How would climate-change science look if it was structured “as if people mattered”?

By Ted Shepherd

The scientific understanding of climate change is represented by the Assessment Reports of the Intergovernmental Panel on Climate Change (IPCC), most recently its Sixth Assessment Report. IPCC Working Groups II and III deal respectively with adaptation and mitigation, both of which explicitly relate to human action. Working Group I is different: its scope is the physical science basis of climate change.

Physical science is generally seen as concerning objective properties of the real world, where scientists should act as dispassionate observers. This paradigm is known as the ‘value-free ideal’, and has long underpinned Western science. Although individual scientists have human weaknesses, the argument is that the wider institutional arrangements of science counteract these effects. However, the value-free ideal has been criticized by philosophers of science because unconscious biases can be embedded in what might appear to be objective scientific practices. It is important to emphasize that this critique does not undermine science, which is still grounded in the real world; indeed, identification of such issues only serves to strengthen science. The same is true of climate-change science, as has been acknowledged by IPCC Working Group I (Pulkkinen et al. 2022).

This raises the question of whether climate-change science — where for brevity the term is used here in the restrictive sense of physical climate science, represented by IPCC Working Group I — might usefully adopt a more human face. Such a prospect makes some physical climate scientists nervous, because it seems to open the door to subjectivity. But if some degree of subjectivity is unavoidable —  and note that IPCC Working Group I is entirely comfortable with the concept of ‘expert judgement’, which is intrinsically subjective —  then perhaps it is better for the subjectivity to be explicit rather than swept under the carpet and invisible.

Contrast between the ‘‘top-down’’ approach in climate-change science, which is needed for mitigation action, and the ‘‘bottom-up’’ approach needed for adaptation action. From Rodrigues and Shepherd (2022).

Figure 1: Contrast between the ‘‘top-down’’ approach in climate-change science, which is needed for mitigation action, and the ‘‘bottom-up’’ approach needed for adaptation action. From Rodrigues and Shepherd (2022).

The questions asked of climate-change science for the purposes of adaptation and mitigation are quite different (Figure 1). For mitigation, the science informs the United Nations Framework Convention on Climate Change, and the questions mainly revolve around the anthropogenic greenhouse gas emissions that are compatible with global warming levels such as 1.5C or 2C. This “top-down” perspective aligns with the international policy context which requires single (rather than multiple) expert judgements on quantities such as climate sensitivity and carbon feedbacks. For adaptation, in contrast, climate-change science informs locally coordinated action, where multiple voices need to be heard, societal values necessarily enter in, and a more plural, “bottom-up” perspective is arguably more appropriate.

Nearly 50 years ago, the economist E.F. Schumacher published his celebrated book, Small is Beautiful. Schumacher asked how economics might look if it was structured “as if people mattered”, i.e. from a people-first perspective. There might not seem to be much in common between physical climate science and economics, but economics also strives to be an ‘objective’ science. With oceanographer Regina Rodrigues at the University of Santa Catarina in Brazil, we asked Schumacher’s question of climate-change science for adaptation, and found many interesting parallels (Rodrigues and Shepherd 2022).

Causal network for the 2013/14 eastern South America drought. The purple shading indicates elements whose causality lies in the weather and climate domain, the blue shading indicates the hazards, the gray shading exposure and vulnerability, and the green shading the impacts. From Rodrigues and Shepherd (2022).

Figure 2: Causal network for the 2013/14 eastern South America drought. The purple shading indicates elements whose causality lies in the weather and climate domain, the blue shading indicates the hazards, the gray shading exposure and vulnerability, and the green shading the impacts. From Rodrigues and Shepherd (2022).

The first is the need to grapple with the complexity of local situations. The nature of the challenge is exemplified in a case study of the 2013/14 eastern South America drought, which affected the food-water-energy nexus (Figure 2). The proximate cause of the drought was a persistent blocking anticyclone. The understanding of how this feature of the local atmospheric circulation will respond to climate change is very poor. Yet it crucially mediates compound events such as this one. We argue, with Schumacher, that the way to respect the complexity of the local risk landscape whilst acknowledging the deep (i.e. unquantifiable) uncertainty in the climate response is to express the climate knowledge in a conditional form, as in the causal network shown in Figure 2.

The second parallel is the importance of simplicity when dealing with deep uncertainty. Schumacher argued for the centrality of ideas over conveying a false sense of precision from overly sophisticated methods. We argue that the way to do this is through physical climate storylines, which are self-consistent articulations of “what if” hypotheticals expressed in terms of a set of causal elements (e.g. how the influence of remote teleconnections on local circulation could change). In particular, several storylines spanning a range of plausible outcomes (including extreme events) can be used to represent climate risk in a discrete manner, retaining the correlated aspects needed to address compound risk.

The third parallel is the need to empower local communities to make sense of their own situation. We argue that this can be addressed by developing what Schumacher called ‘‘intermediate technologies’’ which can be locally developed. In Schumacher’s case he was referring to physical equipment, but in our case we mean analysis of climate data. Causal networks and storylines represent such “intermediate technologies”, since they privilege local knowledge and involve comparatively simple data-science tools (see Kretschmer et al. 2021).

Regina and I aim to put this vision into practice over the coming years through our co-leadership of the World Climate Research Programme (see Rowan Sutton’s blog) Lighthouse Activity ‘My Climate Risk’ (https://www.wcrp-climate.org/my-climate-risk).

References:

Kretschmer, M., S.V. Adams, A. Arribas, R. Prudden, N. Robinson, E. Saggioro and T.G. Shepherd, 2021: Quantifying causal pathways of teleconnections. Bull. Amer. Meteor. Soc., 102, E2247–E2263, https://doi.org/10.1175/BAMS-D-20-0117.1

Pulkkinen, K., S. Undorf, F. Bender, P. Wikman-Svahn, F. Doblas-Reyes, C. Flynn, G.C. Hegerl, A. Jönsson, G.-K. Leung, J. Roussos, T.G. Shepherd and E. Thompson, 2022: The value of values in climate science. Nature Clim. Change, 12, 4–6,  https://doi.org/10.1038/s41558-021-01238-9

Rodrigues, R.R. and T.G. Shepherd, 2022: Small is Beautiful: Climate-change science as if people mattered. PNAS Nexus, 1, pgac009, https://doi.org/10.1093/pnasnexus/pgac009

 

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