Climate model biases and projected changes in climate extremes

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Climate extremes such as intense storms, floods, or droughts have enormous impacts on societies and ecosystems around the world. To adapt societies to adverse climate change impacts, accurate projections of future climate extremes are needed. Our confidence in these projections strongly varies among variables. While a future intensification of hot temperature extremes is virtually certain, changes in other events such as extratropical cyclones (ETCs) are less clear. Reducing uncertainties requires a thorough understanding of the mechanisms that cause (i) biases in climate extremes under current climate conditions and (ii) future changes in climate extremes in response to projected greenhouse gas (GHG) concentrations in global climate models (GCMs). This is challenging due to the dynamical nature of extreme events. Statistical approaches often used in this context are limited as they cannot fully prove causality, nor disentangle dynamically interacting mechanisms. I will develop an alternative framework that explores new ways to understand the physical mechanisms that cause GCM biases and projected changes in climate extremes. Important advancements in the next 5 years will be made by achieving four short-term objectives that assess ETC biases and projections in the mid-latitudes and in the Arctic using piecewise potential vorticity inversion (PPVI) and a simplified GCM. This is an innovative approach, as PPVI has so far been used mainly to study individual historic events in reanalysis data. The proposed method will, therefore, set a precedent for using PPVI to evaluate GCMs and advance our understanding in new ways that cannot be achieved through statistical approaches used in previous studies. My first objective is to quantify the contributions from different atmospheric levels to ETC biases and projections in GCMs using PPVI. The results will allow me to address my second objective, which is to identify the mechanisms that cause ETC biases and to assess whether GCMs with small ETC biases perform well for the right reasons. My third objective is to then identify the dominant mechanisms that are responsible for projected changes in ETCs and to evaluate to what extent these changes are affected by ETC biases and compensating processes. My fourth objective is to verify these mechanisms in sensitivity experiments conducted with a simplified GCM. The new framework will provide guidance for improving GCMs and reducing GCM uncertainties, which will ultimately help societies in becoming more resilient to climate extremes under changing climate conditions. The requested funds will support the research of two Ph.D. students who will engage in a training program that will support their transition from being a Ph.D. student to becoming a productive professional in the field. My role as a mentor will be to guide the HQPs through this process and to assist them in launching a successful career.