Weather and Climate Extremes最新文献

Compound flash drought and heatwave (FDHW) events have garnered increasing amounts of attention due to their substantial impacts on agriculture, water resources, and public health. However, studies on their intensity and classification in China are limited. In this study, we classified FDHW events in China from 1980 to 2022 using a classification framework designed to address regional patterns and explore their characteristics further. The results showed that FDHW events in northern China mostly occurred in early to mid-summer, whereas in southern China, excluding the Southwest River Basin, they occurred predominantly in mid to late summer. Furthermore, the spatial coverage of FDHW events across China significantly expanded. From 1980 to 2022, FDHW events in China evolved toward higher intensities and longer durations. This trend was especially notable in the Jiang-Huai River Basin, the main grain-producing region and a densely populated area of China. From the perspective of land‒atmosphere coupling, the amplifying effect of flash droughts and high temperatures increased with their intensity. When high temperatures reached the extreme level, the amplification effect on flash droughts was evident: 35.76% from the water deficit perspective and 38.82% from the soil moisture perspective. During extreme flash droughts, the amplification effect on high temperatures intensified: 41.51% from the water deficit perspective and 45.06% from the soil moisture perspective. The Southwest River Basin became a hotspot for the interaction between flash droughts and high temperatures. This study has implications for developing science-based policies to tackle risks in the water, energy and food sectors in China.

Hailstorms are severe weather events with the potential for devastating impacts. The consequences can be significantly worsened when hail events are accompanied by strong winds, intensifying both hail momentum and damage to property sidings and windows. Additionally, rainfall extremes during hailstorms can disrupt the drainage systems, potentially leading to flash flooding. Therefore, understanding the inter-dependencies and joint behaviour of these hazards is crucial for developing effective risk mitigation strategies. In this study, we conduct a multivariate probabilistic assessment of concurrent hail, wind, and rainfall extremes over the Alberta's “hail alley” using radar and ground-based observations. The analysis comprehensively explores individual hazards, as well as bivariate and trivariate scenarios using a vine copula approach. We quantify individual, conditional, and joint return periods (JRPs) for the various scenarios. Findings indicate that in both wind-driven hail and hail-rainfall extreme hazards, the joint occurrences based on JRP, can be underestimated by 20% and 70% when assuming independence, respectively, which has substantial implications for risk assessment and management, as well as infrastructure design and maintenance. The analysis of the trivariate case suggests the potential for the concurrent occurrence of multiple hazards in the region. Furthermore, results show that Archimedean copula families outperform elliptical copulas in simulating extreme variables related to compound events associated with hailstorms. The study stresses the importance of assessing the joint behaviour of these hazard components in hailstorms, with the objective of mitigating potential impacts on vulnerable regions.

In July 2022, regions with elevations exceeding 5 000 m on the inner Tibetan Plateau (TP) witnessed a record-breaking heatwave. But how the atmospheric circulation and soil moisture play roles in the occurrence and maintenance of the heatwave in such high elevation climate sensitive region remains unknown. Here, by using the flow analogue method, we find that negative soil moisture anomalies explain more than half of the extreme high temperature during the heatwave, while atmospheric circulation explains less than half. The high soil moisture-temperature coupling metric and the increased correlation between latent heat flux and soil moisture during heatwave revealed strong land-atmosphere feedback in the Qiangtang Plateau which has amplified the heatwave. Analyses of numerical experiments confirm that the presence of interaction between soil moisture and the atmosphere has increased the intensity of hot extreme event under the same atmospheric circulation conditions. Under the warming background, land-atmosphere coupling leads to a faster increase in extreme high temperatures compared to the global mean warming rate, and it is twice as fast as the increase in extreme high temperatures without coupling. We highlight the increased probability of extreme high temperature over the TP in the future due to soil moisture feedback and the results are hoped to inform policymakers in making decisions for climate adaptation activities.

Rapid urbanisation along the coasts of the world in recent decades has increased their vulnerability to storm surges, especially in response to mean sea level rise. The unique geographical and social conditions of Copenhagen, a major European coastal city, have prompted urban expansion along Køge Bay to the south of the city. However, this new urbanisation area is confronted with the common obstacle of developing a coastal defence strategy, i.e., the lack of long-term observational data required to determine a reliable storm surge protection level. This study aims to address this issue by developing a framework that integrates historical records of extreme storm surge events into coastal defence strategies, using Copenhagen as a case study. We propose a four-step work framework, including (1) Data collection and analysis: We collected and analysed data from neighbouring cities and used modelling and reanalysis data sets. By combining these sources, we aim to reconstruct historical time series for the study site dating back to 1836. This extended information set enhances our understanding of past storm surge events. (2) Statistical modelling and forecasting: Using Bayesian statistical methods, we fitted the historical storm surge data to appropriate probability distributions. This enabled us to generate probabilistic forecasts of storm surge magnitudes, providing insight into the likelihood of future events and their potential impacts on the coastal area. (3) Sensitivity analyses: We performed sensitivity experiments using Markov chain Monte Carlo (MCMC) methods to identify the most influential parameters, such as thresholds, that affect storm surge levels. This analysis improved our understanding of the key drivers of storm surge events and their uncertainties, further informing coastal defence strategies. (4) Expert judgement and risk management: Expert judgements are implemented to establish the necessary security level to manage flood risks in the city. This helps to ensure that high-impact, low-probability events are adequately considered in risk management efforts. Following this framework, we can develop a comprehensive understanding of storm surge risks in the urbanised region south of Copenhagen and use historical data to inform coastal defence strategies. This study emphasises the importance of incorporating long-term observational data and expert insights to improve the resilience of coastal cities facing the challenges of urbanisation and climate change.

Unprecedentedly large areas were burned during the 2016/17 and 2022/23 fire seasons in south-central Chile (34-39°S). These seasonal-aggregated values were mostly accounted for human-caused wildfires within a limited period in late January 2017 and early February 2023. In this paper, we provide a comprehensive analysis of the meteorological conditions during these events, from local to hemispheric scales, and formally assess the contribution of climate change to their occurrence. To achieve this, we gathered monthly fire data from the Chilean Forestry Corporation and daily burned area estimates from satellite sources. In-situ and gridded data provided near-surface atmospheric insights, ERA5 reanalysis helped analyze broader wildfire features, high-resolution simulations were used to obtain details of the wind field, and large-ensemble simulations allowed the assessment of climate change's impact on extreme temperatures during the fires. This study found extraordinary daily burned area values (>65,000 ha) occurring under extreme surface weather conditions (temperature, humidity, and winds), fostered by strong mid-level subsidence ahead of a ridge and downslope winds converging towards a coastal low. Daytime temperatures and the water vapor deficit reached the maximum values observed across the region, well above the previous historical records. We hypothesize that these conditions were crucial in exacerbating the spread of fire, along with longer-term atmospheric processes and other non-climatic factors such as fuel availability and increasing human-driven ignitions. Our findings further reveal that climate change has increased the probability and intensity of extremely warm temperatures in south-central Chile, underscoring anthropogenic forcing as a significant driver of the extreme fire activity in the region.

Over the past two decades, there has been a significant shift in tropical cyclone (TC) activity in the western North Pacific (WNP) basin during the boreal summer. Our analysis of data spanning from 1979 to 2021 reveals significant shifts in the WNP TC characteristics and rainfall pattern variation. To deepen our understanding of TC-related precipitation dynamics, we expressly address the difference between TC-related core precipitation (TCP) and remote precipitation (TRP). The results show that TRP significantly impacts the East Asian (EA) continent, especially on the Korean Peninsula. Notably, TCP exhibits decadal variability, with a pronounced negative correlation identified between it and the Pacific decadal oscillation (PDO) following a strong climate shift. This pivotal shift was marked by the PDO first transitioning to its negative phase in 1997, a notable change since 1979, resulting in a marked increase in TC-related extreme rainfall over the EA area. Concurrently, the rising sea surface temperatures (SSTs) over the WNP have intensified the western Pacific subtropical high (WPSH) circulation. The easterly steering flow associated with the WPSH then strengthened, leading to the continental migration of TC trajectories, thereby intensifying TC-related extreme precipitation.

Terrestrial vegetation plays a vital role in global carbon recycling, but it is also affected by compound events (CEs); however, little is known about the impacts of these CEs on vegetation in terms of their occurrence and magnitude. Using meteorological observations and vegetation indices (leaf area index (LAI), gross primary productivity (GPP), and net primary productivity (NPP)) from 1981 to 2020, we explored the occurrence of 13 CEs types and identified the dominant CEs types across different eco-geographical regions of China, and quantified the response of various vegetation types to dominant CEs. We found that CEs of extreme hot-dry, extreme hot-dry-high fire weather, dry-high fire weather, and high fire weather-strong wind were the dominant types of compound events during the growing season in China, and their hazards increased at a rate of >0.1HI/10a during 1981–2020. We further detected that more than 60% of the total vegetation areas showed a strong negative correlation with compound extreme hot-dry-high fire weather-strong wind events, which was relatively higher than compound extreme hot-dry events. The response of vegetation to compound events varied at the national scale, which was related to the vegetation type, dominant compound event type, and local natural conditions. This study highlights the benefits of a multivariate perspective on compound events and reveals the regional differences in the response of vegetation to compound events, which can provide initial guidance to assess the regional compound event risk of vegetation against the background of carbon neutrality by 2060.

In this work, we compare the rate of warming of summertime extreme temperatures (summer maximum value of daily maximum temperature; TXx) relative to the local mean (summer mean daily maximum temperature; TXm) over the Northern Hemisphere in observations and one set of large ensemble (LE) simulations. During the 1979–2021 historical period, observations and simulations show robust warming trends in both TXm and TXx almost everywhere in the Northern Hemisphere, except over the eastern U.S. where observations show a slight cooling trend in TXx, which may be a manifestation of internal variability. We find that the observed warming rate in TXx is significantly smaller than in TXm in North Africa, western North America, Siberia, and Eastern Asia, whereas the warming rate in TXx is significantly larger over the Eastern U.S., the U.K., and Northwestern Europe. This observed geographical pattern is successfully reproduced by the vast majority of the LE members over the historical period, and is persistent (although less intense) in future climate projections over the 2051–2100 period. We also find that these relative warming patterns are mostly driven by the local hydroclimate conditions. TXx warms slower than TXm in the hyper-arid, arid, semi-arid and moist regions, where trends in the partitioning of the turbulent surface fluxes between the latent and sensible heat flux are similar during regular and extreme hot days. In contrast, TXx warms faster than TXm in dry-subhumid regions where trends in the partitioning of the surface fluxes are significantly different between regular and extreme hot days, with a larger role of sensible heat flux during the extreme hot days.