Heat Wave Events Research Articles

A novel framework for the assessment of hydro-meteorological risks taking into account nature-based solutions

The growing exposure to hydro-meteorological hazards translates into increasing risks for people, territories, and ecosystems. The frequency of occurrence and magnitude of these hazards are expected to further increase in the next decades urging tangible decisions to reduce anthropogenic climate change and adapt to the risks to be faced. In this context, risk assessment is an essential tool for becoming aware of dangers and taking countermeasures. This paper proposes a novel predictive, yet holistic, framework that allows to take into account multiple risks classified according to six research fields, i.e. healthcare, society, ecosystem, heritage, infrastructure, and agriculture. Each contribution to the overall risk is evaluated in terms of economic losses and carbon-dioxide emissions that in turn affect adaptation ability and contribute to exacerbating climate change. Both economic losses and emissions are estimated as a cost per day to support political decision-making processes. In this regard, the framework integrates the effects of adaptation and mitigation strategies to include societal capacities to cope with hazards and respond to their potential consequences. As a guideline, this study reports a preliminary investigation of a heatwave event over a portion of Bologna Province (Italy) concluding that the current use of air-conditioning systems is not sustainable leading to a huge amount of losses. The novel framework can be adopted in future studies for selecting more cost-effective strategies as expected for Nature-based Solutions (NbS). The framework can indeed stand as a tool for estimating the local impact of NbS in the current or future climate scenarios.

Response of Sustainable Solar Photovoltaic Power Output to Summer Heatwave Events in Northern China

Response of Sustainable Solar Photovoltaic Power Output to Summer Heatwave Events in Northern China

A case study on more recent heat wave occurred in South Africa, based on background weather synoptic and dynamic characteristics analysis

This study investigates the characteristics of the more recent heat wave episode in South Africa during January 2023. The evaluation of several meteorological parameters using different reanalysis models and observational datasets have demonstrated that the domination of the anticyclonic pattern over the study area associated with a omega-blocking high. The dominant subtropical Botswana subtropical high along with the low-level omega blocking high pressure over South Africa is one of the main factors for the abnormally hot weather event. The upper-level anomaly wind analysis illustrates the weakening of the zonal wind accompanied by the Rossby waves meridionally stretching. Also, this is correlated to abnormal both tropical easterly and southern westerly jets meandering around an omega-blocking pattern weather system over South Africa which causes warm air mass trapping over the study region. The outcome model results prove the anomalies of the surface higher temperature happened close to the center of the blocking high, where an intensified southward shift of the easterly tropical jet along with the northward shift (jet entrance) of an intensified westerly jet formed two strong cores creating confluent. This research also shows that the January heat wave is demonstrated by an anomalous upper tropospheric anticyclonic inflow (southern hemisphere) causing the strong subsidence, resulting in the surface temperature increase. In comparison with the heat wave event in January 2016, the current study displays the high impact of the internal and local dynamical processes. Also, the current case study addressed in drier condition with less health risk than the previous case study noticed in 2016.

A New Method to Identify the Maximum Time Interval between Individual Events in Compound Rainstorm and Heatwave Events

Growing evidence indicates that extreme heat and rain may occur in succession within short time periods and cause greater impacts than individual events separated in time and space. Therefore, many studies have examined the impacts of compound hazard events on the social-ecological system at various scales. The definition of compound events is fundamental for such research. However, there are no existing studies that support the determination of time interval between individual events of a compound rainstorm and heatwave (CRH) event, which consists of two or more potentially qualifying component heatwave and rainstorm events. To address the deficiency in defining what individual events can constitute a CRH event, this study proposed a novel method to determine the maximum time interval for CRH events through the change in CRH event frequency with increasing time interval between individual events, using southern China as a case study. The results show that the threshold identified by the proposed method is reasonable. For more than 90% of the meteorological stations, the frequency of CRH events has reached a maximum when the time interval is less than or equal to the threshold. This study can aid in time interval selection, which is an important step for subsequent study of CRH events.

Predicting seagrass ecosystem resilience to marine heatwave events of variable duration, frequency and re‐occurrence patterns with gaps

AbstractBackgroundSeagrass, a vital primary producer habitat, is crucial for maintaining high biodiversity and offers numerous ecosystem services globally. The increasing severity and frequency of marine heatwaves, exacerbated by climate change, pose significant risks to seagrass meadows.AimsThis study acknowledges the uncertainty and variability of marine heatwave scenarios and aims to aid managers and policymakers in understanding simulated responses of seagrass to different durations, frequencies and recurrence gaps of marine heatwaves.Materials and MethodsUsing expert knowledge and observed data, we refined a global Dynamic Bayesian Network (DBN) model for a specific case study on Halophila ovalis in Leschenault Estuary, Australia. The model evaluates the potential impact of marine heatwaves on seagrass resilience, examining stress resistance, recovery and extinction risk.ResultsSimulations of different marine heatwave scenarios reveal significant impacts on seagrass ecosystems. Scenarios ranged from 30‐ to 90‐day heatwaves, with longer durations causing more significant biomass decline, reduced resistance, higher extinction risk and prolonged recovery. For instance, recovery time may increase from 18 to 26 months with four 60‐day and from 24 to 47 months with four 90‐day marine heatwave events. Increasing the frequency of marine heatwaves from one to four annual events, with no gaps between occurrences, could raise extinction risk from 11% to 55% for 60‐day events and from 17% to 83% for 90‐day events. However, introducing gaps between heatwaves enhanced resilience, with spaced events showing lower extinction risks and quicker recovery than consecutive yearly events.DiscussionThe study demonstrates the DBN model's utility in simulating the impact of marine heatwaves on seagrass, providing tools for risk‐informed assessment of management and restoration efforts. While these simulations align with existing research on temperature impacts on seagrass, they are not empirical.ConclusionFurther research is necessary to expand our understanding of climate change effects on seagrass ecosystems, guide policy and develop strategies to strengthen marine ecosystem resilience.

Influence of climate extremes on long-term changes in cyanobacterial blooms in a eutrophic and shallow lake

Climate change and human activities have crucial effects on the variations in phytoplankton blooms in lakes worldwide. A record-breaking heatwave and drought event was reported in the middle and lower reaches of the Yangtze River during the summer of 2022, but only little is known about how cyanobacterial blooms in lakes respond to such climate extremes. Here, we utilized MODIS images to generate the area, occurrence, and initial blooming date (IBD) of cyanobacterial blooms in Lake Chaohu from 2000 to 2022. We found that the area and occurrence of cyanobacterial blooms were largely reduced. At the same time, the IBD was delayed in 2022 compared with the previous 20 years. The annual occurrence and mean area of cyanobacterial blooms in 2022 were 17 % and 23.1 km2, respectively, which were the lowest reported levels since the 21st century. The IBD in 2022 was four months late compared with the IBD in 2020. The high wind speed in spring delayed the spring blooms in 2022. The record-breaking heatwaves and drought from June to August reduced the blooms by influencing the growth of cyanobacteria and reducing the flow of nutrients from the watershed into the lake. This study highlights the compound impact of heatwave and drought climate events on reducing cyanobacterial blooms in a long-term period, enhancing additional understanding of the changes in phytoplankton blooms in lakes.

Spatiotemporal dependence of compound drought–heatwave and fire activity in China

Climate strongly influences fire activity, and the alignment of multiple weather and climate extremes, such as co-occurrence of hot and dry, leads to more severe fires. Recognizing the knowledge gap on the combination of compound drought–heatwave events and fire activities, we applied an event coincidence analysis to investigate their spatiotemporal dependence in China during 2003–2020 based on remote sensing active fire data and 2 206-site meteorological observations. It is found that the spatial extent of fire activities and their simultaneous occurrence with compound drought–heatwaves both expanded. The geographical hotspots of frequent fire activities following compound drought–heatwave events were predominantly situated in southwestern and southern China. There was a significant upward trend of fire activities following compound drought–heatwave events, with the ratio of compound drought–heatwave events being followed by fire activities reached 0.70 ± 0.06 in 2013–2020, indicating a growth of 19% compared to the period of 2003–2012. Our findings contribute to a better understanding of the spatiotemporal dependence of compound drought–heatwave and fire activity and provide insights into their mitigation strategies.

Probabilistic medium-range forecasts of extreme heat events over East Asia based on a global ensemble forecasting system

This study suggests a methodology for probabilistic forecasts of the extreme heat events in East Asia based on an operational global ensemble prediction used by the Korea Meteorological Administration (KMA). It focuses on the medium range of up to 11 days, providing probabilities of heatwave and tropical night occurrence each day. Forecast validation in the summer from 2016 to 2021 shows that the deterministic heatwave forecast provides 5 days of optimal forecast range, while the probabilistic forecast can extend the practically predictable range up to 10 days in the Korean Peninsula and 7 days in Japan, respectively. Comparing prediction skills for heatwave and tropical night, the skills for tropical night tend to be inferior, presumably due to complex mechanisms of the tropical night and large uncertainty in the numerical model, such as microphysics and radiation. In addition, the coarse resolution of the operational system does not seem to resolve temperature variability at night. As a case study, this study also examines the forecast of the onset and offset of the 2018 South Korean heatwave event. The temporal evolution of the heatwave matches well with the changes in the upper-level atmospheric circulation pattern, which can be used for useful forecast guidance. This probabilistic forecast based on the global ensemble forecasting system is expected to provide reliable prediction information for heatwaves in advance, reducing exposure to extreme events.

Evaluating the effects of heatwave events on hydrological processes in the contiguous United States (2003–2022)

Extreme heat and drought conditions are affecting water availability in many regions worldwide, leading to negative impacts on human societies, agriculture, and ecosystems. However, current research lacks comprehensive spatiotemporal analysis examining the interplay between multiple hydrological factors and heatwave events, especially in the context of climate change. This research broadly pertains to understanding the dynamics of hydrological factors and their potential responses to heatwave during warm seasons across the contiguous United States for the period from 2003 to 2022. Utilizing data from the Global Land Data Assimilation System (GLDAS), we analyzed surface runoff, evapotranspiration (ET), precipitation, Groundwater Storage (GWS), Root Zone Soil Moisture (RZSM), and Total Water Storage (TWS) to discern annual patterns and the impacts of heatwave. The spatial patterns of heatwave highlighted a higher occurrence in the western, central, and northeastern U.S., with longer average durations in the western and south-central regions. These events are predominantly dry, characterized by low Relative Humidity (RH), except in the southeastern U.S., where heatwave coincide with high RH levels. Post-heatwave analysis indicated a reduction in GWS, TWS, RZSM, and ET, alongside an increase in surface runoff, RH, and precipitation. An in-depth examination of rainfall and temperature dynamics during heatwave revealed weak correlations between rainfall and temperature, as well as between rainfall and heatwave duration, highlighting the complex nature of these interactions. The study also found an enhanced probability of rainfall following heatwave, particularly in the eastern regions, drawing attention to the potential for increased flood risks post-heatwave. Our findings contribute to the growing body of knowledge on the impacts of heatwave on hydrological factors, providing valuable insights for climate change adaptation and water resource management strategies.

Enhancing community resilience to urban heat waves: A simulation-based approach for volunteer management and shelter selection

This study proposes a novel approach to enhancing urban resilience and emergency management practices in the face of heatwave events, often exacerbated by the urban heat island effect. Recognizing the limitations of traditional government-led responses in shelter allocation—characterized by high costs, logistical challenges, and a lack of adaptability—this paper introduces an innovative framework that integrates community-based volunteer efforts with advanced simulation and stochastic modelling techniques. The primary objective is to optimize the allocation of resources and volunteers to improve the efficiency and cost-effectiveness of heatwave response mechanisms. Utilizing Data Envelopment Analysis (DEA), the research identifies and enhances resource and volunteer distribution strategies, paving the way for more effective emergency services. A case study conducted in Blacktown City, Western Sydney, serves to demonstrate the practical application and implications of these strategies, underscoring the necessity for a paradigm shift towards more adaptable, volunteer-focused, and resource-efficient approaches in mitigating the impact of climate-change-induced heat waves on vulnerable urban populations. The anticipated outcomes include measurable improvements in response times, cost reductions, and enhanced volunteer mobilization efficiency.

Using clustering to understand intra-city warming in heatwaves: insights into Paris, Montreal, and Zurich

We introduce a novel methodological advancement by clustering paired near-surface air temperature with the planetary boundary layer height to characterize intra-city clusters for analytics. To illustrate this approach, we analyze three heatwaves (HWs): the 2019 HW in Paris, the 2018 HW in Montreal, and the 2017 HW in Zurich. We assess cluster-based characteristics before, during, and after heatwave events. While the urban clusters identified by this clustering align well with built-up areas obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) land cover data, additional local hot spots spanning several kilometers can also be recognized, extending outside the built-up areas. Using the objective hysteresis model, we further determine the overall strength coefficient of the hysteresis loop between ground storage flux and all-wave downward radiative flux, ranging from 0.414 to 0.457 for urban clusters and from 0.126 to 0.157 for rural clusters during the heatwave periods. Across all cities, we observe a consistent refueling-restoration mode in the cumulative ground heat flux as the heatwaves progress. Future developments of this proposed two-component clustering approach, with the integration of more influential physics and advances in spatial and temporal resolutions, will offer a more comprehensive characterization of cities for urban climate analytics.

Amplification of the discrepancy between simplified and physics-based wet-bulb globe temperatures in a warmer climate

The Simplified Wet Bulb Globe Temperature (sWBGT) is widely used in heat stress assessments for climate-change studies, but its limitations have not been thoroughly explored. Building on recent critiques of sWBGT's use for current climate on global scale, this study examines sWBGT's biases using dynamically-downscaled sub-daily climate projections under multiple future emission scenarios. The analysis is aimed at understanding caveats in the application of sWBGT and the uncertainties in existing climate change analysis dependent on sWBGT. Results indicate sWBGT's biases are heavily influenced by local near-surface air temperature, with overestimation of heat stress in East Asia regions, particularly hot and humid areas, due to static assumptions of radiation and wind speed. This overestimation is amplified in warmer climates, leading to exaggerated projected heat stress increases in future. In contrast, underestimations are found for heat stress levels attributed to low wind speeds and strong radiations, such as over the Tibetan Plateau and certain extreme events. Additionally, sWBGT underestimates variability in extreme heatwave events compared to WBGT in both current and future climates, irrespective of overestimation in absolute heatwave intensities. This study emphasizes the limitations of sWBGT, especially in future warmer climates. Importance of sub-daily data for capturing daily maximum heat stress level and reflecting diurnal variations in different components is also discussed. In conclusion, we recommend using Liljegren's model (i.e., physics-based calculation) with high-resolution sub-daily climate data for more accurate outdoor heat stress assessments in climate change studies.

Identification of compound drought and heatwave events on a daily scale and across four seasons

Abstract. Compound drought and heatwave (CDHW) events can result in intensified damage to ecosystems, economies, and societies, especially on a warming planet. Although it has been reported that CDHW events in the winter season can also affect insects, birds, and the occurrence of wildfires, the literature generally focuses exclusively on the summer season. Moreover, the coarse temporal resolution of droughts as determined on a monthly scale may hamper the precise identification of the start and/or end dates of CDHW events. Therefore, we propose a method to identify CDHW events on a daily scale that is applicable across the four seasons. More specifically, we use standardized indices calculated on a daily scale to identify four types of compound events in a systematic way. Based on the hypothesis that droughts or heatwaves should be statistically extreme and independent, we remove minor dry or warm spells and merge mutually dependent ones. To demonstrate our method, we make use of 120 years of daily precipitation and temperature information observed at Uccle, Brussels-Capital Region, Belgium. Our method yields more precise start and end dates for droughts and heatwaves than those that can be obtained with a classical approach acting on a monthly scale, thereby allowing for a better identification of CDHW events. Consistent with existing literature, we find an increase in the number of days in CDHW events at Uccle, mainly due to the increasing frequency of heatwaves. Our results also reveal a seasonality in CDHW events, as droughts and heatwaves are negatively dependent on one another in the winter season at Uccle, whereas they are positively dependent on one another in the other seasons. Overall, the method proposed in this study is shown to be robust and displays potential for exploring how year-round CDHW events influence ecosystems.

Surface urban heat island analysis based on local climate zones using ECOSTRESS and Landsat data: A case study of Valencia city (Spain)

Extreme heat events in cities are becoming more intense, frequent and prolonged. The spatiotemporal dynamics of surface temperature are closely related to land cover and atmospheric conditions, especially for urban areas with extensive surface heterogeneity. Two high spatial resolution satellites, ECOSTRESS and Landsat, provide land surface temperature (LST) for a typical Mediterranean climate city, Valencia, Spain. In total of 17 images throughout two heatwaves in the period of July and August from 2022 to 2023 were selected to monitor LST and surface urban heat island (SUHI). The Local Climate Zone (LCZ) scheme and hotspot analysis were applied to analyze the patterns of LST and SUHI during and after the heatwaves. Daytime images show LCZ 2/3/6/8 and LCZ C/E/F exhibit elevated SUHI intensity, meanwhile the LCZ 4, A/B and G have lower SUHI. The SUHI intensity of compact buildings (LCZ 1/2/3), LCZ 8/E/G are significantly higher at night, especially on heatwave days, the SUHI of all types increased by 0.1–0.9 °C. Furthermore, the meteorological parameters were introduced trying to explain the obvious diurnal difference of SUHI during heatwaves. This research serves as a proxy for understanding the spatiotemporal dynamics of SUHI during heatwave events, offering valuable insights for city planners and policymakers to enhance thermal comfortable level and effectively cope with extreme weather.

Temporal changes in temperature-related mortality in relation to the establishment of the heat-health alert system in Victoria, Australia

Extreme heat alerts are the most common form of weather forecasting services used in Australia, yet very limited studies have documented their effectiveness in improving health outcomes. This study aimed to examine the temporal changes in temperature-related mortality in relation to the activation of the heat-health alert and response system (HARS) in the State of Victoria, Australia. We examined the relationship between temperatures and mortality using quasi-Poisson regression and the distributed lag non-linear model (dlnm) and compared the temperature-mortality association between the two periods: period 1– prior-HARS (1992–2009) and period 2– post-HARS (2010–2019). Since the HARS heavily weights heatwave effects, we also compared the main effects of heatwave events between the two periods. The heatwaves were defined for three levels, including 3 consecutive days at 97th, 98th, and 99th percentiles. We also controlled the potential confounding effect of seasonality by including a natural cubic B-spline of the day of the year with equally spaced knots and 8 degrees of freedom per year. The exposure-response curve reveals the temperature mortality was reduced in period 2 in comparison with period 1. The relative risk ratios (RRR) of Period 2 over Period 1 were all less than one and gradually decreased from 0.86 (95% CI, 0.72–1.03) to 0.64 (95% CI, 0.33–1.22), and the differences in attributable risk percent increased from 13.2 to 25.3%. The reduction in the risk of heatwave-related deaths decreased by 3.4% (RRp1 1.068, 95% CI, 1.024–1.112 versus RRp2 1.034, 95% CI, 0.986–1.082) and 10% (RRp1 1.16, 95% CI, 1.10–1.22 versus RRp2 1.06, 95% CI, 1.002–1.119) for all groups of people. The study indicated a decrease in heat-related mortality following the operation of HARS in Victoria under extreme heat and high-intensity heatwaves conditions. Further studies could investigate the extent of changes in mortality among populations of differing socio-economic groups during the operation of the heat-health alert system.

Prolonged exposure to elevated temperature leads to severe thermal stress in the broad-nosed pipefish, Syngnathus typhle

ABSTRACT Changes in water temperature may have profound effects on physiology, metabolism, and fish behaviour. However, much of the existing research is based on relatively short-term experiments. In the context of climate change, where water temperatures are increasing seasonally, and the frequency and duration of extreme heatwave events are rising, incorporating longer exposure periods will provide a better understanding of the potential effects of warming on marine species. Here, we tested the effects of prolonged exposure to elevated temperature on broad-nosed pipefish, Syngnathus typhle. Fish were exposed to ambient (20ºC) and high (24ºC) temperatures for a four-month period, during which activity levels, growth and survival were monitored. Fish under high temperature were less active when compared to fish under ambient temperature, grew less, and survival was dramatically decreased. These findings have significant implications for the long-term sustainability of broad-nosed pipefish populations, as the species may struggle to adapt to future ocean conditions.

Effect of heatwaves on daily hospital admissions in Portugal, 2000–18: an observational study

Climate change has increased the frequency, intensity, and duration of heatwaves, posing a serious threat to public health. Although the link between high temperatures and premature mortality has been extensively studied, the comprehensive quantification of heatwave effects on morbidity remains underexplored. In this observational study, we assessed the relationship between heatwaves and daily hospital admissions at a county level in Portugal. We considered all major diagnostic categories and age groups (<18 years, 18-64 years, and ≥65 years), over a 19-year period from 2000 to 2018, during the extended summer season, defined as May 1, to Sept 30. We did a comprehensive geospatial analysis, integrating over 12 million hospital admission records with heatwave events indexed by the Excess Heat Factor (EHF), covering all 278 mainland counties. We obtained data from the Hospital Morbidity Database and E-OBS daily gridded meteorological data for Europe from 1950 to present derived from in-situ observations. To estimate the effect of heatwaves on hospital admissions, we applied negative binomial regression models at both national and county levels. We found a statistically significant overall increase in daily hospital admissions during heatwave days (incidence rate ratio 1·189 [95% CI 1·179-1·198]; p<0·0001). All age groups were affected, with children younger than 18 years being the most affected (21·7% [20·6-22·7] increase in admissions; p<0·0001), followed by the working-age (19·7% [18·7-20·7]; p<0·0001) and elderly individuals (17·2% [16·2-18·2]; p<0·0001). All 25 major disease diagnostic categories showed significant increases in hospital admissions, particularly burns (34·3% [28·7-40·1]; p<0·0001), multiple significant trauma (26·8% [22·2-31·6]; p<0·0001), and infectious and parasitic diseases (25·4% [23·5-27·3]; p<0·0001). We also found notable increases in endocrine, nutritional, and metabolic diseases (25·1% [23·4-26·8]; p<0·0001), mental diseases and disorders (23·0% [21·1-24·8]; p<0·0001), respiratory diseases (22·4% [21·2-23·6]; p<0·0001), and circulatory system disorders (15·8% [14·7-16·9]; p<0·0001). Our results provide statistically significant evidence of the association between heatwaves and increased hospitalisations across all age groups and for all major causes of disease. To our knowledge, this is the first study to estimate the full extent of heatwaves' impact on hospitalisations using the EHF index over a 19-year period, encompassing an entire country, and spanning 25 disease categories during multiple heatwave events. Our data offer crucial information to guide policy makers in effectively and efficiently allocating resources to address the profound health-care consequences resulting from climate change. None.

Large‐scale remote sensing analysis reveals an increasing coupling of grassland vitality to atmospheric water demand

AbstractGrasslands provide important ecosystem services to society, including biodiversity, water security, erosion control, and forage production. Grasslands are also vulnerable to droughts, rendering their future vitality under climate change uncertain. Yet, the grassland response to drought is not well understood, especially for heterogeneous Central European grasslands. We here fill this gap by quantifying the spatiotemporal sensitivity of grasslands to drought using a novel remote sensing dataset from Landsat/Sentinel‐2 paired with climate re‐analysis data. Specifically, we quantified annual grassland vitality at fine spatial scale and national extent (Germany) from 1985 to 2021. We analyzed grassland sensitivity to drought by testing for statistically robust links between grassland vitality and common drought indices. We furthermore explored the spatiotemporal variability of drought sensitivity for 12 grassland habitat types given their different biotic and abiotic features. Grassland vitality maps revealed a large‐scale reduction of grassland vitality during past droughts. The unprecedented drought of 2018–2019 stood out as the largest multi‐year vitality decline since the mid‐1980s. Grassland vitality was consistently coupled to drought (R2 = .09–.22) with Vapor Pressure Deficit explaining vitality best. This suggests that high atmospheric water demand, as observed during recent compounding drought and heatwave events, has major impacts on grassland vitality in Central Europe. We found a significant increase in drought sensitivity over time with highest sensitivities detected in periods of extremely high atmospheric water demand, suggesting that drought impacts on grasslands are becoming more severe with ongoing climate change. The spatial variability of grassland drought sensitivity was linked to different habitat types, with declining sensitivity from dry and mesic to wet habitats. Our study provides the first large‐scale, long‐term, and spatially explicit evidence of increasing drought sensitivities of Central European grasslands. With rising compound droughts and heatwaves under climate change, large‐scale grassland vitality loss, as in 2018–2019, will thus become more likely in the future.

Characteristic changes in compound drought and heatwave events under climate change

Compound drought and heatwave events (CDHWs) have severe impacts on both humans and ecosystems, and climate change is gradually increasing their frequency. Therefore, it is crucial to deeply analyze the relative impacts of droughts, heatwaves, and their coupling in CDHWs to better understand the extent to which individual events and their interactions contribute to CDHWs formation. The analysis of Earth System Models (ESMs) simulations indicates that the frequency and intensity of CDHWs increased significantly during the historical period (1941–2014), showing a notable rise after 1990 and remaining in a state of high fluctuation. Their total frequency and cumulative heat reveal a decreasing trend after reaching their maximum in the middle of the 21st century, with the greatest rate of decline occurring in the SSP585 scenario. Furthermore, the duration of each CDHWs occurrence will continue to increase, particularly for the SSP370 and SSP585 scenarios, which have a maximum value exceeding 18 days. The intensity of these events is expected to continue to increase in the future. The relative contribution of heatwaves to CDHWs averages above 40%, which is the dominant contribution. This can rise to 80% in some areas in the SSP585 scenario, while the relative contribution of droughts to CDHWs is only about half that of heatwaves. Nonetheless, the relative contribution of drought-heatwave coupling effects to CDHWs should not be overlooked, particularly in North Asia and North Africa, where the contribution is more pronounced. In addition, the results of the ESMs analyses indicate that the likelihood of drought and heatwave occurrence is significantly higher under anthropogenic disturbances, and that the coupling effect between them is stronger. This trend is generalized to all regions of the globe and is particularly evident in drylands. Attribution analyses indicate that anthropogenic forcing is the primary cause of the increases in CDHWs. The above findings emphasize that we are facing a serious threat from CDHWs and should take timely action to address the impacts of climate change.

Global Analysis of Surface Ocean CO2 Fugacity and Air‐Sea Fluxes With Low Latency

AbstractThe Surface Ocean CO2 Atlas (SOCAT) of CO2 fugacity (fCO2) observations is a key resource supporting annual assessments of CO2 uptake by the ocean and its side effects on the marine ecosystem. SOCAT data are usually released with a lag of up to 1.5 years which hampers timely quantification of recent variations of carbon fluxes between the Earth System components, not only with the ocean. This study uses a statistical ensemble approach to analyze fCO2 with a latency of one month only based on the previous SOCAT release and a series of predictors. Results indicate a modest degradation in a retrospective prediction test for 2021–2022. The generated fCO2 and fluxes for January–August 2023 show a progressive reduction in the Equatorial Pacific source following the La Niña retreat. A breaking‐record decrease in the northeastern Atlantic CO2 sink has been diagnosed on account of the marine heatwave event in June 2023.