Projections of the Transient State‐Dependency of Climate Feedbacks. Issue 20 (21st October 2021) - Bastiaansen, Robbin; Dijkstra, Henk A.; Heydt, Anna S. von der
Abstract: When the climate system is forced, for example, by the emission of greenhouse gases, it responds on multiple time scales. As temperatures rise, feedback processes might intensify or weaken. Such state dependencies cannot be fully captured with common linear regression techniques that relate feedback strengths linearly to changes in the global mean temperature. Hence, transient changes are difficult to track and it becomes easy to underestimate future warming this way. Here, we present a multivariate and spatial framework that facilitates the dissection of climate feedbacks over time scales. Using this framework, information on the composition of projected transient future climates and feedback strengths can be obtained. The new framework is illustrated using the Community Earth System Model version 2. Plain Language Summary: When the Earth warms, the internal processes of the climate system change. This can lead to additional warming, forming a feedback loop. For instance, as the ice melts due to increased temperatures, less solar radiation gets reflected back to outer space, causing temperatures to rise even more. To properly understand and assess (future) climatic changes, it is, therefore, necessary to quantify these so‐called climate feedbacks and track how they change over time. However, with current techniques, it is not easy to explicitly track these temporal changes, which hampers the interpretation of long‐term projections of the future climate state and easily leads to systematic underestimation of future (committed) warming. Here, we present a new feedback framework that can capture the temporal evolution of climate feedbacks. Consequently, a better insight into the development of a (projected) future climate is obtained, because not only global mean temperatures can be tracked, but also the temporal change in individual climate feedbacks, including their spatial distribution. Key Points: A multivariate climate feedback framework is introduced that takes into account the transient state dependency of climate feedbacks Using the new framework, changes in feedback processes can be analyzed per time scale and temporal evolution can be tracked Within the framework, it is possible to create transient and equilibrium projections of (the spatial patterns of) climate feedbacks