Can geoengeneering be optimised?
Lead Research Organisation:
University of Oxford
Abstract
Solar radiation management is a form of geoengineering that has been discussed as a potential counterbalance to warming induced by greenhouse gases.The method that seems most likely to provide a counteractive radiative forcing is sulphate aerosol injection, which mimics the natural process by which volcanoes have been observed to cool the climate. Yet grave uncertainties about the consequences of such an approach remain.Many scientists agree that modelling such scenarios could teach us much, both about the response of the climate system to forcings, but also about the possible pros and cons of such a technique. Areas of concern include the 'termination shock' of rapid warming that occurs if the sulphate aerosol injection is stopped, the inhomogeneous response of the climate system to the applied forcing, and the impact on the hydrological cycle.It seems that the least reckless scenario for deployment of such scheme - which is far inferior to mitigation and carbon dioxide removal - would be in combination with carbon dioxide removal, ensuring that the scheme was less prone to catastrophic failure.Previous studies such as the Geoengineering Model Intercomparison Project (GEOMIP) have sought to demonstrate that sulfate injection could be used to return a high-CO2 world to closer to a preindustrial baseline in a variety of earth-system models.These experiments tend to be quite idealised - in some cases, the sulphate aerosol model is discarded in favour of a compensatory reduction of the solar constant - and the forcing is usually considered as homogenous, or else the climate response is considered to linearly scale with the amount of geoengineering applied. Although they can often provide broad climactic diagnostics, the impact on extreme weather is less clear.
Avenues of enquiry in the project include the following:
1) Can a spatially inhomogenous application of sulphate aerosols change the response of the climate system, and can a Green's function be found for the response of the climate system?
2) Would currently-proposed experiments - such as those of the GEOMIP project - have deleterious or positive impacts on extreme weather events in comparison to "doing nothing"? Of particular interest in this question is the Sahel, which is a drought-prone region that millions depend on for food production. The Mount Pinatubo eruption, often seen as an analogue for the sulphate strategy, caused a Sahelian drought.
3) What is the impact on the climate system of large-scale carbon dioxide removal in combination with some level of SRM?How likely are extreme weather events to occur, and how dependent are they on the rate of change of temperature?
The project would seek to answer these and similar questions using the large-ensemble setups of climateprediction.net - for the climate questions - and weather@home, for the link between geoengineering and extreme weather events.The advantage of this ensemble is that questions can be answered statistically;at the same time, attribution of extreme weather can occur.The HADCM3s model has 72 latitude bands for sulphate aerosol, corresponding to volcanic eruptions in each of those bands; it is therefore possible to use such an ensemble to obtain a Green's function of the climate response to this forcing.Large ensembles could also be used to investigate the impact of uncertainties in physics parameters on the effectiveness of this scheme, the potential risks of unintended consequences of such a scheme, and the impacts of different rates of carbon-dioxide removal on the scheme.Recent research has indicated that even if sea-surface temperatures are held constant, carbon dioxide concentration alone can have a negative impact on extreme heat. Regarding extreme weather, it seems logical to first test a benchmark scheme and see about its extreme-weather impacts, and then test an improved or optimised scheme to see if conditions are improved.The policy consequences of any such results can then be analysed
Avenues of enquiry in the project include the following:
1) Can a spatially inhomogenous application of sulphate aerosols change the response of the climate system, and can a Green's function be found for the response of the climate system?
2) Would currently-proposed experiments - such as those of the GEOMIP project - have deleterious or positive impacts on extreme weather events in comparison to "doing nothing"? Of particular interest in this question is the Sahel, which is a drought-prone region that millions depend on for food production. The Mount Pinatubo eruption, often seen as an analogue for the sulphate strategy, caused a Sahelian drought.
3) What is the impact on the climate system of large-scale carbon dioxide removal in combination with some level of SRM?How likely are extreme weather events to occur, and how dependent are they on the rate of change of temperature?
The project would seek to answer these and similar questions using the large-ensemble setups of climateprediction.net - for the climate questions - and weather@home, for the link between geoengineering and extreme weather events.The advantage of this ensemble is that questions can be answered statistically;at the same time, attribution of extreme weather can occur.The HADCM3s model has 72 latitude bands for sulphate aerosol, corresponding to volcanic eruptions in each of those bands; it is therefore possible to use such an ensemble to obtain a Green's function of the climate response to this forcing.Large ensembles could also be used to investigate the impact of uncertainties in physics parameters on the effectiveness of this scheme, the potential risks of unintended consequences of such a scheme, and the impacts of different rates of carbon-dioxide removal on the scheme.Recent research has indicated that even if sea-surface temperatures are held constant, carbon dioxide concentration alone can have a negative impact on extreme heat. Regarding extreme weather, it seems logical to first test a benchmark scheme and see about its extreme-weather impacts, and then test an improved or optimised scheme to see if conditions are improved.The policy consequences of any such results can then be analysed
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
NE/S007474/1 | 01/10/2019 | 30/09/2027 | |||
1936118 | Studentship | NE/S007474/1 | 01/10/2017 | 31/12/2022 | Thomas Hornigold |
NE/W502728/1 | 01/04/2021 | 31/03/2022 | |||
1936118 | Studentship | NE/W502728/1 | 01/10/2017 | 31/12/2022 | Thomas Hornigold |
Description | Research Policy Internship |
Geographic Reach | National |
Policy Influence Type | Participation in a guidance/advisory committee |
Title | Substantial climateprediction.net data |
Description | My research so far has involved substantial (~500,000 model years) running of the climate-prediction.net HadCM3 climate model. This data is stored on JASMIN but can be accessed by any of the users for the CPDN project, and for example the lowCO2 and 4xCO2 runs have been requested by several other members of the team. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | No |
Impact | While the use of this data is still ongoing, I anticipate that many of the runs that I've generated so far will be of use to the wider research community that uses CPDN. |
Description | Machine Learning and Climate Change collaboration |
Organisation | University of Oxford |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Ongoing collaboration between myself and another PhD student at Oxford to develop machine learning methods for understanding climate change + the impacts of geoengineering. I provide the expertise in the use of climate models, he provides the machine learning skills. |
Collaborator Contribution | Ongoing collaboration between myself and another PhD student at Oxford to develop machine learning methods for understanding climate change + the impacts of geoengineering. I provide the expertise in the use of climate models, he provides the machine learning skills. |
Impact | => Poster and presentation at ICML => Submission of project for Future Development Lab in which we will serve as joint PIs in the Summer => Ongoing negotiations for collaboration with ESA and/or NASA |
Start Year | 2019 |
Description | "Physical Attraction" physics podcast includes insights from research |
Form Of Engagement Activity | A broadcast e.g. TV/radio/film/podcast (other than news/press) |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Media (as a channel to the public) |
Results and Impact | Throughout my DPhil I have engaged with the public through publishing popular articles and hosting a podcast on physics - experiences from my research feed into my discussion of climate change, the use of machine learning to impact climate change, and energy use throughout. |
Year(s) Of Engagement Activity | 2018,2019,2020 |
Description | Oxford School of Climate Change - Geoengineering talks |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Undergraduate students |
Results and Impact | The Oxford School of Climate Change is a regular series of talks that is hosted within Oxford University. In December 2019 and March 2020, I delivered a two-hour lecture on "technical interventions for climate change", including discussing geoengineering, to audiences of approximately 50 individuals taken from across the University's undergraduate population - I was invited to do so because of my specific expertise in this area. |
Year(s) Of Engagement Activity | 2019,2020 |
Description | Regular articles for Singularity Hub on topics surrounding climate change and machine learning |
Form Of Engagement Activity | A magazine, newsletter or online publication |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Media (as a channel to the public) |
Results and Impact | Throughout my DPhil I have engaged with the public through publishing popular articles and hosting a podcast on physics - experiences from my research feed into my discussion of climate change, the use of machine learning to impact climate change, and energy use throughout. |
Year(s) Of Engagement Activity | 2018,2019,2020 |