Climate Change: Models, Metrics and Meaning Making
Doctoral thesis, 2018
This thesis, combining research in climate science and educational science, investigates different aspects of climate knowledge. It consists of five papers and covers three major topics: emission metrics, public understanding of atmospheric CO2 accumulation, and spatial modelling of natural resource use.
In Paper I-II, we study emission metrics that compare the climate impact of different climate forcers in two different ways. For Paper I, we use Sea Level Rise (SLR) as the basis for comparison, proposing two novel emission metrics. We find that all examined climate forcers – even short-lived – have considerable influence on SLR on at least a century time scale. Paper II focuses on how the Climate-Carbon cycle Feedback (CCF) affects emission metric values, in relation to how the CCF caused by non-CO2 forcers is modeled. For emission pulses, we show that with an approach previously used to calculate climate metrics using linear feedback analysis for the CCF, the effect of it will persist basically forever, while with an approach based on an explicit carbon cycle model, the CCF effect by non-CO2 forcers eventually vanishes, leading to lower metric values for longer time-horizons.
Paper III-IV, related to climate science literacy, focus on public understanding of atmospheric CO2 accumulation and its potential link to climate policy support. In Paper III, we identified five qualitatively different ways of reasoning about CO2 accumulation; only one of these is consistent with mass balance principles. We also found that task formulation has a strong bearing on the assessment of understanding, but that strong
climate policy support does not require that people can solve typical CO2 tasks. In Paper IV, we draw attention to a range of challenges that university students experience when reasoning about CO2 accumulation, ranging from cognitive to metacognitive and affective challenges. Most notable for the cognitive domain was the failure to understand how uptake of CO2 depends on emission pathways.
In Paper V, we model low-income villagers’ spatial natural resource use while removing constraining assumptions on villagers’ behaviour. We find that removing commonly used constraints lead to higher degrees of heterogeneity among villagers’ spatial behaviour, especially for intermediate distance cases.
Climate Science Literacy
Short-lived Climate Forcers
Sea Level Rise
Common Pool Resources