Investigating state and timescale-dependency of climate variability using an isotope-enabled coupled general circulation model

点击翻译按钮获取中文摘要

It is fundamentally unclear whether global and regional climate variability will increase or decrease along with global mean temperature rise. For societies, variability changes are crucial to understand, and expensive to prepare for, as they entail changes in the frequency of extreme events. In light of this, the aim of this project is to understand and quantify links between mean changes and variability in temperature.The Earth's state during the last Glacial Maximum (LGM, 21000 years ago) and the mid-Holocene warm period (6000 years ago) is well suited for this purpose, as many proxy and modeling studies have helped to characterize their mean state climates. However, even the most advanced, coordinated modeling efforts so far cannot be used for variability-oriented model-data comparison. Firstly, published simulations are often only a few centuries long, close to what a single polar ice core data point typically represents. Secondly, the role of natural forcing in creating temperature variability in these climate states is unknown, as the state-of-the-art climate simulations were run without varying solar and volcanic forcing. Thirdly, most high-resolution evidence for past temperature variability is derived from stable isotope ratios in polar ice cores, whose calibration to temperature is largely unconstrained, particularly for Antarctica.To overcome these challenges, and to identify relationships between global mean temperature changes and variability changes systematically, ensemble trajectories of four Earth system states will be simulated using an isotope-enabled general circulation model. A glacial state will be modeled according to the LGM, an interglacial state as the mid-Holocene. For a super-glacial and a super-interglacial state, global temperature is further reduced and increased, respectively, by changing the atmospheric CO2 concentrations and the continental ice-sheet size. Two suites of millennial simulations will be performed, one with constant, a second with varying solar and volcanic forcing.The ensemble approach allows time-series analyses on up to millennial timescales, bridging the gap between proxy and model resolution. Since the model explicitly simulates the isotopic signature of water, the mean-state dependence of the proxy calibration can be investigated, and linked to changes in atmospheric and oceanic dynamics. Furthermore, comparing the experiments with and without forcing will, for the first time, shed light on the role of natural forcing in creating climate variability in different climate states.Together, model experiments and proxy data will provide a comprehensive view on the relationship between mean temperature and temperature variability changes, thus contributing to a better understanding of potential changes to future climate variability.