Yeah

...

so you look at those impacts and you say, "Where were these impacts reported?" Right? So 'cause you're trying to triangulate, understand where these extreme re- event happened.

And in observation, you want to know what is the climatology? What is the normal rainfall in that city? So Abidjan, for example, or Lagos, for example, what is the normal rainfall that happens there? And then you want to understand, okay, if the normal rainfall, where we call climatological rainfall, is 50 millimeters, for example, I'm giving an example, but then during this event, what was different? So you know that this was a rare event.

You know, like, it's, it's beyond the normal, right? And then the next step you want to do is that you now want to use climate models sort of to simulate that event, right? So you want...

'Cause as essentially what we want to do is that we want to compare the weather of now or the event that happened now in this weather of 2026 versus the weather that would have happened in 1850s, right? 'Cause this is what we call the preindustrial climate or the counterfactual climate, which we consider as the climate before the onset of Industrial Revolution, and that is where we base our analysis on.

So you want to say to us-

Like holding emitters accountable.

Yeah.

And the response to that question is science is never 100%, and it's not just the weather science or the climate science.

It's in any other weather.

And I said even in medicine, in any oth- in, in all science, we just use probabilis- probabilities.

So, um, science cannot be 100%, and as I said, you're looking at different parameters and trying to put it together.

The- there are things that are very, there are uncertainties that are very inherent to any field of science.

And let me just come back to my field of science, which is weather prediction or climate, um, climate science.

But we used to have, watching news, weather used to be the last item on the news.

But I think, Joyce, if you'd like to, as our guest, you're very welcome to volunteer your views and opinions first, and then we'll get into it.

Yeah.

I, I have opinions too.

[laughs]So I have been part of this process, uh, myself as well, and I think I introduced myself by saying that, uh, on top of being a scientist at, at Imperial College London, I do this also, this other sort of technical advice to, um, policy processes in, back in my country.

And I happen to be... to work with people in this sort of the space of the COP or the loss and damage.

And also, I have been speaking with lawyers, or some lawyers have wanted to speak with me, and I didn't say no.

I said, "Okay, we can chat," about how they can use attribution science to support some of the cases that they're trying to build or to pursue.

What was your motivation for moving into the world of, of weather and climate science? Was it something that you were always interested in, or did it happen by accident? This is a question I usually ask people, and I'm always interested in the, in the story.

Mm-hmm.

Than, th- than, like, 10 years ago, for example.

Journalists are quite interested to, like, want to speak to us.

So, and, um, what we do at WWA, of course, has really contributed to that because when you, when we do extreme events in, in Africa, we have this, uh, press briefing with journalists.

And you'll find that s- journalists from, from, from the region would reach out to me later to say, "Hey, Joyce, can you break down some of the, the stuff that, uh, uh, were discussed in the, in the, in the press briefing? Or from, from those studies, what does that mean for the continent?" Even when you don't do a study, they just ask me all general stuff about climate change, about weather, how could, uh, you know, like, general stuff.

And of course I'm involved in not just the, um, the, uh, science of attribution, but I engage with stakeholders a lot as well.

So there's a lot of policy science work that I do, uh, in the continent and in Kenya, so I get a lot of, uh, questions, and so that has really improved, um, sort of, um, mainstreaming of climate information.

Mm-hmm.