Weather-dependent climate change

Climate is defined by the statistics of the weather. We are thus used to the notion that weather depends on climate in the sense that a weather state is a quasi random realization drawn from the climatological distribution of weather states. Consequently, weather obviously also depends on climate change. Here it is argued that it can be very instructive to consider this dependence the other way around and to investigate how climate change depends on the weather. More specifically, the question is how different parts of the climatological distribution change, depending on certain relevant characteristics of the weather. For example, one may ask how the climate at some time of the year and at some location changes between a pre-industrial and a globally +4K warmer climate, considering only days where the local winds at some height blow from a specific direction. Alternatively, one may investigate how the climate change pattern differs between certain large-scale atmospheric circulation regimes, such as NAO⁺ and NAO^- situations. While such conditional climate change analyses can be based for example on reanalysis or CMIP-type climate model data, a more extreme variant are storyline simulations where the evolution of the large-scale circulation is imposed in a climate model using different climate backgrounds, allowing to assess climate change conditional on a specific evolution of the large-scale circulation. Storyline simulations inevitably ignore possible changes in the likelihood of circulation patters. In contrast, analyses based on sufficiently large samples of reanalysis or CMIP-type data also allow for quantifying changes in likelihoods and constitute a proper decomposition of the complete (unconditional) climate change signal. Here the concept of weather-dependent climate change is explained and its potential to help unravel the complexities of climate change is demonstrated.