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This study investigates future changes in daily precipitation extremes and the involved physics over the global land monsoon (GM) region using climate models from phase 6 of the Coupled Model Intercomparison Project (CMIP6). The daily precipitation extreme is identified by the cutoff scale, measuring the extreme tail of the precipitation distribution. Compared to the historical period, multimodel results reveal a continuous increase in precipitation extremes under four scenarios, with a progressively higher fraction of precipitation exceeding the historical cutoff scale when moving into the future. The rise of the cutoff scale by the end of the century is reduced by 57.8% in the moderate emission scenario relative to the highest scenario, underscoring the social benefit in reducing emissions. The cutoff scale sensitivity, defined by the increasing rates of the cutoff scale over the GM region to the global mean surface temperature increase, is nearly independent of the projected periods and emission scenarios, roughly 8.0% K−1 by averaging all periods and scenarios. To understand the cause of the changes, we applied a physical scaling diagnostic to decompose them into thermodynamic and dynamic contributions. We find that thermodynamics and dynamics have comparable contributions to the intensified precipitation extremes in the GM region. Changes in thermodynamic scaling contribute to a spatially uniform increase pattern, while changes in dynamic scaling dominate the regional differences in the increased precipitation extremes. Furthermore, the large intermodel spread of the projection is primarily attributed to variations of dynamic scaling among models. [ABSTRACT FROM AUTHOR]

Identifying and separating the signal of urbanization effects in current temperature data series is essential for accurately detecting, attributing, and projecting mean and extreme temperature change on varied spatial scales. This paper proposes a new method based on machine learning to classify the observational stations into rural stations and urban stations. Based on the classification of rural and urban stations, the global and regional land annual mean and extreme temperature indices series over 1951–2018 for all stations and rural stations were calculated, and the urbanization effects and the urbanization contribution of global land annual mean and extreme temperature indices series are quantitatively evaluated using the difference series between all stations and the rural stations. The results showed that the global land annual mean time series for mean temperature and most extreme temperature indices experienced statistically significant urbanization effects. The urbanization effects in the mean and extreme temperature indices series generally occurred after the mid-1980s, and there were significant differences of the magnitudes of urbanization effects among different regions. The urbanization effect on the trends of annual mean and extreme temperature indices series in East Asia is generally the strongest, which is consistent with the rapidly urbanization process in the region over the past decades, but it is generally small in Europe during the recent decades. [ABSTRACT FROM AUTHOR]