ACCCA Experiences; Content of the communication: risk
We now need to give some thought to the content of the messages about climate risks that we wish to communicate. This is where we face the challenge of conveying meaning between people with different knowledge domains and attitudes, based on their type and level of education, area of work, cultural references, belief systems, etc. For that reason contextualising information is critical! Here we initially focus on developing messages out of scientific information, but ultimately it would be useful to add sections on articulating messages regarding local perceptions of vulnerability, experiences of climate impacts and existing activities being undertaken to address these. NGOs like ActionAid, Red Cross and Oxfam already have notable experience in this area.
There are multiple languages of risk and this makes fertile ground for miscommunication. A number of risk-related terms are used in every-day language (e.g. risky, probable, unlikely, rare) but meanings given to these tend to vary between people and change over time (Thomson et al, 2005). Professionals in fields such as disaster management, financial management and healthcare use statements about risk extensively when talking to donors, clients, patients, etc. and while there are commonalities between them, meanings are not always consistent and risk statements are presented in a number of different ways.
As noted in an earlier section, in the context of environmental change, risk has been conceptualised as a condition of both the nature and occurrence of a hazard (whether periodic events or persistent conditions) and the exposure and sensitivity (i.e. vulnerability) of the people / entity in question (sometimes referred to as the exposure unit). Based on this we understand risk to:
- change over time (levels of existing risks may become higher or lower, some risks may cease to exist while new risks may emerge, thereby changing the prevailing complex of risks)
- vary across space (biophysical / environmental factors)
- differ between groups of people (social factors including economic, political and cultural)
This means that risk information to be communicated can relate to the existence, nature, form, likelihood, probability, severity, acceptability, or other aspects of risk. It may include exchanges around possible and appropriate courses of action to address these risks i.e. coping and adaptation measures to tackle climate change risks, which determine how the risks evolve over time.
In terms of formal analyses of risk, it is useful to distinguish between current risk, based on historical data, and future risk, derived from model-based projections and scenario-building processes. We can usually make some fairly comprehensive statements about current risk (or baseline risk), using empirical data to analyse both the nature and occurrence of the hazard and the current vulnerability of the people (or ecosystems, infrastructure) exposed. What is far more difficult is establishing the basis for making statements about future risks, and then formulating how to communicate those with all the necessary caveats and uncertainties, not to mention understanding and exploring with others the processes by which we move from the current state of risk to some future state. But equally, this is where things get particularly interesting for the field of risk communication, because it is exactly this evolution of risk that we seek to influence. By communicating on issues of risk we lay the foundation for making better informed decisions on the course of action that in turn shapes the future state of risk. In other words, risk communication (or the lack thereof) is central to determining what risk pathways are realised and how we navigate these pathways (toward more inequitable risk distributions and crises or more sustainable / resilient states, etc.). This points to two critical elements in analysing and thereby communicating risks, those of time frames and uncertainty, which we discuss further below.
Messages concerning risk can be in a quantitative or qualitative format. Here is an example of a statement regarding the hazard part of future climate risk, which is in a purely qualitative form, taken from the recently released UK Climate Projections (UKCP09) findings: It is likely that, of the total amount of precipitation (rain, hail, snow, etc.) that falls annually over London, more of it will fall in the winter, with drier summers. What we may or may not know, is that this statement is comparing historical rainfall characteristics over London with those projected for 2070 to 2099; and that the statement is general in the sense that we have to assume it holds true for a range of different emissions scenarios i.e. these changes are likely (to varying degrees) whether there are large, moderate or small reductions made in global emissions going forward. But we don’t get told what the historical distribution of annual rainfall is and by how much this will change. We know vaguely what ‘likely’ means, but what it actually means in this context is having a greater than 66% probability of occurring. This of course (although maybe not obvious to everyone) is related to a whole lot of uncertainties, like we don’t know exactly what the levels of the emissions will be between now and then, we have an imprecise knowledge of the current state of the climate system, and we can’t (yet) tell just how good different models are at simulating the future. So there is a lot of other information not contained in the original statement that we ideally need to know to make sense of what the statement actually means, but much of it is very technical and in many cases all people will get, or want, or have the time and capacity for, is the original statement.
Let’s now look at an example of a slightly more quantitative version that conveys a bit more detail regarding the same message (UKCP09):
- Under medium emissions, the central estimate of change in winter mean precipitation is 20%; it is very unlikely to be less than 3% and is very unlikely to be more than 46%.
- Under medium emissions, the central estimate of change in summer mean precipitation is –22%; it is very unlikely to be less than –46% and is very unlikely to be more than 7%.
These two statements give us more specific information about the likelihood of different amounts of change (still without knowing what the baseline is) regarding London’s precipitation. We are told that these figures are based on inputting the ‘medium’ GHG emissions scenario into the model(s) (from that we understand there has been a reduction in global emissions but not massively so) and that on average the outputs suggest a increase of 20% in winter mean precipitation and a drop of 22% in summer mean precipitation, comparing historical data with projections for 2070-2099. We then get given a range to indicate that we can’t be certain of these exact figures but we can be fairly confident that it won’t be more or less that the upper and lower bounds they provide.
This example shows just some of the difficulties associated with distilling from the science, climate risk messages that can effectively be communicated with x or y participants (particularly if they are not scientists). But as mentioned in the process section, who the X or Y are is critical to deciding what quantity and kind of risk information should be communicated. This relates to the technical know-how of the participants (the ability to interpret and apply the information one is receiving), the intended use of the information (how much detail is required), the amount and time and energy each can invest in the communication process, and how heterogeneous the ‘audience’ or set of participants are. For example: an investment bank policy advisor may want short narrative descriptions that give qualitative insights into the causes of risk and the related uncertainties pertaining specifically to large hydro-electric infrastructure in sub-Saharan Africa via a once off communication; while a district government water manager may want more detailed quantitative information about the probability of flooding and drought events comparing current risks with those expected for 2040 based on more regular interactions with risk analysts as new information becomes available.
The language around risk associated with climate change is fairly new and is in many ways still evolving, which makes risk communication particularly tricky. The Intergovernmental Panel on Climate Change (IPCC) has made a significant contribution to building consensus around how certain terms are used and what they can be understood to mean in the context of climate change (e.g. likely means there is a greater than 66% probability of occurrence). However, the meanings of many of these terms remain contested, partly due to politics and partly as scientific knowledge in the field of climate change rapidly expands, and this inherently generates considerable confusion. We have to work within this state of confusion and handle communication with particular care as a result. We need to be particularly aware that many audience members or participants may not be familiar with climate risk terminology and risk analysis methodologies. Over and above this, some will be keenly aware of the fact they aren’t familiar with this and will try to compensate, while others may be largely oblivious to the depth of what they don’t know in this area and so may take information at face value and make poor judgements on the basis on it. There is no commonly accepted way to present risk and probability but some tend to confuse and cloud judgement, e.g. relative risk statements that don’t convey the baseline level of risk, while others foster insight, e.g. comparative risk statements that use a natural frequency format, instead of a percentage, and have a consistent denominator (Thomson et al, 2005). We need to take this into account when developing messages tailored for different audiences and/or participants.
As mentioned above, one of the main challenges with communicating information about climate change risks is that of time frames. Because of the way the climate modelling is done most of the information we have on how the climate hazards will evolve pertains to the second half of the 21st century. On the other hand it is very difficult to say much about vulnerability conditions that far into the future because economic and political realities can change substantially in the interim in any number of ways. However this climate change information can still be useful in informing planning processes, to make sure that decisions taken now do not lead to mal-adaptation and push us in a direction of facing greater levels of risk in the future, and rather build flexibility and robustness into the system, thereby building adaptive capacity. This information about future climatic conditions can be especially helpful if we use it in combination with the information we have on historical climate variability and change, the impacts associated with those, what different peoples have done in the past to address these and what is currently possible for us to do to prepare for a range of future conditions that we are now confident will be different from what we are used to.
Evidence from various fields, including health, financial and disaster management (think smoking, sub-prime mortgages and hurricane Katrina as examples), tells us that we humans have not been good changing our ways in anticipation of a negative impact, and the further into the future the risk is perceived to be the less proactive we tend to be, but hopefully we are learning that we need to do this better (facilitated in part through processes of communication).
There may well be another framing issue in additional to that of timing that plays into people’s choices on how to act based on the information, that is whether the risk is presented in the negative or positive form (e.g. financial loss versus gain, death versus survival, crop loss versus gain, etc.) and whether generalised risk or localised / personalised risk (e.g. projected global sea level risk versus sea level rise expected for Dakar). In other words, people react differently if the information is presented as a threat or an opportunity, and if is related to their immediate sphere of influence or something perceived to be far bigger than they are. This is a topic that we should explore further at the next opportunity.
The final issue we will cover for now on the topic of message content, is that of uncertainty. For people to make a sound decision based on risk information one needs to convey the sense, and preferably the extent, of uncertainty associated with the risk statement. We touched on this in the London example above, which highlighted the extensive technical considerations associated with understanding the sources of uncertainty. It also came out in the time frames discussion that some aspects of risk we can simulate in models with some accuracy while others we can only make informed guesses about, and in both cases there are usually a number of assumptions involved. If we are communicating the results of risk analyses or assessments then we need to make the implications of these data limitations, methodological considerations, assumptions, etc. explicit in a form that is understandable by others, whether it is giving probability ranges where possible (and defensible) or describing in qualitative ways how certain the user can be in the information, what it can confidently be used for and what it shouldn’t be used for.
Thomson, R., Edwards, A., and Grey, J. (2005) Risk Communication in the Clinical Consultation. Clinical Medicine, 5(5), Sept/Oct 2005, pp. 465-469.
UKCP09, UK Climate Projections 2009 website 
Authors: Anna Taylor (SEI Oxford), Tahia Devisscher (SEI Oxford)
SciDev Net Practical Guide to communicating statistics and risk