Addressing the “climate futures information gap”

Climate change poses risks to agriculture, water resources, human health, and beyond. Each of us will potentially need to adapt. Planning that adaptation requires anticipating changes in risk, and there is great demand for information about future climate.

There has been remarkable progress in climate modelling in recent decades. Climate models can be run to simulate future temperature, rainfall, and extreme weather. Meanwhile, a new area of research and practice has also emerged, known as “climate services”, designed to support decision-makers, where scientists and decision-makers work together to explore how planning can be made more resilient to climate change, often using data from climate models. Climate services has many challenges and requires input from many different areas of expertise.

One key challenge is in using climate model data to generate information about the real world. Scientists can analyse simulations to describe the climate of the 2050s in the modelled worlds, but it is impossible to know with certainty what will happen in the real world. This means that there is a necessary “step” in the analysis, to convert the model data into a description of what could happen in reality. There are multiple ways in which scientists and consultants do this. They might estimate a range of what is possible in the 2050s. They might estimate the most likely outcome for the 2050s. They then need to find a way to communicate this to decision-makers, and this is often done using graphs, maps, or statements.

This “step” in the analysis is vitally important because it will determine which future risks are incorporated into decisions. If it is not done well, adaptation planning may fail to take into account climate change risks, potentially leading to unexpected loss and damage from future climate change impacts. And this “step” is very hard to do well! There is no consensus on how to do it. Climate models are imperfect tools for exploring uncertainties, it is very difficult to assess confidence in their outputs and to communicate their results to non-specialists.

In some countries, such as the UK, large programmes have been funded which address this challenge. However, it remains understudied, particularly in the Global South, where the information is arguably most needed. This is the “climate futures information gap” and the focus for the SALIENT research programme, which is founded on two key areas of innovation:

  1. Reorienting climate science analysis to better characterise the influence of climate change on a regional scale. Climate science is often led by the model dataset being used. This programme of climate science will be driven by the need to better understand what is possible, plausible, and probable in future. It will involve analysis of many different kinds of climate datasets, and multiple new approaches to analyse uncertainty, including combining model-based estimates and expert judgements. 
  2. Drawing on insights and methods from communications research to improve information about climate futures. Psychologists and scientists in other fields, for example medical research, have gained insights in how to communicate risk, through methods which test and evaluate different messages and approaches. In collaboration with experts in risk communication, this research programme will design and test alternative communications outputs.

The programme will focus first on southern Africa, and regional level climate change information, useful for experts in the civil service and non-governmental organisations when prioritising adaptation action. We are seeking interested experts to participate in the research, to inform the analysis from the outset, and co-design communications outputs. 

Following the research in southern Africa, a framework will be developed and refined in other regions and contexts. The ambition is to deliver a new kind of “climate futures” science, which is urgently needed to support adaptation to a changing climate.

Back to the SALIENT project page.