Publications Published in International Journal of Global Warming

1. Global energy accumulation and net heat emission. Nordell, Bo; Gervet, Bruno.
   International Journal of Global Warming: 2009
   Notes
   The increase in the global air temperature is an inadequate measure of global warming, which should rather be considered in terms of energy. The ongoing global warming means that heat has been accumulating since 1880 in the air, ground and water. Before explaining this warming by external heat sources, the net heat emissions on Earth must be considered. Such emissions from, e.g., the global use of fossil fuels and nuclear power, must contribute to global warming. The aim of this study is to compare globally accumulated and emitted heat. The heat accumulated in the air corresponds to 6.6% of global warming, while the remaining heat is stored in the ground (31.5%), melting of ice (33.4%) and sea water (28.5%). It was found that the net heat emissions from 1880–2000 correspond to 74% of the accumulated heat, i.e., global warming, during the same period. The missing heat (26%) must have other causes, e.g., the greenhouse effect, the natural variations in the climate and/or the underestimation of net heat emission Most measures that have already been taken to combat global warming are also beneficial for the current explanation, though nuclear power is not a solution to (but part of) the problem.
   
   
   
2. The optimal paths of climate change mitigation and adaptation under certainty and uncertainty. Felgenhauer, Tyler; de Bruin, Kelly C..
   International Journal of Global Warming: 2009
   Notes
   Tradeoffs between climate change mitigation and adaptation policies are explored under both certainty and uncertainty with learning using a numerical two-period decision model. We first replicate a version of the Adaptation in DICE climate model (AD-DICE) (de Bruin et al., 2009), which modifies the Dynamic Integrated model of Climate and the Economy (DICE) (Nordhaus and Boyer, 2000) to incorporate climate change adaptation explicitly into the traditional optimisation framework. Our model is then extended to include uncertainty over a probability distribution of expected Climate Sensitivity (CS) values and the implications for optimal mitigation and adaptation levels are then explored. In the certainty model runs, the results of previous studies that incorporated adaptation into the portfolio of climate change responses are largely confirmed. Modelling an uncertain CS with the same expected value as under certainty leads to several insights: • before learning occurs, optimal levels of both mitigation and adapt ion are lower under uncertainty than under certainty • in this same early period, optimal mitigation and adaptation levels are most sensitive to the respective cost of each strategy, with the mitigation level more dependent on adaptation costs than vice versa • variance in CS – a parameter with long-term effects – affects mitigation levels more than adaptation levels.