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Many cyclone detection and tracking methods (CDTMs) have been developed in the past to study the climatology of extratropical cyclones. However, all CDTMs have different approaches in defining and tracking cyclone centers. This naturally leads to cyclone track climatologies of inconsistent physical characteristics. More than that, it is typical for CDTMs to produce a non-negligible amount of bogus tracks which can be perceived as “false positives”, or more generally as CDTM artifacts, i.e. tracks of weak atmospheric features that do not correspond to large or mesoscale vortices. Lack of consensus in CDTM outputs and the inclusion of significant amounts of bogus tracks therein, has long prohibited the production of a commonly accepted reference dataset of extratropical cyclone tracks. Such a dataset could allow comparable results on the analysis of storm track climatologies and could also contribute to the evaluation and improvement of CDTMs. To cover this gap, we present a new methodological approach that combines overlapping tracks from different CDTMs and produces composite tracks that concentrate the agreement of more than one CDTM. In this study we apply this methodology to the outputs of 10 well-established CDTMs which were originally applied to ERA5 reanalysis in the 42-year period of 1979–2020. We tested the sensitivity of our results to the spatio-temporal criteria that identify overlapping cyclone tracks, and for benchmarking reasons, we produced five reference datasets of subjectively tracked cyclones. Results show that climatological numbers of composite tracks are substantially lower than the ones of individual CDTM, while benchmarking scores remain high (i.e. counting the number of subjectively tracked cyclones captured by the composite tracks). This suggests that our method is able to filter out a large portion of bogus tracks. Indeed, our results show that composite tracks tend to describe more intense and longer-lasting cyclones with more distinguished early, mature and decay stages than the cyclone tracks produced by individual CDTMs. Ranking the composite tracks according to their confidence level (defined by the number of contributing CDTMs), it is shown that the higher the confidence level, the more intense and long-lasting cyclones are produced. Given the advantage of our methodology in producing cyclone tracks with physically meaningful, distinctive life stages and including a minimum number of bogus tracks, we propose composite tracks as reference datasets for climatological research in the Mediterranean. The supplementary material provides the composite Mediterranean tracks for all confidence levels and in the conclusion we discuss their adequate use for scientific research and applications.

Air quality models are essential tools to meet the United Nations Sustainable Development Goals (UN-SDG) because they are effective in guiding public policies for the management of air pollutant emissions and their impacts on the environment and human health. Despite its importance, Brazil still lacks a guide for choosing and setting air quality models for regulatory purposes. Based on this, the current research aims to assess the combined WRF/CALMET/CALPUFF models for representing SO2 dispersion over non-homogeneous regions as a regulatory model for policies in Brazilian Metropolitan Regions to satisfy the UN-SDG. The combined system was applied to the Rio de Janeiro Metropolitan Region (RJMR), which is known for its physiographic complexity. In the first step, the WRF model was evaluated against surface-observed data. The local circulation was underestimated, while the prevailing observational winds were well-represented. In the second step, it was verified that all CALMET three meteorological configurations performed better for the most frequent wind speed classes, so that the largest SO2 concentrations errors occurred during light winds. Among the meteorological settings in WRF/CALMET/CALPUFF, the joined use of observed and modeled meteorological data yielded the best results for the dispersion of pollutants. This result emphasizes the relevance of meteorological data composition in complex regions with unsatisfactory monitoring given the inherent limitations of prognostic models and the excessive extrapolation of observed data that can generate distortions of reality. This research concludes with the proposal of the WRF/CALMET/CALPUFF air quality regulatory system as a supporting tool for policies in the Brazilian Metropolitan Regions in the framework of the UN-SDG, particularly in non-homogeneous regions where steady-state Gaussian models are not applicable.

Heat waves (HWs) are extreme weather conditions characterized by persistent high temperatures with considerable impacts on society in terms ofmortality, thermal stress and energy demand of the population. One of the most interesting aspects of HWs concerns the interaction with the phenomenonof urban heat island (UHI). The UHI is the tendency of urbanized areas to have warmer temperatures than the surrounding rural areas, mainly due to the thermalproperties of materials forming urban environment and the heat produced by human activities. Some studies analyzed the behavior of UHI during periods ofextreme heat, showing an amplification of the gradient of temperature between urban and rural areas in HW conditions, but results are often limited to casestudies with a single HW and/or a specific city. Other papers dealt with the same topic by examining events on various cities using outputs of global models,but with resolution insufficient to include in detail urban-scale processes and therefore to take into account specific properties of the cities investigated. Theapproach of this work consisted in providing observational evidence and extending the aforementioned results, studying the effect of HWs on UHI in 41 European citieswith different characteristics (geography, topography, urban planning) through the analysis of daily maximum / minimum temperatures data measured bymeteorological stations for the summers of period 2000-2019. In particular, the intensity of UHI was assessed through the computation of a Composite UHI Index(UHII), defined as the difference between averaged urban and non-urban values. The different behavior of UHII during HWs compared to "normal" summer days(NO) in selected European cities was investigated, detecting an intensification of index values regarding periods of extreme heat for the majority of examinedlocations. More specifically, the analysis of temporal evolution of UHII was conducted, revealing an average increase of this index during the occurrence ofHW events due to higher urban than rural temperatures. This work provides an indication of how European urban areas respond to severe hot periods and couldbe useful to validate numerical model simulations for more detailed analysis, for example regarding mitigation strategies. Finally, the emergence of some outliers,namely cities whose UHI manifested a different reaction to HWs, may deserve dedicated studies in the future.

This study focuses on developing a new Cyclone Detection and Tracking Method (CDTM) to take advantage of the recent availability of a high-resolution reanalysis dataset of ECMWF ERA5. The proposed algorithm is used to perform a climatological analysis of the cyclonic activity in the Mediterranean Region (MR) into a 40-year window (1979–2018). The tuning of the new CDTM was based on the comparison with currently available CDTMs and verified through careful subjective analysis to fully exploit the finer details of MR cyclones features. The application of the new CDTM to the ERA5 high-resolution dataset resulted in an increase of 40% in the annual number of cyclones, mainly associated with subsynoptic and baroclinic driven lows. The main cyclogenetic areas and seasonal cycle were properly identified into the MR context, including areas often underestimated, such as the Aegean Sea, and emerging new ones with cyclogenetic potential such as the coast of Tunisia and Libya. The better cyclone features description defined three distinct periods of cyclonic activity in the MR with peculiar and persistent characteristics. In the first period (Apr-Jun), cyclones develop more frequently and present higher velocities and deepening rates. In the second (Jul-Sep), the cyclonic activity is governed by thermal lows spreading slowly over short tracks without reaching significant depths. In the last and longest season (Oct-Mar), cyclones become less frequent, but with the highest deepening rates and the lowest MSLP values, ranking this period as the most favourable to intense storms.

Hydro-meteorological risk (HMR)management involves a range ofmethods, such asmonitoring of uncertain climate,planning and prevention by technical countermeasures, risk assessment, preparedness for risk by earlywarnings,spreading knowledge and awareness, response and recovery. To executeHMR management by risk assessment,many models and tools, ranging from conceptual to sophisticated/numerical methods are currently inuse. However, there is still a gap in systematically classifying and documenting them in the field of disaster riskmanagement. This paper discusses various methods used for HMR assessment and itsmanagement via potentialnature-based solutions (NBS), which are actually lessons learnt from nature. We focused on three hydrometeorologicalhazards (HMHs), floods, droughts and heatwaves, and their management by relevant NBS. Different methodologiesrelated to the chosen HMHs are consideredwith respect to exposure, vulnerability and adaptationinteraction of the elements at risk. Two widely used methods for flood risk assessment are fuzzy logic (e.g.fuzzy analytic hierarchy process) and probabilistic methodology (e.g. univariate andmultivariate probability distributions).Different kinds of indices have been described in the literature to define drought risk, dependingupon the type of drought and the purpose of evaluation. For heatwave risk estimation, mapping of the vulnerableproperty and population-based on geographical information system is awidely used methodologyinaddition toa number of computational, mathematical and statistical methods, such as principal component analysis, extreme value theorem, functional data analysis, the Ornstein–Uhlenbeck process and meta-analysis. NBS (blue,green and hybrid infrastructures) are promoted for HMR management. For example, marshes and wetlands inplace of dams for flood and drought risk reduction, and green infrastructure for urban cooling and combatingheatwaves, are potential NBS. More research is needed into risk assessment and management through NBS, toenhance its wider significance for sustainable living, building adaptations and resilience.

O presente trabalho tem por escopo apresentar o efetivo uso compartilhado e harmônico das terras da União a partir do sucesso na governança fundiária em terras jurisdicionadas ao Comando do Exército. Para tanto, será apresentado um panorama sobre a importância das terras vocacionas aos interesses da defesa nacional, a legislação correlata, particularmente ao Exército, bem como algumas evoluções alcançadas após a resolução de invasão em área militar conhecida como o “caso Puraquequara”, no Estado do Amazonas. Por fim, a conclusão tratará da harmonia entre os interesses da defesa nacional e os interesses sociais, sem prejuízo de sua destinação principal.

Droughts are comprehensive and complex naturally occurring hazards in any climatic region around the world and often result in the loss of life and severe ecosystem damage. Drought monitoring is usually based on single-variables that may not represent the corresponding risk appropriately to its multiple causation and impact characteristics under current and future climate scenarios. In order to address this issue, the multidimensional copulas function, which is a flexible statistical tool, could be applied to develop multivariate drought indicators and solve the complicated and nonlinear associations. The aim of this paper is to develop reliable designing, monitoring and prediction indicators for the proper assessment and intervention of drought risk by nature-based solutions (NBS). Using a copula-based multivariate drought indicator (CMDI) that considers all possible variables related to meteorological, agricultural and hydrological droughts is essential for better drought risk assessment and intervention. The CMDI was developed by integrating univariate marginal cumulative distribution functions of meteorological (precipitation), agricultural (soil moisture) and hydrological (streamflow) variables into their joint cumulative distribution function. CMDI was then applied to the selected study catchment (Po Valley, Italy and Spercheios River, Greece) using hydro-meteorological data from gauging stations and ERA5 gridded data for the period 1979-2017. The result of CMDI showed moderate, severe and extreme drought frequencies in the two selected catchments. The constructed CMDI captured more severe to extreme drought occurrence than the considered single drought indicators. This proved that the CMDI could appropriately represent the complex and interrelated natural variables. The uncertainty analysis based on Monte Carlo experiments confirmed that CMDI is a more robust and reliable approach for assessing, planning and designing a nature-based intervention for drought risk. The findings of this research can provide a reliable way to develop approaches that can be used for assessing and predicting non-linearly related variables or any risk that may occur simultaneously or cumulatively over time.

Abstract Droughts are comprehensive and complex naturally occurring hazards in any climatic region around the world and often result in the loss of life and severe ecosystem damage. Drought monitoring is usually based on single-variables that may not represent the corresponding risk appropriately to its multiple causation and impact characteristics under current and future climate scenarios. In order to address this issue, the multidimensional copulas function, which is a flexible statistical tool, could be applied to develop multivariate drought indicators and solve the complicated and nonlinear associations. The aim of this paper is to develop reliable designing, monitoring and prediction indicators for the proper assessment and intervention of drought risk by nature-based solutions (NBS). Using a copula-based multivariate drought indicator (CMDI) that considers all possible variables related to meteorological, agricultural and hydrological droughts is essential for better drought risk assessment and intervention. The CMDI was developed by integrating univariate marginal cumulative distribution functions of meteorological (precipitation), agricultural (soil moisture) and hydrological (streamflow) variables into their joint cumulative distribution function. CMDI was then applied to the selected study catchment (Po Valley, Italy and Spercheios River, Greece) using hydro-meteorological data from gauging stations and ERA5 gridded data for the period 1979-2017. The result of CMDI showed moderate, severe and extreme drought frequencies in the two selected catchments. The constructed CMDI captured more severe to extreme drought occurrence than the considered single drought indicators. This proved that the CMDI could appropriately represent the complex and interrelated natural variables. The uncertainty analysis based on Monte Carlo experiments confirmed that CMDI is a more robust and reliable approach for assessing, planning and designing a nature-based intervention for drought risk. The findings of this research can provide a reliable way to develop approaches that can be used for assessing and predicting non-linearly related variables or any risk that may occur simultaneously or cumulatively over time. Keywords: Drought risk; multidimensional copulas; multivariate indicators, uncertainty analysis; frequency Acknowledgements: This work is carried out under the framework of OPERANDUM (OPEn-air laboRAtories for Nature baseD solUtions to Manage hydro-meteo risks) project, which is funded by the Horizon 2020 under the Grant Agreement No: 776848.

The main target of this study is to evaluate the Cyclone Detection and Tracking Methods (CDTM) using the ECMWF ERA5 dataset, state-of-the-art in reanalysis models, to identify the main cyclogenesis zones and cyclone tracks inside the Mediterranean region during a climatological period. Several studies based on ECMWF analysis and reanalysis (ERA40 and ERA Interim) datasets indicate a large divergence related to the average number of cyclones passing through the Mediterranean region by year. However, the majority agrees on the most important cyclogenesis areas, seasonality variation of the number of cyclones, and trends of cyclone track. In general, the differences between those methodologies concerns to the meteorological variable used to detect cyclones and the metric used to define its intensity. Nevertheless, spatial and temporal resolutions were fundamental to achieve the results, since the most advanced dataset used in the literature presented relatively low values ​​such as 1.125°x1.125° and 6h, respectively. Past studies reported that these values ​​were already high enough to produce numerical noises. Here, the geopotential height at 1000 hPa (Z1000) was used, with horizontal spatial resolution of 0.25°x0.25° and time resolution of 1h, to identify the local minima for each time step (hereafter, candidates), and filtering those with negative gradients of Z1000 within a radius of 1000 km to exclude candidates associated with thermal lows or geopotential troughs.Following the literature, the domain for Mediterranean region was defined by the area within 9°W to 42°E, and 27°N to 48°N, where were considered only cyclones with at least one tracking point inside the domain. Also, the results were produced for the period 1979-2008 using two types of input data: (Model I) ERA5 data with resolutions reduced to 1.5°x1.5° and 6h, as well as the main previous studies; and (Model II) full-resolution ERA5 data. As expected, Model I results were very similar to those found in the literature in all aspects (number of cyclones, seasonal distribution, areas of cyclogenesis and tracks). On the other hand, since the use of higher resolution data provides greater spatiotemporal detailing of the climatological period, the results of Model II presented a total number of cyclones substantially higher than that of Model I (~25%), but still within the range described in the literature. The models indicated more frequent cyclones during the spring months with maximums in April (Model I) and May (Model II). An interesting point highlighted in other studies but not observed in their results, is an increase in cyclone frequency between August and October, captured in both Models I and II and more evident in Model II. An explanation is found in the greater number of short-life cyclones, which act in relatively narrow areas intangible to datasets with limited resolution.

Extreme hydro-meteorological events are often defined by the statistical analysis of some parameter that measures the strength of the event over a long enough time series. The parameter could refer to the intensity of the event in terms of energy or to the impact of the event on the environment. This attribution becomes even more relevant when used as reference for future climate projections, suggesting a possible increase in the number of extreme events considering the attribution applied to the past database. In the literature concerning storm-surge, the use of significant wave height (Hs) percentiles to define thresholds of an extreme event is a common practice when dealing with sufficiently long datasets. Usually, this value ranges from 90th up to 99.5th trying to highlight about 3-6 Hs peaks per year. But, in fact, thresholds should provide a benchmark for how much a region can withstand an extreme event. The Italian coast of the northern Adriatic is recently increasing its sensitivity to such episodes, that threaten one of the most active touristic hub of Italy, the highly valuable Po Delta UNESCO Biosphere Reserve and city of Venice fragile structure. Recently in late 2019, a strong event hit Venice with high tides flooding the city's main monument, St. Mark's Basilica, for the 6th time in 1200 years, with levels very similar to the worst event in history in 1966. Attempting to better understand the distribution of these extreme events throughout last decades and how reanalysis products can be useful for storm-surge studies, this paper presents a climatological comparison of significant wave height data extracted from ECMWF ERA5 against the entire historical series available to the Nausicaa wave buoy. This station, owned and managed by ARPAE, is located about 8 km offshore the Municipality of Cesenatico, where the seabed is about 10m, and since 2007 has been used to monitor and prevent sea level related events. In the last 12 years, at least 10 extreme events have been reported based on hourly measured data in Nausicaa and the damage observed along the coast, allowing the local authorities to define Hs thresholds as 1.5 m to significant events and 3.0 m for extreme events. However, analysing the measured data in this period, at least 26 events that exceeded the 3 m threshold were observed, representing the percentile 99.81th of the historical series, whereas only 10 storm-surge events resulted in damage to cities or environmental protection areas. When analysing Hs extracted from ERA5 at the nearest grid point to Nausicaa (~ 30 km) for the same 26 events, all events were correctly identified by reanalysis and represented with an averaged correlation of 0.96. For Hs series extracted from ERA5, values above 3 m reached the 99.83rd percentile for the same period from 2007 to 2018, and 99.84th when expanded to the last 30 years (since 1989), showing that, although quite restricted, the 99.8th percentile seems to be a good value for identifying extreme events of storm-surge in the northern Adriatic Sea.

Nature-based solutions (NBS) are being promoted as adaptive measures against predicted increasing hydrometeorological hazards (HMHs), such as heatwaves and floods which have already caused significant loss of life andeconomic damage across the globe. However, the underpinning factors such as policy framework, end-users' interestsand participation for NBS design and operationalisation are yet to be established. We discuss theoperationalisation and implementation processes of NBS by means of a novel concept of Open-Air Laboratories(OAL) for its wider acceptance. The design and implementation of environmentally, economically, technicallyand socio-culturally sustainable NBS require inter- and transdisciplinary approaches which could be achievedby fostering co-creation processes by engaging stakeholders across various sectors and levels, inspiring more effective use of skills, diverse knowledge, manpower and resources, and connecting and harmonising the adaptationaims. The OAL serves as a benchmark for NBS upscaling, replication and exploitation in policy-makingprocess through monitoring by field measurement, evaluation by key performance indicators and buildingsolid evidence on their short- and long-term multiple benefits in different climatic, environmental and socioeconomicconditions, thereby alleviating the challenges of political resistance, financial barriers and lack ofknowledge.We conclude that holistic management of HMHs by effective use of NBS can be achieved with standard compliant data for replicating and monitoringNBS inOALs, knowledge about policy silos and interaction betweenresearch communities and end-users. Further research is needed for multi-risk analysis of HMHs andinclusion of NBS into policy frameworks, adaptable at local, regional and national scales leading to modificationin the prevalent guidelines related to HMHs. The findings of this work can be used for developing synergies betweencurrent policy frameworks, scientific research and practical implementation of NBS in Europe and beyondfor its wider acceptance.

Nature-based solutions (NBS) are being promoted as adaptive measures against predicted increasing hydrometeorological hazards (HMHs), such as heatwaves and floods which have already caused significant loss of life and economic damage across the globe. However, the underpinning factors such as policy framework, end-users' interests and participation for NBS design and operationalisation are yet to be established. We discuss the operationalisation and implementation processes of NBS by means of a novel concept of Open-Air Laboratories (OAL) for its wider acceptance. The design and implementation of environmentally, economically, technically and socio-culturally sustainable NBS require inter- and transdisciplinary approaches which could be achieved by fostering co-creation processes by engaging stakeholders across various sectors and levels, inspiring more effective use of skills, diverse knowledge, manpower and resources, and connecting and harmonising the adaptation aims. The OAL serves as a benchmark for NBS upscaling, replication and exploitation in policy-making process through monitoring by field measurement, evaluation by key performance indicators and building solid evidence on their short- and long-term multiple benefits in different climatic, environmental and socio-economic conditions, thereby alleviating the challenges of political resistance, financial barriers and lack of knowledge. We conclude that holistic management of HMHs by effective use of NBS can be achieved with standard compliant data for replicating and monitoring NBS in OALs, knowledge about policy silos and interaction between research communities and end-users. Further research is needed for multi-risk analysis of HMHs and inclusion of NBS into policy frameworks, adaptable at local, regional and national scales leading to modification in the prevalent guidelines related to HMHs. The findings of this work can be used for developing synergies between current policy frameworks, scientific research and practical implementation of NBS in Europe and beyond for its wider acceptance.

Brazilian cities have been constantly exposed to air quality episodes of high ozone concentrations (O3). Known for not be emitted directly into the environment, O3 is a result of several chemical reactions of other pollutants emitted to atmosphere. The growth of vehicle fleet and government incentives for using alternative fuels like ethanol and Compressed Natural Gas (CNG) are changing the Brazilian Metropolitan Areas in terms of acetaldehyde and formaldehyde emissions, Volatile Organic Compounds (VOC's) present in the atmosphere and known to act on the kinetics of ozone. Driven by high concentrations of tropospheric ozone in urban/industry centers and its implications for environment and population health, the target of this work is understand the kinetics of ozone formation through the creation of a mathematical model in FORTRAN 90, describing a system of coupled ordinary differential equations able to represent a simplified mechanism of photochemical reactions in the Brazilian Metropolitan Area. Evaluating the concentration results of each pollutant were possible to observe the precursor's influence on tropospheric ozone formation, which seasons were more conducive to this one and which are the influences of weather conditions on formation of photochemical smog. Nas últimas décadas diversas metrópoles brasileiras vêm sofrendo constantemente com eventos relacionados à qualidade do ar, a exemplo do Smog Fotoquímico, fenômeno caracterizado pelos altos níveis de concentração de ozônio (O3) na baixa atmosfera. No entanto, sabe-se que este poluente não é emitido diretamente para o ambiente, o O3 é fruto de diversas reações químicas que ocorrem na atmosfera na presença de outros poluentes. O crescimento da frota veicular e os incentivos do governo ao uso de combustíveis alternativos, como o álcool e o GNV, fizeram com que as grandes cidades do país registrassem um aumento nas concentrações de espécies como o formaldeído que, até então, não despertavam preocupações. Este poluente é um dos Compostos Orgânicos Voláteis (COV's) presentes na atmosfera, e estes compostos também são conhecidos por atuarem na cinética de formação do ozônio. Motivados pelos altos níveis de concentração de ozônio troposférico em centros urbano/industriais e suas implicações à saúde da população e do meio ambiente, buscamos neste trabalho entender a cinética de formação do ozônio através da criação de um modelo matemático computacional em linguagem FORTRAN 90, descrito por um sistema de equações diferenciais ordinárias acopladas, representando de forma simplificada os mecanismos de reações fotoquímicas da atmosfera. Em nossos resultados conseguimos observar como os poluentes precursores influenciam no processo de formação do ozônio na troposfera, quais as estações do ano mais propícias a este processo e quais influências das condições meteorológicas na formação do principal poluente do Smog Fotoquímico.

This paper investigates local circulation features in the industrialised coastal region of Santa Cruz, Rio de Janeiro, Brazil. A better understanding of local circulation affects directly the choice of suitable dispersion models and/or development of new ones to plan mitigation strategies to reduce air pollution in the area. The topographic characteristics and the variety of atmospheric phenomena acting over the area suggest the formation of internal boundary layers (IBLs) during cold front and bay breeze flows with direction upstream of the major industries. Vertical profiles of main meteorological variables are evaluated together with surface weather stations and satellite data to derive a detailed physics-based description of the various stages of bay breeze in terms of the main forces, duration, and atmospheric stabilities. It is found that the development phase of the sea breeze coincides with the largest bay/land differences and, consequently, it is the most pronounced condition to observe the IBL formation.

Parasitological detection of Schistosoma is the cornerstone of schistosomiasis diagnosis in areas of transmission worldwide. However, a steep decrease of sensitivity in low-endemicity areas (LEAs) compromises estimation of schistosomiasis. Despite the restricted utilization of molecular and immunodiagnostic techniques, recent improvements and advances have been contributing to change this scenario, especially in LEAs. Nonetheless, the main issue in a new era of diagnosis overcomes technical advances per se and relates to the loss of 'gold standards' in schistosomiasis diagnosis in LEAs. Here, we review and discuss the current role of molecular and immunodiagnostic methods in schistosomiasis management.

In this paper is proposed a novel predictive controller to improve the Power Electronic Load (PEL) dynamic. Moreover, details of the developed three-phase PEL prototype (25 kVA) are provided with capability of burn-in-test series, shunt and series-shunt power conditioners. In order to validate the load emulation effectiveness and dynamic improvement, experimental results and a power flow analysis are provided.

The iUPQC is a dual approach of the well-known UPQC, which uses the series compensator as sinusoidal current source and the shunt compensator as sinusoidal voltage source. In this way, the control references outputs are sinusoidal signals at the fundamental frequency. This paper compares two different controllers for the PWM reference signal generations, using α-β and d-q reference frame, respectively. Experimental results using both controllers are presented as well.

A heatwave (HW) is a large-scale meteorological event characterised by persistent and extremely high-temperature condition. At the local scale, the urban heat island (UHI) is another thermal-related phenomenon defined as an urban area warmer than its surrounding regions due to different surfaces’ capabilities to absorb and store heat. However, the assessment about the effect produced on UHI by HW events is not homogeneous. Indeed, regarding the capability of HWs to influence the urban-rural temperature difference, several studies report different conclusions describing both an exacerbation and a reduction of UHI during HW events. In this context, the present study analyses in situ long records of temperature measurements (20 years) to provide observational shreds of evidence of UHI modification under HW conditions. We examine data from the European Climate Assessment & Dataset and World Meteorological Organization computing the UHI index (UHII) to quantify the UHI effect intensity in 37 European cities during the last 20 summers. The results show an UHII intensification for 28 of the 32 cities affected by positive UHI during extremely high temperatures at night, while substantial variations are not observed during the daytime. The time evolution of UHI during a HW highlights that a more significant and persistent urban-rural temperature gradient explains the UHI intensification. Finally, the relationship between the large and local-scale temperature phenomena reveals that continental high-temperature periods are often associated with prominent temperature differences between small-scale urban and rural environments, assessing the impact of large-scale features on thermal stress at the local scale.