This study presents trends in a newly compiled temperature extreme indices dataset for Asia covering the period of 1958–2012. Daily data were homogenized prior to the calculation of the indices. A clear warming trend was observed in all indices, which is consistent with the global warming. In most of the indices, larger warming was observed at high latitudes than at low latitudes. We also compared observations with simulations from the Coupled Model Inter-comparison Project Phase 5 for some indices using an optimal fingerprinting method. These indices include the number of days with daily maximum or minimum temperatures greater than their 90th percentiles or smaller than their 10th percentiles, the annual highest daily maximum and minimum temperatures, and the annual lowest daily maximum and minimum temperatures. We determined that the warming trend was inconsistent with the natural variability of the climate system but agreed with climate responses to external forcing as simulated by the models. The anthropogenic and natural signals could be detected and separated from each other in the region for almost all indices, indicating the robustness of the warming signal as well as the attribution of warming to external causes.

This paper examines new evidence from observational and detection and attribution studies of changes in extreme precipitation in China since the early 1960s. We have also designed a series of sensitivity tests to explore the robustness of detection and attribution results to the differences in sample size, in extreme precipitation index, and in data processing procedure. Our analyses used the most recent update of observational records as well as simulations conducted with the climate models participated in the Coupled Model Intercomparison Project Phase 6. Based on the existing studies and our additional analyses, we found that human influence is detectable in extreme precipitation in China regardless of the period, extreme precipitation index, or data treatment considered, in both China as a whole and in northern and southern China separately. We also found, as is often encountered in detection and attribution studies, it is difficult to separate the contribution from anthropogenic forcing from that of natural external forcing, and it is also challenging to decompose the anthropogenic component into a greenhouse gas forcing component and a component that reflects other anthropogenic forcing agents (dominantly, aerosols).

The Aridity Index (AI), calculated from 99 homogeneous meteorological stations from 1961 to 2020, was used to analyze the variation of dryness/wetness climate change in Xinjiang in the past 60 years. The results show that the annual AI in Xinjiang has demonstrated a significant decreasing trend over the past 60 years; that is, the climate in Xinjiang, especially southern Xinjiang, has shown a relatively wetting trend. The interdecadal variations from the 1960s to 2010s explained that the total station ratio of arid and extremely arid areas showed a decreasing trend. In contrast, the semi-arid, humid, and semi-humid areas showed increasing trends, especially since the beginning of the twenty-first century. The interdecadal spatial evolution characteristics show that Xinjiang’s dryness/wetness climate reversed in the 1990s. An abrupt change in the annual AI occurred in 1986, after which the study region was continuously wetting. The first empirical orthogonal function (EOF) decomposition mode is consistent in Xinjiang; that is, the climate in Xinjiang is generally dry or wet, and the intensity of this change varies among different regions. The second mode reflects the opposite spatial distribution characteristics of the dryness/wetness climate in southern and northern Xinjiang with the Tianshan Mountains. Dryness/wetness climate changes in Xinjiang mainly exhibit 2.5-year and 6-year oscillation periods, between which the 6-year period is even more significant.