Weather and Climate Extremes最新文献

Severe compound drought-heatwave events were observed over three regions of the Contiguous United States (CONUS), Northwest (NW), Great Plains (GP), and Northeast (NE) regions, during July and August 2022. In this study, we have found that the developments of these drought-heatwave events were shaped by different land-atmosphere coupling behaviors which are associated with water and energy limitation regimes in these regions. In the NW and GP regions, the surface soil moisture (SM) and evapotranspiration (ET) were coupled through water-limited processes. Heatwaves in these two regions were affected by the decrease of ET and the available SM due to the precipitation deficit. This type of land-atmosphere coupling was especially prominent in the GP. In the NE region, the heatwave governed ET through the increase of potential ET (PET) based on energy-limited coupling, which played a crucial role in the development of drought.

The impacts of the different land-atmosphere coupling behaviors on the predictability of the 13-km Geophysical Fluid Dynamics Laboratory (GFDL) System for High-resolution prediction on Earth-to-Local Domains (SHiELD) were also investigated by checking its 10-day forecasts during the same period. The analysis was particularly focused on the GP and NE regions, where different land-atmosphere coupling behaviors were observed. The model's warm bias in the GP region was associated with the overestimated net radiation, and the bias was further amplified through the water-limited coupling. In the NE region, the PET-related variables, including surface air temperature, influenced the predictability of drought onset by limiting ET through the energy-limited coupling. Based on our findings, this study highlights the crucial role of land-atmosphere coupling behaviors and provides a scientific strategy for enhancing the model predictability of compound drought-heatwaves.

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.