In January, global SRM research reached an important milestone: the publication of the world’s first African research paper on solar geoengineering. The paper’s lead author was Mozambican climatologist Dr Izidine Pinto, working with colleagues at the University of Cape Town and the American National Center for Atmospheric Research (NCAR). It was also the first publication to come from the DECIMALS Fund, the developing country research fund set up by SRMGI (The Degrees Initiative) in 2018. It’s a considerable achievement for Izidine, not least because he failed physics and chemistry in high school. Growing up in Quelimane, Mozambique, he came through the poorly funded public education system, where there were more than 60 pupils in his science classes. He found physics fascinating and kept persevering, however, taking opportunities as they came to him. He pursued a postgraduate degree (Licenciatura) in meteorology at Eduardo Mondlane University in Maputo, before earning a bursary to study for a master’s degree in Atmospheric Science at the University of Cape Town, South Africa. The master’s was followed by a PhD, then a postdoctoral position in the Climate Systems Analysis Group (CSAG) and now he is also a lead author on Working Group I of the 6th Assessment Report of the Intergovernmental Panel on Climate Change (IPCC).
Izidine first learned about SRM following the DECIMALS call for proposal in 2018. He has been working to model its impacts as part of the South African project led by Principal Investigator Dr Romaric Odoulami and co-PI Dr Chris Lennard. Their recent paper, published in the Journal of Geophysical Research, explores how SRM might affect extremes of temperatures and rainfall around Africa. We spoke to Izidine about his research while he was locked down in Maputo after coronavirus hit while he was back home visiting family.
What motivated you to work on climate change?
I was fascinated by physics but I didn’t want to study something theoretical—I wanted to study something that I could apply, and so I chose meteorology. That led into the study of climate change.
What is the greatest climate threat faced by Mozambique?
There is no main threat—we have all of them! Because of its geographical location next to the Indian ocean, we are exposed to frequent tropical cyclones. Idai was one of the most recent cyclones that caused a lot of damage in the central part of the country – hundreds of deaths and hundreds of millions of dollars of damage in Mozambique alone. We also have rivers coming from inland countries so when there is heavy rainfall upstream there is high probability of flooding downstream. Then when there is a lack of rain in the region, the countries reduce the flow of water from the dams upstream causing agricultural droughts. There is also sea level rise affecting coastal cities. All these climate hazards are projected to continue in the future if mitigation strategies are not implemented.
What did you think of SRM when you first heard about it? And have your thoughts changed at all?
I thought it was a crazy idea, something from a James Bond movie! I still think it is a crazy idea, but it is very interesting. I don’t know how feasible it is yet, but it is very interesting from the curiosity point of view.
Can you tell us about the paper that has just been just published?
The title of the paper is “Africa’s Climate Response to Solar Radiation Management With Stratospheric Aerosol” and the goal is to understand how SRM could impact the climate over the region. There was a gap in knowledge there and an opportunity to contribute to the discourse of SRM in Africa.
What was the research focused on and how did you conduct it?
Mainly it focused on how SRM might affect temperature and rainfall—including extremes—across Africa. And it is based on climate modelling experiments. We used the Stratospheric Aerosol Geoengineering Large Ensemble (GLENS) dataset that was developed by a team at NCAR in Colorado. It models a world with a very high emissions pathway (RCP8.5) and simulates what would happen if sulphur dioxide were injected into the stratosphere at different latitudes in order to hold global temperature rises below 2C, even where high greenhouse gas emissions continued.
Firstly, we evaluated the models’ ability to simulate the climate over Africa. This is the done by comparing the model data with observations for the historical period of 1981-2009. The analysis showed that the model was skilful in reproducing the current climate and gave us some confidence in using the model for projections.
Then we compared the future projected changes for the 2051-2080 period with the historical period to see how a world with and without SRM would look like in the future—in this case with and without mitigation strategies.
What were your findings?
What we found is that, at least in our modelled scenario, SRM worked to reduce temperatures across the whole African continent. But the picture with rainfall was more mixed.
A figure from our paper shows some of the effects on temperatures variables. Plot (a) shows mean temperature changes, relative to today, under a high emissions scenario. Plot (b) shows the change in the maximum daily temperature, and Plot (c) shows the change in the lowest minimum temperature. Unsurprisingly, everywhere in African is hotter under global warming. Plots (d), (e), and (f) show how using SRM to hold global temperatures steady at 2C, despite increasing emissions, would affect these variables around Africa. We found that SRM effectively reduced mean and extreme temperatures.
The response for rainfall was not so homogeneous, however, because the physical mechanisms from aerosol-based cooling that affect temperatures and rainfall are different. There are many ways to measure changes to rainfall impacts. Different indices will matter to different people, countries, plants, animals, and crops, and so we analysed:
Total precipitation on wet days (PRCPTOT)
- Maximum consecutive 5‐day precipitation (RX5day)
- Simple daily intensity (SDII)
- Days with heavy precipitation (R10mm)
- Consecutive dry days (CDD)
The figure below shows our findings. Plots (a) to (e) show rainfall changes in a world of global warming. Plots (f) to (j) show rainfall changes in a world of global warming that has been cooled by SRM. Plots (k) to (o) show a comparison between the warmed world and the SRM world – showing where SRM was found to be effective at reducing rainfall disruption, and where it was found to be counter-effective, increasing disruption relative to a warmed world.
We found that the response of rainfall is very different depending on the region. In some areas SRM is not effective in keeping rainfall at its historical levels and in some other areas it is effective. If you look at boxes (a), (f) and (k), for instance, you see the effects on total rainfall on wet days. Under global warming (plot a), much of Africa is expected to get much wetter. Where SRM is used to stop global warming, generally there are less extreme changes (plot f). And plot (k) shows that in our scenario SRM is effective at reducing rainfall disruption across large parts of Africa, but not all. There are some regions in where SRM is not effective, for instance it doesn’t do much to change the impacts of global warming. And in some areas of West Africa SRM looks counter-effective, in that changes to rainfall were larger with SRM than changes without it. Similar patterns are seen for other rainfall indices.
So our modelling found that SRM works for reducing the temperature, but one cannot generalize what SRM does for rainfall—we need to look at the region’s specifics.
What research project would you like to do next?
One of the findings in this study is that rainfall changes are not as homogenous as changes in temperature. Next I would like to understand why rainfall is changing in this way as a response to SRM over Africa—to look at the physical processes and circulation patterns to have more confidence in the results. It would also be useful to see how different emission and SRM scenarios affect the results we found in different regions.
Interview by Andy Parker