Alleviating climate wait-and-see
May 03 2012
There have been a number of evidences for wait-and-see preferences. In a recent US survey, 60 per cent of participants chose either the option, “until we are sure that global warming is really a problem, we should not take any steps that would have economic costs” or the option “its effects will be gradual, so we can deal with the problem gradually”.
The wait-and-see preference is also seen among policymakers. GW Bush on February 12, 2002 said, “Slow the growth of greenhouse gas emissions (GHGs), and as the science justifies stop, and then reverse that growth”. Thus, he believed that climate mitigation actions could be taken at a slow pace until science confirmed climate change as a real problem. Also, climate initiatives such as the Kyoto Protocol and Clear Skies, have also expressed support for wait-and-see preferences, which would work well in simple systems with short delays between the detection of a problem and the implementation of corrective actions. Unfortunately for a complex system like earth’s climate, there are much longer delays between the decision to mitigate emissions and the corresponding changes in atmospheric GHG concentrations. As there are long feedback delays, wait-and-see preferences become problematic. Because even if mitigation actions are taken, atmospheric CO2 accumulation would continue to rise until emissions fell below the absorption rate. Average atmospheric temperature would then peak, and consequences such as rising sea levels and thermal expansion would continue. Therefore, wait-and-see preferences are likely to cause abrupt, persistent, and costly regime changes on earth in the future.
Through a number of laboratory studies we, at Carnegie Mellon University, have shown that people’s wait-and-see preferences on climate are related to their reliance on heuristic and biases. People exhibiting wait-and-see preferences for climate change seem to rely on two particular heuristics: correlation thinking and violation of mass balance. For climate, relying on the correlation heuristic means wrongly inferring that an accumulation (CO2 concentration) follows the same path as the inflow (CO2 emissions); hence, stabilising emissions would rapidly stabilise the concentration, and emissions cuts would quickly reduce the concentration and damages from climate change. Consequently, people who rely on this heuristic would demonstrate wait-and-see preferences because they would underestimate the delay between reductions in CO2 emissions and in the CO2 concentration. Thus, they would also underestimate the magnitude of emission reductions needed to stabilise the concentration.
It has also been shown that people’s wait-and-see preferences for climate change are related to the violation of mass balance, whereby people incorrectly infer that atmospheric CO2 concentration can be stabilised even when emissions exceeds absorptions. Violating mass balance leads to wait-and-see preferences because people think the current state of the climate system, where emissions are double that of absorptions, would not pose a problem to future stabilisation.
Recently, researchers at Columbia University suggested that experiencing the adverse consequences of climate change in simulation-based tools is likely to improve people’s understandings of the climate system. Recent studies done at Carnegie Mellon University have validated this claim and shown that these simulation-based tools that depict the dynamics of CO2 concentrations, emissions, and absorptions help people to correct their reliance on heuristics about earth’s climate. Results from using a simulation-based tool called the Dynamic Climate Change Simulator (DCCS) have been particularly noteworthy. DCCS provides repeated feedback on the changes in the CO2 concentration each year as a result of CO2 emission and absorption policies set by participants, allowing participants to observe the results of their decisions as they try to control the concentration to a goal. One main and consistent result of our study is that acquiring experiential feedback in the DCCS helps to reduce participants’ misconceptions about the way the climate system works.
Experiential feedback in DCCS enables participants to test several hypotheses they might have about how CO2 emission and absorption processes affect the CO2 concentration. It is likely that the ability to test several hypotheses repeatedly about the cause-and-effect relationship in DCCS enables them to understand that the concentration increases when CO2 emissions are greater than absorptions, decreases when emissions are less than absorptions, and stabilises at a particular value when emissions equal absorptions. Therefore, it seems that the experience gained in DCCS enables participants to decrease their reliance on the correlation heuristic and violation of mass balance.
The above explanations about feedback in DCCS are also supported by similar findings for other dynamic tasks. In a world where people with non-scientific backgrounds are plentiful and their support is clearly needed, the climate experts should understand and pay close attention to the underlying mental models, pre-existent knowledge, and needs of lay people. Again here, the use of simulation tools like DCCS is likely to help improve lay people’s understanding of the cause-and-effect relationships that govern earth’s climate.
(The writer is on the faculty of Carnegie Mellon University, Pittsburgh, US, and knowledge editor of Financial Chronicle)