Compound extreme events and health risks in China: A review

Impacts of compound extreme weather events on summer ozone in the Beijing-Tianjin-Hebei region

Comparison and evaluation of the performance of reanalysis datasets for compound extreme temperature and precipitation events in the Qilian Mountains

Rapid increase in warm‒wet compound extreme events with high health risks in southern China: Joint influence of ENSO and the Indian Ocean

The northern permafrost regions are increasingly experiencing frequent and intense extreme events, with a rise in the occurrence of compound extreme events. Many climate-related hazards in these areas are driven by such compound events, significantly affecting the stability and functionality of vegetation ecosystems. However, the cumulative and lagged effects of compound extreme events on vegetation remain unclear, which may lead to an underestimation of their actual impacts. This study provides a comprehensive analysis of the spatiotemporal variations in compound extreme events and the vegetation response to these events in the northern permafrost regions from 1982 to 2022. The primary focus of this study is on examining the cumulative and lagged effects of compound extreme climate events on the Kernel Normalized Difference Vegetation Index (kNDVI) during the growing seasons. The results indicate that in high-latitude regions, the frequency of extreme high temperature–precipitation compound events and high temperature–drought compound events have increased in 58.0% and 67.0% of the areas, respectively. Conversely, the frequency of extreme low temperature–drought compound events and extreme low temperature–precipitation compound events has decreased in 70.6% and 57.2% of the areas, with the high temperature–drought compound events showing the fastest increase. The temporal effects of compound extreme events on kNDVI vary with vegetation type; they produce more cumulative and lagged effects compared with single extreme high-temperature events and fewer effects compared with single extreme precipitation events, with compound events significantly affecting forest and grassland ecosystems. Notably, extreme high temperature–precipitation compound events exhibit the strongest cumulative and lagged effects on vegetation, while extreme low temperature–drought compound events influence wetland and shrubland areas within the same month. This study underscores the importance of a multivariable perspective in understanding vegetation dynamics in permafrost regions.

Global warming has increased the probability of extreme climate events, with compound extreme events having more severe impacts on socioeconomics and the environment than individual extremes. Utilizing the Coupled Model Intercomparison Project Phase 6 (CMIP6), we predicted the spatiotemporal variations of compound extreme precipitation-high temperature events in China under three Shared Socioeconomic Pathways (SSPs) across two future periods, and analyzed the changes in exposed populations and identified influencing factors. From the result, we can see that, the CMIP6 effectively reproduces precipitation patterns but exhibits biases. The frequency of compound event rises across SSPs, especially under high radiative forcing, with a stronger long-term upward trend. Furthermore, the economically developed areas, notably China's southeastern coast and North China Plain, will be hotspots for frequent and intense compound extreme events, while other regions will see reduced exposure. Finally, in the long-term future (2070-2100), there is a noteworthy shift in population exposure to compound events, emphasizing the increasing influence of population factors over climate factors. This highlights the growing importance of interactions between population and climate in shaping exposure patterns.

Abstract. The Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) was used to study the effect of extreme weather events on ozone in the US for historical (2001–2010) and future (2046–2055) periods under the RCP8.5 scenario. During extreme weather events, including heat waves, atmospheric stagnation, and their compound events, ozone concentration is much higher compared to the non-extreme events period. A striking enhancement of effect during compound events is revealed when heat wave and stagnation occur simultaneously as both high temperature and low wind speed promote the production of high ozone concentrations. In regions with high emissions, compound extreme events can shift the high-end tails of the probability density functions (PDFs) of ozone to even higher values to generate extreme ozone episodes. In regions with low emissions, extreme events can still increase high-ozone frequency but the high-end tails of the PDFs are constrained by the low emissions. Despite the large anthropogenic emission reduction projected for the future, compound events increase ozone more than the single events by 10 to 13 %, comparable to the present, and high-ozone episodes with a maximum daily 8 h average (MDA8) ozone concentration over 70 ppbv are not eliminated. Using the CMIP5 multi-model ensemble, the frequency of compound events is found to increase more dominantly compared to the increased frequency of single events in the future over the US, Europe, and China. High-ozone episodes will likely continue in the future due to increases in both frequency and intensity of extreme events, despite reductions in anthropogenic emissions of its precursors. However, the latter could reduce or eliminate extreme ozone episodes; thus improving projections of compound events and their impacts on extreme ozone may better constrain future projections of extreme ozone episodes that have detrimental effects on human health.

This study analyzes the change characteristics of compound extreme events (CEEs) of temperature and precipitation (including warm‐wet, warm‐dry, cold‐wet and cold‐dry) in China on interannual and interdecadal scales between 1901 and 2019. The results demonstrate a long‐term increasing trend and interdecadal oscillations in CEEs total frequency. However, the frequency of each type of CEEs changes in a different manner compared with total CEEs frequency. There are fewer CEEs but increasing warm‐dry during 1901–1950. The period 1951–1995 are characterized by frequent cold CEEs (cold‐wet and cold‐dry), cold‐wet are largely distributed in most areas except for northeast and coastal areas of China, while cold‐dry are distributed in most areas except for the northwest regions of China. There are frequent warm CEEs (warm‐wet and warm‐dry) and fewer cold CEEs during 1996–2019. Warm‐wet frequently occurs in the Tibetan Plateau and northwest China, and warm‐dry mainly concentrates in southwest and northern China during this period. The frequency of warm‐dry and cold‐wet were higher than that of warm‐wet and cold‐dry over the past 119 years, whereas warm‐wet increased fastest in the northwest region after 1996, consistent with the warming and wetting characteristics in the northwest region of China. Further study show that long‐term change and low frequency oscillations have the greatest impact on CEEs among different time scale factors. Furthermore, the temperature rise caused by climate change affects the interdecadal characteristics of CEEs in China through the changes of circulation fields such as East Asian trough and subtropical high and the configuration between them.

While the influence of compound extreme events is gaining attention with advancing extreme climate research, the variations in their impacts on regional crop production require further exploration. Here, we primarily analyze the changes in compound hot‐dry events and compound hot‐wet events in China from 1985 to 2019, based on meteorological observations from 686 stations. Then, their contributions to losses in cropland net primary productivity (CNPP) are identified using the extreme gradient boosting and Shapley additive explanations models. Results indicate that compound extreme events have become increasingly frequent, persistent, and severe over the past 35 years. With the increasing risks of compound extreme events, greater CNPP losses are observed in the northern regions compared to the southern regions. Throughout the growing season, CNPP losses caused by compound extreme events initially increase, peak in summer, and then gradually decrease. CNPP losses in China are primarily influenced by compound hot‐dry events. From north to south, the events dominating CNPP losses shift sequentially from compound daytime hot and dry events to compound day‐night hot and dry events, and finally to compound nighttime hot and dry events. This study explores the threats posed by compound extreme events to regional crop production and provides new insights into extreme climate risks in China, supporting climate‐adaptive agricultural development.

Compound extreme weather events are frequent and exhibit new features in the context of global change. This study unravels the characteristics, variations, and driving factors of compound extreme temperature‐extreme dust events in the Gobi Desert (GD) during the springs of 2000–2023. The temperature in the GD is high before extreme dust events (EDEs), while that is low during EDEs. Correspondingly, extreme hot events (EHEs) occur prior to EDEs and extreme cold events (ECEs) occur during EDEs. The frequency of EHEs associated with EDEs in 2012–2023 is 100% higher than that in 2000–2011, while the frequency of ECEs associated with EDEs in 2012–2023 is 75% lower than that in 2000–2011. Accordingly, compound extreme events associated with EDEs shift from EDE‐ECEs to EHE‐EDEs. By strengthening East Asian anomalous high pressure, enhanced Arctic Oscillation during the pre‐EDE periods and weakened Eurasian teleconnection during EDEs increases EHEs and decreases ECEs, respectively, and combined drive the shift in the compound extreme events. This study reveals a new feature of compound extreme weather events in the context of climate change, which manifests as the shift from EDE‐ECEs to EHE‐EDEs in the GD. The occurrence of more EHE‐EDEs will put already fragile ecosystems of the GD at even greater risk. Therefore, the containment of global warming, especially in arid and semiarid regions, is necessary and urgent.

Contrasting vegetation response to compound temperature and moisture extremes across Northern Hemisphere.

Spatial-temporal dynamics of population exposure to compound extreme heat-precipitation events under multiple scenarios for Pearl River Basin, China

<p>Compound events are the extreme weather and climate events that result from a combination of physical processes (climatic drivers and extreme events) occurring across different temporal (successive) and spatial (simultaneous) scales. Further, multiple drivers with a complex chain of processes, conditional dependencies and extreme return periods of such events lead to severe socio-economic and environmental impacts. The quantification and predictions of such extreme events still need to be advanced with changing climate and global warming. In previous literature, it is documented that precipitation and temperature are the fundamental drivers of different climatic variations resulting in compound extreme events. In light of these perspectives, a Standardized Compound Extreme Event Index (SCEEI) is modelled in this study integrating the joint properties of Standardized Precipitation Index (SPI) and Standardized Temperature Index (STI) that are derived from precipitation and temperature; respectively employing the India Meteorological Department (IMD) data series. The Gaussian model-based multivariate technique is applied to derive SCEEI. The severity of drought and extreme temperature at an annual scale is analysed using SCEEI for two neighbouring river basins of Eastern India, i.e. Brahmani and Baitarani river basins for the study period of 1979-2018. The variations of the extreme events and their severity are further assessed at a multi-decadal scale. The trends of these compound events for different time scales are checked by the Mann-Kendall test followed by Sen’s slope estimator. The multi-decadal time scale is divided as D<sup>1</sup> (1979-1988), D<sup>2</sup> (1989-1998), D<sup>3</sup> (1999-2008), and D<sup>4</sup> (2009-2018). It is observed that SCEEI captures drought events along with extreme temperatures reasonably well than the individual index (SPI and STI). The outcomes of this study conclude that the multivariate approach is a reliable perspective to assess the severity of compound extreme events. The developed approach in this study is novel for monitoring the compound extreme event severity under the non-availability basin-scale hydrological data that is advantageous for several worldwide data scare river basins to purpose an adaptation strategy and achieve the Sustainable Development Goals (SDGs).</p><p><em>Keywords:</em> Compound events; SCEEI; IMD; multi-decadal; Brahmani; Baitarani; SDGs</p>

By using the daily average wind speed and precipitation data of 125 stations in Jiangsu and Anhui Provinces of China from 1961 to 2020 and the monthly NCEP/NCAR reanalysis data, the interannual variation characteristics and its possible reasons of spring compound extreme wind and precipitation events in the Jiangsu–Anhui region were discussed. Results show that the spring compound extreme wind and precipitation events generally present a lesser distribution in the south and more in the north. The events occurring in south (north) of 32° N are basically less than (above) three days, and in some areas of northern Jiangsu, it can reach more than four days. On a regional average, the spring compound extreme wind and precipitation events have presented a significant downward trend in the past 60 years. In addition, there was an interdecadal mutation from more to less in the early 1990s, with the most significant decline in the coastal areas of northern Jiangsu. Further analysis reveals that the synthetic height anomaly field at 500 hPa corresponding to the frequent occurrence of the spring compound extreme wind and precipitation events is positive in the northern region of 45° N, while it is negative in the southern region of 45° N, which enhances the high pressure in high latitudes, increases the meridional gradient of circulation, and promotes the activity of high-latitude short-wave trough ridges and cold air. Meanwhile, a strong southwest airflow exists in the corresponding middle and low latitudes at 850 hPa, so the water vapor from the Bay of Bengal can be continuously transported to the Jiangsu–Anhui region. Overall, the abundant water vapor transportation and the convergence of southward cold air in high latitudes are conducive to the occurrence of extreme wind and precipitation events.

Association between compound extreme weather event types and the spectrum of emergency ambulance calls: A metropolitan study in Shenzhen

Global warming, sea-level rise, and rapid urbanization all increase the risk of compound extreme weather events, presenting challenges for the operation of urban-related infrastructure, including transportation infrastructure. In this context, some questions become important. For example, what are the temporal and spatial distribution and development trends of transportation resilience when considering the impact of multilpe extreme weather events on the urban transportation system? What is the degree of loss of urban transportation resilience (UT resilience) under different extreme event intensities, and how long will it take for the entire system to restore balance? In the future, if extreme weather events become more frequent and intense, what trends will urban transportation resilience show? Considering these problems, the current monitoring methods for transportation resilience under the influence of extreme events are lacking, especially the monitoring of the temporal and spatial dynamic changes of transportation resilience under the influence of compined extreme events. The development of big data mining technology and deep learning methods for spatiotemporal predictions made the construction of spatiotemporal data sets for evaluating and predicting UT resilience-intensity indicators possible. Such data sets reveal the temporal and spatial features and evolution of UT resilience intensity under the influence of compound extreme weather events, as well as the related future change trends. They indicate the key research areas that should be focused on, namely, the transportation resilience under climate warming. This work is especially important in planning efforts to adapt to climate change and rising sea levels and is relevant to policymakers, traffic managers, civil protection managers, and the general public.