bluuebunny/crossref_metadata_2025 huggingface dataset:
Identifying Past Droughts in El Hierro (Canary Islands) With ERA5 Climate Reanalysis and SPI
Authors: Caballero-Fernández Damián , Salvador-Franch Ferran , Salvà-Catarineu Montserrat
Published: July 2024

The island of El Hierro, situated as the southwesternmost territory within the Canary Islands archipelago, is renowned for its distinctive climate. Global warming is anticipated to increase the frequency and severity of droughts in the area, posing a significant threat to its inhabitants, economy, and delicate ecosystems.The main aim of this research is to identify droughts that affected El Hierro Island between 1941 and 1970. This will be achieved through by analyzing of hourly total precipitation data obtained from the ERA5 climate reanalysis.In addition to precipitation data, this study also integrated various variables from ERA5 that influence droughts, including surface pressure, mean sea level pressure, geopotential height at 500 hPa, temperature at 2 meters above the land surface, sea surface temperature, volumetric soil water content, wind components (U and V), and surface downward solar radiation. To assess the accuracy of ERA5 estimates, precipitation data from eight stations provided by the Spanish State Meteorological Agency (AEMET) were utilized. Furthermore, documentary research was conducted to identify droughts prior to 1941, involving a thorough examination of digital repositories such as the National Library of Spain (BNE) and the Virtual Library of Historical Press (Spain).The Standardized Precipitation Index (SPI) was employed to assess the severity, magnitude, and duration of the droughts. Additionally, R packages such as TIDYVERSE, DPLYR, SP, SPEI, and PSYCH were utilized for the analysis of the variables. Moreover, CLIMATOL and TREND were used to ensure the quality of the observational records.This research pioneers the quantitative analysis of the droughts that affected El Hierro Island between 1941 and 1970. This period has been largely overlooked in previous studies and is characterized by a scarcity of high-quality observational records. The findings reveal that droughts are recurrent on the island, with at least one persistent drought per decade. Notably, the 1947-1949 drought stands out as the most prolonged and severe, impacting hydrological, agricultural, and socioeconomic aspects.In conclusion, this analysis offers valuable insights into the historical patterns and future trends of droughts on El Hierro Island, laying the groundwork for the development of informed adaptation strategies. Moreover, it contributes to enhancing our understanding and monitoring of droughts, which could reduce their impact on the population in the future.
The Impact of Changing Ice Surfaces on the Glacier Boundary Layer Structure: A Large-eddy Simulation Case Study from Hintereisferner Glacier, Austria
Authors: Goger Brigitta , Stiperski Ivana
Published: July 2024

The glacier boundary layer with katabatic down-slope wind strongly governs the exchange of heat between the ice surface and the atmosphere aloft. Glaciers are mostly located in mountainous regions, therefore mountain boundary layer processes (eg., other thermally-driven flows) and dynamically-driven processes such as gravity waves interact with the local glacier boundary layer, leading to disturbance or erosion of it.In this study, we explore the impact of  dynamically-driven disturbances of the glacier boundary layer with large-eddy simulations. The location of the study is the Hintereisferner glacier in the Austrian Alps. We employ the WRF model at dx=48m to simulate the the evolution of the glacier boundary layer for one day during the HEFEX field campaign in 2018. The day is characterised by  mesoscale cross-glacier flow from the North-West. In a second simulation run, we remove the upstream glaciers to validate the impact of the ice surface on the formation of gravity waves. Generally speaking, removing the upstream glaciers leads to a modulation of the gravity waves and a changed sensible heat flux structure over the glacier, a weaker glacier boundary layer, and the propagation of an up-valley flow onto the glacier surface. As a final step, we remove all the glaciers from the domain to give an insight on the changed land-atmosphere exchange. The removed glaciers lead to a complete change from a partly stable glacier boundary layer to a convective valley boundary layer disturbed by weaker gravity waves.This numerical study tries to untangle the processes behind thermally- and dynamically-driven flows in an complex environment and gives possible scenarios for "what to expect” in terms of boundary layer and mesoscale dynamics in a future ice-free catchment area.
Atmospheric circulation representation in CMIP6 models for extreme temperature events using Latent Dirichlet Allocation
Authors: Malhomme Nemo , Podvin Bérengère , Faranda Davide , Mathelin Lionel
Published: July 2024

Climate models aim at representing as closely as possible the statistical properties of the climate components, including extreme events on which fine-tuning data may be less available. This is a fundamental requirement to correctly project changes in their dynamics due to anthropogenic forcing. In order to estimate how much models can be trusted, we must evaluate how closely they match observations. We need algorithms capable of selecting, processing and evaluating relevant dynamical features of the climate components. This has to be reiterated efficiently for large datasets such as those issued from the Coupled Model Intercomparison Project 6 (CMIP6). In this work, we use Latent Dirichlet Allocation (LDA), a statistical soft clustering method initially designed for natural language processing, to extract synoptic patterns from sea-level pressure data. We propose to use LDA as a tool for extracting new information from model data and evaluating their performance.LDA allows for learning a basis of decomposition of maps into objects called "motifs". From the ERA5 sea-level pressure data, the method robustly extracts a basis of motifs that are interpretable objects at synoptic scale, i.e. cyclones or anticyclones associated to locations. Pressure data can be projected onto this basis, yielding motif weights that contain local information about the large-scale atmospheric circulation. LDA decomposition is efficient and sparse: most of the information of a given map is contained in few motifs. It is therefore possible to decompose any map in a limited number of easy-to-interpret synoptic objects. This allows for a variety of new angles for statistical analysis.The weights statistics can be used to characterize general and extreme event-specific dynamics in reanalysis and model data. By comparing the statistics obtained from reanalysis data with those obtained from a selection of CMIP6 models, we can quantify errors on each localized circulation pattern and identify model-specific and model-independent errors. We find that, thought models make higher errors on extreme events cases such as heatwaves and cold spells, on average, large-scale circulation patterns are well predicted by the models.By projecting model simulations of several future scenarios, we can also measure changes in time of synoptic patterns predicted by the models. These changes can be general, season-specific or extreme event-specific. We find several predicted changes in motif weights statistics, some of which are consistent with currently observed changes in synoptic configuration statistics. By comparing the amplitude of the changes in different shared socio-economic pathways, we can link some of these changes to anthropogenic climate forcing, at least according to the models.
The dynamics of Storm Ciarán (2023): from diabatic Rossby wave to warm-seclusion cyclone with a sting jet
Authors: Riboldi Jacopo , Volonté Ambrogio
Published: July 2024

Storm Ciarán was an impactful weather system that affected western Europe in the first days of November 2023. The main threat from Ciarán were extreme winds, that particularly hit the areas around the English Channel: the highest wind gust recorded was 207 km/h at Pointe du Raz, in Bretagne (France), just as the storm was rapidly deepening. In this work, we discuss some dynamical characteristics of storm Ciarán related to the occurrence of those extreme winds: its origin as a diabatic Rossby wave, and its evolution as a warm-seclusion cyclone with the development of a sting jet.Diabatic Rossby waves (or vortices) are a particular type of cyclones driven by latent heat release along a baroclinic zone. These shallow systems have a smaller scale than usual extratropical cyclones, and are driven by the low-level vorticity generation that results from intense, localized condensational heating. Ciarán’s evolution resembled the infamous storm Lothar (1999), because both underwent explosive intensification starting from the diabatic Rossby wave stage, and both resulted in extreme winds.Rapidly deepening cyclones that develop a warm seclusion are also associated with strong surface winds, as they can provide a favorable environment to the development of sting jets. A sting jet is an airstream that accelerates as it descends out of the tip of the hooked cloud head, generating strong low-level winds into the frontal-fracture region of the cyclone. Storm Ciarán indeed originated as a diabatic Rossby wave and then developed into a rapidly deepening warm-seclusion cyclone containing a sting jet. We thus illustrate its evolution, highlighting the occurrence of a “diabatic Rossby wave-sting jet” dynamical pathway leading to the generation of high-impact winds.
Enhancing seasonal forecasting in mountain regions of the Iberian Peninsula through statistical downscaling
Authors: García-Maroto Diego , González-Cervera Álvaro , Mohino Elsa , Durán Luis
Published: July 2024

Mountainous areas are of particular interest due to their critical role in the hydrological resource, especially in the Iberian Peninsula, a region subjected to strong climate variability and change. In this work, we seek to evaluate the seasonal prediction of precipitation and temperature over these areas. Interannual variability of these two variables is of great importance, as it influences the onset, offset, melting rate and other characteristics of the seasonal snow cover. The seasonal snowpack is of great relevance, as its melting during late spring can reduce the impact of the summer drought by providing a crucial water resource.To date, seasonal prediction models lack the necessary spatial resolution to resolve processes regarding complex orography or local phenomena. Furthermore, even widely used reanalysis products cannot accurately represent alpine sites, and therefore high-resolution products or on-site observations are required. In this regard, statistical downscaling methods can provide a necessary improvement at low computational costs. In this study, statistical methods, such as the analogs method and Principal Component Analysis (PCA), are employed to link large-scale atmospheric patterns predicted by seasonal prediction systems, such as ECMWF's fifth generation seasonal forecast system (SEAS5), to local data in the form of observations or high-resolution gridded products. These methods can provide a more accurate representation of local climatology in mountain regions, thereby improving seasonal forecasting skill in such crucial areas. Furthermore, the methodology allows for the calculation of snow-related indices that may prove useful for early water management decisions and for the interests of the ski industry. The findings of this research have significant implications for seasonal prediction and climate services, contributing to our understanding of climate variability and predictability in the Iberian Peninsula and in high-elevation areas within.
Jet Configurations Leading to Extreme Winter Temperatures Over Europe
Authors: Garcia-Burgos Marina , Ayarzagüena Blanca , Barriopedro David , Garcia-Herrera Ricardo
Published: July 2024

The North Atlantic eddy-driven jet (EDJ) is the main driver of winter weather in Europe and is typically described by its latitude or strength. Here, we show that the relationship between the EDJ and European winter temperature extremes can be better understood by using a multiparametric perspective that accounts for additional aspects of the EDJ structure (tilt, zonal elongation, etc.). First, we identify four regions where the influence of the EDJ on extreme temperatures is different: Scandinavia, Central Europe, Eastern Europe, and Western Mediterranean (WMED). Overall, the main mechanism leading to extreme event occurrence is the anomalous horizontal advection induced by blockings during cold spells and enhanced westerlies during warm events. In the case of the WMED region, diabatic processes play though a principal role in the occurrence of warm events. Additionally, the circulation anomalies and radiative fluxes involved in both processes generate asymmetric effects in minimum and maximum temperatures, leading to more intense cold than warm events. These extreme events are accompanied by different EDJ configurations entailing perturbed EDJs during cold spells and strong tilted EDJs during warm events, but with distinguishable characteristic depending on the region. In almost every region, the probability of cold and warm events is increased when considering the combined effects of more than two EDJ parameters, suggesting an oversimplification of traditional approaches based on a single EDJ parameter. More importantly, our results derived from logistic regression models highlight the relevance of EDJ parameters others than latitude and intensity to drive the largest changes in the odds of extremes.
 Awareness and expectations from the climate change adaptation digital twin
Authors: Terrado Marta , Baulenas Eulàlia , Versteeg Gerrit , Bojovic Dragana
Published: July 2024

Digital Twins have become a buzzword often associated with innovation and transformation. The notion of digital twin includes a tight integration between models, data and decisions, which has resulted in a diverse and proliferating set of use cases, with applications across multiple areas of science, technology, and society. In the field of earth sciences, the digital twin for climate adaptation promises the potential to predict the impact of climate change with unprecedented reliability at regional and national scales. However, despite the opportunities and challenges it may bring to the climate adaptation community, researchers and practitioners working in the climate adaptation field may not be aware of such a digital twin and the added value of the information it can provide, and may even hold unrealistic expectations for purposes it can be applied to. To assess the awareness and expectations from the climate adaptation digital twin, a survey was launched targeted to adaptation researchers and practitioners. The analysis of results shows that the community sample reached with the survey (25 answers) is generally unaware of digital twins, let alone the one for adaptation to climate change, except for some academics involved in research projects of technical nature. The increase in the spatial and temporal resolution of climate and impact models, together with the simulation of different climate adaptation options to develop better regional and local adaptation strategies are the main highlighted opportunities, although for many it remains unclear who will be able to access the data and how to handle it. We suggest that a more tailored engagement and communication strategy is needed to raise awareness on the climate adaptation digital twin, the opportunities it may provide to the climate adaptation community and to the general public, and the interaction modes available for the uptake of the information generated. This calls for a stronger involvement of other disciplines, including experts in communication and dissemination, social sciences and humanities, user experience and data visualisation, in this undertaking. 
The long-term trends in blocking events frequencies in the Euro-Atlantic sector of NH midlatitudes
Authors: Wibig Joanna , Jędruszkiewicz Joanna , Piotrowski Piotr
Published: July 2024

Blocking anticyclones are planetary-scale phenomenon. They typically develop close to the Pacific and Atlantic jet-streams. Blocking anticyclones  usually have a strong impact on weather, not only in the regions they occur, but also in their surroundings, sometimes leading to heat waves in summer and cold spells in winter (Trigo et al., 2004). The strong decrease in ice cover extent and thickness together with accompanying warming in the Arctic caused changes in frequency, persistence and mean localization of blocking anticyclones in the middle and high latitudes of Northern Hemisphere. This paper is aimed on the analysis of spatial and temporal variability of blocking events in the middle and latitudes in the sector 60W to 120E, i.e. in the region where blocking anticyclones have a strong impact on weather in Europe.The daily values of geopotential at 500 hPa level (G500) from ERA5 dataset acquired from the ECMWF's Meteorological Archival and Retrieval System (MARS) were used. A blocking index based on the modificated Tibaldi and Molteni method was used. In the area extending from 60ºW to 120ºW and from 35ºN to 65ºN, the daily values of blocking index were calculated for each grid point and and the extend of blocking events was extablished. On this basis the frequencies of blocking episodes were assessed as the number of days per month where a blocking event can be identified in the surrounding of selected grids. Then the trends in these frequencies were identified and discussed.This research was funded by National Science Center (NCN), grant number 2019/33/B/ST10/0113
Recent Advances in Understanding the Historical Climate of Extremadura and the Southwest of Iberia: A Review
Authors: Vaquero José Manuel , Gallego María Cruz
Published: July 2024

Over the past decade, significant progress has been made in elucidating the historical climate of the southwestern region of the Iberian Peninsula, with a particular focus on the Spanish region of Extremadura. This communication provides a comprehensive review of these advancements.Firstly, a notable body of research has investigated catastrophic flooding events in the Guadiana River basin spanning the last five centuries [1]. Detailed studies have been conducted on the devastating flood that occurred in December 1876 in Badajoz, as well as in other areas within the Guadiana River basin [2-3].Furthermore, substantial efforts have been dedicated to data recovery initiatives. Specifically, more than 0.8 million meteorological readings have been retrieved from Extremadura [4], alongside other early meteorological data of significance from Almada (Portugal) [5] and San Fernando (Spain) [6].Additionally, non-instrumental documentary sources have been leveraged to examine the historical climate of Extremadura. This includes an analysis of correspondence between the Duke of Feria [7] and preserved documents regarding the observance of rain prayer rituals [8], with detailed insights into the findings presented.[1] N. Bravo-Paredes et al. (2021) Science of the Total Environment 797, 149141, doi: 10.1016/j.scitotenv.2021.149141[2] J. González-Cao et al. (2021) Journal of Hydrology 599, 126292, doi: 10.1016/j.jhydrol.2021.126292[3] J. González-Cao et al. (2022) Journal of Hydrology 610, 127883, doi: 10.1016/j.jhydrol.2022.127883[4] J.M. Vaquero et al. (2022) Geoscience Data Journal 9, 207-220, doi: 10.1002/gdj3.131[5] N. Bravo-Paredes et al. (2023) Climate 11, 193, doi: 10.3390/cli11090193[6] N. Bravo-Paredes et al. (2023) Climate of the Past 19, 1397–1408, doi:  10.5194/cp-19-1397-2023[7] M.I. Fernández-Fernández et al. (2014) Climatic Change 126, 107–118, doi: 10.1007/s10584-014-1201-5[8] N. Bravo-Paredes et al. (2020) Atmosphere 11(3), 282, doi: 10.3390/atmos11030282
A study on optimizing the diabatic initialization of very short-range forecast model in KMA
Authors: Lee Seungyeon , Won Hye Young , Lee Keun Hee , Kim Seungbum
Published: July 2024

The Korea Meteorological Administration (KMA) operates the Korea Local Analysis and Prediction System (KLAPS), a very short-range forecast model providing real-time and 12-hour forecasts information at 10-minute intervals at 5 km horizontal resolution. The analysis process of KLAPS, based on the LAPS (Local Analysis and Prediction System) from NOAA, is the data assimilation system that ingests radar, satellite, aircraft, surface observations, and regional atmospheric model data to analyze 3-D atmospheric conditions. After that, to ensure that the momentum and mass fields are consistent with the cloud-derived vertical motions during the diabatic initialization process, optimizing the thermodynamic balance between wind and cloud fields is performed. This diabatic initialization process is critical to the initial condition of KLAPS for improving performance of model forecasting. In this step, user-defined weights, derived from the known error characteristics of analysis and background models, are utilized to minimize the variational cost function. By fine-tuning the weights of the variational cost function, the gaps between the model’s spin-up and current weather conditions and short-term extrapolation are reduced. Sensitivity experiments are performed to estimate optimal weights of the variational balance processes, achieving improved initial fields for KLAPS. The predictability of precipitation is also evaluated based on the improved initial fields to verify the effects of weight optimization in adiabatic initialization process. This indicates the significant impacts of improved initial fields on forecast accuracy. The optimization of weights in initialization process of KLAPS is expected that initial state of the model will be improved and these results can contribute to enhancement of predictability performance for precipitation of the KLAPS.Acknowledgement: This work was supported by Development of Numerical Weather Prediction and Data Application Techniques (KMA2018-00721) 
Converting a high-level air temperature and wind speed to a reference level ones: Application to the Ieodo Ocean Research Station
Authors: Park Moon-Soo , Baek Kitae , Cheong Kwang-Young
Published: July 2024

Air temperature and wind speed observed at reference levels (the former 2 m and the latter 10 m) are essential for validating a performance of meteorological models as well as for parameterizing a boundary-layer processes such as air-sea momentum and heat interactions. This study developed a converting method for wind speed and air temperature observed at a higher level to ones at a reference level, the methods were applied to the data at the Ieodo Ocean Research Station (I-ORS), Korea. The I-ORS is located in the northeast part of the East China Sea, and more than half of typhoons affecting the Korean Peninsula pass near the station. The I-ORS measures wind speed and temperature at 41.4 m and 35.7 m, respectively. Obstacle correction factors was applied to the observed wind speed to reflect the effect of station structure on wind. Then, wind speeds at a reference level with the use of wind speed observed over the rooftop level (41.4 m) was computed by applying the log-wind profile, neural drag coefficient assumption, and power-wind profile methods. The retrieved wind speeds were compared with the observed one at 10 m during the special experiment period. The coefficients for the methods were determined. Air temperature at 2m from the temperature observed at sea surface and rooftop level (35.7 m) was calculated by applying a power-temperature profile. The optimal power for the power profile was determined as different values according to day and night by minimizing errors. 80% of the retrieved temperatures fell within a mean bias less than 0.5°C, while 95% fell within a mean bias less than 1.0°C. The results are expected to contribute to parameterize the air-sea momentum and heat interaction in terms of air temperature and wind speed under strong wind over ocean surfaces.  Key words: Ieodo Ocean Research Station (I-ORS), reference level temperature, reference level wind speed, air-sea momentum and heat interactionAcknowledgements: This work is funded by the Korea Hydrographic and Oceanographic Agency (KHOA) and National Institute of Meteorological Sciences (NIMS).
Enhance the meteoblue City Climate Model by Climate Projections to assess Urban Climate Hazard
Authors: Bader Nico , Zurfluh Nicolas , Shin Jungmin , Schlögl Sebastian
Published: July 2024

Urban areas face unprecedented challenges due to the combination of growing cities and climate change, with impacts ranging from heatwaves and extreme precipitation to sea-level rise and urban flooding. Artificial surfaces in cities and the differences in the surface structure cause urban areas to overheat significantly compared to rural areas and lead to a high inner-city air temperature variability. As climate change and heat forcing increase, the urban heat island effect will intensify in the future. Understanding the future climate scenarios is crucial for effective planning of adaptation and mitigation strategies.Climate projections referred to as Global Climate Models (GCMs) and Regional Climate Models (RCMs) do not accurately represent urban-scale climate variables. Computational constraints and limitations in simulating the complexity of earth system processes limit the spatial resolution of climate projections to the order of 10 – 100 km and the time resolution to a daily basis. Hence, climate models are not able to fully resolve the urban heat island effect and the urban air temperature variability which occur on a micro-scale.This work highlights the importance of downscaled climate prediction data to capture localized effects and uncertainties associated with urban areas. Downscaling climate models to building-level is done by combining the meteoblue City Climate Model (mCCM) - a dynamic statistical downscaling model - with climate projections in the framework of the sixth phase of the Coupled Model Intercomparison Project (CMIP6).The mCCM is based on a high-resolution model grid with a horizontal resolution of 10 m. It resolves the differences in the surface energy budget and help understanding the air temperature variability and dynamics in an urban environment. The model is fully driven by surface texture parameters derived from high-resolution satellites and meso-scale NWP models. In this framework, the climate signal of CMIP6 data is added to the hourly air temperature time series of the mCCM. This allows the calculation of temperature-related climate indices on a high-resolution grid of 10 m for future time periods and various SSP scenarios. Furthermore, this approach allows to estimate the probability that certain climate indices such as e.g., number of tropical nights, or number of hot days reach a critical threshold.Enhancing the mCCM with climate predictions creates a reliable information basis for city planners, decision makers, and companies. It helps cities become more resilient, sustainable, and adaptable in the face of a changing climate, ultimately improving the quality of life for urban residents.
High resolution observational daily gridded dataset for Greece: The CLIMADAT-hub project
Authors: Varotsos Konstantinos V. , Karali Anna , Kitsara Gianna , Lemesios Giannis , Patlakas Platon , Hatzaki Maria , Tenentes Vasilis , Katavoutas George , Sarantopoulos Athanasios , Koutroulis Aristeidis G. , Grillakis Manolis G. , Psiloglou Basil , Giannakopoulos Christos
Published: July 2024

CLIMADAT-hub is a two-year project within the framework of H.F.R.I call “Basic research Financing (Horizontal support of all Sciences)” under the National Recovery and Resilience Plan “Greece 2.0” funded by the European Union – NextGenerationEU. The project aims at bridging the gap between the available climatic information and the information required for assessing climate risks at the local scale by creating high resolution observational gridded datasets, as well as statistically downscaled seasonal forecasts and climate change projections for Greece. Regarding the observational gridded datasets, the primary goal is to construct a state-of-the art, 1km high resolution gridded dataset for daily temperature, precipitation, relative humidity and wind speed for the period 1981-2021. Starting with temperature and precipitation, long term daily values have been collected from various meteorological networks and databases for a large number of locations in Greece. These raw daily data underwent quality control and homogenization. To obtain the daily gridded values for air temperatures (maximum, minimum, mean) and precipitation, at a spatial resolution of 1km the following methods have been examined: i) combination of classical geo statistical methods such as Thin Plate Splines and Kriging as used in the early versions of E-OBS and Iberia01, ii) Regression-Kriging, a spatial prediction technique commonly used in geostatistics that combines a regression of the dependent variable (e.g., temperature) on auxiliary/predictive variables (e.g., elevation, distance from shoreline) with kriging of the regression residuals (similar to EOBSv17 and afterwards), iii) ensemble machine learning, an approach to modeling, where instead of using a single best learner, multiple strong learners are used and, consequently, are combined into a single union, iv) hybrid method, where the available observations are blended with the Weather Research and Forecasting (WRF) model to produce the high resolution observed gridded datasets through gridding and bias adjustment techniques.We report the results from evaluating all the created gridded datasets for temperature and precipitation against withheld station data to determine the best performing approach for each variable. Future work will extend these methodologies to include the remaining variables.
A prototype for automated wind gust warnings
Authors: Felsberg Anne , Koser Daniel , Brune Sebastian , Breitenbach Björn , Baumgartner Manuel , Klink Martin
Published: July 2024

In 2022, the German Meteorological Service (DWD) started the program RainBoW (“Risk-based, Application-oriented and INdividualizaBle delivery of Optimized Weather warnings”) aiming at a rework of the warning system. Among others, one important goal of the program is to extend the forecast horizon of warnings in order to inform authorities and the general public early-on about possible hazardous weather. This so-called “warning trend” is envisioned for all warning parameters, but has been explored first for wind gusts. In this contribution, the outline of the prototype for wind gusts, that is already available and running in a test mode, will be presented.One of the main features of the prototype is its modularity, i.e. it consists of several different components which are tied together with modern messaging techniques. The wind gust prototype is based on data of DWD's inhouse model ICON, but is easily extensible to other data sources. It combines ensemble data from all ICON model versions to allow the construction of a warning trend up to 7 days. This comprises the local area version for Germany (ca. 2 km spatial resolution and forecast up to 48 hours), the EU version (ca. 13 km spatial resolution and forecast up to 120 hours) and the global version (ca. 26 km resolution and forecast up to 180 hours). After spatial and temporal aggregation of the individual model data, exceedance probabilities for given warning thresholds are computed and combined into a single, coherent warning trend dataset. Since this warning trend dataset changes with each new model run, an additional post-processing step is necessary to reduce the inherent jumpiness. Overall, the prototype thereby provides a smooth, automated wind gust warning trend.
Towards a low-cost approach to identify sting jets in numerical models
Authors: Eisenstein Lea , Pinto Joaquim G. , Knippertz Peter
Published: July 2024

Sting jets (SJ) have been a research interest in the extratropical cyclone community for the last two decades. An SJ is a descending airstream that can develop in Shapiro-Keyser-type cyclones, bringing high winds to the surface. As extratropical cyclones are usually accompanied by high wind gusts and heavy precipitation, they are considered one of the most hazardous weather phenomena in Europe, especially during wintertime. While winds are often associated with the warm or cold jet (WJ and CJ, respectively), cold-frontal convection or cold-sector winds, SJs are less common but –if occurring– are often found to have caused the highest gusts.Recently, we introduced RAMEFI (RAndom-forest-based MEsoscale wind Feature Identification), the first objective and flexible identification tool for high-wind features within cyclones, using a probabilistic random forest. RAMEFI can be applied to observational and gridded datasets independently of spatial distribution based on eight surface parameters. However, it is challenging to distinguish the SJ from the CJ in surface parameters alone, as their characteristics are similar such that the two features have been combined in RAMEFI so far. Nevertheless, the origin and potential for damage differ. While the SJ is a descending air stream originating within the cloud head, the CJ stays at low levels throughout its lifetime. With the descent, the SJ brings high momentum from mid-levels down to the top of the boundary layer or even to the surface. This commonly creates higher winds and gusts and, thus, a separate detection is desirable.In this work, we aim to extend RAMEFI to identify potential SJs, especially focusing on output from high-resolution numerical weather prediction models. This way we want to create a suitable alternative to the data-intensive and computationally expensive computation of Lagrangian trajectories, the most established SJ identification method. Our approach is based on a simple detection of a coherent three-dimensional region of high winds. We further use relative humidity to ensure the proximity to the cloud head following previous literature and gust speeds to connect the region to actual surface impact. Initial results using model simulations and the deterministic forecast from the German weather service (ICON-EU) show promise, with a high hit and low false alarm rate. The method provides a basis for further refinement and increasing robustness, such that it can be used on different models and resolutions.
From local impacts to country-wide warnings: progress and challenges of developing an operational impact-warning chain 
Authors: Mühlhofer Evelyn , Willemse Saskia
Published: July 2024

Severe weather poses significant threats to society, necessitating the development of effective forecasting and warning systems to mitigate their impacts. Integrating impact-based forecasts into warnings, with the premise of reducing people’s harm, currently consists in a paradigm change for many national weather services. Being at the intersection of probabilistic forecasts, uncertainty analysis and state-of-the art risk modelling, this new paradigm also entails significant challenges.This contribution presents the ongoing efforts at MeteoSwiss to incorporate impacts into weather warnings. Through collaboration with stakeholders, including first responders and local authorities, MeteoSwiss is initiating a local pilot project focusing on heavy precipitation and deployment planning in the canton of Zurich. This impact case study, tailored to specific locations and use case, serves as a pilot to learn for further development and scaling up of impact-based warnings.Furthermore, as a national-scale counterpart, we work on establishing a quasi-operational demonstrator for Switzerland, which integrates impact proxies (hazard-exposure) rather than full-fletched impact computations. We address the trade-offs inherent to developing impact-based warnings, including the need to balance data availability, specificity and utility across varying warning scales, and the need for seamless integration within an operational weather service.This contribution discusses potentials and draw-backs of integrating many-dimensional impact considerations into weather warnings from the perspective of a national weather service, highlighting the importance of interdisciplinary collaboration and stakeholder co-development, and demonstrating the use of impact modelling tools in a (quasi-)operational context, with the ultimate aim to better cater to the diverse needs of society in the face of severe weather events.
Online portal »Drought meter« for monitoring the drought situation in Slovenia
Authors: Medved Anže , Sušnik Andreja , Moderc Andreja , Vlahović Živa , Žun Maja
Published: July 2024

The frequency of droughts in Slovenia has been increasing in recent decades. In the last twenty years we have recorded 7 droughts that affected Slovenia on the scale of a natural disaster, with the most recent one in 2022 causing around 148 million euros of direct damage to agriculture. Droughts have been occurring with increasing intensity, and in areas and seasons where they have not been a problem in the past.For the purpose of detecting drought conditions in near real time and informing the public about these, Slovenian Environment Agency has developed the »Drought meter« online portal where estimated drought conditions in three parts of the water cycle (topsoil layer, surface water, groundwater) are published on a weekly basis throughout the year. For each part of the water cycle, drought conditions are monitored at representative stations using a specific indicator; in case of topsoil layer, the surface water balance for the past 30 days is used. Regional estimation of drought conditions is then determined based on a percentile analysis of the indicator at representative stations, which gives information on how often in the past similar conditions have occurred in the selected time period.In addition to drought conditions in the three parts of the water cycle, »Drought meter« also consists of a climate analysis of three basic variables influencing these conditions, namely temperature, precipitation and reference evapotranspiration over the last 7 and last 30 days. This is also done on a weekly basis, where for each variable we highlight the spatial distribution and meteorological stations that deviated the most. For the last 30 days, maps of deviations by percentile classes are shown. An outlook for the following week is also provided through a meteorological forecast, consisting of a description of the synoptic situation for the coming week and an estimate of expected precipitation amount and temperature range by the end of the selected period.The »Drought meter« online portal represents a progress in providing information on drought conditions in Slovenia, since near real time drought information for all three parts of the water cycle is available in one place and on a uniform spatial and temporal scale. In our talk, we will provide an overview of the development of the drought in 2022. That year the estimated drought conditions in »Drought meter« also served as the basis for the competent authorities to determine the onset of the period for assessing damage to agricultural crops due to drought.
How can we make information on climate change actionable for users? 
Authors: Böhnisch Andrea , Zilker Marion , Beck Inga , Ludwig Ralf
Published: July 2024

While a plethora of climate data exists, e.g. from observational records or modelling experiments, much of this information remains unused in many cases and targeted action on climate change impacts is not taken. Why is that? What must be done to overcome this persistent challenge?Climate change largely affects nearly all aspects of everyday life: water, energy, and food consumption, personal health (e.g., diseases, heat stress, allergens), work (e.g., concerning working conditions or commuting infrastructure), safety of life and goods (e.g., concerning natural disasters). Often, climate change strikes by altering the frequency or intensity of extreme events, changing seasonality or compounding multiple stressors temporally and spatially. For adaptation purposes, information on ongoing and expected climate change impacts are thus of utmost importance to, e.g., agriculture, water management, energy production and supply, emergency services, insurance, or health care.Clearly, the exchange of relevant climate information between scientists, stakeholders and the general public is marked by a gap between what is provided and what is needed in real-world applications.One of the main reasons is very likely missing communication between scientists and decision-makers. Furthermore, users often have limited knowledge and/or capacities or a different perception of the subject matter to convert the provided, often generic climate data into suitable information for very specific needs. This gap between demand and supply can be described in terms of temporal and spatial scales (e.g., provided information is valid for large areas, whereas users are interested in single fields), variable selection (e.g., when information is sought for variables that are not observed/produced directly), specificity of needs (e.g., climate models being designed for understanding the system instead of specific user applications), and consideration of uncertainty as opposed to the requirement for clear statements on trends.In order to close this gap, communication between users and scientists requires a two-way format of co-creating (a) a viable form of information exchange and (b) the relevant information itself, while recognising the needs of users and capabilities of providers. This is to ensure that relevant information can be provided to users who are motivated to apply them – without the need for further postprocessing among the users. At the same time, creating data “into the blue” without actual usability can be avoided.We here describe the offer--need gap and present possible strategies for closing it with examples from a central European region: Within the EU-project ARSINOE, the Main River Catchment, Germany, is one of 9 case studies for which scientists and stakeholders jointly develop strategies for fostering climate resilience. Promoting a productive exchange of climate change information between scientists and users is crucial to this effort.
Arctic and Pacific Ocean Conditions Were Favourable for Cold Extremes over Eurasia andNorth America during Winter 2020/2
Authors: Zhang Ruonan
Published: July 2024

A sequence of extreme cold events occurred across mid-high-latitude Eurasia and western North America during winter 2020/2021. Here, we explore the causes and associated mechanisms for the extremely cold temperatures using both ERA5 observations and large-ensemble atmospheric model simulations. Experiments were conducted with observed ocean surface boundary conditions prescribed globally, and regionally to discern the specific influence of Arctic, tropical Pacific and North Pacific drivers. Increased likelihood of daily cold extremes in mid December to mid January are found in Eurasian midlatitudes in response to reduced Arctic sea ice. Tropical sea surface temperature anomalies, more specifically the La Niña pattern, increased probability of extreme cold over high-latitude Eurasia in early January to early Febraury. Both reduced Arctic sea ice and La Niña increased the probability of daily cold extremes over western North America in late January to late Febraury. We conclude that a combination of reduced Arctic sea ice, La Niña, and a sudden stratospheric warming in January 2021 were factors in the February 2021 extreme cold-wave that caused huge societal disruptions in Texas and the Southern Great Plains. Although the magnitude of the simulated cold extremes are relatively small when compared with observed anomalies, the Arctic and Pacific Ocean surface conditions in winter 2020/21 increased the probability of cold days as cold or colder than observed by approximately 17%~43%. Extreme cold events occurred across Eurasia and North America during winter 2020/21 were made more likely by a combination of reduced Arctic sea ice, La Niña, and a sudden stratospheric warming.
Temporal trends of global UV solar irradiation over the last 20 years in Valencia (eastern Spain)
Authors: Matos Violeta , Marín María José , Gómez-Amo Jose Luis , Estellés Víctor , Utrillas María Pilar
Published: July 2024

The amount of solar ultraviolet radiation (UV) is a crucial parameter due to its relation to health effects, being associated with more than 90% of melanomas. But it also has significant influences on ecosystems, environments and the Earth’s atmospheric processes.In this work, we analyze the temporal trends exhibited by the daily values of UV erythemal irradiance (UVER) and the ultraviolet Index (UVI) at noon and the daily maximum. The measurements were taken with a YES-UVB-1 radiometer located at Burjassot AtmoSpheric Station (BASS, 39º 350N, 0º 250W, 60 m.a.s.l.), covering a measurement period from 2003 to 2023. The seasonal behavior of these parameters have been characterized previously by Marín et al. (2023). The Mann-Kendall test has been now used to identify increasing or decreasing temporal trends in the data. This is a randomization vs. trend test, based on ranges. In addition to identifying the existence of a temporal trend, the Sen’s slope estimator allows to calculate the annual rate of change.  Due to the seasonality of the variables, the seasonal extension of the test was applied, using the monthly medians instead of annual values.The UVER exhibits statistically significant increasing trends in February, May, June, July and December at 90%, 90%, 95%, 90% and 90% confidence levels, respectively. UVI at noon also shows statistically significant increasing trends in February, May, June, September and December at 90%, 99%, 99%, 80% and 80% confidence levels, respectively. Lastly, the maximum daily UVI has increased in May, June and September at 95%, 99% and 90% confidence levels. Similar results have been reported by Marson et al. (2021) at United States, attributing the increased US melanoma incidence to ground-level UV radiation intensity trends; and by Fountoulakis et al. (2021) for several months (especially in April and summer months) in three sites of Italy.Further analysis will make use of simultaneous atmospheric composition and meteorology datasets at Valencia site to clarify the main causes for such short- and long-term trends, by use of regression analyses. It will be studied whether factors such as the decrease in total aerosol extinction and absorbing species such as black carbon could influence the trends.