Search

Compared to individual dry or hot events, compound dry and hot events (CDHEs) usually pose more severe economic and societal impacts. A growing body of literature investigates the role of anthropogenic forcing on variations of individual dry and hot events at different spatial scales. However, the attribution of CDHEs in China using model simulations from the Coupled Model Intercomparison Project Phase 6 (CMIP6) has received little attention. This study investigates the anthropogenic influence on CDHEs during summer in China and projects their future occurrences using CMIP6 simulations with data from the Climatic Research Unit (CRU) as observations. The results show that large regions of China experienced a significantly increased frequency of CDHEs during 1971–2010 relative to 1931–1970, which is overall captured by the CMIP6 simulations. Anthropogenic forcing is shown to contribute to the high likelihood of CDHEs in recent decades over most parts of China, with remarkable contributions in southwestern regions. Under future socioeconomic development scenarios, these CDHEs are projected to become more frequent in 2021–2100, which will increase by approximately 51.56–55.00% on average compared to that in 1931–2010. This study could aid the development of mitigation strategies of CDHEs across China under global warming. [ABSTRACT FROM AUTHOR]

Both droughts and hot extremes may exert critical impacts on human society, and their concurrence is no exception. Global warming is expected to increase the frequency and intensity of compound dry and hot events widely, the impacts of which will be particularly severe for sensitive and vulnerable sectors. However, projected risk and impact of compound dry and hot events in China are less assessed, especially in the context of the goals specified by the Paris Agreement in 2015. Here, we show an overall increased risk of compound dry and hot events on human health in China, particularly in eastern regions, for the two warming levels (1.5 and 2°C) based on Coupled Model Intercomparison Project Phase 5 climate models. The population exposure to extreme compound dry and hot events is projected to increase by about 165.46% for the 1.5°C warming and about 200.49% for the 2°C warming compared with the exposure in the present period 1986–2005. These potential variations are driven by climate change and population change with climate effect being the dominantly positive contributor. These findings highlight the urgent need for more efforts to limit warming within 1.5°C to reduce the risk of compound dry and hot events and associated impacts on human society. [ABSTRACT FROM AUTHOR]

Compound weather and climate events, which may cause devastating impacts on economic and social development, have become major threats in the twenty‐first century, especially to countries with complex climate and terrain like China. A better understanding of the driving factors of compound weather and climate events is essential for reducing their impacts, which remains overall lacking. In this study, we evaluate the potential influence of large‐scale circulation patterns on compound dry and hot events (CDHEs) during summer for the period 1921–2016 in mainland China using the composite analysis. Furthermore, the logistic regression model and correlation analysis are also used to confirm the result. The Atlantic Multidecadal Oscillation is found to affect CDHEs for about 18.52% of mainland China, followed by North Atlantic Oscillation and Pacific Decadal Oscillation accounting for about 14.64% and 12.96%, respectively. El Niño–Southern Oscillation affects CDHEs for small areas (about 5.27%). In general, regions with significant impacts of these indices from the three methods are overall consistent (mainly shown in northern parts of mainland China) with relatively larger areas estimated from the correlation analysis. These results are expected to be helpful for understanding occurrences of CDHEs and mitigating their negative impacts in China. Key Points: Compare impacts of climate indices on compound dry and hot events using different methodsInfluence from Atlantic Multidecadal Oscillation (AMO) and North Atlantic Oscillation (NAO) is mainly shown in northern parts of mainland ChinaInfluence from AMO is shown in larger areas than that from the other three climate indices [ABSTRACT FROM AUTHOR]

Under global warming, dry and hot events have been increasing in recent decades and are projected to increase in the future across global land areas. The impacts of compound dry and hot events may lead to increased stress to the natural and human systems than separate dry or hot events. Thus, quantitative assessments of global land areas affected by these compound events are needed to understand their risks. This study focuses on the variation in global land and cropland areas affected by compound dry and hot events for both historical and future periods using observations from Climatic Research Unit (CRU) and simulations from Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models. Based on historical observations and simulations, a substantial increase in the spatial extent of these compound events was detected, especially since the 1980s. Climate model projections under the Representative Concentration Pathway (RCP) 8.5 scenario reveal that both global land and cropland areas affected by compound dry and hot events will increase to approximately 1.7–1.8 times by the end of the 21st century. Based on different thresholds of compound events, the spatial extent of global land areas during the June–July–August (December–January–February) season will increase by 12.38–17.20% (7.83–11.19%) in 2050–2099 relative to that in 1950–1999, and the spatial extent of global cropland areas will increase by 14.69–19.63% (9.60–14.48%). The increase in areas affected by compound dry and hot events may lead to more losses in different sectors in the future and more efforts are needed to cope with their potential impacts. [ABSTRACT FROM AUTHOR]

• Compare two indices for assessing severity changes of compound dry and hot events. • The severity of compound dry and hot events increased in most parts of China. • Increased severity was mainly dominated by temperature compared to precipitation. Compound dry and hot events have received increasing attention due to their serious impacts on different sectors of the society. Understanding their variability is of critical importance for developing adaptation measures to reduce their adverse impacts. Previous studies have shown increased frequency of these compound events in past decades at regional and global scales; however, the investigation of changes in their severity has been rather rare. The objective of this study is to evaluate severity changes of compound dry and hot events for the warm season during the period 1961–2012 in China using two indices, namely, Standardized Compound Event Indicator (SCEI) and Standardized Dry Hot Index (SDHI), based on monthly precipitation and temperature. Results show a significant increase in the severity of compound dry and hot events in most parts of China, which is mainly dominated by temperature compared to precipitation. In addition, significant increase of the spatial extent of compound dry and hot events at different severity levels in China is observed, with more areas affected by these compound events after the 1990s. For large regions from northeast to southwest China, severe conditions of compound dry and hot events are shown to be associated with high risk of agricultural droughts. Both the two indices show similar trends in the severity of compound dry and hot events, which indicates the robustness of increased spatial and temporal patterns, highlighting the pressing need for improved understanding to reduce their adverse impacts. [ABSTRACT FROM AUTHOR]

• Evaluate changes in compound dry and hot events over global maize producing area. • Compare changes in compound dry and hot events based on different drought indicators. • Assess impacts of base periods and thresholds on variations of compound events. The nonexistence of universal drought indicators may lead to uncertainties in the variability of drought, leading to discrepancies in the frequency change in compound dry and hot events (CDHEs) in different regions across the globe. Understanding the impact of the selection of drought indicators on the variability of CDHEs is important for assessing their risks and pursuing mitigation measures. However, quantitative assessments of differences in CDHEs variabilities based on different drought indicators have been lacking. In this study, we evaluate changes in CDHEs based on three different drought indices, including self-calibrating Palmer Drought Severity Index (scPDSI), Standardized Precipitation Index (SPI), and Standardized Precipitation-Evapotranspiration Index (SPEI), and Standardized Temperature Index (STI) as the hot indicator over global maize-producing areas. Generally, the compound dry and hot event defined by SPEI & STI shows a relatively higher magnitude of increase in the frequency and spatial extent compared with that defined by SPI & STI and scPDSI & STI from 1949–1980 to 1981–2012 over most regions. For the top ten maize-producing countries, the frequency of different countries affected by CDHEs at the same time also increases from 1949–1980 to 1981–2012 for these three types of compound events. Consistent patterns are shown based on different thresholds and different base periods in defining compound events. Results from this study could help understand compound event variations and provide useful insights for agricultural management under global warming. [ABSTRACT FROM AUTHOR]

• Evaluate ENSO impacts on multiple categories of compound dry and hot events. • Propose a categorical prediction approach of compound dry and hot events. • Assess prediction performance of compound dry and hot events in northeast China. Due to the devastating impact of compound dry and hot events (CDHEs), reliable early warming information is particularly important for reducing their potential damages. Previous studies on the evaluation and prediction of CDHEs are commonly conducted by defining the compound event as a binary variable (i.e., occurrence or not), which is simple to use but lacks information on the severity level of these events. The prediction of multiple categories (or different severity classes or levels) of CDHEs, which could be useful for operational decision-making, is still lacking. This study employs the ordinal regression model to predict different categories of CDHEs during July-August in northeast China (NEC) based on preceding El Niño-Southern Oscillation (or ENSO) for the period from 1952 to 2012. Correlation analysis and composite analysis show that preceding La Niña is closely related to CDHEs over northeast China and can be used to predict CDHEs several months in advance. The performance of the probabilistic prediction of CDHEs for 1-month to 6-month lead time is assessed using the leave-one-out cross-validation (LOOCV). Results show that the proposed method outperforms the reference prediction (i.e., climatology) for predicting different categories of CDHEs of August in northeast China (with limited prediction skills in July). The CDHE during 1975 is used as a case study to demonstrate the application of the proposed model for categorical prediction. This study could be useful to provide early warning information of CDHEs for decision-making to mitigate their negative impacts. [ABSTRACT FROM AUTHOR]