bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparison of parallel temperature measurements from digital thermometers and mercury-in-glass thermometers for cooperative observation network in Catalonia
Authors: Ripoll Ricard , del Amo Xènia , Vendrell Roger , Oriol Jordi
Published: July 2024

The Minamata Convention on Mercury is a global treaty to protect human health and the environment from the adverse effects of mercury. The Regulation (EU) 2017/852 of the European Parliament and of the Council of 17 May 2017 on mercury, came into force in 2020 and banned all production, import and export of observing instruments that containing mercury in Europe.In Meteorological Service of Catalonia our meteorological observing network have long involved the use of mercury-in-glass thermometers, with more than 130 observers. The replacement of this instruments is required, and a comparative study has been done in Catalonia with two digital thermometers. Those new instruments provide a simple and easy solution by the observers, while requiring the observer to go to the weather station every day. This allows the collection of the rest of the essential meteorological variables such as precipitation, cloud cover and type, visibility, wind direction and wind Beaufort, etc.Since December 2022, two digital thermometers were installed into a medium wooden screen in Calonge (Girona, Catalonia) where there are a typical mercury-in-glass thermometers. One of these thermometers is from Metspect, and the other one is from Navimet. Within more than one year of parallel measurements, this study explains the results obtained and a characterization of the performance. The advantages and disadvantages of each digital device will be exposed. The results will be used by the Meteorological Observers Network (XOM) from Meteorological Service of Catalonia (SMC) to select which device it uses as a reference for this cooperative network in Catalonia.
Effects of the modified Physiologically Equivalent Temperature on mortality and morbidity in the Mediterranean, a case study for Cyprus
Authors: Tzyrkalli Anna , Giannaros Christos , Kekkou Fragkeskos , Economou Theo
Published: July 2024

Human health faces a significant threat from climate change, especially in regions like the Mediterranean, and the Middle East and North Africa, which have experienced extreme temperatures in recent decades. Extreme heatwaves are becoming common in these areas, impacting enclosed populations more severely. However, hot weather is experienced in different ways by different demographics. This is an aspect that must be accounted for in any analysis aiming at studying the human health related effects of heat exposure. For this, here, were use the modified Physiologically Equivalent Temperature (mPET) – an advanced human-biometeorological index, which is capable of  considering the variability of thermo-physiological responses among different population groups. mPET in particular combines temperature, humidity, wind and radiation loads with anthropometric (e.g. age), activity and clothing factors to assess human thermal comfort for a wide variety of sub-populations. Focusing on Cyprus, a Mediterranean island, mPET was computed in the present study based on population-weighted climate data derived from Copernicus European Regional Reanalysis (CERRA), at 5.5 km spatial resolution and at 1 h temporal resolution, using the RayMan Pro Model. The mPET estimates were specifically provided for the five districts of Cyprus and for six different population groups: female and male children, adults, and seniors. Regarding epidemiological data, we considered daily mortality counts and daily morbidity records associated with cardiovascular and respiratory diseases (ICD10 codes: I00-I99 and J00-J99), spanning nearly two decades (2004-2019). To understand how the thermo-physiologically relevant heat stress affects mortality and morbidity rates, we applied Distributed Lag non-Linear models (DLNMs) within the general framework of Generalized Additive Models (GAMs). This modelling framework produces estimates of the temporally distributed effect of mPET on mortality/morbidity rates. We demonstrate how the health risk varies across the various population sub-groups and districts in Cyprus and that using mPET rather than single heat-related meteorological metrics enables such differences to be better highlighted. This is the first time that health risks arising from heat were assessed for various demographics in Cyprus, providing crucial information for better understanding the climate change impact in the country.
ECOAZUL-MED climate service tool: supporting aquaculture, fisheries and coastal tourism in the Spanish Mediterranean coasts 
Authors: de la Vara Alba , Cabos William , Matamoros Alba
Published: July 2024

The Mediterranean region is considered a climate change hotspot because it provides an amplified warm climate signal and is highly favorable to the development of extreme weather events. In the coming decades, climate models project an increase in the frequency and/or intensity of these events. These factors make Mediterranean coasts densely populated, such as the Spanish eastern coast, prone to suffer negative socioeconomic impacts. In this respect, blue economy, defined as those economic activities related to seas and oceans, which represent a key source of growth, incomes and employment in the region, is very exposed to climate conditions, with potential concomitant economic losses. Thus, the implementation of adaptation measures to ensure the sustainable development of the blue economy is of vital importance in the current context of climate change. Adaptation strategies must be built upon scientific knowledge regarding the future climate signal which allows for effective policies and practices by public administrations and entities that operate in implied sectors.  

In particular, aquaculture, fisheries and coastal tourism are relevant sectors of the blue economy for their contribution to social and economic development on the Spanish Mediterranean coast. The ECOAZUL-MED project offers, for the first time, a public climate service tool which provides relevant climate data for the management of the aquaculture, fishing and coastal tourism in the Spanish Mediterranean coast for the next 40 years. Data offered comes from the analysis of an ensemble of regional, air-sea coupled simulations from the Med-CORDEX initiative and is available for two emission scenarios. The tool provides oceanic and atmospheric information, including extremes with the potential to cause large negative socio-economic impacts (e.g., heat waves, heavy precipitation). Also, the tool is accompanied by documentation created over the project’s life e.g., reports on socio-economic impacts of climate change on the sectors, policy recommendations for the different sectors, among others. Our tool will support companies, public administration and other agents in decision-making processes regarding adaptation to climate conditions. The tool has been created using a comprehensive approach which combines quantitative research e.g., climate data analysis, and qualitative research, through which a wide range of stakeholders have been involved in different participatory activities since the beginning of the project. This co-creative, user-driven approach is key to ensure that the tool is usable and is adapted to the expectations of potential end users. In this work we will present the ECOAZUL-MED project and related climate service tool, and will provide details about the methodology followed for its creation. Practical examples of how the tool could be used to support decision or policy making will be given. 
Analysis of long-term temperature data (1948–2022) shows the growing threat of extreme heat in the city of Ljubljana, Slovenia
Authors: Crepinsek Zalika , Znidarsic Zala , Pogacar Tjasa
Published: July 2024

Climate change is the greatest threat and risk to urban health and manifests itself in more intense, more frequent, and longer extreme weather events. Although Ljubljana has a relatively small population compared to other European capitals, the city faces problems in summer due to the urban heat island. The aim of this study was to characterize the intensity, frequency and duration of extreme high temperature events and their variability over a 75-year period (1948–2022) for Ljubljana. This study uses 23 indices recommended by the WMO Expert Team on Climate Change Detection and Indices (ETCCDI). The indices are calculated with the Climpact-v2 software. For each index, the type of trend and significance were calculated using the Mann–Kendall test and the magnitude of the trend was calculated using Sen’s slope estimator. The trends in annual mean maximum (TXm), minimum (TNm) and daily mean (TMm) temperatures were all positive and statistically significant with rates of 0.37 °C/decade, 0.41 °C/decade and 0.39 °C/decade, respectively. Both the annual minimum value of daily TN (TNn) and the annual maximum value of daily TN (TNx) have increased significantly in recent times, showing that the coldest and hottest nights of the year in Ljubljana are now warmer, with an increase of almost 7 °C on the coldest nights and a smaller increase of 3.8 °C on the hottest nights. The number of events with a fixed threshold temperature, summer days (TX > 25 °C), hot days (TX ≥ 30 °C) and very hot days (TX ≥ 35 °C) showed statistically significant positive trends. Ljubljana has an average of 68 summer days and 18 hot days per year. Until recently, these days were only typical of summer, but now they occur in May and even continue into September. In the period 1948–2012, we could expect a very hot day only once every three years, and the average of the last 10 years, 2013–2022, is 4 very hot days per year. The number of tropical nights (TN > 20 °C) increased at a rate of 0.3 days/decade, especially after 2000. Thermal heat sum indices, heating degree days (HDDheat) and cooling degree days (CDDcool), indicators of weather-related energy consumption for heating and cooling buildings, showed a significant decrease for HDDheat and an increase for CDDcool. Heat waves (HW) are becoming a growing problem in Ljubljana as all investigated HW indices are increasing, i.e. HW number (trend 0.5 events/decade), frequency (2.0 days/decade), magnitude (0.36 °C/decade) and maximum amplitude (0.73 °C/decade).According to the research results, it is necessary to accelerate the adoption of a heat action plan that will include observations, forecasts, warnings, and education for the city's residents. 
Modelling the summer 2022 marine heatwave around France: disentangling atmospheric and oceanic contributions
Authors: Beuvier Jonathan , Lebeaupin Brossier Cindy , Guinaldo Thibault
Published: July 2024

The AROBASE (AROme-BAsed coupled SystEm) project of CNRM aims to assemble a multi-coupled regional modelling platform of the physico-chemical atmosphere, the ocean (including sea ice and marine biogeochemistry), the waves and the continental surfaces (soil, vegetation, cities, snow, lakes and rivers), at kilometric scale.In this context, a new high-resolution regional ocean configuration of the NEMO model has been developed. Named FRA36, it covers the maritime domain around mainland France with a resolution of ~2.5 km (ORCA 1/36° grid).In order to prepare the future ocean-atmosphere coupled system, FRA36 is first used in a configuration forced by the operational analyses of the AROME-France atmospheric model, at a horizontal resolution of 1.3 km and a 3h temporal resolution. FRA36 uses the global Copernicus Marine Service operational oceanographic productions with data assimilation (GLO12 analyses product) for initialisation and boundary conditions.We use this configuration to reproduce and analyse the summer 2022 succession of marine heatwave events around mainland France (English Channel, Bay of Biscay, North-Western Mediterranean Sea), using a continuous 3-month ocean simulation initialised the 1st of June 2022.First, the spatial and temporal evolution of the Sea Surface Temperature (SST) in this simulation is validated using satellite products. FRA36 reproduces well the succession of observed long-lasting warming periods, interspersed with sudden cold spells. Then, heat budgets in the ocean mixed layer are used to separate atmospheric (solar and non-solar fluxes) and oceanic (advection, mixing, entrainment) contributions to surface and sub-surface temperature variations. Following on from the Guinaldo et al. 2023 study, we here take advantage of the added value of having a 3D oceanic component, including explicit tides, and the atmospheric forcing at high spatio-temporal resolution from AROME-France, to characterise the respective atmospheric and oceanic contributions in the occurrences, maintenances and ends of this succession of high-stakes events.
Heat Health Action Plans - The Role of Human Biometeorology and Urban Climatology
Authors: Matzarakis Andreas
Published: July 2024

Heat is one of the most important adaptations possibilities, which cannot only be helpful for the reduction of mortality and morbidity but also an issue in term of work productivity and in general for quality of life worldwide. For the quantification of heat and heat stress, methods from urban climatology and human biometeorology can provide results and information which can be directly applied for combatting/assessing climate impact and for the development of strategies and action against heat. Heat health action plans (HHAP) are a comprehensive tool, which focuses on short, medium and long term goals/aims and are relevant for the protection of vulnerable and risk groups. They consider factors, such as coordination and responsibilities of the Plans, heat health early warning system, information ways and plans, possibilities of reduction of indoor heat, specific actions for the protection of vulnerable people (mostly elderly), education options for health sectors, urban planning options for reduction of heat and finally the monitoring of actions and their evaluation. The evaluation factor considers the monitoring of the actions. The mitigation of heat and the implication on human health bring several disciplines together and the application and implementation of actions require scientific results and analysis based not only on measurements but also the application of micro scale models, under consideration validation of results. In addition, the knowledge of quantification of heat implications and the use of heat health warning systems are crucial for the protection of human life from extreme heat and heat waves. Finally, HHAPs should be often updated and consist from a preparation and post-processing part and are an issue not only during summer and extreme heat conditions and heat waves.
The accordance of synoptic-scale circulation in atmospheric reanalyses and its methodological sensitivity
Authors: Stryhal Jan
Published: July 2024

Several global-scale atmospheric reanalyses (ARs) have been developed since the mid-1990s providing outputs that reach back into the pre-satellite era. These datasets, despite their deficiencies, are routinely used in climate research, prompting the need for validation and inter-comparison studies. Here, we compare synoptic-scale atmospheric circulation in an ensemble of ARs, namely, in the NCEP/NCAR Reanalysis 1 (NCEP1), ECMWF ERA-40 reanalysis, the Japanese 55-year reanalysis (JRA-55), ECMWF Reanalysis v5 (ERA5), and two ARs that assimilate only a limited number of surface variables—NOAA-CIRES-DOE Twentieth Century Reanalysis version 3 (20CRv3) and ECMWF twentieth century reanalysis (ERA-20C).A survey on the accordance of daily circulation types (CTs) identified in daily mean sea level pressure, 700 hPa and 500 hPa geopotential height fields is carried out for boreal (DJF) and austral (JJA) winters. The CTs are independently calculated in many 30° × 20° (longitude × latitude) overlapping regions by a k-means algorithm, each region centred on one of the total of 9,360 grid points that cover the Earth from 80°S to 80°N at the step of 2.5° × 2.5°.Not surprisingly, marked differences can be found between ARs in the pre-satellite era, particularly at the surface and over the Southern Hemisphere. Although the accordance of ARs tends to increase over time, there are several regions in which significant differences persist into the 21st century (central South America, sub-equatorial Africa, northern parts of the Indian subcontinent, western parts of China, and Antarctica).In the presentation, methodological issues (number of CTs, size of classification domain, choice of circulation variable, choice of classification method, and type of normalization of fields prior to their classification) will be discussed, and a physical interpretation of inter-reanalysis differences will be provided.
Influence of buildings and trees on PALM model’s shortwave radiation modeling
Authors: Radović Jelena , Belda Michal , Geletič Jan , Bureš Martin , Eben Kryštof , Krč Pavel , Resler Jaroslav , Řezníček Hynek
Published: July 2024

The utilization of micrometeorological models for urban planning purposes, mitigation strategies development, and studying the atmospheric boundary layer of densely built urban environments has become ever-increasing. Due to the high complexity and variety of urban structures within the cities (e.g., urban fabric, transit roads, green urban areas, water bodies, sports, and leisure facilities, etc.), a comprehensive assessment of these areas and their interaction with the atmosphere is a complicated task. One of the physical processes strongly influenced by the city’s configuration, presence of trees, and buildings is the radiative transfer within the urban environment (e.g., absorption, scattering, emission, reflections between individual surfaces, etc.). Precise modeling of the radiative transfer processes is of particular importance due to their influence on the surface radiation budget, human energy balance, building energy management, etc. Hence, for a model to be operational for various purposes its validation and assessment of the radiation modeling aspect is necessary for everyday usage.   In this study, the numerical simulations are performed by the micrometeorological model PALM. The model was configured and run in the spin-up mode, during which LSM, BSM PCM, RTM, BIO, and MESO modules were utilized. The selected domain is located in a realistic and densely built urban area within the city of Prague, has an extent of 800 x 500 m, and is simulated in 1 m resolution. For experiment purposes, we selected two different episodes with clear-sky conditions during the year 2019. The PALM model outputs have been evaluated against three different stations, both quantitatively and qualitatively.We validate the shortwave radiation modeled by PALM at the height corresponding to the height of the sensor and show how the microscale model modifies direct and reflected shortwave radiation by performing a comparison against measurements collected at three different locations within the simulation domain. The findings of this study show and lead to a better understanding of how trees, buildings, and albedos of different surfaces affect and modify shortwave radiation in urban environments. 
Ensemble forecast of extreme precipitation in Europe by combining a stochastic weather generator with dynamical models 
Authors: Krouma Meriem , Messori Gabriele
Published: July 2024

Ensemble precipitation forecasts with sub-seasonal lead times provide useful information for decision-makers when they sufficiently sample the possible outcomes of trajectories. In this study, we present a forecasting tool for extreme precipitation ensemble forecast over Europe using a stochastic weather generator (SWG) based on analogs of the atmospheric circulation. This approach is tested for sub-seasonal lead times (from 2 to 4 weeks) to forecast European precipitation and temperature as well as the Madden Jullian Oscillation (Krouma et al, 2022,2023). SWG ensemble forecasts yield promising probabilistic skill scores for shorter and sub-seasonal timescales for precipitation (Krouma et al., 2022,2024) as well as for temperature (Yiou and Déandréis, 2019).An updated version of the SWG, HC-SWG forecasting tool (HC refers to Hindcast and SWG to the stochastic weather generator) based on a combination of dynamical and stochastic models, was used to forecast European precipitation for the sub-seasonal lead time (Krouma et al., 2024, in review, QJRMS). The HC-SWG is based on analogs of the S2S model of the ECMWF and CNRM ensemble members 5 days ahead. We obtained reasonable forecast skill scores at the station level with respect to climatology. And we found that the HC-SWG shows improvement against the ECMWF precipitation forecast until 25 days.In this work, we aim to use the HC-SWG to generate an ensemble of 100 members for extreme precipitation over Europe at the station level (Stockholm, Madrid, Paris..). We evaluate the ensemble forecast of the HC-SWG and we compare the HC-SWG forecast with other precipitation extreme forecasts to further confirm the advantage of our method.
Development of a Pedestrian-Feeling Temperature Prediction (PeFT) Model during the Heatwave using Artificial Intelligence
Authors: Kang Minsoo , Park Moon-Soo , Kim Seok-Cheol , Baek Kitae
Published: July 2024

The urban heat island is intensified due to the continuous temperature increase caused by climate change, leading to consistent property and casualty damages in urban areas. Urban areas are more vulnerable to heatwave events than rural areas. In order to reduce the damage caused by heatwaves in urban areas, it is necessary to analyze and predict meter-scale pedestrian-feeling temperature in street canyon surrounded by high-rise buildings. This study developed a pedestrian-feeling temperature prediction (PeFT) model using the data obtained from the building-block 3-dimensional urban meteorological experiment (BBMEX) campaign, conducted at urban center in Seoul, Korea during heatwave period. The thermal comfort types (TCTs) were defined to reflect the comfortability of pedestrians in urban areas. The TCTs and meteorological variables observed by the Korea Meteorological Administration were used as input data for the PeFT model. The temperatures at surface, 0.5m, 1.5m, and 2.5m high, observed by BBMEX campaign, were trained as target data for the model. Four machine learning techniques (generalized linear model, random forest, support vector machine and automatic machine learning) and four types of input data sets were tested. The optimal PeFT model was constructed by considering the root mean square error and determination coefficient (R2). The model was applied to produce the gridded temperature at four levels in the same area during another period. The PeFT model showed a potential to produce the 3-dimentional temperature distribution with a horizontal resolution of less than 5m within 3m height using the operational air temperature.Keywords: meter-scale, pedestrian-feeling temperature, Pedestrian-Feeling Temperature prediction (PeFT) model, street canyon, Thermal Comfort Type (TCT)Acknowledgements: This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF , 2021R1I1A2052562) funded by the National Institute of Meteorological Sciences (NIMS). 
A Comparative Analysis of Nowcasting Floods with Augmented Data
Authors: Baydaroğlu Özlem , Demir Ibrahim
Published: July 2024

Climate change is linked to changes in rainfall patterns and an increased susceptibility to both floods and droughts. There is a pressing need to enhance forecasting and monitoring technologies in response to the occurrence of flash floods and severe flooding. Rainfall prediction is a challenging but critical issue owing to the complexity of atmospheric processes, the spatial and temporal variability of rainfall, and the dependency of this variability on several nonlinear factors. Accurate real-time rainfall nowcast is crucial for taking necessary precautions, implementing control measures, and planning, as excessive rainfall is responsible for disasters including floods and landslides. This study examines the application of NASA Giovanni satellite-derived precipitation products with the ConvLSTM method, a variant of LSTM, for the purpose of nowcasting rainfall. Data augmentation is employed using interpolation techniques including nearest neighbor, bilinear, bicubic, distance weighted average, first and second order conservative and largest area fraction techniques to meet the data requirements of deep learning-based prediction algorithms. The objective of the study is to evaluate the influence of data augmentation on flood nowcasting. Thanks to these methods, the study utilized three types of satellite-derived rainfall data, including spatial, temporal, and spatiotemporal interpolated rainfall data, to conduct a comparative analysis of the results obtained through nowcasting rainfall. This research examines two catastrophic floods that transpired in Türkiye Marmara Region in 2009 and Central Black Sea Region in 2021, which are selected as the focal case studies. The Marmara and Black Sea regions are prone to frequent flooding, which, due to the dense population, has devastating consequences. Furthermore, these regions exhibit distinct topographical characteristics and precipitation patterns, and the frontal systems that impact them are also dissimilar. The results of nowcasts for floods exhibit substantial variations, both between the two regions and across nowcasts generated using raw and augmented data.
The impacts of energy burden and social vulnerability in Taiwan under climate change and urban heat island
Authors: Chang Cing , Lin Tzu-Ping
Published: July 2024

As global temperatures rise, there is a significant increase in the demand for cooling energy in buildings, leading to heightened attention on urban energy demands. The direct impact of cooling demand on urban energy burdens, coupled with a growing body of literature on energy, poverty, and other social factors, has underscored the importance of this issue. This study focused on exploring the relationship between Taiwan's regional climate conditions in high-temperature environments, social factors in geographical context, and energy burdens. The objective was to analyze the distribution of energy burdens affected by thermal shocks and social vulnerability, identifying vulnerable areas to facilitate climate change adaptation strategies.Covering 20 counties and cities in Taiwan, this study employed administrative divisions as analytical units to discuss the distribution of energy burdens in Taiwan in 2018 and 2023. Regarding climatic factors, this study adopted the dynamical downscaling data produced by National Science and Technology Center for Disaster Reduction (NCDR). The data included the changes in energy demand under the current and IPCC-defined RCP8.5 warming scenarios. Additionally, the study examined the influence of social factors such as population structure, socioeconomics, and social vulnerability.The results reveal variations in the distribution of energy burdens in 2023, ranging from a minimum of 0.2% to a maximum of 30%. Over half of the counties and cities have energy burdens concentrated between 5.4% and 7.9%. Cooling demand in Taiwan is highest in July, followed by August. Therefore, the high energy burden is reflected in the months of August and September. In the climate change scenario, the demand for cooling increases by up to 26.3% in August. The spatial distribution shows that energy burdens are higher in mountainous and suburban areas, despite lower cooling demand there. Conversely, high cooling demand is concentrated in major urban centers, where energy burdens are lower. Finally, the study integrates distribution maps of cooling demand and other social factors to explore the relationship between energy burdens and climate, population, and society.Keywords: Energy Burden; Cooling Degree Hours; Spatial Analysis; Climate Change
Health risks of extreme temperatures on mortality and ambulance operations in Finland
Authors: Haga Lisa , Ruuhela Reija
Published: July 2024

Climate change is expected to increase various health effects on human health such as  increased temperature-related mortality and morbidity and spread of different vector or viral borne new diseases. Finland is a sparsely populated country which generates challenges and uncertainties in modelling heat-related mortality and morbidity.In this presentation, we will present preliminary results on future temperature-mortality relationships from different wellbeing areas in Finland using mortality and climate model data. In the results we will show how future projections of heat-related mortality will look like until 2100 with selected CMIP6 models under two climate change scenarios, SSP2-4.5 and SSP5-8.5. Heat-related mortality is heterogeneous in different regions of the country and in the future the most heat vulnerable areas are found in the capital region and the southern parts of Finland. For other regions, such as the northern, central and western parts of the country the results are mixed and present only a slight increase in the heat-related mortality change.Extreme temperatures also influence on ambulance operations in various ways. We will show examples how ambulance operations are affected by extreme temperatures in Helsinki applying a distributed lag nonlinear model (DLNM). Understanding associations between weather and different emergency service operations is important for resource management and preparing for the future.Modelling future heat-related mortality and analyzing ambulance service weather dependencies include limitations and uncertainties and these factors are also discussed from different perspectives. Longer and more frequent heatwaves might also lead to higher than estimated mortality rates in other regions of the country than expected and thus people living in these areas should also implement heatwave adaptation plans.
Drought Monitoring and Analysis in Mainland Portugal 
Authors: Pires Vanda , Cota Tânia
Published: July 2024

Climate describes how the atmosphere behaves over a long period of time informing us on the “average of weather”, as well as the description of other aspects of weather patterns and meteorological parameters’ distribution, including anomalous, rare and extreme events. Some examples of extreme weather or climate events include heat waves, cold waves, floods, extreme precipitation, drought, tornadoes and tropical cyclones (WMO-CCL, 2018).Drought is a natural weather phenomenon that occurs in all climates and can differ greatly from other extreme events. Unlike other extreme events, such as floods, which are weather events that are immediately detectable, droughts develop slowly, making it difficult to determine the onset and end.Portugal is a country with recurrent phenomena’s of drought, which creates the strong need for impact reduction strategies as an integral part of drought preparedness plans.To better understand the risk of droughts in mainland Portugal, was used indices that rely on precipitation deficits and allows us to characterize and monitor drought in Portugal, determining drought onset, duration and intensity. In this study was used the PDSI (palmer Drought Severity Index), SPI (Standardized Precipitation Index), SMI (Soil Moisture Index).These indices were computed using daily and monthly data and based on the recommendations of CCL task team on the definition of extreme weather and climate events: Threshold (is determined based on historical values of the index); Temporal (Station-level information on starting date, ending date, and duration of the event); Spatial (calculates the area affected, by providing the distribution of stations where the threshold was surpassed and uses a geographical information system (GIS) to determine the area affected by the event, the magnitude, and severity).In order to characterize the drought events was used the following properties:Magnitude: measures the departure from the threshold and reflects unusualness or extremity of the event.
Duration: defined by the time at which the event begin and end.
Extent: defined as the geographical area affected by the extreme event.
Severity: severity should indicate the potential damages and impacts that can be associated to the event. It is a combination of magnitude and persistence of a drought.
It is also aimed the framing of this extreme event with climate changes based on trend analyses and simulation of scenarios with variables such as precipitation, temperature and evapotranspiration.
Changes in bioclimatic conditions in Nuuk (SW Greenland) in the years 1874–202
Authors: Araźny Andrzej , Chmist Konrad , Przybylak Rajmund , Wyszyński Przemysław , Singh Garima
Published: July 2024

Human biometeorology as a discipline of applied climatology is important in various spheres of human activity (from everyday life to natural environmental protection, tourism and recreation, spatial organisation and others). In polar areas, e.g. in the Arctic, the thermal load on the human body caused by the environment is an important indicator of climatic discomfort, where extreme cold is recorded often combined with strong winds.The aim of this study is to present changes in bioclimatic conditions over the last ~150 years in south-west Greenland. This is an attempt to estimate, for the first time, the conditions experienced by humans in the Arctic over such a long time horizon, i.e. from the end of the 19th century to the beginning of the 21st century.The study for the Nuuk station used meteorological data (air temperature and wind speed) from the Danish Meteorological Yearbooks (Meteorologisk Aarbog) from the period 1874–1957. Modern (1958–2020) meteorological data for Nuuk (station no. 4250) are taken from the collection of the Danish Meteorological Institute (DMI) from report No. 21-08 archived at https://www.dmi.dk/publikationer/. Data are stored in two different formats for the particular periods 1958–2013 and 2014–20 (for more details, see Cappelen 2021).The study analysed two biometeorological indexes: wind chill temperature (WCT) and predicted clothing insulation (Iclp). Apparent cold and extent of frostbite risk to the human body were assessed using the WCT. On the other hand, the thermal insulation of clothing required for a person to maintain thermal equilibrium in a given set of meteorological conditions was estimated using the Iclp index. Both biometeorological indices were calculated using BioKlima 2.6 software (https://www.igipz.pan.pl/bioklima-crd.html).The work was supported by the National Science Centre, Poland, project No. 2020/39/B/ST10/00653. References:Cappelen J. 2021. Weather observations from Greenland 1958–2020, DMI Report 21–08, https://www.dmi.dk/fileadmin/Rapporter/2021/DMIRep21-08.pdfMeteorologisk Aarbog.  1874–1957. Det Danske Meteorologiske Institut, Kjøbenhavn  
A Case Study for the Application of the GraphCast AI Model in Hungary
Authors: Varga-Balogh Adrienn , Leelőssy Ádám , Varga László , Mészáros Róbert
Published: July 2024

This study investigates the applicability of the recently released (2023) GraphCast artificial intelligence (AI) model for weather forecasting in Hungary. We assess the model's accuracy in forecasting for grid data at various points across Hungary for a case study of crossing of a cold frontal zone in March 2023. We compared GraphCast predictions with observations and established weather models to evaluate its potential for weather forecasting.GraphCast is a machine learning system for weather forecast developed by DeepMind. Unlike traditional weather models that rely on complex physical equations, GraphCast leverages historical weather data to identify patterns and relationships between different locations. By feeding the model with data from two time points (6 hours apart), up to 7-day GraphCast predictions were made with 6-hour temporal and 1° spatial resolution. Model predictions were compared to the data of the nearest weather station.Our analysis involves a detailed comparison between modeled outputs from GraphCast and actual measurement data series collected from Hungarian meteorological measurement stations, ERA5 reanalysis and the operational weather forecasts of the GFS numerical weather prediction model. The purpose of this comparison is to quantify the effectiveness of the model in reproducing grid point data across various time scales. To strengthen the generalizability of our findings, we explore the sensitivity of the model's predictions on different initialization times and forecast lengths overlapping the arrival of the cold frontal zone.The findings from this research will contribute to the ongoing evaluation of AI-based predictive models. By analyzing GraphCast's performance in a case study, we can determine its potential for application in weather forecast.The research was funded by the National Multidisciplinary Laboratory for Climate Change, RRF-2.3.1-21-2022-00014 project.
ONA-ENS, the multimodel sea wave prediction system of the SMC
Authors: Assimenidis Sotiris , Bravo Manel , Mercader Jordi , Moré Jordi
Published: July 2024

In Catalonia, with around 580 km of coast, most of the population living in the littoral and a lot of socioeconomic activities relying on the sea, accurate wave prediction is essential. The Meteorological Service of Catalonia (SMC) plays a critical role in issuing warnings to the authorities and the population to mitigate potential risks associated with the sea state. Due to the intrinsic uncertainty of the wave models and the probabilistic nature of the early warnings, an Ensemble Prediction System (EPS) is of great help, if not mandatory, to issue these early warnings.  

ONA-ENS (multimOdel oceaN wAve Ensemble for the catalaN coaSt) is the multimodel and multiphysics sea wave EPS developed in the SMC for the Balear-Catalan Sea, in the western Mediterranean. It uses the two spectral wave models that are already running in the SMC, SWAN and WW3. In order to take into account the model uncertainty, each model is run with three different parameterizations of the generation and dissipation of the waves. In addition, the initial conditions uncertainty is introduced by using two atmospheric global models, IFS and GFS, that initialize two configurations of the regional model WRF. These atmospheric models produce the wind fields that drive the wave models. Thus, there are four atmospheric members that initialize six wave configurations, creating a 24-member sea wave ensemble. The system is run every day at 00 UTC, with hourly time steps up to five days, at a 3 km spatial resolution.  

Here we share the verification results of the ONA-ENS using the data obtained from the 7 buoys of Puertos del Estado available in the Balear-Catalan Sea during 2023. Comparisons against the deterministic operational models at the SMC reveal a reduction in bias. From a probabilistic point of view, comparisons with the ENS ECWAM from ECMWF show an improvement in the dispersion for the first days of the forecast. 
Strong winds in Poland from the 13th to 18th centuries
Authors: Przybylak Rajmund , Araźny Andrzej , Filipiak Janusz , Oliński Piotr , Szwaba Artur
Published: July 2024

For the first time, a comprehensive database of strong winds related to the period prior to 1800 has been created for Poland by team of climatologists and historians based on all documentary evidence available for us. The work was done within a NCN project entitled The occurrence of extreme weather, climate and water events in Poland from the 11th to 18th centuries in the light of multiproxy data. The following documentary sources were used: handwritten and unpublished, published, and so-called “secondary” literature. The database contains detailed information about the occurrence of strong winds (the location/region, time, duration and indexation for intensity, extent and character of damage), as well as the exact textual content of the original weather note, the name of the source, and an evaluation of the source’s quality. Indexation of intensity, initially done by the author of a particular contribution (record), was then evaluated by the whole team preparing the database. Four categories of strong winds were delimited: 1 − fresh and strong breeze (Beaufort scale 5–7), 2 − gale (8–9), 3 − storm (10–12), and 4 − squall (i.e., gusty wind during a thunderstorm). Extent and character of damage was estimated based on the proposition given by Brázdil et al. (2004), slightly modified by us to include the Baltic Sea and its influence on coastal parts. In the database, ~1,200 thus-defined strong winds were identified. The first weather note reporting an occurrence of strong wind (gale) was found for the year 1283. In the paper, the preliminary results describing frequency of occurrence of strong winds in the area of Poland and in its different regions will be presented. In addition, results of the extent and character of damages will be shown. Some case studies of particularly strong winds (including identified tornadoes) will be analysed in detail. The frequency of occurrence of strong winds in the historical period (1201–1800) and some of its sub-periods will be compared with contemporary results taken from 12 meteorological stations (Świnoujście, Chojnice, Olsztyn, Suwałki, Poznań, Kalisz, Warszawa, Siedlce, Kraków, Tarnów, Wrocław and Opole) from the period 1991–2020.The work was supported by the National Science Centre, Poland, project No. 2020/37/B/ST10/00710. Reference:Brázdil R, Dobrovolný P., Štekl J., Kotyza O., Valášek H, Jež J., 2004, History of weather and climate in the Czech Lands VI: Strong winds, Masaryk University, Brno.
Saharan dust in the Finnish atmosphere and on the ground: Citizen science to verify transport and deposition modeling
Authors: Meinander Outi , Kouznetsov Rostislav , Uppstu Andreas , Sofiev Mikhail , Kaakinen Anu , Salminen Johanna , Rontu Laura , Welti André , Francis Diana , A. Piedehierro Ana , Heikkilä Pasi , Heikkinen Enna , Laaksonen Ari
Published: July 2024

Long-range transported mineral dust has a wide range of direct and indirect effects as a pollutant, nutrient and climate-forcer.  On 21–23 February 2021, dust from a sand and dust storm in northern Africa was transported to Finland, north of 60°N.  The episode was predicted 5 days in advance by the global operational SILAM forecast (silam.fmi.fi). The scavenging of dust by snowfall and freezing rain in Finland resulted in a rare case of substantial mineral dust contamination of snow surfaces over a large area in the southern part of the country. A citizen science campaign was set up to collect contaminated snow samples prepared according to the scientists’ instructions. The campaign gained wide national interest in television, radio, newspapers and social media, and dust samples were received from 525 locations in Finland, up to 64.3°N. The samples were utilised in investigating the ability of an atmospheric dispersion model to simulate the dust episode. The magnetic properties and mineralogy of the particles combined with modeling confirmed that dust came from a wide Sahara and Sahel area from 5000 km away. The modeled deposition area agreed well with the citizen observations and measured particle size distributions. Overall, our results revealed the features of this rare event and demonstrate how deposition samples can be used to evaluate the skills and limitations of current atmospheric models. Previously, a strong Saharan dust deposition in Finland has been documented for northern Finland in 1991. It is estimated that Saharan dust reaches Finland every year, but most often the dust remains in the atmosphere and deposits on the ground only seldom in Finland. ReferencesMeinander, O., Kouznetsov, R., Uppstu, A. et al. African dust transport and deposition modelling verified through a citizen science campaign in Finland. Sci Rep 13, 21379 (2023). https://doi.org/10.1038/s41598-023-46321-7
Impact of climate change on wind resource along the French coastline
Authors: Patra Anindita , Oueslati Boutheina , Kervella Youen , Renaud Paul , Dubus Laurent
Published: July 2024

Climate change will have clear impacts on wind resource that are highly dependent on regions and on greenhouse gases emission scenario. These changes will significantly affect the development and utilization of regional wind energy given the massive integration of wind power in the electrical system. In this context, we aim to assess the impact of climate change on wind resource along the French coastline in order to provide stakeholders in the offshore wind sector with appropriate indicators and trends to assess the expected evolution for the next few decades and to quantify associated uncertainties. First, we investigate several sets of wind-speed data from in-situ measurements (LIDAR and coastal meteorological stations) at the local scale on the different coastline regions of mainland France: English Channel, Bay of Biscay, and Mediterranean Sea. Then comparisons between measurements and numerical reanalyzes (ERA-5, COSMO-REA6, CERRA) are carried out for inter-annual variability, seasonal cycle, diurnal cycle and distribution of wind at different levels. The wind speed from CMIP6 Climate models is also evaluated for the historical period in comparison to reanalyzes and measurements to select the best performing models. Climate change effects on wind speed are then assessed on particular sites of interest on the different coastline regions of mainland France based on bias-corrected climate projections. The possible drivers and tendencies are identified. In addition, events of low wind speed, under cut-in velocity of offshore wind turbines, and high wind speed, above the cut-off velocity are studied to best determine future changes in electrical production.
Understanding reference evapotranspiration distribution and evolution in the Northwestern Mediterranean basin
Authors: Cortès Maria , Altava-Ortiz Vicent
Published: July 2024

Drought episodes are among the most devasting natural disasters impacting agriculture, forests, the environment, and economic activity. Catalonia, in the Northwestern Mediterranean basin, is currently experiencing its most severe drought episode on record.For a comprehensive examination of drought episodes, it is crucial to consider different processes involved in water balance. However, many studies tend to focus solely on precipitation scarcity, often overlooking other critical variables like evapotranspiration or approximating it through simplified methods.While uncertainty persists regarding present and future precipitation patterns in the Mediterranean basin, the temperature is showing a steady increase and is projected to rise even more in the future. This rise could intensify evapotranspiration rates, exacerbating drought episodes. Nonetheless, it is essential to note that evapotranspiration is not only influenced by temperature; other meteorological variables such as solar radiation, relative humidity, and wind also play significant roles. This study aims to analyze the relative impact of different meteorological variables on evapotranspiration to better understand the factors affecting this relevant phenomenon for drought management in Catalonia. Such insights will provide valuable information for adapting to future droughts episodes.The study proposes an  in-depth analysis of evapotranspiration in Catalonia, using data collected by the XEMA observation network of the Meteorological Service of Catalonia (SMC). This network extensively covers the region, providing data for calculating evapotranspiration on  monthly, daily, and even hourly time scales. Taking advantage of this dataset, the Penman-Monteith formulation is employed to compute reference crop evapotranspiration (ETo). The evolution of this variable in the territory, its spatial distribution, and case studies such as the recent 2020-2024 episode are studied.