bluuebunny/crossref_metadata_2025 huggingface dataset:
Upgrade of the educational and outreach activities of the Meteorological Service of Catalonia 
Authors: Busto Montserrat , del Amo Xènia
Published: July 2024

The technical staff of the Meteorological Service of Catalonia (SMC) has consistently collaborated with schools, organizations, and associations to expand knowledge related to meteorology and climatology. A group of volunteer technicians carried out educational tasks spontaneously, lacking clear organization, structure, or standardized content.To improve this situation, the SMC developed an Educational Program in 2021. The main goals of the Educational Program of the SMC are to enhance the public's knowledge of meteorology and climatology, to create a ‘learning space’ focused on the acquisition of ideas and values (inclusive material, avoid gender bias, etc.), to form a critical, committed, and active citizenry to develop a better society.The development of this Educational Program has resulted in a significant improvement in the quality of educational activities. It promotes the definition of objectives, fosters the development of specific pedagogical resources for each age group, clarifies pedagogical goals, defines final assessments, and facilitates the pedagogical task and the dedication of volunteer staff. It also allows for the comprehensive planning of educational activities and engagement with the external public.Once the Educational Program was defined, voluntary pedagogical training sessions were conducted -open to all technical staff of the SMC- to facilitate the transmission of concepts and values following current pedagogical parameters (importance of emotions, social learning, connectivity between different knowledge, existence of different learning rhythms and styles, evaluation as a tool for constant improvement).The activities of the Educational Program are structured into three axes: Meteorology, Climate, and Climate Change. In 2022, a public competition was held to find a support company that would facilitate the development of educational activities. Throughout 2023, the deployment of the Educational Program began with the development of twenty-one new educational activities.Current educational activities cater to all types of audiences, from kindergarten to high school, including the general public. Some activities are designed to be developed by SMC technical staff, while others have been designed to be carried out autonomously by teachers. There is a wide range of activities: experiments, learning scenarios, ‘weather walks’ through Barcelona, games (severe weather phenomena), videos (prevention in dangerous weather situations), etc.
Influence of the previous North Atlantic Oscillation (NAO) on the spring dust aerosols over North China
Authors: Li Yan , Li Xu
Published: July 2024

The North Atlantic Oscillation (NAO) has been confirmed to be closely related to the weather and climate in many regions of the Northern Hemisphere; however, its effect and mechanism upon the formation of dust events (DEs) in China have rarely been discussed. By using the station observation dataset and multi­ reanalysis datasets, it is found that the spring dust aerosols (DAs) in North China (30-40° N, 105- 120° E), a non-dust source region, show high values with a strong interannual variability, and the spring DAs in North China are significantly correlated with the previous winter's NAO. According to the nine spring DEs affected significantly by the negative phase of the preceding winter's NAO in North China during 1980-2020, it is shown that before the outbreak of DEs, due to the transient eddy momentum (heat) convergence (divergence) over the DA source regions, the zonal wind speed increases in the upper-level troposphere, strengthening the zonal wind in the middle-lower levels through momentum downward transmission. Simultaneously, there is transient eddy momentum (heat) divergence (convergence) around the Ural Mountains, which is favorable for the establishment and maintenance of the Ural ridge, as well as the development of the air temperature and vorticity advections. The combined effects of temperature and vorticity advections result in the Siberian Highs and Mongolian cyclone to be established, strengthen, and move southward near the surface, guiding the cold air from high latitudes southward, and is favorable for the uplift and transmission of DAs to North China downstream. Simultaneously, the changes in upstream transient eddy flux transport can cause both energy and mass divergence in North China, resulting in diminishing winds during DEs, which would facilitate the maintenance of dust aerosols here and promote the outbreak of DEs. This study reveals the impact of transient eddy flux transport on the dusty weather anomalies modulated by the NAO negative signal in North China, which deepens the understanding of the formation mechanism of DEs in China.
Unveiling Harmful Algal Bloom Dynamics with Sparse Identification of Nonlinear Dynamics and the Model-based Web Platform for Lakes
Authors: Baydaroğlu Özlem , Yeşilköy Serhan , Linderman Marc , Demir Ibrahim
Published: July 2024

The proliferation of harmful algal blooms (HABs) is a significant environmental issue exacerbated by climate change. They have many detrimental impacts on public health, recreational activities, ecological equilibrium, animals, fisheries, microbiota, water quality, and the economy. HABs can be attributed to various factors, including water pollution resulting from agricultural activities, discharges from wastewater treatment plants, leakages from sewer systems, natural factors such as pH and light levels, and the impacts of climate change, such as increased water temperature, reduced water flows due to droughts, and water-related disasters like flooding and inundation. Although numerous causes of HABs are acknowledged, the mechanisms by which toxin-producing algae develop, as well as the crucial processes and components that contribute to their proliferation, remain unknown. This lack of understanding is primarily due to the unique dynamics of each lake's algal population and the nonlinear nature of the conditions that influence these dynamics. Modeling HABs in a changing climate is critical to meeting sustainable development targets for clean water and sanitation. Nevertheless, the absence of adequate and sufficient data on HABs poses a substantial obstacle for research endeavors. This study utilized the sparse identification nonlinear dynamics (SINDy) technique to model microcystin, which is a toxin produced by algae, using dissolved oxygen as a variable for water quality and evaporation as a meteorological parameter. SINDy is a state-of-the-art approach that integrates sparse regression and machine learning methodologies to reconstruct the analytical representation of a dynamic system. Furthermore, a web platform was developed that utilizes models and is accessible through the web. This tool aims to promote and enhance environmental education, increase the public's awareness of these events, and generate more efficient solutions to them by using what-if scenarios. This web platform allows tracking the status of HABs in lakes and observing the impact of specific parameters on harmful algae formation. On an interactive and user-friendly platform, users may effortlessly share photographs of HABs in lakes, enabling others to monitor the lakes' status.
Forecasting global radiation directly from Meteosat SEVIRI spectral observations 
Authors: Carpentieri Alberto , Meyer Angela
Published: July 2024

Renewable energy forms a major pillar of climate change mitigation. Yet, the inherent volatility of solar irradiance as a primary renewable energy source poses significant challenges. The stochastic dynamics of clouds induce rapid fluctuations in photovoltaic energy production by modulating incoming solar irradiance, which is a challenge for grid operators. More accurate solar irradiance forecasts encompassing the grid area and associated photovoltaic plants will help address this challenge.We will provide an overview of regional forecasting methods for surface solar irradiance (SSI) using satellite observations for forecast lead times of minutes to hours. Existing solar forecast models are based on Level-2 products that comprise satellite-derived estimates of SSI or clear-sky index (e.g., Carpentieri et al., 2023) such as the third edition of the Surface Solar Radiation Data Set - Heliosat (SARAH-3; Pfeifroth et al., 2021).We present a probabilistic regional solar forecast model for lead times of up to several hours that has been trained directly on visible and infrared satellite radiances. We utilise the multispectral Level-1.5 images of the Spinning Enhanced Visible Infra-Red Imager (SEVIRI) imager aboard the Meteosat Second Generation geostationary satellite to this end. Our solar forecast model is based on the architecture of the generative SHADECast model (Carpentieri et al., 2024). Leveraging multiple years of SEVIRI scans, we demonstrate accurate probabilistic forecast of spatially extended surface solar irradiance fields and forecast model runtimes reduced to the order of seconds to minutes. We chacterise the model performance including benchmarks with existing solar forecast models and discuss the Meteosat channel importance for solar forecasting. Carpentieri, A., S. Pulkkinen, D. Nerini, D. Folini, M. Wild, A. Meyer, Intraday probabilistic forecasts of surface solar radiation with cloud scale-dependent autoregressive advection, Applied Energy, 351, 2023. doi:10.1016/j.apenergy.2023.121775 Carpentieri, A., D. Folini, J. Leinonen, A. Meyer, 2024, Extending intraday solar forecast horizons with deep generative models, arXiv:2312.11966, doi:10.48550/arXiv.2312.11966 Pfeifroth, U., J. Drücke, J. Trentmann, R. Hollmann, 2021, SARAH-3 - a new satellite-based Cimate Data Record for surface radiation parameters from the CM SAF, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-454, doi:10.5194/ems2021-454
Evaluation of the mortality risk reduction effects of countermeasures to nocturnal UHI
Authors: Yamaguchi Kazuki , Iwanaga Hiroyuki , Takane Yuya , Ihara Tomohiko
Published: July 2024

Heatstroke mortality during nighttime sleep is expected to rise as global warming and urban heat islands (UHI) become more prevalent. Measures that can reduce nighttime temperatures include greening and anthropogenic heat reduction. However, it is difficult to compare health impacts using the same temperature index because the peak time period when temperature reduction is most effective, varies greatly between measures. Therefore, this study proposed a daily temperature index that can consider health effects by time of day and used this index to compare and evaluate the mortality risk reduction effects of measures on nocturnal UHI.When the human body is exposed to a certain temperature, health effects can last for days or even weeks. This study used a distributed lag nonlinear model (DLNM) to assess the relationship between temperature indices and mortality risk taking into account the lag effect. The study was conducted in the Tokyo metropolitan area from 2000 to 2010, using data from demographic surveys on air temperature and mortality. First, a mortality risk prediction model was developed using the DLNM, with the temperature every hour of the day as the explanatory variable, and the optimal temperature with the lowest mortality risk was determined for each hour. Next, the mean deviation between the optimal temperature and the observed temperature at each time of day was calculated for each of three time periods (2–9, 10–17, and 18–1 h), and the daily weighted average deviation ΔTday was calculated using the combination of weight coefficients that minimizes the Quasi Akaike Information Criterion (QAIC) of the forecast model. This combination (0.67, 0.13, and 0.20) suggests that the temperature deviations have a five-fold greater impact at night (2–9 h) than during the daytime (10–17 h). The model with ΔTday had a lower QAIC and higher prediction accuracy than models with daily maximum or daily mean temperatures.Three countermeasure scenarios for nocturnal UHI were compared and evaluated: ground greening (doubling the area of green space), electric vehicles (with 100% penetration), and air-source heat pump (HP) water heaters (with 100% penetration) that emit cold exhaust heat at night. The evaluation target area included the entire 23 wards of Tokyo, and the daily ΔTday was estimated on a mesh-by-mesh basis using an urban canopy model to compare and evaluate heat-related excess mortality risk reduction rates in August. The results showed that the three scenarios had similar mortality risk reduction effects for the entire area, but their effects had different geographic distribution characteristics. The HP water heater scenario showed particularly large impact in residential areas with large nighttime populations.
Assessing the exposure of diverse populations to heat under a thermo-physiologically consistent approach in a large Mediterranean urban area
Authors: Galanaki Elissavet , Agathangelidis Ilias , Giannaros Christos
Published: July 2024

Population exposure to hot weather and heat waves endangers human liveability and survivability. The assessment of heat exposure spatiotemporal patterns in both recent past and future can provide essential guidance for targeted adaptation measures. However, existing studies on the topic focus only on environmental heat loads, using single meteorological variables (e.g. air temperature) or simple composite indices (e.g. heat index) to define heat. This diminishes the value of human physiological and behavioral responses to heat. Here, we extend the heat exposure concept to account for these factors and their variability among different population subsets when characterizing heat. For this purpose, we employ a novel, open-access 30-year (1991-2020) human thermal bioclimate dataset that includes hourly values of mPET (modified physiologically equivalent temperature) for diverse populations (https://doi.org/10.5281/zenodo.10893914). We focus on the Athens Urban Area (AUA), which consists of five regional units at the local administrative level, and it is situated in the eastern Mediterranean climate change hot spot. At a first stage, we analyze the long-term trends of acclimatization-based strong heat stress (accliSHS) experienced by male and female adults and seniors in the five AUA regional units. This stage of analysis accounts for accliSHS duration and frequency, as these factors are key in relation to adverse heat-related health outcomes. Then, we combine the mPET estimates with population data for each targeted group and regional unit to compute accliSHS exposure and assess its long-term trends. At this stage, contributions arising for variations in accliSHS and population sizes are decoupled and discussed, focusing on the differences between the examined populations and regional units in AUA. This work is conducted in the framework of the HEAT-ALARM research project and provides valuable insights with respect to population heat exposure for diverse groups of people under a comprehensive human-biometeorological context.
Assessment on the continuous measurements of snow water equivalent on the Monte Rosa massif (Italy) performed with state-of-the-art sensors in the 2023-24 winter season
Authors: Gallarate Mario , Colombo Nicola , Freppaz Michele , Gazzola Enrico , Henkel Patrick , Maiorano Michele , Viani Cristina , Benech Andrea , Giardino Marco , Acquaotta Fiorella
Published: July 2024

The effects of anthropogenic climate change are particularly evident in mountainous regions, where the warming rate is higher than the global average. In this framework, the Alps have recently experienced multiple seasons characterized by a deficit of solid precipitation compared to the historical records. This deficit resulted in a critical situation regarding the status of the snowpack in the Alpine Region. Since the vast majority of the hydrological assets present in Northern Italy are highly dependent on the snow melting from the Alps, a lack of solid precipitation during the snow season could lead to dire impacts on the hydrological balance of the region, as it has already happened during the snow-drought events occurred in the years 2022 and 2023. Therefore, it is of the outmost importance to accurately assess the amount of water present in the snowpack of the Alps, especially at high elevation, where observations are lacking. The snow water equivalent (SWE) represents the equivalent amount of liquid water stored in the snowpack. It is usually measured in situ during campaigns carried out by researchers and technicians. However, the measurements obtained in the field with this method may lack temporal density and continuity. To address this problem, it is widespread practice to derive the SWE from models which account for the snow density and the snow height. Recently, instruments have been developed to perform continuous measurements of the SWE even in remote areas. Here we present the SWE data of the 2023-24 season retrieved from a high elevation monitoring station located on the Monte Rosa massif in the Western Italian Alps. The station (45°52’30’’ N; 7°52’18’’ E; 2900 m a.s.l.) is equipped with two sensors which measure the SWE adopting different techniques. The first, developed by Finapp Srl, is based on the Cosmic Ray Neutron Sensing (CRNS) technology, and retrieves hourly measures of the SWE integrated on a circular area with a diameter of roughly 20 m. The second sensor, developed by ANavS GmbH, employs antennas with Global Satellite Navigation System (GNSS) to evaluate the daily SWE in a solid angle with an amplitude in the order of ten degrees. The data from the sensors are compared with each other and with SWE values obtained during field campaigns and by means of model simulations (with data obtained using the model SNOWPACK) to assess the performance of the installed instruments. The main goal is to determine the feasibility and the limits of these kinds of solutions, with the aim of extending the framework adopted for this work to remote Alpine sites that would benefit from the possibility of retaining continuous monitoring of the snowpack status.
Increasing complexity in Aerodynamic Gradient flux calculations inside the roughness sublayer applied on a two-year dataset
Authors: Melman Ewout , Rutledge-Jonker Susanna , Braam Miranda , Frumau Arnoud , Moene Arnold , Shapkalijevski Metodija , Vilà-Guerau de Arellano Jordi , van Zanten Margreet
Published: July 2024

Over tall canopies such as forests the atmospheric surface layer is subdivided into an inertial sublayer (ISL) and a roughness sublayer (RSL). Inside the RSL the classic aerodynamic gradient method using Monin-Obukhov similarity theory (MOST) by itself does not represent the gradient well and is insufficient to calculate fluxes. Over the past decades multiple studies have proposed methods to extend MOST to account for the different turbulent conditions, containing a wide range of approaches and complexity. In this study we investigate how much complexity is necessary to calculate the flux more accurate and what we can learn from the respective complexity. A large dataset is required to assess the statistical robustness of the respective complexity during different environmental conditions. To this end, we study and apply the effect of forest roughness and directional heterogeneity in our flux calculations on a two-year dataset (2009-2010) of the sensible heat flux measured over a Douglas fir forest in the Netherlands. We apply standard MOST, an observational based method (the α-factor) and a physically based method (Harman and Finnigan, 2007, 2008) (hereafter HF07/08) together with a range of methods for the displacement height (d). Our results show that both a simple method (the α-factor) and a complex method (HF07/08) are able to more accurately represent the flux but that, as expected, standard MOST (regardless of the method estimating d) alone is insufficient. Both the α-factor and (HF07/08) allow to analyze large scale patterns in canopy turbulence. Differences between the methods lie in the level of detail and practical usability.
20 years of data rescue initiatives at the Meteorological Service of Catalonia
Authors: Herrero-Anaya Monica , de Yzaguirre Xavi , Prohom Marc , Cunillera Jordi , Barrera Toni , Ruiz Adrian , Montserrat Jordi
Published: July 2024

Since the restoration of the Meteorological Service of Catalonia (SMC) in 2002, data rescue, quality control and homogeneity analysis of climate series have been one of the main focuses of the Climatology Area ofSMC. Working with continuous series, having a wide temporal coverage and ensuring good spatial density are essential for accurately characterizing climate change and variability.To achieve this goal, significant effort must be invested in data preservation and rescue, identifying meteorological series of interest, and ensuring good digitization, transcription and cataloging. This work describes the process of data rescue at SMC, from identifying meteorological significant collections, to entering all data into the historical base of SMC, while preserving original documentation.Collections with meteorological documentation vary widely.Historical newspapers. In recent years many state, provincial and local archives in Catalonia have tried to digitize historic newspapers.SMC has identified over 175 periodicals containing meteorological observations and metadata information.
Private archives. Several private archives, both religious and corporate, have been found to contain documentation related to meteorological observations.
Observers or their relatives who have preserved the original documentation, contact SMC for the preservation.
When a collection arrives at SMC, there are essentially four possibilities. (1) First, it may involve a temporary transfer of documentation, in which case it is digitized and returned to the owner. (2) Alternatively, if photography of the documentation is not permitted, it may be necessary to visit the location and transcribe the data. (3) A third option is that, once the documentation is digitized, it is restored if necessary and then entered into the National Archive of Catalonia through an agreement with SMC to ensure optimal preservation conditions. (4) Finally, data may be provided directly by the observer (already digitized or not), which can then be entered directly into the historical database.Once the data is extracted, any existing gaps in the historical database are filled, and coverage periods of the stations are extended. Data from previously unpublished stations are also incorporated, enriching and enhancing our ability to monitor variability and climate change in Catalonia.
Aerosol optical depth regime over megacities and possible links with their population changes 
Authors: Papachristopoulou Kyriakoula , Michailidis Konstantinos , Ciocan Gabriela , Kosmopoulos Georgios , Poutli Maria , Tokgöz Deniz D. G. , Dosev Stefan , Balakrishnan Priji , Gkikas Antonis , Kazadzis Stelios
Published: July 2024

More than 50% of the global population is hosted in cities of the world. The United Nations estimate that the number of inhabitants in the cities will be increased by about 2.5 billion people by 2050. Worldwide, the most pronounced urban population growth (up to 90%) is projected   for Asia and Africa. Such a population increase is expected to also increase the emissions of fine aerosols originating from anthropogenic activities. The World Health Organization estimates that the exposure to fine aerosol particles is responsible for 4.2 million premature deaths on an annual basis. In some countries, strategic national measures (i.e., U.S. and European Clean Air Acts, China's Air Pollution Prevention and Control plan) are applied for the mitigation of aerosol emissions. Such initiatives have been designed to tackle the urgent needs for combating air quality degradation, which in turn has subsequent impacts on human health.In this study, high resolution satellite-based data of aerosol optical depth (AOD) from the MODerate resolution Imaging Spectroradiometer onboard the Aqua satellite (MODIS-Aqua), in addition to ground-based sun photometric aerosol measurements and population data for 81 megacities (cities with more than 10 million inhabitants) are analyzed. Aspects that are addressed deal with the correlation of AOD variability and population growth and the effect of regional emissions in the AOD vs population links. As an example, India and China show contradictory AOD trends, being continuously increasing for India and declining for China, despite the recorded population growth in both countries. In addition, high spatial resolution data identify intra-city correlations among aerosols and population growth. In this case ground-based observations are also used aiming to understand possible spatial AOD inhomogeneities within a few kilometers in megacities and in the neighboring areas. Moreover, in the context of this work, long-term AOD retrievals obtained by the MAIAC (Multi-Angle Implementation of Atmospheric Correction) will be used for better data availability and for the potential to use additional auxiliary data to investigate the effects on several aspects. Finally, as a number of megacities are affected by natural aerosols (e.g. desert dust) we have tried to eliminate such effects as they are not linked with population growth, by using a fine spatial resolution dust optical depth product derived by the MIDAS (ModIs Dust AeroSol) dataset.AcknowledgementsThis study was funded by the COST (European Cooperation in Science and Technology) funding agency for research and innovation network; COST Action HARMONIA (International network for harmonization of atmospheric aerosol retrievals from ground-based photometers), CA21119.
Homogenisation and interpolation of subdaily bright sunshine duration time series in Slovenia
Authors: Vertačnik Gregor
Published: July 2024

Homogenisation and interpolation of bright sunshine duration time series in Slovenia have recently been renewed at Slovenian Environment Agency (ARSO). First, the quality of measured hourly to daily data at meteorological stations for the period 1960–2022 was checked. QC data was then aggregated to monthly sums, obtaining 27 stations’ time series, separately for three subdaily intervals. Monthly data was normalized relative to the maximum possible sunshine duration and transformed by arcus sinus function to improve the homogenisation with the HOMER software tool. Homogenisation was run in several iterations, using metadata and applying additive correction model with seasonally dependent corrections. Resulting homogenised time series were then back-transformed to the measurement units (hours).Original subdaily values of sunshine duration were adjusted to match the monthly values of homogenised data. The first step of the adjustment procedure was the normalization of the subdaily data (i.e. division with the maximum possible sunshine duration for the day of year). Resulting ratio values from 0 to 1 were transformed by arcus sinus functions and then shifted by such a value that the monthly sum of back-transformed values matched the homogenised monthly sum. Shifted values below –π/2 were set to –π/2, whereas values above π/2 were set to π/2. This way all the original ratio values of 0 (no sunshine) and 1 (maximum possible sunshine) remain unchanged. This adjustment procedure takes into account both the sunshine duration frequency distribution and the influence of expected inhomogenities.Missing subdaily data was replaced by spatially interpolated values of homogenised daily ratios. The distribution of raw interpolated values was partly adjusted to the distribution of the corresponding homogenised data in order to improve the statistics of extreme values.The resulting collection of homogenised and interpolated subdaily data of bright sunshine duration was statistically analysed. Time series of the data show a statistically significant positive linear trend on an annual scale throughout the 63-year period. The trend is stronger for morning (around 3.7 % per decade) than for midday (2.0 % per decade) and afternoon values (2.5 % per decade). For autumn the trend is weak and insignificant, whereas for winter morning hours the trend reaches around 8 % per decade in the lowlands of eastern Slovenia.Homogenised an interpolated time series have been used for the calculation of climate normals for the latest WMO standard reference period (1991–2020) and are planned to be used to improve climate projections for Slovenia.Keywords: sunshine duration, climate change, homogenisation, spatial interpolation
Extreme precipitation and flooding in Berlin under climate change conditions
Authors: Nissen Katrin , Tügel Franziska , Fauer Felix , Rust Henning , Hinkelmann Reinhard , Ulbrich Uwe
Published: July 2024

The effect of climate change on extreme precipitation and its impacts are investigated for the city of Berlin. The study is based on regional climate scenario simulations with a convection permitting horizontal resolution of 3 km conducted with CCLM (COSMO model in CLimate Mode).The regional model was forced with a CMIP5 global model simulation (MIROC5). Precipitation output is available at an hourly temporal resolution. We show results from simulations with historical greenhouse gas concentrations (1971-2000) and compare them to results with RCP8.5 greenhouse gas forcing. The relationship between duration, intensity and probability of the simulated precipitation is evaluated with a duration dependent general extreme value approach. The results are presented in the form of intensity-duration-frequency (IDF) curves. The curves for the historical period fit well to the corresponding product of the German weather service based on station observations (KOSTRA). The comparison of the IDF curves between the historical and the scenario periods reveals that extreme precipitation will strongly increase in a warmer climate for all analysed accumulation times between 1 hour and 5 days. Hourly events that occurred on average every 100 years in the historical period, for example, are found to be 45% more intense in Berlin during the period 2031-2060 at RCP8.5 conditions. For events with a very low probability (return periods above 50 years) this increase is ,however, not steady in time.If no adaptation measures are taken, the projected increase in extreme precipitation can also be expected to have an impact on the intensity andprobability of urban flooding. Risk maps for pluvial flooding are usually based on statistical precipitation events estimated from past observation, also known as design rainfall. Often the 100-year return value for an hourly accumulation time is used. To demonstrate how the anticipated changes in extreme precipitation reflect on the potential future flood risk for Berlin, risk maps for the future climate scenario are produced using the design rainfall from the climate scenario simulations as input for hydro-numerical simulations. The hydro-dynamical simulations are performed with the robust 2-D shallow water model hms++ coupled to the canal-system model of the Berlin water company (BWB). In addition to the maps, changes in flood depth for selected hot-spots and increases in sewer overflow volumes are presented. 
A New Refinement of Mediterranean Tropical‐LikeCyclones Characteristics
Authors: Gutiérrez-Fernández Jesús , Miglietta Mario Marcello , González-Alemán Juan Jesús , Gaertner Miguel Ángel
Published: July 2024

Mediterranean tropical‐like cyclones (TLCs) are damaging weather systems, which form over the Mediterranean Sea, resembling tropical cyclones. These cyclones can drive important socio‐economic losses in coastal areas. However, due to their small size and the relatively recent investigation of these cyclones, there is currently no robust categorization of which Mediterranean cyclones can be considered TLC. . Therefore, in this work, we propose a method to differentiate cyclones that attain actual tropical‐like characteristics in part of their lifetime, as they develop a warm core through intense convective processes. Several warm‐core cyclones in the Mediterranean, which were analyzed in the literature, are studied using ERA5 reanalysis, to identify the environment where they develop and distinguish tropical‐like cyclones from non‐tropical warm‐core cyclones. Initially, the cyclone phase space is analyzed to distinguish the cyclones that have a symmetrical deep warm core. Subsequently, the temporal evolution of several parameters is considered, including the distance between the area of maximum tangential wind speed and the cyclone center. The main results of this study show that part of the analyzed cyclones have features similar to tropical cyclones. Some differences are observed between the cyclones analyzed: one category of cyclones develops in areas of moderate‐low baroclinicity and intense convective processes, as occurs in tropical cyclones. Another group of cyclones develops in a strongly baroclinic environment with weak convective processes and intense vertical wind shear, as occurs in warm seclusions. Two cyclones, showing similarities with polar lows, are also identified. The results of this study propose a key to identify the Mediterranean cyclones that have tropical‐like characteristics.
Plain language and warning communication in Norway
Authors: Gislefoss Kristian , Sivle Anders , Finstad Svehagen Mai-Linn
Published: July 2024

Weather warnings issued by the Norwegian Meteorological Institute (MET Norway) are communicated in many different formats and channels. The Yr weather service (www.yr.no), made in collaboration with the Norwegian Broadcasting Corporation (NRK), is our main channel to the public. We also post on social media, where many news agencies and journalists pick up the warning message and put it on their front page. Every day a TV-meteorologist from MET Norway presents a weather forecast in the news at NRK. A detailed map of the different regions in Norway is shown and the TV-meteorologist has the opportunity to put warning symbols on these maps, in addition to the standard weather symbols. When MET Norway has issued a red or an orange warning the TV-meteorologist will have more time to cover the weather situations, e.g. showing a map layer with precipitation or wind. If there is an extreme event, the meteorologist is used as an expert in the studio. When dangerous weather occurs, it is important to communicate  how you prepare and what actions are needed. Since the TV-meteorologist is well known and has great credibility, the audience appreciates advice from the TV-meteorologist.  In Norway we use a color system to explain the warning; from yellow to orange and red. Existing literature and studies shows that the color system used in warning services are intuitive for people. However, colors alone do not provide an intuitive understanding of what to do when you see a warning. To help people understand how to respond to a dangerous situation, weather warnings typically include additional information, such as possible consequences of the weather conditions and instructions on what to do. This appears to be helpful information to assess the meaning of a weather warning. Nevertheless, including consequences and instructions is not always enough to trigger an action.  In an ongoing attempt to make the warnings more actionable, we have worked to improve communication from a plain language perspective. In this process, we moved from a focus on fixing single words and expressions, to a focus on structuring the warning with relevant and content-bearing headings and subheadings. For example, we replaced the subheading “Instruction” with the subheading “Difficult driving conditions” to help readers to understand and use the warning. The new and thematic headings and text modules are not yet implemented. However, they were generally well received in tests among various user groups. Early testing shows that the revised warnings provide the key messages, and give a quick situational awareness. Even though the focus in the project was not on TV, we think similar headings can be reused there, and in our social media channels, to strengthen the warning communication.
Introduction of the KMA/NIMS atmospheric research aircraft observations for 6 years and scientific missions.
Authors: Goo Taeyoung , Jung Suengpil , Kim Minseong , Kang Deokdu , Han Seungbeom , Lee Gwangjae , Kang Myeonghun , Shin Jonghun
Published: July 2024

The Korea Meteorological Administration (KMA) has operated atmospheric research aircraft since 2018. The KMA introduced Kingair 350HW that was modified for multiple purpose of atmospheric observations. After modification, 2 pilots, 2 instrument operators and 1 research scientist are on board. Usually duration a flight is about 4.5 hours. The KMA aircraft has 400-hour flight in a year in the purpose of four scientific missions: severe weather monitoring (SW), environmental monitoring (EM), climate change monitoring (CM), and cloud physics and weather modification (CP). For those missions, 27 instruments and devices are installed.Unlikely usual aircraft observations that intensively carry out during specific period, the KMA aircraft has routine observation about 400 hours an every year. In addition, as long as without any risk of damage for instruments, all of those are turn-on during observation. This gives us a merit of integrated insights and comprehensive understandings. The KMA aircraft observations are only carried out in flight information restriction of South Korea. From 2018 to 2023, total flight time (frequency) of SW, EM, CM, and CP are 299(43.3%), 85(12.3%), 85(12.3%), and 130(18.9%), respectively.SW is focusing on weather events such as heavy rainfall, snowfall and typhoon. Most of those events are populated during summer season. EM is related to a study on something like Asian dust, aerosols, particles and reactive gases. Aerosol events are usually concentrated on spring season. CM is interested in the variability of greenhouse gases and is carried out every month. Most CP activities are experiments of weather modification. Approximately 250 species of atmospheric variables are observed and estimated a single flight with full operation of instruments. 
Assessing an Haboob Event Triggered by Land Cover/Land Use Change: A Case Study of Polatlı, Türkiye
Authors: Aslanoğlu S. Yeşer , Güllü Gülen
Published: July 2024

An extreme mesoscale dust storm hit Türkiye's capital, Ankara, on 12th of September, 2020. During the storm, there was no long-range dust transport, particularly from the neighboring desert regions of North Africa and the Middle East. Instead, convective systems in the surroundings of Konya province, located south of Ankara, generated high-speed winds of up to 30 m/s, causing a significant amount of continental dust to rise from the district of Polatlı, situated about 70 km southwest of Ankara. Quickly evolving into a haboob, the storm brought life in Polatlı to a halt for approximately 20 minutes. As it progressed northeastward, the storm lost its haboob effect, but its impact on air quality persisted for about 24 hours, affecting not only Polatlı but also surrounding settlements, including central Ankara. MODIS Aqua overpass could catch the event partially but the observed AOD levels reached over 1. The air quality index reached hazardous levels, with the Polatlı air quality monitoring station recording a record hourly average PM10 concentration of 5,446 µg/m3 during the event. The primary cause was a dramatic change in land cover. Polatlı, covering an area of approximately 22 thousand hectares, is predominantly engaged in dry farming, with 80% of the land dedicated to it. The prolonged absence of rainfall, coupled with improper farming practices, has led to desertification of the land cover and, consequently, its susceptibility to erosion by wind. This study analyzes the mechanisms leading to the formation, progression, and environmental impacts of the storm using data from the Turkish State Meteorological Institute's observations and the C-Band Doppler weather radar data; CALIPSO and MODIS aerosol observations; Sentinel moisture and normalized vegetation difference indices; and measurement data from air quality monitoring stations belonging to the Ministry of Environment, Urbanization, and Climate Change.
Diagnostic study of the forecast accuracy of the ensemble models at the recurvature point of the typhoon
Authors: Yun Sug-gyeong , Shin Hyun-Cheol , Cha Eun-Jeong , Kim Eun-Jeong , Park Jong Im , Choi Won Jun , Ha Jong-Chul
Published: July 2024

Climatologically, typhoons are generated over the western North Pacific (WNP) and move towards the East Asian countries, such as China, Korea, and Japan, etc. The typical track of typhoons in this case is a C-type curve, and they change their track over the ocean in the midlatitude. This turning point of the track of typhoon is called the recurvature point. However, the untypical track typhoon frequently occurred in recent years and the track forecast is difficult.For example, the 6th typhoon Kanun in 2023, made two sharp recurvature while moved to the north. Kanun has an increase in track error in the early and mid-stage of prediction, which is estimated to be an error caused by the inability to accurately predict the two recurvature point. The maximum error of the models was approximately 400km for the 72-hour forecast and approximately 700km for the 120-hour forecast, respectively. This is larger than the average error of other typhoons in 2023 as well as the overall error average of Kanun. The question of why is the Kanun’s track error is larger than average is raised.This study is motivated in order to explain the reason of unusual large track error of typhoons. In the first step, we investigate the two unusual track typhoons errors such as, 11th typhoon Hinnamnor in 2022 and 6th typhoon Khanun in 2023. The model track error will be analyzed by calculating the error at the recurvature point of 102 members of the global ensemble model of KIM (Korean Integrated Model, 26 members), UM (Unified Model, 25 members), and ECMWF (The European Centre for Medium-Range Weather Forecasts, 51 members), respectively. The individual prediction data of the ensemble members rather than the ensemble mean is used. The recurvature point is automatically calculated from the predicted track at each issue time and compared with the recurvature point calculated on the best track. The prediction trend and performance of the ensemble model are identified by analyzing the distribution of the forecast time error and forecast position error at the recurvature point. Furthermore, the prediction field is classified and diagnosed according to the forecast error.
Occurrence of tornado outbreaks in the context of solar wind coupling to magnetosphere-ionosphere-atmosphere
Authors: Prikryl Paul , Rušin Vojto
Published: July 2024

The National Oceanic and Atmospheric Administration National Weather Service database of tornadoes provided by the Storm Prediction Center is used to investigate the occurrence of tornado outbreaks in the United States from 1963 to 2021 in the context of solar wind that impacts the Earth’s magnetosphere. A link between the solar wind and large tornado outbreaks is found. Superposed epoch analysis of tornado occurrence reveals a peak in the cumulative number of tornadoes near the interplanetary magnetic field sector boundary (heliospheric current sheet) crossings. The latter often closely precede or coincide with co-rotating interaction regions at the leading edge of high-speed streams from coronal holes. Most of the large tornado outbreaks (20 or more tornadoes per 24 hours) are associated with high-density plasma adjacent to heliospheric current sheets and co-rotating interaction regions. Other large tornado outbreaks followed impacts of interplanetary coronal mass ejections or occurred in a declining phase of major high-speed streams. We consider the role of the solar wind coupling to the magnetosphere-ionosphere-atmosphere system in severe weather development, mediated by globally propagating aurorally excited atmospheric gravity waves. While these gravity waves reach the troposphere with attenuated amplitudes, when over-reflecting in regions of low-level wind shear and opposing winds, they can contribute to conditional symmetric instability release in frontal zones of extratropical cyclones leading to intensification of supercells that spawn tornado outbreaks. The ERA5 meteorological re-analysis is used to evaluate slantwise convective available potential energy (SCAPE) to assess conditional symmetric instability and slantwise convection in cases of large tornado outbreaks.
Climate Change Energy Data Simulation Scenarios: Urban Thermal Environment Improvement through Demand Control Strategy
Authors: Wang Shiang Yu , Cheng Ching-Yin , Lin Tzu-Ping
Published: July 2024

Due to various factors such as urban construction development and excessive energy usage, the urban heat island effect causes the air temperature in urban centers to be higher than in surrounding suburban areas. The causes of the urban heat island effect are numerous, including the thermal environmental impact caused by heat emissions from air conditioning energy, which is a concern for countries around the world. This study focuses on the built-up areas of Taipei City and New Taipei City in Taiwan and proposes solutions based on previous research literature. The approach involves using machine learning methods to identify high-energy usage areas caused by air conditioning and their corresponding temperature differences to formulate strategies for mitigation.The study uses the National Science and Technology Center for Disaster Reduction and the High Resolution Atmospheric Model (HiRAM) to conduct global climate simulation under the RCP8.5 warming scenario. Through dynamic downscaling using WRF, the data was scaled down to a 5km resolution for the Taiwan region. The climate data produced was then used in Energy Plus to simulate residential air conditioning cooling power consumption and estimate Energy Usage Intensity (EUI). Additionally, cooling demand was controlled in areas with higher EUI, and a neural network prediction model was utilized to estimate air conditioning cooling demand in various heat zones.The study aims to implement control strategies using the public sector's Building Energy Management System, such as controlling air conditioning usage during peak periods through load shedding to keep air temperature rise within a set threshold. This approach not only reduces energy consumption but also effectively reduces air conditioning heat emissions, thereby enhancing thermal comfort in urban environments. Based on the research framework, the results show that under the HiRAM scenario of a 2°C temperature rise, building air conditioning EUI is expected to increase by 15-20%. The accumulated air conditioning heat emissions become one of the major factors in air temperature rise. Furthermore, simulation verification using neural networks and the implementation of energy strategies demonstrate that effective control of EUI thresholds can lower regional air temperatures by approximately 0.2 to 0.5°C. Keywords: Urban heat island, High resolution atmospheric model, Energy plus, Demand control, Machine learning