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In recent years, the frequent occurrence of extreme climate disasters has seriously affected agriculture in Northeast China. Based on precipitation data derived from 83 geographical stations in the study area for 60 years (1960–2019), we chose the reliable statistical methods of the Mann–Kendall test, Sen's slope, and the Standardized Precipitation Index, and regarded drought and flood as a whole in this paper, to identify the temporal and spatial variation characteristics of precipitation and extreme climate events in Northeast China. The results show that an increasing trend of disasters was detected at the 95% confidence level (Z = 2.3). According to the timescale analysis, abrupt climate changes started in 2006. Temporal and spatial distribution of extreme climate disasters, mainly drought and flood disasters, showed a significant upward trend from 2006 to 2019. According to the spatial analysis, the precipitation in Northeast China decreased from south to north and fluctuated less from east to west. Moreover, stations with extreme climate trends (trend of climatic anomaly with confidence level > 90%) followed the same spatial pattern as those with a high frequency of extreme climate disasters (more than 17.87 times/decade). The severity and frequency of extreme climate have increasingly threatened Northeast China in the past decade. In particular, the Northeast Plain experienced the most severe and extreme climate events that seriously threatened the study area in 2007, 2009, 2010, and 2019. Our results highlight the urgent need for the development of monitoring and early warning of droughts and flood disasters to reduce economic losses. [ABSTRACT FROM AUTHOR]

Concurrent compound dry and hot events (CDHEs) amplified more damange on the ecosystems and human society than individual extremes. Under climate change, compound dry and hot events become more frequent on a global scale. This paper proposes a mathematical method to quantitatively attribute changes of CDHEs to changes of precipitation, change in temperature and change in the dependence between precipitation and temperature. The attribution is achieved by formulating the total differential equation of the return period of CDHEs among Meta-gaussian model. A case study of China is devised based on monthly precipitation and temperature data during the period from 1921 to 2020 for 80 major river basins. It is found that temperature is the main driving factor of increases in CDHEs for 49 major river basins in China, except for the upper and middle reaches of the Yangtze River. In West China, precipitation changes drove the increase in CDHEs in 18 river basins (23%), particularly in parts of North Xinjiang, Qinghai and Gansu. On the other hand, dependence between precipitation and temperature dominated changes of CDHEs in 13 river basins (16%) of China with other factors, including parts of South China, East China and Northwestern China. Furthermore, changes in both the mean and spread of precipitation and temperature can also contribute to changes in CDHEs. [ABSTRACT FROM AUTHOR]

Spatiotemporal changes in climatic extremes in the Yellow River Basin from 1959 to 2008 were investigated on the basis of a suite of 27 climatic indices derived from daily temperature and precipitation data from 75 meteorological stations with the help of the Mann-Kendall test, linear regression method and GIS technique. Furthermore, the changes in the probability distribution of the extreme indices were examined. The results indicate: (1) The whole basin is dominated by significant increase in the frequency of warm days and warm nights, and dominated by significant decrease in the frequency of cold days and cold nights. Although trends in absolute temperature indices show less spatial coherence compared with that in the percentile-based temperature indices, overall increasing trends can be found in Max Tmax (TXx), Min Tmax (TXn), Max Tmin (TNx) and Min Tmin (TNn). (2) Although the spatial patterns and the number of stations with significant changes for threshold and duration temperature indices are also not identical, general positive trends in warm indices (i.e., summer days (SU25), tropical nights (TR20), warm spell duration indicator and growing season length) and negative trends in cold indices (i.e., frost days, ice days and cold spell duration indicator) can be found in the basin. Annual nighttime temperature has increased at a faster rate than that in daytime temperature, leading to obvious decrease in diurnal temperature range. (3) The changes in precipitation indices are much weaker and less spatially coherent compared with these of temperature indices. For all precipitation indices, only few stations are characterized by significantly change in extreme precipitation, and their spatial patterns are always characterized by irregular and insignificant positive and negative changes. However, generally, changes in precipitation extremes present drying trends, although most of the changes are insignificant. (4) Results at seasonal scale show that warming trends occur for all seasons, particularly in winter. Different from that in other three seasons, general positive trends in max 1-day precipitation (Rx1DAY) and max 5-day precipitation (Rx5DAY) are found in winter. Analysis of changes in probability distributions of indices for 1959-1983 and 1984-2008 indicate a remarkable shift toward warmer condition and a less pronounced tendency toward drier condition during the past decades. The results can provide beneficial reference to water resource and eco-environment management strategies in the Yellow River Basin for associated policymakers and stakeholders. [ABSTRACT FROM AUTHOR]

Variations and trends in extreme climate events are more sensitive to climate change than the mean values, and so have received much attention. In this study, twelve indices of temperature extremes and 11 indices of precipitation extremes at 32 meteorological stations in Hengduan Mountains were examined for the period 1961-2008. The results reveal statistically significant increases in the temperature of the warmest and coldest nights and in the frequencies of extreme warm days and nights. Decreases of the diurnal temperature range and the numbers of frost days and ice days are statistically significant. Regional averages of growing season length also display the trends consistent and significant with warming. At a large proportion of the stations, patterns of temperature extremes are consistent with warming since 1961: warming trends in minimum temperature indices are greater than those relating to maximum temperature. As the center of the Shaluli Mountain, the warming magnitudes decrease from inner to outer. Changes in precipitation extremes is low: trends are difficult to detect against the larger inter-annual and decadal-scale variability of precipitation, and only the wet day precipitation and the regional trend in consecutive dry days are significant at the 0.05 level. It can be concluded that the variation of extreme precipitation events is not obvious in the Hengduan Mountains, however, the regional trends generally decrease from the south to the north. Overall, the spatial distribution of temporal changes of all extreme climate indices in the Hengduan Mountains illustrated here reflects the climatic complexity in mountainous regions. [ABSTRACT FROM AUTHOR]

Since there are many destructive effects caused by extreme climate events in the Yellow River, it is of great theoretical and practical significance to explore the variations of climatic extremes in this key basin. We used a meteorological dataset from 66 stations within the Yellow River basin (YRB) for the period 1960–2017 to calculate magnitude and frequency of precipitation/temperature extremes. We also analyzed the relationships between the main large-scale atmospheric circulation patterns (ACPs) and precipitation/temperature extremes. The trends in precipitation extremes were nonsignificant, only a few stations were characterized by significantly increasing or decreasing anomalies; this indicates the precipitation intensity may have been strengthened, and the extreme rainfall duration appears to have been reduced during 1960–2017. The trends of magnitudes for "cold" extremes were larger than those for "warm" extremes, changes of trends in frost days were higher than those for summer days, and the trends in increasing warm nights were higher than those of warm days. The influence of the El Niño–Southern Oscillation (ENSO) and Arctic Oscillation (AO) on temperature extremes outweighed the influence of the North Atlantic Oscillation (NAO), Indian Ocean Dipole (IOD), and Pacific Decadal Oscillation (PDO) for the other extreme climate indices. The YRB might be at risk of increased extreme high temperature events, and more attention should be paid to this higher risk of extreme climatic events. [ABSTRACT FROM AUTHOR]

To avoid more severe impacts from climate change, countries worldwide pledged to implement intended nationally determined contributions (INDCs) for emission reductions (as part of the Paris Agreement). However, it remains unclear what the resulting precipitation change in terms of regional extremes would be in response to the INDC scenarios. Here, we analyzed China's extreme precipitation response of the next few decades to the updated INDC scenarios within the framework of the Paris Agreement. Our results indicate increases in the intensity and frequency of extreme precipitation (compared with the current level) in most regions in China. The maximum consecutive five-day precipitation over China is projected to increase ~16%, and the number of heavy precipitation days will increase as much as ~20% in some areas. The probability distributions of extreme precipitation events become wider, resulting in the occurrence of more record-breaking heavy precipitation in the future. We further considered the impacts of precipitation-related extremes and found that the projected population exposure to heavy precipitation events will significantly increase in almost all Chinese regions. For example, for heavy precipitation events that exceed the 20 year baseline return value, the population exposure over China increases from 5.7% (5.1–6.0%) to 15.9% (14.2–16.4%) in the INDC-pledge scenario compared with the present-day level. Limiting the warming to lower levels (e.g., 1.5 °C or 2.0 °C) would reduce the population exposure to heavy precipitation, thereby avoiding impacts associated with more intense precipitation events. These results contribute to an improved understanding of the future risk of climate extremes, which is paramount for the design of mitigation and adaptation policies in China. [ABSTRACT FROM AUTHOR]