and efficacy | slow ramp up over a few decades as sulfur burden in troposphere is reduced; or modulate global radiative forcing over a shorter period |
Figure 1.Mapping of experiment types and classes of models (red lines) to physical scales illustrates the breadth and complexity of solar geoengineering research. No single model or experiment can bridge the gap from smallest to largest scale. For example, microphysical models describe aerosol processes at scales of nanometres and cloud drops and ice crystals at micrometre to millimetre scale. Clouds (ranging from 10 to 1000 m) are addressed by large eddy simulation models and more generally by cloud resolving models. Mesoscale models and general circulation models (GCMs) have similar physics, but mesoscale models can be nested to provide high-resolution simulations that cannot be matched by GCMs. Chemistry can be built into dynamic models (typically mesoscale models and GCMs) or simulated in off-line chemical-transport models. The different types of field experiments, particularly process studies, scaling tests and climate response tests could bridge gaps between scales reducing the uncertainty of large-scale predictions of the risks and efficacy of SRM.
Figure 2.Schematic concept of a geoengineering research programme illustrating the phasing and interrelationship of various types of investigation defined in table 1. Incremental improvements in knowledge are linked to incremental increases in scale and risk. A decision to proceed from one stage to another should depend both on technical factors internal to the programme as well as on external factors such as the development of legitimate governance and evolving knowledge of the climate risks. The definition of ‘works’ and ‘fails’ is—of course—ambiguous and contingent. The distinction between field research and gradual deployment with monitoring represents a step-change in scale, risk and objectives, and should be made at a political level that transcends research management. Finally, even if the technology ‘works’ there may be good reasons to forgo deployment.
Workshop attendees.
| name | institution |
|---|---|
| Tom Ackerman | University of Washington |
| Jim Anderson | Harvard University |
| Neil Donahue | Carnegie Mellon University |
| Riley Duren | Jet Propulsion Laboratory |
| John Dykema | Harvard University |
| Sebastian Eastham | MIT |
| Steve Hamburg | Environmental Defense Fund |
| Josh Horton | Harvard University |
| David Keith | Harvard University |
| Frank Keutscha | University of Wisconsin |
| Mark Lawrencea | IASS/Potsdam |
| Thomas Leisnera | KIT/Karlsruhe |
| Jane Long | Bipartisan Policy Center |
| Doug MacMartin | Caltech |
| David Mitchella | Desert Research Institute |
| Granger Morgan | Carnegie Mellon University |
| Armand Neukermans | unaffiliated |
| Andrew Parker | Harvard University |
| Phil Rasch | Pacific Northwest National Laboratory |
| Lynn Russella | Scripps |
| Stefan Schafer | IASS/Potsdam |
| Dan Schrag | Harvard University |
| Armin Sorooshian | University of Arizona |
| Graeme Stephens | Jet Propulsion Laboratory |
| Trude Storelvmo | Yale University |
| Matt Watson | University of Bristol |
| Debra Weinstein | Harvard University |
aAttended only by phone or video.
Summary of field test experiment concepts explored in this study. For each experiment, we provide (if known) the local peak radiative forcing (ΔRF), area of the experiment domain (A), individual test duration (T), number of tests in an experiment (N), equivalent energy (E=pΔRF×A×T×N), the primary composition and mass of materials injected into the atmosphere, and the type of experiment. TBD, to be determined. Experiment costs are very uncertain. In each case, experiment duration is limited to the active period of injection (in some but not all cases, continuous) and does not indicate months of preparatory efforts or data analysis. ΔRF represents the maximum quasi-instantaneous change in radiative forcing over the domain indicated in response to a given experiment (assuming the experiment is operating at ‘steady state’); it does not account for natural variability or start-up.
| exp. no. | informal title | category type(s) | cost ($M) | local forcing, area, duration and equivalent energy | material and mass | synopsis |
|---|---|---|---|---|---|---|
| 1 | SCoPEx | process study | 10 | ΔRF=0.01–0.1 Wm−2 | 103 g of S and less than 105 g of H2O | stratospheric propelled balloon to test chemistry response to H2SO4 and H2O and to test aerosol microphysical models |
| 2 | cirrus cloud seeding | process study | 0.5 | ΔRF=1–10 Wm−2 | 3×10 g of BiI3 | ice nucleation seeding from aircraft in upper troposphere to test cirrus dispersal mechanisms |
| 3 | MCB phases 1–2 | technology development, process study | 1 | ΔRF=0.1–5 Wm−2 | sea salt | (i) boundary layer injection of sea salt from coastal site to test sprayer technology; (ii) coastal test of cloud brightening |
| 4 | MCB phase 3 | process study, scaling test | 2 | ΔRF=5–50 Wm−2 | sea salt | ocean test of MCB (sea salt injection into boundary layer from single ship—e.g. single enhanced ship track) |
| 5 | MSGX | scaling test, technology development | 100 | ΔRF=0.2 Wm−2 | 5×108 g of S | sustained stratospheric injection of H2SO4 from aircraft, observe mesoscale effects from satellites and aircraft |
| 6 | climate response test | climate response test | >1000 | ΔRF=0.5 Wm−2 | 1×1012 g of S per year | test global climate response to large-scale modulated input (either stratospheric sulfate or MCB) |
| 7 | MOCX | scaling test, technology development | 10 | ΔRF=50–100 Wm−2 | sea salt | large-scale test of MCB in open ocean with multiple, coordinated ships |
| 8 | SPICE-2 | technology development | 0.5 | ΔRF=none | 103 g of H2O | test 1 km scale balloon injection approach |
| 9 | volcanogenic particles | process study | 2 | ΔRF=none | small amounts of H2S, SO2, | observe physical/chemical fate of candidate particles from (i) volcano and (ii) aircraft injection (S-bearing species and SiO2) |
Figure 3.Comparison of the climate forcing of field experiments. Area and local radiative forcing (ΔRF) are plotted as red bars on the axes of a log–log plot, where the bars indicate the range of possible ΔRF from table 3. Duration is indicated by the size of the grey circles as show in the key (the area of the circles is proportional to the square root of the duration). A useful measure of the total climate forcing is the product area×duration×ΔRF which has units of energy; this value is given under the experiment name (using average of the maximum and minimum ΔRF). The aggregate forcing energies span 11 orders of magnitude. Finally, note that the cirrus, MCB-3 and MCB-2 all have an area of 100 km2, but the x-axis values have been offset in the figure to show the three red range bars.