Meteorological Extremes Research Articles

Vulnerability to extreme weather events: mapping future hazards in Wielkopolska region, Poland

The aim of this study is to assess future hazards due to extreme meteorological events in the Wielkopolska region, Poland, based on five climate model projections and three scenarios: SSP126, 370, and 585. The paper analyzes the changes of mean and extreme precipitation, mean and extreme temperatures, and humidity index, as well as changes in difference between maximum temperatures observed from day to day and changes in difference between mean atmospheric pressure at the sea level observed from day to day. Additionally, we look at possible future occurrence of wildfires due to changes in fire weather conditions. Based on climate model projections, future hazard due to extreme meteorological events in Wielkopolska region is to be more serious and will be most noticeable in the end of twenty-first century and for two higher scenarios: SSP370 and SSP585. For near future, 2021–2050, projected conditions of meteorological extremes for analyzed scenarios are quite consistent. Therefore, there is a strong need for implementing adaptation actions. Nevertheless, such activities are so far lacking, and several adaptation options are not present in local and national legislation, even though they are recognized as effective.

Sap Flow Density of the Prevailing Tree Species in a Hemiboreal Forest under Contrasting Meteorological and Growing Conditions

This study aimed to assess the adaptive capacity of the dominant tree species in Lithuania, namely Scots pine, Norway spruce, and silver birch, to current climate conditions based on their changes in transpiration expressed through the tree sap flow intensity. The species-specific responses were investigated at two typical edaphically different forest sites with water-limited and water-saturated soils. Contrasting events like overflow in 2017 and drought in 2019 provided an opportunity to detect the adaptative capacity of the monitored tree species to these meteorological extremes. Norway spruce trees, due to having both the most intense sap flow at the beginning of the growing season and the longest period of active transpiration, demonstrated the highest annual transpiration rate, regardless of the hydrological regime of the site. Their decreased resilience to subsequent biogenic damage caused by pests due to a significant decrease in sap flow density during intense and prolonged droughts may reduce their importance in Lithuanian forestry. Silver birch trees, which demonstrated a reduction in sap flow after a drought following the untimely drop of their leaves and the end of active vegetation, even at the end of a prolonged warm period, can be seen to not have appropriate adaptations to current climate conditions. Scots pine trees are the best adapted to mitigating the recent threats of climate change.

Disaster effects of climate change in High Mountain Asia: State of art and scientific challenges

High Mountain Asia (HMA) shows a remarkable warming tendency and divergent trend of regional precipitation with enhanced meteorological extremes. The rapid thawing of the HMA cryosphere may alter the magnitude and frequency of nature hazards. We reviewed the influence of climate change on various types of nature hazards in HMA region, including their phenomena, mechanisms and impacts. It reveals that: 1) the occurrences of extreme rainfall, heavy snowfall, and drifting snow hazards are escalating; accelerated ice and snow melting have advanced the onset and increased the magnitude of snowmelt floods; 2) due to elevating trigger factors, such as glacier debuttressing and the rapid shift of thermal and hydrological regime of bedrock/snow/ice interface or subsurface, the mass flow hazards including bedrock landslide, snow avalanche, ice-rock avalanches or glacier detachment, and debris flow will become more severe; 3) increased active-layer detachment and retrogressive thaw slumps slope failures, thaw settlement and thermokarst lake will damage many important engineering structures and infrastructure in permafrost region; 4) multi-hazards cascading hazard in HMA, such as the glacial lake outburst flood (GLOF) and avalanche-induced mass flow may greatly enlarge the destructive power of the primary hazard by amplifying its volume, mobility, and impact force; and 5) enhanced slope instability and sediment supply in the highland areas could impose remote catastrophic impacts upon lowland regions, and threat hydropower security and future water shortage. In future, ongoing thawing of HMA will profoundly weaken the multiple-phase material of bedrock, ice, water, and soil, and enhance activities of nature hazards. Compounding and cascading hazards of high magnitude will prevail in HMA. As the glacier runoff overpasses the peak water, low flow or droughts in lowland areas downstream of glacierized mountain regions will became more frequent and severe. Addressing escalating hazards in the HMA region requires tackling scientific challenges, including understanding multiscale evolution and formation mechanism of HMA hazard-prone systems, coupling thermo‒hydro‒mechanical processes in multi-phase flows, predicting catastrophes arising from extreme weather and climate events, and comprehending how highland hazards propagate to lowlands due to climate change.

Long-term trend and variability in surface temperatures over Emilia-Romagna from 1962 to 2022

Scientific interest is increasingly drawn towards regional meteorological extremes, given their impacts on populations, infrastructure, and ecosystems. These extremes are shaped by complex interactions between internal climate variability and long-term trends. The aim of the present work is to evaluate changes in high-frequency variability and the influence of long-term trends on the frequency of occurrences of extremes, with a focus on surface temperatures over the period from 1962 to 2022 in Emilia-Romagna, a region of Northern Italy. Daily data of 2 m air temperatures averaged over the region are retrieved from ERACLITO, a high-resolution climate analysis. The distributions of daily temperature anomalies show a general broadening in 1992–2022 with respect to 1962–1991. This is true for maximum, minimum, and mean daily surface temperatures, especially during the summer and spring seasons. A significant warming trend of 0.37 °C/decade is detected in annual mean surface temperatures over the period considered. The study is completed with a comparison between the observed frequency of record-breaking annual temperature events, a hypothetical stationary climate distribution and a theoretical derivation that accounts for changes in trends and variability. During the last decade, the theoretical count of extreme events is 1.26, which yields a likelihood of 86% that this is owed to the trend rather than interannual variability. Idealized experiments demonstrate that the expected occurrences of record-breaking events in future decades depend on the warming rate rather than the warming level. Finally, an analysis performed at seasonal level shows that the majority (minority) of record events are occurring in the summer (spring) seasons.

Multivariate analysis of long-term climate data in connection with yield, earliness and the problem of global warming.

Climate change is the key challenge to agriculture in the XXI century. Future agricultural techniques in the Russian Federation should involve the optimization of land utilization. This optimization should apply algorithms for smart farming and take into consideration possible climate variations. Due to timely risk assessment, this approach would increase profitability and production sustainability of agricultural products without extra expenditures. Also, we should ground farming optimization not on available empirical data encompassing limited time intervals (month, year) or human personal evaluations but on the integral analysis of long-term information bodies using artificial intelligence. This article presents the results of a multivariate analysis of meteorological extremes which caused crop failures in Eastern and Western Europe in last 2600 years according to chronicle data and paleoreconstructions as well as reconstructions of heliophysical data for the last 9000 years. This information leads us to the conclusion that the current global warming will last for some time. However, subsequent climate changes may go in any direction. And cooling is more likely than warming; thus, we should be prepared to any scenario. Plant breeding can play a key role in solving food security problems connected with climate changes. Possible measures to adapt plant industry to the ongoing and expected climate changes are discussed. It is concluded that future breeding should be based on the use of highly adapted crops that have already been produced in pre-breeding programs, ready to meet future challenges caused by potential climate change.

Changes in Concurrent Meteorological Extremes of Rainfall and Heat under Divergent Climatic Trajectories in the Guangdong–Hong Kong–Macao Greater Bay Area

Concurrent meteorological extremes (CMEs) represent a class of pernicious climatic events characterized by the coexistence of two extreme weather phenomena. Specifically, the juxtaposition of Urban Extreme Rainfall (UER) and Urban Extreme Heat (UEH) can precipitate disproportionately deleterious impacts on both ecological systems and human well-being. In this investigation, we embarked on a meticulous risk appraisal of CMEs within China’s Greater Bay Area (GBA), harnessing the predictive capabilities of three shared socioeconomic pathways (SSPs) namely, SSP1-2.6, SSP3-7.0, and SSP5-8.5, in conjunction with the EC-Earth3-Veg-LR model from the CMIP6 suite. The findings evidence a pronounced augmentation in CME occurrences, most notably under the SSP1-2.6 trajectory. Intriguingly, the SSP5-8.5 pathway, typified by elevated levels of greenhouse gas effluents, prognosticated the most intense CMEs, albeit with a temperate surge upon occurrence. Additionally, an ascendant trend in the ratio of CMEs to the aggregate of UER and UEH portends an escalating susceptibility to these combined events in ensuing decades. A sensitivity analysis accentuated the pivotal interplay between UER and UEH as a catalyst for the proliferation of CMEs, modulated by alterations in their respective marginal distributions. Such revelations accentuate the imperative of assimilating intricate interdependencies among climatic anomalies into evaluative paradigms for devising efficacious climate change countermeasures. The risk assessment paradigm proffered herein furnishes a formidable instrument for gauging the calamitous potential of CMEs in a dynamically shifting climate, thereby refining the precision of prospective risk estimations.

The Extraordinary March 2022 East Antarctica “Heat” Wave. Part II: Impacts on the Antarctic Ice Sheet

Abstract Between 15 and 19 March 2022, East Antarctica experienced an exceptional heat wave with widespread 30°–40°C temperature anomalies across the ice sheet. In Part I, we assessed the meteorological drivers that generated an intense atmospheric river (AR) that caused these record-shattering temperature anomalies. Here, we continue our large collaborative study by analyzing the widespread and diverse impacts driven by the AR landfall. These impacts included widespread rain and surface melt that was recorded along coastal areas, but this was outweighed by widespread high snowfall accumulations resulting in a largely positive surface mass balance contribution to the East Antarctic region. An analysis of the surface energy budget indicated that widespread downward longwave radiation anomalies caused by large cloud-liquid water contents along with some scattered solar radiation produced intense surface warming. Isotope measurements of the moisture were highly elevated, likely imprinting a strong signal for past climate reconstructions. The AR event attenuated cosmic ray measurements at Concordia, something previously never observed. Last, an extratropical cyclone west of the AR landfall likely triggered the final collapse of the critically unstable Conger Ice Shelf while further reducing an already record low sea ice extent. Significance Statement Using our diverse collective expertise, we explored the impacts from the March 2022 heat wave and atmospheric river across East Antarctica. One key takeaway is that the Antarctic cryosphere is highly sensitive to meteorological extremes originating from the midlatitudes and subtropics. Despite the large positive temperature anomalies driven from strong downward longwave radiation, this event led to huge amounts of snowfall across the Antarctic interior desert. The isotopes in this snow of warm airmass origin will likely be detectable in future ice cores and potentially distort past climate reconstructions. Even measurements of space activity were affected. Also, the swells generated from this storm helped to trigger the final collapse of an already critically unstable Conger Ice Shelf while further degrading sea ice coverage.

Characteristics of flash droughts and their association with compound meteorological extremes in China: Observations and model simulations

Flash droughts have gained considerable public attention due to the imminent threats they pose to food security, ecological safety, and human health. Currently, there has been little research exploring the projected changes in flash droughts and their association with compound meteorological extremes (CMEs). In this study, we applied the pentad-mean water deficit index to investigate the characteristics of flash droughts and their association with CMEs based on observational data and downscaled model simulations. Our analysis reveals an increasing trend in flash drought frequency in China based on historical observations and model simulations. Specifically, the proportion of flash drought frequency with a one-pentad onset time showed a consistent upward trend, with the southern parts of China experiencing a high average proportion during the historical period. Furthermore, the onset dates of the first (last) flash droughts during year are projected to shift earlier (later) in a warmer world. Flash droughts become significantly more frequent in the future, with a growth rate approximately 1.3 times higher in the high emission scenario than in the medium emission scenario. The frequency of flash droughts with a one-pentad onset time also exhibits a significant upward trend, indicating that flash droughts will occur more rapidly in the future. CMEs in southern regions of China were found to be more likely to trigger flash droughts in the historical period. The probability of CMEs triggering flash droughts is expected to increase with the magnitude of warming, particularly in the far-future under the high emissions scenario.

Elevating Extreme Weather Forecasting Precision Through the NEMY Generation Framework

This paper presents an innovative methodology known as New Extreme Meteorological Years (NEMY) for comprehensively understanding extreme weather patterns. In contrast to conventional approaches, NEMY meticulously accounts for meteorological parameters, their respective weights, and explores critical factors such as intensity, duration, and the establishment of dynamic thresholds. This dynamic and adaptable framework facilitates precise simulations of extreme weather conditions. In an era characterized by climate change, where preparedness and mitigation of extreme weather impacts are imperative, this research holds paramount significance. The heart of this study revolves around the development and examination of the NEMY framework, which significantly enhances the accuracy in simulating extreme weather scenarios. It is worth emphasizing that, within the context of this paper, the consideration of both the intensity and duration of extreme weather events, as well as the meticulous discussion on the establishment of dynamic thresholds, are central to our approach. The importance of this framework extends beyond meteorology, with practical implications for assessing wind and solar energy resources. This paper not only outlines the methodology of NEMY but also vividly discusses the critical aspects of accounting for the intensity and duration of extreme weather events, as well as the nuanced process of dynamically setting thresholds. Furthermore, it demonstrates the application of NEMY in energy assessment, thereby contributing significantly to the global energy revolution. Additionally, it underscores the urgency of climate change adaptation and mitigation. The subsequent sections delve deeper into the NEMY framework’s design, testing, and potential applications, with a particular focus on the intricate considerations of extreme weather event intensity, duration, and dynamic threshold establishment.

Stronger typhoons, weaker electricity systems? A review of the impacts of extreme weather events on coastal communities and strategies for electric system resilience

Access to adequate and reliable electricity is paramount for the adaptation and resilience of typhoon-prone coastal communities, particularly in the face of intensifying challenges posed by climate change. Climate-related extreme weather events, such as typhoons and their consequent flooding and storm surges, exert significant pressure on electricity systems in these vulnerable regions, affecting every aspect from generation to transmission, distribution, and end-user utilization. Therefore, urgent action is required to fortify these communities with electric systems that are resilient enough to withstand such meteorological extremes. This review paper examines the far-reaching impacts of extreme weather events on electricity systems and showcases illuminating case studies that highlight innovative strategies to bolster these systems against such extremes. The review emphasizes the pivotal role of meticulous energy planning, strong support from local governments, and the significance of infrastructure hardening in building resilient energy systems. Future research opportunities exist in integrating renewable energy, engaging community members, assessing climate risks, and cross-sectoral resilience.

A new method for predicting hurricane rapid intensification based on co-occurring environmental parameters

Tropical cyclones (TCs) that undergo Rapid Intensification (RI) can pose serious socioeconomic threats and can potentially result in major damaging impacts along coastal areas. Considering the complexity of various physical mechanisms that play a role in RI and its relatively low probability of occurrence, predicting RI remains a major operational challenge. In this study, we propose a simple deterministic binary classification model based on the co-occurrence of environmental parameters (MCE) to predict an RI event. More specifically, the model determines the possibility of RI based on a simple count of the number of environmental predictors deemed favorable and unfavorable. We compare our model results to logistic regression (LR) and decision tree (DT) models, well-trained using the same set of environmental predictors. Results reveal that at an RI threshold of 30 kt, the MCE exhibits a critical success index score of 0.233 which is 14% higher than DT and LR model performances. When tested at multiple RI thresholds, the MCE displays relatively higher skill scores across multiple metrics. By simultaneously evaluating the favorability of predictors, the MCE is able to comparatively reduce the number of false alarms predicted when certain predictors are unfavorable toward RI. Interpreting these model results to gain a physical understanding of how co-occurring environmental parameters can affect RI, we highlight future directions for using models based on the MCE approach to understand and predict TC RI as well as other meteorological extremes.

Comprehensive Analysis of Extreme Meteorological Conditions for the Safety and Reliability of Floating Photovoltaic Systems: A Case on the Mediterranean Coast

In recent decades, renewable energy projects have required careful consideration of environmental factors. This study investigates the impact of a mid-latitude cyclone on planned floating photovoltaic (FPV) facilities in Antalya, Turkey, focusing on the severe thunderstorm events that brought heavy rainfall and tornadoes in January 2019. Synoptic analysis reveals a deep cut-off low over the Genoa Gulf, causing trough formation and vertical cloud development due to moisture convergence. Warm air advection pushed an unstable thunderstorm system northward along an occluded front. Using the Weather Research and Forecast (WRF) model, sensitivity analysis is conducted, highlighting regional variations in wind speeds. The model outputs are compared with observations, identifying the best configuration using statistical indicators. The Mellor–Yamada–Janjic (MYJ) planetary boundary layer (PBL) scheme and the Milbrandt microphysics scheme produced better results in the western and central regions. The model output of the best configurations is used to calculate regional wave characteristics with a modified Shore Protection Manual (SPM) method for water reservoirs. These findings offer invaluable insights for future FPV projects, providing a better understanding of how to address challenges posed by extreme weather conditions and how to enhance system safety and reliability.

Battling the extreme: lessons learned from weather-induced disasters on electricity distribution networks and climate change adaptation strategies

Abstract Electricity infrastructures are critical lifeline systems that are designed to serve with a high degree of reliability the power supply of consumers under normal operating conditions and in case of common failures or expected disturbances. However, many recent weather-induced disasters have brought unprecedented challenges to the electricity networks, underlining that power systems remain unprepared to absorb disruptive large-scale and severe events. Worse still, it is expected that such climate hazards will take place at rising frequency and intensity rates due to climate change. The intensification of meteorological extremes will lead to higher losses and changes in transmission capacity, increasing the frequency and importance of material damage to the aging electric infrastructure, thus resulting in significant disruptions, cascading failures, and unpredictable power outages. This review paper presents real-life examples of different types of extreme weather incidents and their impacts on the distribution network in Greece, a country that is highly vulnerable because of its location, geomorphology, and the existing overhead network assets, highlighting lessons learned related to adaptation options and disaster management best practices. Literature review and benchmarking with other grid operators are also employed to explore resilience-enhancing technical capabilities, weatherproof solutions, and operational strategies on which policy-making initiatives should focus.

Constraining decadal variability regionally improves near-term projections of hot, cold and dry extremes

Hot, cold and dry meteorological extremes are often linked with severe impacts on the public health, agricultural, energy and environmental sectors. Skillful predictions of such extremes could therefore enable stakeholders to better plan and adapt to future impacts of these events. The intensity, duration and frequency of such extremes are affected by anthropogenic climate change and modulated by different modes of climate variability. Here, we use a large multi-model ensemble from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and constrain these simulations by sub-selecting those members whose global sea surface temperature anomaly patterns are most similar to observations at a given point in time, thereby phasing in the decadal climate variability with observations. Hot and cold extremes are skillfully predicted over most of the globe, with also a widespread added value from using the constrained ensemble compared to the unconstrained full CMIP6 ensemble. On the other hand, dry extremes only show skill in some regions with results sensitive to the index used. Still, we find skillful predictions and added skill for dry extremes in some regions such as Western North America, Southern central and Eastern Europe, Southeastern Australia, Southern Africa and the Arabian Peninsula. We also find that the added skill in the constrained ensemble is due to a combination of improved multi-decadal variations in phase with observed climate extremes and improved representation of long-term changes. Our results demonstrate that constraining decadal variability in climate projections can provide improved estimates of temperature extremes and drought in the next 20 years, which can inform targeted adaptation strategies to near-term climate change.

Reservoir operation affects propagation from meteorological to hydrological extremes in the Lancang-Mekong River Basin

Hydrological extremes intensified by meteorological extremes are threatening water security in the Lancang-Mekong River Basin (LMRB), and reservoir operation may mitigate hydrological extreme through regulating hydrological processes during meteorological extreme. However, the capacity of reservoirs in modulating propagation from meteorological extremes to hydrological extremes has seldom been quantified. This study adopted the VIC-Reservoir hydrological model to assess the impact of reservoir operation on the propagation at multi-timescales in the LMRB. The Standardized Precipitation Index and Standardized Streamflow Index were adopted to characterize meteorological extreme and hydrological extreme, respectively, on a range of timescales. The results indicate that reservoir operation has effectively delayed the propagation from meteorological to hydrological extremes during the period of 2008–2016 with rapid reservoir development in the LMRB, compared with the period of 1984–2007 with natural condition. The transmission process of extreme events with a duration of no more than 6 months has been suppressed during the reservoir impact period. However, the influence of reservoir regulation on long-term extreme events that last more than 12 months is generally low. In the upstream basin where reservoir impact is largest, reservoirs can exert a weak mitigation effect on long-term dry extremes. This study provides quantitative assessment of the role of reservoirs in regulating propagation between meteorological and hydrological extremes in the LMRB, and facilitate decision making for the management of water hazards under changing environment.

Extreme value statistical analysis of meteorological parameters observed at Rawatbhata Rajasthan site

Abstract Knowledge of extreme meteorological parameters plays an important role, for the selection of any civil structure at nuclear site or to design important nuclear structures to withstand design basis values of meteorological extremes that are likely to occur during the lifetime of these structures. The method used for the evaluation of extreme parameters is least square fit method. In this study, statistical analyses of extreme values of meteorological parameters at Rawatbhata Rajasthan site (RR site) are presented for the period 1980 to 2022 and for rainfall, it is for the period 1964 to 2022. Meteorological parameters such as extreme wind speed and wind gust (5 min) at 10 m and 30 m heights, extreme surface air temperature, extreme atmospheric pressure and extreme rainfall (yearly, monthly, and daily) are evaluated and discussed. From the extreme value analysis, it is observed that the variables for monthly maximum rainfall, annual maximum rainfall, maximum air temperature, maximum atmospheric pressure, maximum hourly wind speed at 10 m and 30 m heights and wind gust (5 min.) at 10 m height obey Fisher-Tippette Type I distribution, whereas daily maximum rainfall, annual minimum rainfall, minimum air temperature, minimum relative humidity, minimum atmospheric pressure and wind gust (5 min.) at 30 m height obey Fisher-Tippette Type II distribution. Distribution function parameters, i.e., location, scale, and shape parameter for each variable, have been determined and design basis values corresponding to return periods of 50 years and 100 years are derived and presented. The derived extreme values are particularly useful for arriving at suitable design values to ensure the safety of civil structures at RR site area with respect to stresses due to weather conditions. The values are also compared with corresponding values at other nuclear reactor sites of Tarapur, Narora, and Kalpakkam.

2015/16 El Niño increased water demand and pushed plants from a Mesic tropical montane grassland beyond their hydraulic safety limits

AbstractIn 2015/16, a strong El Niño event caused anomalously high temperatures and reduced precipitation resulting in Pantropical drought‐induced diebacks and wildfires. Although many studies have documented the El Niño impacts on tropical forests, little we know about its effects on tropical grasslands. Here, we investigated plant drought responses during and after the 2015/16 El Niño event (Jun 2016 to Aug 2017) in 12 species with contrasting drought strategies (tolerance, avoidance and escape) in a Brazilian tropical montane grassland. We tested if (1) the El Niño event induced meteorological drought anomalies, (2) the atmospheric and/or soil drought led to plant water stress and (3) plants showed signs of drought recovery. In contrast to other tropical areas, we found that the 2015/16 El Niño event did not strongly affect precipitation in our study site. However, it increased air temperature and vapour pressure deficit, thus pushing all grassland species, even the most drought‐tolerant ones, beyond their hydraulic safety margins during the dry season. Most species showed signs of drought recovery, returning to positive hydraulic margins in the wet season after the El Niño. However, the finding that all evaluated species, regardless of their drought‐response strategy, are already operating close to their hydraulic safe thresholds for stomatal closure and turgor loss suggests that this cool–humid tropical montane grassland is especially vulnerable to meteorological extremes exacerbated by the additive effects of El Niño and climate change.

Non‐Stationary Lags and Legacies in Ecosystem Flux Response to Antecedent Rainfall

AbstractEcosystem function can be affected directly by climate, including by meteorological extremes, and also by sustained lags and legacies on timescales that surpass those of the weather events themselves. However, important gaps remain in our understanding of the influence and timescale of persistence of antecedent climate, known as environmental memory, on terrestrial carbon and water fluxes. Identifying the interactions between the lagged response to climate and the legacies to climate extremes, and whether the influence of memory varies through time, has not been fully explored. Here, we used a novel k‐means clustering plus regression approach to examine timeseries of the sensitivity of terrestrial fluxes to antecedent precipitation at 65 eddy‐covariance sites across a range of ecosystems. Quantifying the sensitivity to past precipitation and temperature reveals that the role of memory in ecosystem fluxes varies across sites and in time. When memory was accounted for in the model, relative improvement in modeled site flux r2 compared to an instantaneous model varied between 0% and 57%, with mean of 12%. Our results show that vegetation type was a stronger predictor of memory importance than site aridity, implying a need to understand vegetation resilience conferred by physiological traits and acclimation capacity. The influence of memory varied strongly through time at many sites, with the role of different timescales exhibiting consistent non‐stationarity. Our results demonstrate the importance of accounting for time‐varying vegetation response to antecedent rainfall in land surface models to accurately predict future terrestrial fluxes.

Intensity Estimation of Extreme Meteorological and Hydrological Factors Induced by Tropical Cyclones Affecting Hong Kong

Intensity Estimation of Extreme Meteorological and Hydrological Factors Induced by Tropical Cyclones Affecting Hong Kong

Meteorological extremes and their impact on tinnitus-related emergency room visits: a time-series analysis

PurposeExtreme weather events are rising due to the accelerating pace of climate change. These events impact human health and increase emergency room visits (EV) for many morbidities. Tinnitus is a common cause of EVs within otolaryngology in Germany and Austria. The effect of extreme weather conditions on tinnitus-related EVs is unknown.MethodsA total of 526 tinnitus-related EVs at a tertiary care hospital in Vienna were identified. A distributed lag non-linear model with a maximum lag period of 14 days was fitted to investigate the immediate and delayed effect of single-day and prolonged (three-day) extreme atmospheric pressure, relative humidity, mean temperature, precipitation and mean wind speed on EV rates. Extreme conditions were defined as the 1st, 5th, 95th, and 99th percentile of the meteorological variables. Relative risk (RR) is defined as risk for tinnitus-related EVs at an extreme condition compared to the risk at the median weather condition. Cumulative RR (cRR) is the total cumulated EV risk for a given time period.ResultsHigh relative humidity increased same-day RR for tinnitus-related EVs to 1.75. Both low and high atmospheric pressure raised cRR as early as three days after an event to a maximum of 3.24. Low temperatures mitigated cRR within 4 days, while high temperatures tended to increase risk. Prolonged precipitation reduced cRR within one day.ConclusionExtreme meteorological conditions are associated with tinnitus-related EV rates. Further investigation into potential causative links and underlying pathophysiological mechanisms is warranted.