By David Keith | March 11, 2019

This post provides some color commentary as an FAQ about “Halving warming with idealized solar geoengineering moderates key climate hazards”, published 11 March 2019 in Nature Climate Change. Feel free to send me questions and I may add to the FAQ. See also Harvard press release and video.

This feels like the most important solar geoengineering (SG) study I have been lucky to be a part of. From my perspective, it’s more important and should get more attention than progress on our stratospheric experiment.

We use a high-resolution state-of-the-art model to go after a central policy-relevant question: what regions would be made worse off if solar geoengineering was combined with emissions cuts to limit climate risks? We find that no region is made worse off in any of the major climate impact indicators we examined. (It’s easy to cherry pick regions to make SG look great or terrible—we used standard regions from the IPCC SREX report.)

My hope is that the paper will dispel some of the common-but-false assumptions that solar geoengineering necessarily entails massive risks, that its impacts are highly unequal, and that it works for temperature but messes up precipitation. And I hope it demonstrates that further research needs to be done.

How does this matter for climate policy? 

There is strong evidence from multiple climate models that if solar geoengineering were implemented with reasonably uniform global coverage (e.g. uniform aerosols in the stratosphere) and if it’s used in combination with strong emissions cuts—as a complement, not a substitute—then it may offer major reductions in the climate risks that matter most to humans and ecosystems without making any region significantly worse off.

The possibility that solar geoengineering could enable deep reductions in climate risks is a strong argument for a serious global, open access research program aimed at better understanding the risks and efficacy of solar geoengineering. For more on what such a program might look like, here is my case for a responsible research program in the NAS Issues in Science & Technology, as well as an important paper from Douglas MacMartin and Ben Kravitz in PNAS.

Does this mean people who worry about the risks of solar geoengineering are wrong? Does this argue for deployment? 

Not at all. I have worried about this technology’s risks since the early 90’s. At this point research is still dominated by a small group of scientists. This means real danger of groupthink. We may simply be wrong.

What this paper illustrates is that it’s too early to leap to conclusions in either direction. This is true both for those who are convinced solar geoengineering will work, and for those who are convinced that solar geoengineering will cause droughts, or will harm the poor while benefiting the rich.

This paper, along with many previous by many authors, shows that solar geoengineering could have large and equally distributed benefits, but it doesn’t prove it. It is an idealized model. There are still huge uncertainties.

It’s clear that if misused, e.g., by deployment in only one hemisphere, solar geoengineering could have huge impacts. We need technically sophisticated efforts to quantify risks of plausible deployment of uniform and solar geoengineering that is used as a moderate supplement too emissions cuts. Until that work is done it’s too early to leap to conclusions.

Who’s behind this paper? Why does it matter? 

This paper started from a discussion with Gabe Vecchi (now Princeton, then GFDL) following a talk I gave at Princeton in 2016. Gabe decided to study solar geoengineering using GFDL’s new 25-km-resolution tropical cyclone permitting model. This is important because this model does a substantially better job simulating current precipitation extremes than typical models that have been used before on solar geoengineering. It’s also important because it is the first time that GFDL, the oldest and one of the best climate modeling centers, got involved in solar geoengineering research.

Gabe brought in Larry Horowitz (GFDL), one of the model’s developers, and Jie He (now at Georgia Tech). I meanwhile encouraged Peter Irvine, a postdoctoral fellow in my group, to take the lead in analyzing the data and writing the paper.

Gabe was collaborating with hurricane expert Kerry Emanuel (MIT), and as we began to look carefully at the hurricane responses, Gabe did not have confidence in the ocean-basin-by-basin regional response, so we invited Kerry to join the paper.

This new collaboration is relevant because solar geoengineering publications have been too dominated by a small group, and this brings significant new collaborators with deep climate science expertise to this important topic.

What about precipitation?  

This paper highlights a common misunderstanding about solar geoengineering: that a world with solar geoengineering would inevitably have less water availability. If all warming from rising CO2 was offset by solar geoengineering, there would be less rain overall than in the current climate. This has led to concerns about droughts and monsoons. However, global warming increases rainfall so something which reverses this could reduce flood risk. When solar geoengineering is used with emissions cuts to halve warming, global-mean rainfall is more-or-less restored to its original levels. Moreover, while it seems reasonable to assume that less rain means that things are drier, in fact what matters more for ecosystems and farmers is water availability: rainfall minus evaporation. Solar geoengineering reduces rainfall, but it also reduces evaporation by reducing temperatures. So, a decrease in rainfall may be associated with an increase in water availability.

One of the ways this paper takes a step beyond current literature is by focusing on a larger set of variables that (we think) are more relevant to assessing real world climate impacts. Rather than just looking at temperature and precipitation, we looked at: annual average temperature, extreme temperature, extreme precipitation, precipitation minus evaporation as a proxy for water availability, and intensity of tropical cyclones. Note: while we do not highlight them in the paper, we also find that the simulation moderates changes in precipitation. More on this and some data on the seasonal response can be found in the supporting material.

Why did the paper adjust the solar constant rather than attempting a realistic simulation of stratospheric aerosols? 

Here’s the crucial paragraph in the paper:

We analyse the distribution of climate changes resulting from reducing the solar constant to offset roughly half the radiative forcing from doubling CO₂. A spatially uniform reflective stratospheric aerosol layer, which could be achieved by adjusting aerosol injection using feedback, would produce a similar radiative forcing to a solar constant reduction. Even with a uniform distribution, stratospheric sulphate solar geoengineering will differ from a solar constant reduction in that sulphates heat the lower stratosphere, perturb the ozone layer, and increase the ratio of diffuse to direct light. Each of these effects can be reduced by choices of alternate non-sulphate aerosol, though their side-effects are less well understood because there is no direct natural analogue. We nevertheless choose solar constant reduction as a benchmark because, given the diverse implementations of aerosols in models, solar modification allows more direct tests of inter-model differences in climate response to solar geoengineering.

Let me nerd out: In separate work, the group at NCAR, our group, and others have done work that suggests it is possible to adjust the injection of aerosols to achieve roughly uniform radiative forcing. No group has yet simulated this in a way that reasonably approximates the way that feedback from limb-sounds in situ measurements would be used in a stratospheric analysis/forecast system to adjust injection to achieve a specified optical depth profile. Moreover, no existing model can do a good job of simulating this because models with Eulerian grid boxes instantaneously mix aerosol or precursor emissions into the grid box, whereas material would form a linear plume after being dispersed from an aircraft. Local concentrations in the plume will be far higher than simulated in a Eulerian model. This will produce different SO oxidation rates and different rates of particle formation. Several research groups are now beginning to work together to address these problem.

Stepping back from technical complexity, this paper suggests what might be possible with a well-designed aerosol injection method. It also underscores one of the many reasons why research is needed—to better understand what such a method might look like, and what its risks and limitations might be.

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