bluuebunny/crossref_metadata_2025 huggingface dataset:
Spatial and Temporal Characteristics of Unpredicted Upper-Level Turbulence Events using the Global Aviation Turbulence Forecast System and In-Situ Aircraft Data
Authors: Lee Dan-Bi , Kim Jung-Hoon
Published: July 2024

Aviation turbulence, one of the major weather hazards in the aviation industry, is normally classified by generation sources, as follows: convectively induced turbulence (CIT), clear-air turbulence (CAT) that is not directly associated with convective systems, but is mainly caused by various atmospheric instabilities near the jet stream, and mountain wave turbulence (MWT) related to vertically propagating mountain waves generated by low-level flows across mountainous areas. To reduce damage caused by unexpected aviation turbulence encounters, we developed the Korean aviation Turbulence Guidance (KTG) system by combining various large-scale forcing-based CAT and MWT diagnostics calculated from the Korea Meteorological Administration (KMA)’s operational global numerical weather prediction (NWP) model outputs. This has been used successfully for operational turbulence forecast. The KTG system generally shows good performance skills for null- and moderate-or-greater (MOG)-level turbulence, but when focusing only on the performance results for MOG-level turbulence, it shows low performance skill of about 30% (i.e., 0.3 of probability of detection for yes; PODY). In this study, to analyze the cause of the low PODY of the KTG forecast for MOG-level turbulence, we looked at all of the unpredicted MOG-level turbulence events from in situ turbulence observation data for one year. And, the spatial and temporal characteristics of the unpredicted MOG-level turbulence events are analyzed to understand which places are the most unpredicted areas in a given NWP model. We also tried to understand how individual CAT and MWT diagnostics currently used in the KTG system are correlated well with the unpredicted and predicted turbulence events. This will be eventually useful for improving the current version of the KTG system to take into account any possible forecasting capability of CIT and other unknown sources related to CAT and MWT. Acknowledgment: This work was funded by the Korea Meteorological Administration Research and Development Program under Grant KMI2022-00410, and was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (RS-2023-00250021).
Temporal complementarity analysis of solar photovoltaic, onshore, and offshore wind resources in the Iberian Peninsula  
Authors: López de la Franca Arema Noelia , Gaertner Miguel Ángel , Gutiérrez Claudia , Sánchez Enrique , Gallardo Clemente , Ortega María
Published: July 2024

The integration of renewable energies into the electricity systems of European countries plays a key role in the European Union's ambitious goal of achieving a neutral climate by 2050. The geostrategic position of the Iberian Peninsula (IP) makes Spain and Portugal a benchmark in renewable energies, where their share exceeds the European average (around 50% in Spain and 60% in Portugal). Currently, solar photovoltaic (PV) and onshore wind power are the main sources of renewable energies in these countries. However, the offshore wind resource, which is set to play an important role in future energy systems, has great potential for exploitation in the IP. In this context, the Spanish and Portuguese governments have provided a legislative framework to encourage the development of offshore wind farms in the coming years. Furthermore, the annual cycle of energy demand in the IP peaks during the winter and summer. Yet, neither the annual cycle of onshore wind nor solar PV energy generation adjust alone with this demand curve. Previous studies agree that spatial and/or temporal complementarity between these resources can be used to increase renewable energy production and smooth the temporal variability of the combined energy supply. Although in the IP only a few studies analyzing these issues, they conclude that this region presents a great potential in terms of complementarity between these sources. Thus, the objective of this work is to determine whether offshore wind energy presents substantial temporal complementarity with onshore wind and solar PV energies in the IP in winter and summer. For this, hourly solar PV and onshore wind real time generation were obtained from Spanish and Portuguese electrical networks and normalized by the installed capacity. With respect to the offshore wind resource, hourly wind speed at 150 meters hub height was extracted for different locations marked as suitable zones by the Spanish and Portuguese governments from the COSMO-REA6 high-resolution reanalysis for 2015-2019. Once the wind speed was translated into capacity factor, we established a capacity factor threshold representing an appropriate efficient resource. We then analyzed the availability and length of generation/non-generation episodes for each resource based on that threshold. Finally, we analyzed the complementarity and synergy between resources, i.e., cases in which the generation of one resource complements the non-generation of another resource and cases in which any of the resources complements the rest. Some of the initial results show that offshore wind complements solar photovoltaic in winter and onshore wind in summer. This indicates that the exploitation of the offshore wind resource can contribute to diversify and improve the integration of renewable generation in the energy mix of the Iberian electricity system.
Large-scale background and maintenance mechanism of the extreme rainfall in summer 2020 over East Asian
Authors: Qi Yanjun , Zhang Renhe , Wang Zhuo
Published: July 2024

A severe flooding hit central-eastern China along the Yangtze River to southern of Japan in summer 2020. The floods were induced by extreme rains, and the associated dynamic and thermodynamic conditions are investigated. The large-scale southwestward-moving anomalous quasi-biweekly (QBWO) circulation was essentially the fluctuation of cold air mass related to the tropospheric polar vortex over the mid-high latitude Eurasian in boreal summer. The southwestward-moving of cold air mass from mid-high latitudes converged on the northeastward-transporting of warm and moist air by the strong anomalous anticyclone over the western North Pacific, providing important large-scale circulation support for the extreme rainfall.  Eastward zonal transport of a large amount of water vapor from the Bay of Bengal and Indo-China and northward transport from the South China Sea provided the background moisture supply. The quasi-biweekly anomalies of potential of vertically integrated water vapor flux played an important role in maintaining the subseasonal variability of rainfall. The diagnosis of moisture tendency budget shows that the enhanced moisture was primarily attributed to the moisture convergence. Further analysis of time-scale decomposition indicates that the convergence of background mean specific humidity by the QBWO flow played dominant roles in contributing to the positive moisture tendency. In combination with adiabatic ascent over the rainfall region induced by the warm temperature advection, the boundary layer moisture convergence strengthened the upward transport of water vapor to moisten the middle troposphere, favoring the persistence of the extreme rainfall. The vertical moisture transport associated with boundary layer convergence was of critical importance in causing low-level tropospheric moistening. By comparison, the horizontal moisture advection played a secondary important role in maintaining the quasi-biweekly oscillation of extreme rainfall in 2020.
A utilization of new observation data in KLAPS (Korean Local Analysis and Prediction System) and the impacts on a very short-range precipitation forecast 
Authors: Won Hye Young , Lee Keun Hee , Kim Seungbum
Published: July 2024

The Korea Meteorological Administration (KMA) has been operated a very short-range forecast system, named Korean Local Analysis and Prediction System (KLAPS), which runs every 10 minutes at 5 km horizontal resolution since 2019. To reflect rapidly changing atmosphere state in real-time, numerous data sources such as surface observations, upper-air measurement, radar data, satellite, aircraft reports, wind profiler data are ingested into the three-dimensional analysis. To date, 13 different types of observation data have been utilized, and for recent two years, two more observation data are tried to utilize newly to improve the forecast performances. The first one is a freezing level (0oC) data interpreted by a bright band due to the enhanced radar reflectivity. Another one is the commercial aircraft-based meteorological information from Automatic Dependent Surveillance Broadcast (ADSB) Mode-Selective (Mode-S). In this study, we present the method to utilize these data and the result of the very short-range precipitation forecast.  To ingest the freezing level data to KLAPS system, firstly each polar-form data at 10 radar station over the domain is converted into a cartesian coordinate system. And then the individual freezing level data are merged to three-dimension grid on KLAPS, and finally utilized for the temperature analysis with a climatological quality control procedure. Meanwhile, the ADSB Mode-S data are simply applied to KLAPS analysis system by referring to the Aircraft Meteorological Data and Relay (AMDAR) data package. But the Mode-S observation are required a data thinning process to reduce observation redundancy and correlated biases due to its high dense resolution in both space and time (Met Office, 2019). In this study, a median value of the Mode-S data within each 5km horizontal grid, 22-vertical level, and 10-minute time window, is newly considered as a thinning method. During the conference, the improved performances of KLAPS are going to be presented in details.
The effects of climate change on the essential characteristics of catchment runoff in the Uppest-Tisza Basin
Authors: Pongracz Rita , Kis Anna , Szabó János Adolf
Published: July 2024

Water is a key socio-economic factor (e.g. drinking water, sanitation, irrigation, energy) affecting the main challenges of this century. Therefore, it is important to analyse the projected regional hydrological changes related to climate change. The estimated trends may help to build and implement appropriate adaptation strategies in water-management (including flood defence and water storage) in order to mitigate the potential hazards.In the present study, the estimated changes of water discharge are analysed at four cross-sections (i.e. Tiszabecs, Mizshirja, Uszti Csorna, Rahiv) in the Uppest-Tisza Basin, located in Eastern-Central Europe. For the investigation, the DIWA (Distributed Watershed) hydrological model is applied, while the necessary meteorological input data (daily minimum and mean temperature, precipitation) were provided by the CARPATCLIM database for the historical period (1972–2001) and by a regional climate model simulation for the future (2069–2098), taking into account two different RCP scenarios (RCP4.5 and RCP8.5). In order to eliminate the systematic errors of climate model simulations, a bias-correction is completed by adjusting the parameters of the distribution of temperature, dry and wet spells and precipitation amount. The correction factors are determined by the differences between the reference database and the historical climate model simulation. Furthermore, to take into account all the possible changes, the DIWA simulations are embedded in a Monte Carlo cycle, hence, several hundreds of possible realisations of water discharge values can be investigated.According to our results, higher temperature values are likely to occur in the target area by the end of the 21st century, and winter precipitation is projected to increase. The mean water discharge is projected to decrease from April to September in the case of RCP4.5, and from March to October in the case of RCP8.5, while in January and February an increase is likely to occur.Acknowledgements: Research leading to this study has been supported by the Hungarian National Research, Development and Innovation Fund (under grants PD-138023 and K-129162), and the National Multidisciplinary Laboratory for Climate Change (RRF-2.3.1-21-2022-00014). 
Near-time atmospheric observations in urban areas: insights from concurrent operations in multiple cities
Authors: Zeeman Matthias , Christen Andreas , Grimmond Sue , Fenner Daniel , Morrison William , Feigel Gregor , Plein Marvin , Sulzer Markus , Looschelders Dana , Chrysoulakis Nektarios
Published: July 2024

We describe features and results of a data system developed to allow timely access to data from novel modular atmospheric monitoring systems deployed in urban areas in multiple cities of different sizes, simultaneously. The ERC urbisphere project is collecting a wide range of atmospheric environmental data to improve weather and climate models, in order to assess the impact of cities on the atmosphere (e.g., aerosols, greenhouse gases) and human exposure to extreme events (e.g., heat waves, heavy precipitation, air pollution). Modular observing systems involving short-term deployments include customised automatic weather stations, Doppler and ceilometer lidars, scintillometers, balloon radio sounding and spectral imaging. Deployments range from streetlight-mounted to building roofs and indoors to mobile platforms (vehicles, drones). Together this creates challenges to synthesise across multiple sources of diversity.Data are uploaded in near-time to a central data infrastructure via cell phone and IOT networks. A metadata system helps track the location and configuration of all deployed components and provides the backbone for processing instrument records into location-aware, convention-aligned and quality-assured data products according to FAIR. The data system provides services (e.g., APIs, Apps, ICEs) for inspection and computation by campaign participants. Workflow and design considerations also include collaboration tools that ensure attribution for multiple uses in near time by researchers, operational agencies and citizens.We will demonstrate how the systematic, easily adoptable approach can simplify complex campaign workflows, for both modellers and observers. The showcase of the data system will use examples from outdoor/indoor temperature observations and spatial wind field observations from past and ongoing campaigns.  
A bias-corrected CMIP6 climate projection dataset for the Danube Basin 
Authors: Smău Raluca , Dumitrescu Alexandru
Published: July 2024

As the climate keeps changing, it is essential to develop effective solutions to support adaptation and mitigation to the observed and projected climate change. It is imperative that our long term strategies rely on in-depth understanding of the prospective range for expected climate scenarios.The Coupled Model Intercomparison Project (CMIP) framework was developed in response to this need, integrating an extensive collection of global climatic models developed by different modelling groups, each of them with a focus on specific physical and atmospherical processes. These models generate valuable future climate projections that could be integrated in decision-support solutions to foster the delivery of key ecosystem services in water-dependent habitats and improve their resilience to climate change.This study focuses on the Danube Basin, a representative climate change hotspot at European level, which integrates the joint impacts of a wide range of socio-economic factors (i.e., urbanization, land use change). This region is subject to the ecosystemic and biodiversity threats arising from increased temperatures, decreased precipitation and reduced river flow in both present and future climate, challenging the management of restoration actions. This study is aimed to provide an improved understanding of the expected future climate change signals for the timeframe 2015 - 2100 in the top priority CMIP6 scenarios (i.e., SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5) at the Danube Basin scale, using bias-corrected data. The model outputs are calibrated on the historical period 1961–2014 with E-OBS gridded dataset at 0.1° spatial resolution.Our approach includes a performance comparison of several bias-correction methods (e.g., univariate - quantile delta mapping, multivariate – R2D2, MBCn) used within a spatial disaggregation algorithm, to minimize the uncertainty induced by systematic errors in the projection data. The bias-corrected climate projections of air temperature and precipitation will feed the Restore4Life decision-support system for wetland restauration.AcknowledgementsThis research received funds from the project “Restoration of wetland complexes as life supporting systems in the Danube Basin (Restore4Life)” funded by the European Union Horizon Europe programme, under Grant agreement n° 101112736.
Springtime stratospheric ozone trends in the Arctic since 198
Authors: Tichopad David , Láska Kamil
Published: July 2024

The Arctic ozone layer is characterised by high interannual variability, especially in the springtime period, which depends on stratospheric circulation and polar vortex forcing. Since the 1990s, there has been a gradual ozone recovery in the Arctic polar stratosphere. However, the increasing ozone trend may be different in unlike pressure levels of the stratosphere in connection with the ongoing climate change, which is related to the strengthening of the Brewer-Dobson circulation. This strengthening is related to changes in vertical distribution of ozone concentrations in different levels of the stratosphere. The aim of this study is a spatiotemporal analysis of the stratospheric ozone trend at different pressure levels between 10–100 hPa in the spring periods 1980–2023. In the following section, trends of geopotential height, temperature or potential vorticity at pressure levels between 10–100 hPa are analysed in particular. The monthly means of ERA-5 reanalysis layers were utilized. The trend was assessed using linear regression, and its statistical significance was determined using the non-parametric Mann-Kendall test. In March, the statistically significant decreasing trend (p=0.05) of the ozone mass mixing ratio was detected over Siberia at 10 hPa, while at 100 hPa, the statistically significant decreasing trend was registered over eastern Siberia and Greenland. In April, there was a statistically significant increasing trend at 10 hPa over eastern Siberia, and at 100 hPa, the trend over uniform parts of the central Arctic is spatially heterogeneous. In May, a statistically insignificant increasing trend occurred over the Arctic Ocean at 10 hPa, while at 100 hPa statistically significant decreasing trend was registered in the peripheral parts of the Arctic between 60–70°N.  
Passive tracer under stable conditions: impact of background wind and valley geometry in an idealized setup
Authors: Bašić Ivan , Schmidli Juerg , Singh Shweta
Published: July 2024

Accurate representation of atmospheric boundary layer (ABL) processes is crucial for trace gas simulations and inverse modeling on a regional scale, particularly in areas with complex terrain such as the Swiss Midlands. Challenges arise from uncertainties in local turbulent transport, advection, and diffusion. Local circulations in the ABL, influenced by complex terrain, directly impact the vertical profiles of trace gases emitted at the surface. Biases in these processes can lead to significant errors, especially during nighttime stable conditions, affecting the estimation of trace gas concentrations, notably greenhouse gases accumulation. By conducting high-resolution idealized simulations using Cloud Model 1 in Large Eddy Simulation configuration, we aim to provide insights into the trace gas dispersion over the Swiss Midlands, characterised by rolling terrain. This study investigates sensitivities of trace gas simulations to large-scale background wind and valley depth, within stable boundary layers. We investigate how these factors influence the storage and transport processes of passive tracers in nocturnal cold pools, as well as their morning depletion. The main focus of our study is on the temporal evolution of the passive tracer concentration at virtual towers located at the valley center, eastern and western slopes, and the ridge top. The results show that at the valley center the stable regime leads to the build-up of the passive tracer near the valley floor. Furthermore, it is found that the peak values are reduced and the timing of the peak is delayed with increasing inlet height. This means that despite the low vertical turbulent mixing, the local re-circulation within the valley transports the tracer to higher elevations, resulting in stratified tracer accumulation.
Future changes to extra-tropical cyclones: combining CMIP6 projections and idealised modelling.
Authors: Sinclair Victoria , Bouvier Clément , Cornér Joona , van den Broek Daan , Köhler Daniel , Ekblom Madeleine
Published: July 2024

Extra-tropical cyclones (ETCs) are an important part of the climate system and are responsible for much of the weather in the mid-latitudes. The most extreme of these weather systems can cause damaging winds and heavy precipitation and can have adverse impacts on society. While the current generation of climate models are starting to agree on how the number, intensity and location of ETCs will change in the future, considerable uncertainty remains in how impact-relevant parameters such as wind gusts and precipitation will change. Here we use a novel combination of CMIP6 model projections and idealised model simulations of baroclinic waves to identify how precipitation and 10-m winds and wind gusts associated with ETCs may change in the future. We have performed a large ensemble (~6500 members) of baroclinic life cycle simulations with OpenIFS, which is a version of ECMWF’s Integrated Forecast System. The ensemble was created by varying 7 parameters with Latin hypercube sampling: average surface temperature; surface relative humidity; jet width, height and strength; lapse rate; and surface roughness. CMIP6 projections indicate an increase in mean temperature, lapse rate, jet width, and upper-level jet wind strength, and little change in relative humidity, jet height or surface roughness. Using CMIP6 projections from different scenarios, we map future climate projections onto the same 7-dimensional parameter space and thus identify the baroclinic wave simulations which are closest to the mean background states predicted in CMIP6 in the future. As our baroclinic wave simulations produce considerably more output fields at much higher temporal resolution compared to CMIP6, this approach enables a more thorough approach for examining how ETCs, and in particular, their precipitation and wind gusts, will change in the future. Initial results from this analysis will be presented.
Global climatology of cyclone clustering in present and future climates
Authors: Weijenborg Chris , Spengler Thomas , Priestley Matthew
Published: July 2024

Cyclone clustering, the rapid succession of multiple extratropical cyclones at a confined region during a short period of time, causes a large fraction of European weather extremes like wet spells and wind extremes. The idea that several cyclones follow a similar track dates back to the concept of cyclone families of Bjerknes and Solberg. To investigate the dynamical causes of cyclone clustering, it is necessary to diagnose the occurrence of cyclone clustering and to determine their characteristics. However, so far, most diagnostics focused either on local impact or on a statistical analysis of storm recurrence. While the first cannot be applied globally, the latter is difficult to relate to individual events. We therefore use a novel method to globally detect cyclone clustering that is closer to the original concept of Bjerknes and Solberg, where extratropical cyclones follow similar tracks within a given time period.Using this new cyclone clustering diagnostic based on spatio-temporal distance between cyclone tracks, we analyse cyclone clustering globally in Era-Interim for the period 1979 until 2016 as well as for 10 CMIP6 climate models. We separate the cyclone clusters into two types: one representing the ‘classical’ bjerknes-type clusters, and one representing more stagnant clusters. We find that cyclone clustering mainly occurs along the climatological storm tracks, with the Bjerknes-type more common at the western side of the storm tracks, while the stagnant-type of cyclone clusters occurs more downstream. In general, clustered cyclones are stronger than non-clustered cyclones, especially for the Bjerknes-type. CMIP6 models feature a slight bias towards an equatorward shift of the storm tracks, and this bias is stronger for clustered cyclones. This relatively larger bias suggests that the clustered cyclones are important for correctly simulating the storm tracks. In a future climate cyclone clustering occurs more poleward. Furthermore, the average number of storms per cluster decreases in a future climate, though the mean intensity of the cyclones that are clustered increases slightly.
Porting the Meso-NH atmospheric model to GPU architectures allows simulating extreme weather events across scales
Authors: Escobar Juan , Wautelet Philippe , Pianezze Joris , Chaboureau Jean-Pierre , Dauhut Thibaut , Barthe Christelle , Brumer Sophia , Pantillon Florian
Published: July 2024

Numerical simulation of the atmosphere plays a crucial role in understanding and anticipating extreme weather events. Steady advances in computing power have made it possible to increase the complexity and range of scales represented by numerical simulation. However, the advent of heterogeneous computing architectures with multi-core central processing units (CPUs) and graphics processing units (GPUs) requires atmospheric codes to be adapted.Here we describe the adaptation of the Meso-NH non-hydrostatic mesoscale atmospheric model of the French research community. The Fortran code is ported to GPUs by including OpenACC directives to the most computationally expensive parts of the code. This approach allows running the same code on CPUs and on hybrid CPUs/GPUs architectures. To guarantee the accuracy of the port and the absence of bugs, measures have been taken to ensure bit-to-bit reproducibility between executions on these two architectures. A critical point lies in the atmospheric pressure solver, which requires the inversion of an elliptic equation. A geometric multigrid inversion algorithm is integrated, because the fast Fourier transforms approach used in the original version of the code becomes inefficient with a high number of GPUs. Currently, the code runs on different GPU-NVIDIA and GPU-AMD platforms and scales efficiently up to at least 1,024 GPUs, achieving a 3x increase in energy efficiency compared to CPUs only.First scientific applications focus on the simulation of extreme weather events across scales as part of a Grand Challenge GPU pilot project on the AMD-based Adastra supercomputer of GENCI (same architecture as Frontier, the 1st exascale supercomputer). Three representative storms are simulated: a North Atlantic windstorm associated with a mid-latitude cyclone, a Mediterranean convective storm characterized as a derecho, and a mesoscale convective system over the Amazon rainforest. Representation of the North Atlantic storm requires downscaling from the synoptic cyclone scale (>100 km) down to local wind gust formation (
The FLUXNET outreach working group: communicating flux science to society
Authors: Román-Cascón Carlos , Kelley Jason , Bassiouni Maoya , Lee Sung-Ching , Aguilos Maricar , Reich Emma
Published: July 2024

FLUXNET is an international initiative that joins regional networks of scientists working with eddy-covariance (EC) systems around the world. The EC method is currently the most reliable technique to measure exchanges of mass and energy between ecosystems and the atmosphere (for example carbon dioxide, methane, latent heat, sensible heat, or momentum fluxes). Ecosystem-atmospheric flux measurements are key for many studies and applications in agriculture, hydrology, meteorology, and climate change by providing physical verification of carbon, water, and other trace gas budgets.The FLUXNET outreach committee formed in 2022 with the goal of sharing flux science and research findings beyond the typical research community. The overall objective of this committee is to develop new ways of communicating complex science and disseminating these ideas to broad audiences outside the typical domain of research.  The intent is to create new links between flux-science professions to other interdisciplinary scientists, resource conservation professionals, policymakers, and society in general.Over the last year, committee members have worked on several projects to achieve these objectives. In this work, we show some of these initiatives developed in 2023, and other initiatives being carried out in 2024. The Fluxnet Coop and the National Science Foundation are supporting an artist residency program at flux measurement sites to create new interpretations of located-based science conducted at flux measurement sites.  Committee members are developing plain-language materials to explain technical documentation of flux measurement and contributing to the translation of existing materials in English into several other languages. The committee is also working to produce a podcast and open-access publications that serve as a bridge between peer-reviewed science and accessible plain-language reporting. With this presentation, we will open discussion with the audience to help us improve our methods and suggest new projects, and explore other initiatives that share similar objectives. Our activities are initial steps toward creating a more convergent global flux science community and well-informed society. 
Drought in Croatia in the context of weather types
Authors: Marinovic Ivana , Beck Christoph
Published: July 2024

In Croatia, drought causes the highest economic losses inflicting serious damages, especially in the agricultural and water management sectors. Only in 2003, the drought damage was 90 %. Even though drought can occur in every season, the greatest damage caused by drought occurs in the warm part of the year, particularly in summer, when the absence of precipitation is combined with high air temperatures. For spatial and temporal comparison of drought events in different parts of the world and different periods throughout history in meteorological practice the standardized precipitation index, SPI is the most often used. Accordingly, in this analysis, the SPI index is used for detecting drought events in Croatia in previous decades.The products of the COST733 action “Harmonization and Applications of Weather Types Classifications for European Regions”, both catalogue and software, were applied to the Croatian area to improve previous knowledge and practice, and to develop a classification that is intended to be the most appropriate to capture precipitation conditions in Croatian regions. For this purpose, Croatia is divided into five regions to acknowledge the orography and climate diversity of the Croatian area which lead to different weather conditions within the same atmospheric circulation. The efficacy of different objective classifications is examined utilizing Croatian meteorological station data.Selected classifications are compared and their ability to represent drought dynamics in Croatia is evaluated. The goal is to identify classifications that are best suited to capture spatiotemporal drought variability in the Croatian area. For this purpose, the percentage anomalies approach is used for quantifying the relationship between occurrence frequencies of weather types and exceedances/undershootings of specified SPI-thresholds. Further, the analysis aims to identify the main weather patterns responsible for drought events and spatial variations in drought impacts and manifestations among Croatian regions are examined as well. Moreover, temporal variations concerning circulation-drought relationships are also analyzed.
Comparison of two approaches to fitting new IDF curves in Czechia
Authors: Crhová Lenka , Müller Miloslav , Kašpar Marek
Published: July 2024

Characteristics of short-term rainfalls, especially their intensity and design values, are very important for the technical (e.g., sewage system) and hydrological practice. However, measurement and data processing of these characteristics are rather complicated. The still frequently used design values of short-term rainfalls in Czechia come from studies that are more than 60 years old.Therefore, the new design values of rainfall totals are in preparation within the project “Prediction, Evaluation and Research for Understanding National sensitivity and impacts of drought and climate change for Czechia” (PERUN). The intensity-duration-frequency (IDF) curves for the 5min – 3day rainfall totals will be prepared for selected measurement stations of the Czech Hydrometeorological Institute. More than 170 stations with sufficient length (mainly more than 25 years) of joined digitalized pluviographs records and the automatic rain gauge measurement series from 1951–2022 were processed. The 5-year to 100-year design values were estimated using the region-of-influence (ROI) method. Afterwards, the final IDF curves (theoretical function) should be fitted with the estimated design values. However, the classical approach of fitting three-parametric intensity curve is suitable only for a part of the IDF curve (i.e. short-term rainfalls). Thus, a new approach, i.e., use of a polynomial function, was suggested as suitable representation of the whole curve including long-term (approx. 6-hour – 3-days) rainfalls.In our contribution, we focus on comparison of the classical approach to fitting IDF curves (i.e., use of three-parametric intensity curve) and newly suggested approach (i.e., use of polynomial function). We focus on the part of the curve for short-term rainfall (durations of 5-360min) where classical intensity curve is generally used. 
A hybrid approach to predict and explain extreme precipitation events over Northern Italy
Authors: Grazzini Federico , Dorrington Joshua , Grams Christian M.
Published: July 2024

The prediction of extreme precipitation events is one of the main objectives of operational weather services.  Numerical weather prediction models have continuously improved, providing uncertainty estimation with dynamical ensembles. However, explicit forecasting of these events is still challenging due to the limited predictability of precipitation fields. Greater availability of machine learning modules paves the way to a hybrid-forecast approach, with the optimal combination of physical models, event statistics, and user-oriented post-processing. In this contribution, we describe a specific warning chain, called MaLCoX (Machine Learning model predicting Conditions for eXtreme precipitation), specialised in recognizing synoptic conditions leading to precipitation extremes and subsequently classifying them into predefined categories. The application, running in test at ARPAE Emilia-Romagna, focuses on northern and central Italy, taken as a testbed region. The application leverages a hierarchy of predictors, large-scale (non-local predictors), synoptic-scale (local predictors) and direct (precipitation) to improve the prediction of exceeding precipitation thresholds, maximising the predictability of the different scales of motion at increasingly longer time horizons. A practical approach that can be extended to other geographical areas and over long time intervals seamlessly. The system has been trained with the ARCIS gridded high-resolution precipitation dataset as the target truth for precipitation and with the last 20 years of the ECMWF reforecast dataset as input predictors. We show that the optimal blend of larger-scale information with direct model output improves the probabilistic forecast accuracy of extremes in the medium-range. In addition, with specific methods, we provide a useful diagnostic of the physical processes that make a weather event extreme. 
Identification of Key Meteorological Variables and Synoptic Patterns of High-Concentration Asian Dust Storms
Authors: Lee Seungyeon , Park Seon Ki
Published: July 2024

High-concentration Asian dust storm (ADS) events significantly increase atmospheric particulate matter concentrations, adversely affecting respiratory health and causing substantial economic losses in environmental and agricultural productivity. Understanding the mechanisms, pathways, and behavior patterns of ADS is essential for providing early warnings for periods and regions where severe dust events are anticipated, enabling appropriate preventive measures. This research aims to identify key meteorological variables and classify synoptic patterns of high-concentration sand dust events (dust warnings) during the beginning stages at the source regions and the peak concentration stages observed over Korea, using unsupervised learning methods such as Principal Component Analysis (PCA) and K-means clustering. The study analyzed the ADS cases observed from 2002 to 2022, utilizing the ECMWF reanalysis data (ERA5). The results indicate that during the origin stage, the primary meteorological variables were the geopotential height and temperature at lower layers (900-1000hPa), while temperature and humidity were key variables during the peak concentration observation stage. Each stage was classified into five cluster patterns. Temporal analysis of these patterns revealed that most ADSs occurred more frequently at night, except for pattern 4 that was predominantly observed during daytime, and pattern 5 that was exclusively observed at night. During the peak concentration stage, three out of five patterns showed more frequent occurrences at night, while patterns 1 and 4 had more frequent daytime occurrences, and pattern 5 was predominantly observed at night. This research contributes to the improvement of high-concentration ADS prediction by classifying and analyzing the synoptic patterns related to their occurrences.
Studying the effect of climate change in underground systems. A Novel Quality Control Workflow for Subterranean Temperature Data
Authors: Cimenti Alice , Cresi Lorenzo , Acquaotta Fiorella , Senese Antonella , Isaia Marco , Piano Elena , Nicolosi Giuseppe , Pisani Olga , Piquet Anna , Mammola Stefano
Published: July 2024

Caves are some of the most understudied ecosystems on Earth. However, they are of great interest for their stable climate and for the most specialized biodiversity that caves host. Thanks to the PRIN project, Biodiversity conservation goes DEEP: integrating subterranean ecosystems into climate CHANGE agendas and biodiversity targets we can improve our understanding on subterranean environments to fill the biological and climatic knowledge gaps. To best study underground systems dynamics an interdisciplinary study is conducted merging meteorological and ecological disciplines.Within a two years time frame, the project's workflow runs through the understanding the impacts of global change, creating models to predict the future consequences on different scenarios and implementing conservation programs to protect these ecosystems.Seven caves in Western Alps have been selected as benchmark caves. Taxonomic and functional traits data are collected by on-site samplings and literature reviews to create a distribution and functional model of subterranean taxa.Abiotic data are collected through monitoring cave temperatures continuously from 2020 until today and can be compared with previous data of 2012.We created a quality control protocol for the internal cave temperature data structured in three fundamental steps: standardizing the interval between consecutive records every 6 hours; removing sudden temperature breaks using a mobile variance measure; considering the gaps to evaluate the reliability for future studies.Analysis of cave meteorology is run to identify the thermal responses within caves compared to surface environments. Preliminary application of this QC procedure, one of the most stable caves of our dataset, has demonstrated its effectiveness in isolating relevant temporal frames and enhancing data reliability. Our first case study points out an average increase of 0.28°C from 2012 and the cave internal temperature shows a constant increase from 2020 to 2023.The absence of a standardized approach for managing cave temperature data presents anopportunity for innovation. We introduce a scalable and adaptable quality control protocol, designed to be generalizable across different environmental studies.The results can be merged with ecological modelling to obtain a process-based prediction of biodiversity change in subterranean systems. Based on this model, hotspots of conservation value can be identified to create a dynamic network of protected areas that considers climate-driven shifts insubterranean ecoregions.This protocol not only enhances data integritybut also sets a new benchmark for future research insubterranean climate analysis.
UAS measurements as part of the project WINSENT ("Wind Science and Engineering Test Site in Complex Terrain")
Authors: Gruchot Lukas , Bramati Matteo , Schön Martin , Zum Berge Kjell , Bange Jens
Published: July 2024

Wind energy is one of the key technologies in the transition to cleaner energy. WINSENT ("Wind Science and Engineering Test Site in Complex Terrain"), a project funded by the German Federal Ministry for Economic Affairs and Climate Protection (BMWK) and the Baden-Württemberg Ministry of the Environment, has established a wind energy test site in complex terrain, providing invaluable insights into the dynamics of wind energy in such environments.Located on the Swabian Alb near Stuttgart, Germany, the site has unique features, including its proximity to a steep afforested edge and specialised equipment such as research wind turbines (RWTs) and meteorological measurement masts, which allow the study of the turbulent overflow of the seasonally changing slope and the behaviour of wind turbines in complex terrain.The University of Tübingen is contributing to the project by carrying out in-situ measurements using fixed-wing and multi-copter uncrewed aircraft systems (UAS) at the test site. These UAS are deployed in different positions, including the inflow, the slope, above and behind the test site, and resolve turbulent fluctuations down to the sub-metre range. Previous measurement campaigns (Intensive Operation Period, IOP) were carried out in the previous WINSENT project. In the followup WINSENTvalid project, additional IOPs will be carried out to collect in-situ measurement data to validate the numerical models developed by WINSENT. Furthermore, the impact of the newly constructed RWT on the airflow is being investigated by comparing it with pre-construction data.The presentation will include a description of the test site, the IOPs carried out and a presentation of the first measurement data.
The Response of Extreme Jet Stream Waviness on Large-Scale Spatial Warming on an Aquaplanet
Authors: Batelaan Thomas J. , Weijenborg Chris , Steeneveld Gert-Jan , van Heerwaarden Chiel , Sinclair Victoria
Published: July 2024

Key characteristics of anthropogenic climate change are polar amplification and upper tropospheric tropical warming. These large-scale spatial warming patterns alter the equator-to-pole temperature gradient in the lower and upper troposphere. The modified meridional temperature gradients affect the tropospheric jet streams. How the future jet streams will be affected is not fully understood. We perform four aquaplanet simulations with different sea surface temperature (SST) distributions to mimic large scale spatial warming patterns. Compared to the control run the SSTs of the SST4 simulations are increased with 4 K. In the Reduced Temperature Gradient (RTG) simulation the SSTs are gradually warmed from the equator with the maximum temperature increase of 5 K occurring poleward of 60° latitude. The Polar Amplification (PA) simulation uses the SST distribution of control between 45°S and 45°N, with SSTs set to 5 K poleward of these latitudes. We quantify the impact of these sea surface temperature distributions on jet stream strength, wave amplitudes and jet stream  waviness, quantified by a modified Sinuosity Index.Large-scale spatial warming strengthens the jet stream by a uniform warming scenario SST4 and weakens the jet stream in the two scenarios RTG and PA where the meridional temperature gradient is reduced. However, all scenarios indicate substantial decreases in the magnitude of large wave amplitudes, extreme jet stream waviness and reduced variability of these diagnostics. Our results contradict the earlier proposed mechanism that low-level  polar warming weakens the jet stream and increases wave amplitudes and jet stream waviness. We conclude that a weaker jet stream does not become necessarily wavier.
Preparing society for extreme weather: insights from Belgian initiatives to create actionable information for stakeholders
Authors: Caluwaerts Steven , Top Sara , Hellebosch Ian , Vergauwen Thomas , Vandelanotte Kobe , Van Schaeybroeck Bert , Termonia Piet
Published: July 2024

Climate change, primarily through extreme weather events, significantly impacts various societal sectors such as health, industry and agriculture, and it is expected that these impacts will further increase in the coming decades. Despite the abundance of knowledge and data on climate change, translating this information into actionable insights for stakeholders preparing for climate change proves challenging. Communication breakdowns often arise between scientists and stakeholders due to differing terminology, understanding of climate science and expectations.In this presentation, we aim to showcase recent Belgian initiatives focused on effectively communicating climate risks to stakeholders. One notable initiative, triggered by the ongoing CORDEX.be II project to provide high-resolution climate information for Belgium, involves recreating historical heatwaves at future global warming levels based on long-term climatological datasets. Subsequent discussions with diverse sectors, including health authorities, event organizers, and the energy sector, were tailored to each sector's specific needs. For instance, we used the operational Belgian heat and health plan thresholds to visualize the occurrence of warning and alarm phases across various levels of global warming. In this way we effectively concretize the implications of climate change for health stakeholders in a comprehensible form. As a second case, we will present our ongoing collaboration with cities to monitor urban greening projects within their public spaces. Through this collaboration, we gather quantitative data on heat stress at the microscale, e.g. under a tree canopy or next to a water element. This approach allows cities and citizens to grasp the effectiveness of these measures, assisting in the formulation of future plans. The purpose of the presentation is to share our insights and inspire colleagues facing comparable challenges when engaging with stakeholders.