Post by nautonnier on Mar 8, 2017 13:27:48 GMT
Mar 8, 2017 7:22:31 GMT Ratty said:
Translation, anyone?
Conclusion
As is common in climate change science and modeling, IAMs have important limitations and are fraught with uncertainty. Nevertheless, these models are valuable tools for supporting decision making and for exploring the potential economic consequences of climate change. This paper illustrates the large uncertainty in the impact functions projections for small increases in warming, such as that of the observed warming period and those that are projected to occur in the short- and medium-terms. Given the common use of positive discount rates, the impacts in the near and medium future can have a significant weight on the present value estimates of climate change costs. Investigating the differences in IAMs impact functions and improving their calibration for small increases in warming would help providing better estimates of the economic costs of climate change. The results of this paper point to the importance of interaction effects which are currently ignored in IAMs projections of the costs of future climate change. Most IAMs produce temperature projections based exclusively on anthropogenic forcing, implicitly assuming that the different natural and anthropogenic contributions to the climate change costs are linearly separable. Given the nonlinearity of impact functions this is not the case and as is shown in this paper the interaction effects can be large, potentially biasing the estimates if ignored. The consequences of this assumption for the estimates of future climate change costs will be addressed by the authors in a forthcoming paper.
As is common in climate change science and modeling, IAMs have important limitations and are fraught with uncertainty. Nevertheless, these models are valuable tools for supporting decision making and for exploring the potential economic consequences of climate change. This paper illustrates the large uncertainty in the impact functions projections for small increases in warming, such as that of the observed warming period and those that are projected to occur in the short- and medium-terms. Given the common use of positive discount rates, the impacts in the near and medium future can have a significant weight on the present value estimates of climate change costs. Investigating the differences in IAMs impact functions and improving their calibration for small increases in warming would help providing better estimates of the economic costs of climate change. The results of this paper point to the importance of interaction effects which are currently ignored in IAMs projections of the costs of future climate change. Most IAMs produce temperature projections based exclusively on anthropogenic forcing, implicitly assuming that the different natural and anthropogenic contributions to the climate change costs are linearly separable. Given the nonlinearity of impact functions this is not the case and as is shown in this paper the interaction effects can be large, potentially biasing the estimates if ignored. The consequences of this assumption for the estimates of future climate change costs will be addressed by the authors in a forthcoming paper.
The broken climate models might have been useful even if they are wrong as they give a spread of possible scenarios. Except that the models all assume that every change in climate is anthropogenic and that the background climate does not alter at all. This is an incorrect assumption which makes even these broken models totally useless. However, we could still research the bag of bolts; please send more money.