Unintuitive patterns of change in global temperature distribution detected

Following the global warming observed in the past decades, interest in temperature’s variability and extremes has been rising, and has since become clear that it is imperative to identify the exact shape of the temperature’s distribution. Here, we analyze the temporal evolution of the near-surface air-temperature distribution in thousands of stations around the globe over the last centuries. Particularly, we explore a large set of daily timeseries (30–200 years) of average, maximum and minimum standardized temperature, and we apply robust high-order moments (K-moments) in both marginal and dependence structures, as an effective alternative to order statistics, and based on the analysis by Glynis et al. (2021). Results suggest that the average and minimum temperature tend to increase, while overall the maximum temperature is slightly decreasing. We subsequently characterize probabilistically the unintuitive patterns observed in the records.K. Glynis, T. Iliopoulou, P. Dimitriadis, and D. Koutsoyiannis, Stochastic investigation of daily air temperature extremes from a global ground station network, Stochastic Environmental Research & Risk Assessment, doi:10.1007/s00477-021-02002-3, 2021.