- Conference Proceedings Paper
The ability to rapidly simulate the local climate implications of a large number of future climate policy scenarios is important for planning and implementing adequate climate mitigation and adaptation policies. Given the societal impacts from rising local temperature, we build an emulator of spatially resolved near-surface air temperature responses to carbon dioxide (CO2) emissions. Near surface air temperature is approximately proportional to cumulative carbon dioxide (CO2) emissions, allowing for linearization of the temperature response to emissions scenarios. This linearity enables us to diagnose Green’s Functions for the spatial temperature response to CO2 emissions from pulse simulations conducted as part of the CDRMIP experiments. We then apply this emulator across a wide range emissions scenarios to estimate local temperature responses.
We evaluate this emulator with two CMIP6 experiments: 1) a 1% increase in CO2 concentration, and 2) an experiment that branches from this after concentrations of 1000 PgC are reached. We find that this emulation approach captures the spatial temperature response to CO2 emissions within one standard deviation of the CMIP6 range, with some limited accuracy in polar regions where nonlinearities in climate feedbacks dominate and internal variability may influence the Green’s Function. This approach incorporates emissions path dependency, accounting for various timescales of warming due to CO2 emissions. It is useful for evaluating large ensembles of policy scenarios that are otherwise prohibitively expensive to simulate using earth system models, as it takes less than one second to emulate 90 years of temperature response. We apply this emulator to quantify differing local temperature responses when a global mean of 2ºC is reached, showing that some locations (such as Lagos and Buenos Aires) warm slower than the global mean, while others warm faster (such as Boston and Shanghai). We also evaluate varying CO2 emissions trajectories with the same cumulative emissions, showing that the resulting temperature changes are path dependent.
The ability to quantify the climate impacts of changes in future emissions due to various climate policies is important for planning and implementing adequate climate mitigation and adaptation. Given the societal impacts from rising local temperature, we build a rapid model that can quantify local temperature responses to changes in carbon dioxide (CO2) emissions, a key greenhouse gas responsible for climate change. This simple approach takes advantage of a proportional relationship between total CO2 emissions and temperature, and it takes only one second to quantify temperature impacts over 90 years. We test this approach against the Climate Model Intercomparison Project Phase 6 (CMIP6) experiments, finding some limited accuracy in polar regions. We then use this approach to quantify the local temperature impacts in different cities when a global mean increase of 2 ºC is reached, showing that some cities warm faster than the global mean and others warm slower. We also show that the emissions pathway matters, even if the same total CO2 emissions are reached. Importantly, this approach can be used to estimate local temperature response to dozens of policy scenarios without the computational power and time needed for running a climate model.