bluuebunny/crossref_metadata_2025 huggingface dataset:
Development of UAS-based measurement network for routine atmospheric vertical profiling
Authors: Bottyán Zsolt , Gyöngyösi András Zénó , Kardos Péter , Tuba Zoltán , Vranics Ferenc Dávid
Published: July 2023

According to a survey by the World Meteorological Organization (WMO) there is a serious lack of data from measurements describing the vertical characteristics of the atmosphere. This, besides the insufficient determination of the current state, also affects the accuracy of meteorological forecasts. WMO sees the use of Uncrewed Aircraft Systems (UAS) for atmospheric measurement as a possible solution to this problem. Therefore, WMO coordinates a global campaign in 2024 to demonstrate the capabilities of UAS measurements as a possible operational data source. From Hungary, MouldTech Systems (MTS) is the only registered participant so far, and they started the development of an UAS-based measurement network for routine atmospheric vertical profile measurements. The measuring UAS was designed and manufactured at MTS considering the operational weather limits of the flights to approach the level of applicability as radiosondes. The flyability of UAS was validated using ECMWF ERA5 reanalysis fields. The average values of applicability are between 90-95% at the planned measurement sites. MTS as a drone operator organization has already obtained operational authorization from the national competent authority for three different locations in Hungary to perform the profiling operation. During this operation, the drone can climb up to 2500 m AMSL to cover the height of the planetary boundary layer regardless of seasons. In accordance with the WMO's expectations the redundantly installed sensors measure the temperature, the humidity, and the pressure. Besides these variables, the wind vectors are calculated from the telemetry data provided by UAS. All the meteorological information is collected in our data server in real-time via LoRa communication. On an experimental basis, the measured data are assimilated into our numerical weather prediction model to gather as much experience as possible to estimate the effective range of the data assimilation in our NWP domain and determine the ideal spatial density of the measurement sites. In summary, in our presentation, besides the achieved outcomes of the development and the bridged obstacles, we would like to introduce the UAS itself, the complete functionality of the measurement network, and the related future challenges of normal operation.
Use of atmospheric modelling to assess fire danger in mainland Portugal during heatwave periods
Authors: Purificação Carolina , Campos Cátia , Henkes Alice , Couto Flavio T.
Published: July 2023

Intense heatwave periods increase the likelihood of extreme wildfires which can lead to negative impacts on many socio-economic sectors. Also, there is still a need to better understand how this phenomenon can impact specific regions in terms of fire danger. The present study aims to investigate three heatwave periods occurring in 2003, 2018 and 2019. All the periods were associated with significant wildfires, two of them linked to mega fires in southern Portugal. The MesoNH is a full-physics non-hydrostatic limited-area research model able to represent atmospheric motions in different scales and has been used to explore the structure and dynamics of the atmosphere during the events. The model was configured with 2.5 km grid spacing and performed for several days depending on the episode. All the experiments were designed with 50 vertical sigma levels unequally spaced, stretching gradually from 30 m (bottom) to 900 m (top). Initial and lateral boundary conditions were provided by European Centre for Medium-Range Weather Forecasts (ECMWF) analysis, with updates every 6 h. The Monchique wildfires in August 2003 and 2018 burned above 25,000 ha. In 2019, the Vila de Rei wildfire burned almost 10,000 ha. All these wildfires’ events occurred under a heatwave influence. The numerical experiment allowed identifying some areas with potential to be affected by wildfires, mainly the regions where orographic effects act to enhance the fire danger. The atmospheric conditions simulated helped to explain the intense fire activity for several days. The heatwave environment associated with extreme heat, very low humidity, and airflow interacting with the local topography favoured the behaviour and evolution of the fires. In this study, the findings show the benefits of the use of cloud-resolving models over large domains to assess the fire danger conditions and helped us to better understand the atmospheric dynamic influencing the development of wildfires. Furthermore, the results may help define firefighting strategies in specific areas, namely in Southern Portugal. This study was funded by national funds through FCT-Foundation for Science and Technology, I.P. under the PyroC.pt project (Ref. PCIF/MPG/0175/2019).
Co-produced storyline approaches for adaptive climate management and the role of discourse analysis.
Authors: Versteeg Gerrit Bertus
Published: July 2023

Recent European Commission-funded projects Destination Earth and EERIE aim to provide state-of-the-art climate change projections with a strong emphasis on increasing spatial resolution and user interactivity, which is possible due to the significant advancements in high-performance computing. However, rather than just focusing on improvements in climate outputs following traditional modelling exercises, these projects also aim to communicate the potential consequences of climate change in a way that is relevant for particular regional and local decision-makers. In this regard, both projects will apply alternative approaches to represent uncertainty in the future climate, so-called physical climate storylines (PCS). Defined in Shepherd & Lloyd (2021) as ‘physically self-consistent unfoldings of past events, or of plausible future events or pathways’, PCS have many overlaps with the methodology behind surrogate climate change and the likelihood estimations of the IPCC’s extreme weather and climate events. This complementary approach to conventional risk assessment can be applied to simulate historic extreme events in a warmer climate to identify adaptation options (Destination Earth) and tipping points with associated consequences for the global and regional climate (EERIE).
The study aims to find usability gaps in the PCS approaches of Destination Earth and EERIE. Social science can play an important role in filling the gaps by analyzing the user’s discourse on scientific uncertainty and its implications for decision-making. Given that the PCS approach is advantageous on smaller scales with high uncertainty about future changes in climate variability, it should be receptive to an environment accentuated by value judgements and where perspectives, evidence, risk preferences and errors are continuously redefined. Discourse-analytical approaches can help uncover these aspects. Moreover, for adaptive decision-making using a bottom-up approach, climate change is just another factor to consider among a wide range of potentially competing issues and demands. Becoming part of an extensive risk assessment which includes many non-climatic components, implies that PCS should be tailored to the user’s socioeconomic setting, which explains system vulnerabilities, resilience and coping capacities towards the future climate based on conditional statements. Transparent and rigorous insights into creating and managing co-produced climate information are critical for PCS’s objective to fit the local decision context. Therefore, a storyline should include climate analysis anchored in physical knowledge, which can be translated into robust and actionable climate adaptation output. The two European projects will be evaluated on their uptake of PCS as a tool to guide adaptive decision-making. Especially an effort will be made to discover the advantages and limitations of applying PCS of future climates in a co-developmental way.
Development and evaluation of an "optimal" perturbed parameter approach to represent model error in the convective-scale AROME-EPS
Authors: Wimmer Meryl , Berre Loik , Descamps Laurent , Raynaud Laure , Seity Yann
Published: July 2023

AROME-EPS is the regional ensemble prediction system, operational at Météo-France, consisting of 12 perturbed non-hydrostatic forecasts with a 2.5km horizontal resolution. Model errors are currently represented with the Stochastic Perturbed Parametrization Tendency (SPPT) scheme. However, this method presents some disadvantages such as a difficult physical interpretation of its results. In order to overcome this drawback, a more physically-based approach of model error representation is considered, based on the perturbation of parameters from physical parametrization schemes. A two-step procedure is adopted to implement such a technique: a sensitivity analysis of the AROME model to some parameters is first performed, then an optimisation of perturbed parameters values is determined.
Following advice of parametrization experts, 21 parameters from 6 different physical and dynamical parametrizations, with uncertain values, have been selected. Sensitivity analyses, conducted on different seasons and using the Morris screening as well as Sobol' sensitivity indices, have led to reduce this list to a subset of eight parameters with a high influence on different weather-related variables forecasts. 
Several perturbed parameters techniques have then been set up and evaluated over long periods. They largely improve AROME-EPS performances for most near-surface variables including wind speed and accumulated precipitation. Different optimizations improving the statistical CRPS score have also been tested. Thus, a set of parameter values has been identified for each AROME-EPS member. This optimal perturbation parameter method is shown to significantly outperform the current SPPT scheme for several near-surface variables, with improvements of probabilistic scores up to 10%. Furthermore, restricting the perturbation to the eight most influential parameters has shown similar results as the version perturbing the full set of 21 parameters, suggesting a possible cheaper setting of weather prediction models.
How might the occurrence frequency and intensity of extreme rainfall events in Ireland change in projected future climates?
Authors: O'Brien Enda , Wang Jingyu
Published: July 2023

Observed data of extreme rainfall occurrence in Ireland are available from approx. 30 stations over periods ranging from about 30 to 70 years.  They are provided as tables of occurrence dates and magnitudes of 9 different metrics, from “r4in15” (4 mm in 15 minutes) to “r30in24h” (30 mm in 24 hours).  These events are too few and too sparse to be treated with non-parametric statistics.  However, they are all “peak over threshold” (POT) events, and so the well-developed theories of POT statistics applies to them.  In particular, the number of such events in any given time period follow a Poisson distribution (which needs only one parameter, the mean), while the exceedances (i.e., magnitudes above threshold) follow a generalized Pareto distribution (which formally needs 3 parameters, but in practise only 2 need to be determined). 
As climate is projected to change in the future, our basic assumption is that the number of POT events (Poisson distribution) will change, while the exceedances (Pareto distributions) will remain the same, only represented by different numbers of samples.  Since the Poisson distribution is determined by just one parameter (the mean), the only quantity needed to fully characterize the nature of future intense rainfall events are projections of the mean of such events. 
Meanwhile, future climate projections (e.g., from CORDEX) are typically available on daily timescales, so the problem reduces to finding a robust relationship, whether physical  (based e.g., on a Clausius-Clapeyron scaling) or statistical (based, e.g., on the tails of frequency distributions)  between each of the 9 intense rainfall metrics and the daily values of standard surface variables under future climate projections.  Different options are explored, and results are shown based on future projections from the TRANSLATE project, as functions of different future emission scenarios. Typically, large increases in the frequency of all 9 metrics are projected regardless of the exact relationship assumed between the intense rainfall events and the frequency distributions of daily precipitation (or temperature).  Results are best shown as frequency distributions rather than single number percentage changes.
 
Benefits of increasing the reforecast ensemble size of the Météo-France seasonal prediction system
Authors: Li Shan , Specq Damien , Batté Lauriane , Viel Christian
Published: July 2023

The current Météo-France seasonal prediction system (MF System 8) has 25 members for hindcast from 1993 to 2016 and 51 members for real-time forecast. In order to investigate the benefits of increasing the ensemble size within our Copernicus Climate Change Services (C3S) seasonal prediction contract, we extended the system 8 hindcast to 51 members for the four main start dates (February, May, August, November). We compare the forecast skill between the official 25-member hindcast and the 51-member extended hindcast.
We focus on the European region at the lead-time 1 for the next trimester. To describe the performance of forecasts, we use correlation and relative operating characteristic (ROC) on the mean 2-meter temperature (T2M) and the mean precipitation (RR) averaged over Europe. Similarly, we also evaluate the forecast of modes of variability (East Atlantic, North Atlantic Oscillation, and Scandinavian Blocking) which impact the European climate.
The scores with 51 members are similar and not necessarily better than with 25 members. Moreover, we use 1000 random draws of 25 members out of 51 to determine the uncertainty of the official forecast scores. These scores can be at the edge of the confidence interval, while the 51-member scores are close to the median of the 1000 random draws. We did the same analysis for different regions that there is less uncertainty on the scores in the Tropics (e.g. Northeast Brazil) than in the mid-latitudes (e.g. Europe). These results suggest that it is not necessary to increase the ensemble size for verification of the seasonal forecasts beyond the available 25 members.
Modelling Gross Primary Production of a Mediterranean grassland using Sentinel-2 vegetation indices and meteorological field information
Authors: Cicuéndez Victor , Yagüe Carlos , Inclán Rosa , Sánchez-Cañete Enrique P. , Román-Cascón Carlos , Sáenz César
Published: July 2023

Mediterranean grasslands provide different ecosystem, social and economic services to the Mediterranean basin. Their dynamics are conditioned by the influence of the Mediterranean climate, which results in large inter-annual variability. Gross Primary Production (GPP) represents the carbon (C) uptake of ecosystems through photosynthesis, being the largest flux of the global C balance. Hence, GPP estimations are necessary to assess the dynamics of the global C cycle and to plan a sustainable management of these ecosystems. The study of grasslands GPP must be approached from a dynamic point of view, that is, temporal evolution at different spatial scales.
High frequency satellite data, such as Sentinel-2, have open the door to study ecosystems with a high spatial (10, 20 and 60 m) and temporal resolution (5 days). Although extensive research exists about estimating GPP in grasslands with moderate resolution sensors, such as MODIS, the estimation of GPP in this ecosystem type using Sentinel-2 images is relatively new, especially in Mediterranean sites. The GPP derived from remote sensing data must be evaluated at field scales using eddy covariance (EC) measurements from flux towers. Time series analysis (TSA) represents an excellent tool to analyze high temporal resolution data, such as EC and remote sensing data. Although TSA has been widely used in economics, it is not commonly used for the analysis of environmental variables, such as GPP.
The overall objective of this research is to estimate a GPP model for a Mediterranean grassland in central Spain close to a forest influenced by the Guadarrama mountains (El Escorial, Madrid). This is done using Sentinel-2 vegetation indices and meteorological field information obtained from a GuMNet micrometeorological station where all the surface energy balance (SEB) components (and other meteorological and soil variables) are available for several years. The specific objectives are: (1) To compare different vegetation indices to estimate GPP through the ecosystem light-use efficiency model; (2) To estimate the influence of different meteorological variables on the model; (3) To validate the remote sensing model with the measurements from an EC flux tower (GuMNet-Herrería) in terms of quantity and dynamics through time series analysis.
Some preliminary results indicate how the GPP depends strongly on the vegetation indices and on meteorological and soil variables, being the soil water content a relevant one. This approach allows to model GPP based on the information from this analysis.
Using artificial neural-network-based model to better evaluate surface turbulent heat fluxes in weather and climate numerical models
Authors: Zouzoua Maurin , Bastin Sophie , Chiriaco Marjolaine , Lohou Fabienne , Lothon Marie , Jomé Mathilde
Published: July 2023

This work, within the framework of the French ANR project MOSAI (Model and Observation for Surface-Atmosphere Interactions), aims at proposing a novel evaluation approach to better identify the shortcomings in the numerical formulation of surface sensible and latent heat fluxes. Indeed, the common time-to-time comparison between simulated and observed fluxes blends many sources of errors such as incoherent grid-scale representation (e.g. land surface types) and inaccurate environmental forcing (radiation, temperature, humidity and wind). The main objective is to freeze the external sources of errors by using the capabilities of machine-learning models. A supervised statistic model is constructed and optimized by applying the ensemble learning approach to sub-hourly observational data collected at three multi-instrumented sites of the ACTRIS-FR research network (one per site). It consists of several multi-layer perceptrons trained under k-fold cross-validation to estimate the surface turbulent heat fluxes based on relevant environmental variables. As a result, using the modelled weather conditions as input, the statistic model gives fluxes that would have been observed. The comparison of the simulated fluxes with this new baseline would allow us to better identify the weaknesses of the surface parametrization scheme.
A demonstration study will be presented with data gathered at the Météopole supersite (Toulouse, France), from its implementation in mid-June 2012 to December 2021, about 9 years of continuous weather monitoring. Details on the statistic model construction and scores obtained will be given. Subsequently, the statistic model is applied to data from climate simulations over the period 2012-2016 with the RegIPSL model. A discussion on the results of comparisons will be provided.
On the Easterlies/Westerlies wind clash in the Tropical Atlantic and the Atlantic Niño initiation
Authors: Borzelli GIanluca , Carniel Sandro , Russo Aniello , Carniel Cosimo Enrico
Published: July 2023

The Atlantic Equatorial Mode or Atlantic Niño is an important mode of year-to-year variability of the Atlantic Ocean, characterized by an anomaly in the Sea Surface Temperature (SST), having a close similarity with the El Niño-Southern Oscillation (and hence called the “El Niño-Little-Brother”).
This climatic oscillation induced by the ocean-atmosphere coupling is characterized by a SST anomaly centered on the equator between 0° and 30°W, recurring every 3-7 years and peaking in the boreal summer (i.e. between June and August).
The resulting coupled atmosphere-ocean interaction severely influences the African climate by affecting rainfall in the semi-arid Sahel and increasing rainfall in regions along the Gulf of Guinea. These changes determine variations in crop yields, floodings, modified river discharge at sea, leading to increased poverty, sustaining social disorders, enhancing the probability of local conflicts and terrorism. As pointed out in several NATO meetings and reports, improving the climate predictability in this area is considered a relevant theme from the security and stability perspective.
The climatology of the tropical Atlantic region is characterized by the equilibrium between the zonal wind pattern and heat content in the water column, which depends on the depth of the associated thermocline. Trade winds tend to accumulate warm waters in the west, hence causing the thermocline to develop a large zonal slope. This effect charges the western part of the basin, which is then discharged through eastward traveling internal waves, trapped along the equatorial wave-guide.
By using Absolute Dynamic Topography data provided by orbiting altimeters, here we suggest that the wind convergence zone between westerly wind episodes and the nearly stationary trade winds can excite internal downwelling Kelvin (KW) and Rossby (RW) waves. We show that the normalized Sea Surface Temperature Anomaly (SSTA) variability, averaged over the region [5°S - 5°N; 0° - 30°W], is closely related to the amplitude of the KW averaged over the same region, indicating that changes in the SSTA in the Eastern Atlantic are primarily due to KW, with RW paying a minor role.  
Preliminary results suggest the evidence that the Atlantic Niño dynamic can be explained in terms of KW triggered by the confluence between Easterly and Westerly winds.
Are heatwaves and drought more likely to occur simultaneously with warming?
Authors: Wibig Joanna , Jędruszkiewicz Joanna
Published: July 2023

Heat waves and droughts are two the most frequent weather extremes in Poland, both excerbated by the ongoing global warming. Very often they occur simulateously. The aim of this presentation is identification of cases of simultaneous occurence of these extreme situations, examination of their spatial extent, frequency of occurrence and long-term variability. Reasons of their occurrence are also analysed. On the basis of data from the period 1966-2020 from about 40 stations in Poland reference evaporation indices will be estimated based on Palmer-Monteith formula and together with precipitation records used to the water balance determination. The results obtained so far indicate on strong increasing trend of evapotranspiration and only very small, statistically insignificant, increase of precipitation. This causes a decrease of the water balance, defined as a difference between precipitation and evaporation. In Poland the water balance is positive in the cool part of the year and negative in the growing season. This causes that a water deficit  in the growing season will be more and more stressful, especially since the injection of water from the snow cover before the growing season also significantly decreases. Heat waves will be  distinguished basing on maximum daily air temperature. Their number, duration and intensity also have increased considerably from the middle of the twentieth century. The standardized precipitation-evaporation index (SPEI) by  Vicente-Serrano and snow cover data from the winter preceding the drought will be used to find out reasons of simultaneous appearance of heat waves and drought. Among others factors will be considered: the North Atlantic Oscillation, the Arctic Oscillation, Arctic sea ice cover. The research is supported from the Polish National Science Centre (grant 2019/33/B/ST10/01136)
Mesoscale Horizontal Kinetic Energy Spectra of a Tropical Cyclone
Authors: Wang Yuan , Zhang Lifeng
Published: July 2023

A high-resolution cloud-permitting simulation with the Weather Research and Forecasting (WRF) Model is performed to investigate the mesoscale horizontal kinetic energy (HKE) spectra of a tropical cyclone (TC). During the slow intensification period of the TC, the spectrum visibly grows over the central mesoscale in the troposphere and the large end of the mesoscale in the lower stratosphere. The spectral growth then saturates at larger scales and extends to smaller scales during the rapid intensification period. Finally, the spectra reach saturation and stability in the mature period, and the spectrum displays an arc-like shape in the troposphere and a quasi-linear shape in the lower stratosphere for wavelengths below 500 km, while they both develop a quasi –5/3 slope. The total HKE spectrum is dominated by its rotational component in the troposphere but by its divergent component in the lower stratosphere.
Further spectral HKE budget diagnosis reveals a generally downscale cascade of HKE, although a local upscale cascade gradually forms in the lower stratosphere. However, the mesoscale energy spectrum is not only governed by the energy cascade, but is evidently inﬂuenced also by other physical processes, among which the buoyancy effect converts available potential energy (APE) to HKE in the mid- and upper troposphere and converts HKE to APE in the lower stratosphere, the vertically propagating inertia–gravity waves transport the HKE from the upper troposphere to lower and higher layers, and the vertical transportation of convection always transports HKE upward. Note that the vertical transportation processes appear to have the ability to modify the intensity and direction of energy cascade.
Although the relative importance of conditional instability of the second kind (CISK) and wind-induced surface heat exchange (WISHE) mechanism cannot be evaluated directly through the spectral HKE budget diagnosis, some insight can still be achieved. By comparing the energy growth process of different convective systems, it can be found that a mei-yu front system which is strongly governed by the CISK mechanism possesses abundant energy at the convection scale from the beginning of its development, and evident growth and uplift of the tropospheric HKE spectra in the mei-yu front initiate from this scale and subsequently extend up to larger scales, whereas the opposite occurs in our TC. The unique energetics features of the TC indicate that the function of convection differs between the TC and mei-yu front system. Accordingly, the present results potentially do more favor the WISHE mechanism.
The RMI Road Weather Forecasting System
Authors: Van den Bergh Joris , Dehenauw David , Watelet Sylvain , Schmitz Joffrey , Tijm Sander , Termonia Piet
Published: July 2023

Slippery road and highway conditions can cause accidents if necessary maintenance actions are not undertaken. These include the clearing of snow and prevention of ice by salting. Belgium is characterised by a “marginal” winter environment, where the air temperature commonly fluctuates around the freezing point. A few snow events usually occur during winter, while days with frost occur more often. For these types of conditions, great potential in cost savings for winter maintenance lies in the accurate prediction of ice formation. To aid decision making, road weather information systems have long been used. These consist of road weather stations (RWS) that gather meteorological and road observations, combined with models that forecast the road condition and tools to communicate the relevant information to end users for decision support. For forecasting purposes, the use of dedicated road weather models (RWM’s) has become popular approach. At the Royal Meteorological Institute of Belgium (RMI), a road weather forecasting system was developed in collaboration with the Royal Netherlands Meteorological Institute (KNMI). The KNMI RWM is a physical model, which was previously validated and compared with the Finnish RoadSurf model over the Netherlands. This model was taken as the basis to develop a RWM for Belgian highways in 2018, leading to the deployment of the RMI “GMS” system (“Gladheidmeetsysteem” in Dutch). This system has been operational since the winter of 2018-2019, and is being further improved in close collaboration with the regional road maintenance authorities Belgium. GMS forecasts are updated every hour and communicated to users through a GIS-based interface. Users can consult forecasts of road surface temperature (RST), road surface condition and various other meteorological variables for all RWS locations (about 140), in addition to RWS observations. Other map layers include overlays of weather radar images for precipitation and satellite images for cloud cover. Finally, users can consult a static thermal map and webcam images for highways in Flanders, and geolocated weather reports generated by citizens through the RMI weather app for the whole country. The physical RWM has been tuned for Belgian highways, and adapted to make use of various available numerical weather prediction (NWP) models as input. Road surface condition information from RWS is also used for better initialization. Since the winter of 2022-2023, the model is also run with a mini-ensemble input of four NWP models. This information is currently used to present an uncertainty interval around the RST forecasts, but more applications are foreseen. We present the operational system, GIS-interface and preliminary validation results of the ensemble road forecasts for the past winter. We also comment on specific use cases and present avenues for future improvements to the GMS system.
Extreme precipitation in Toruń (Poland), 1871-202
Authors: Pospieszyńska Aleksandra , Przybylak Rajmund
Published: July 2023

Extreme precipitation in Toruń was analysed for the period 1871–2020. The precipitation series was collected from data of the Prussian, German and Polish networks (Archives of the Institute of Meteorology and Water Management National Research Institute). Possible deficiencies in the monthly average data were supplemented by the method of constancy of quotients (precipitation) based on data from the station in Bydgoszcz. The correlation of data from Bydgoszcz and Toruń reaches 0.99 and is statistically significant. The precipitation series was then homogenised using AnClim software. Minimum and maximum absolute values were determined for all analysed parameters. Anomalies of averages and monthly, seasonal and annual sums were determined with respect to the reference period 1871–2020. Based on the percentage criterion, months, seasons and years were determined to be extremely dry (<50% of the average sum for the month/season/year, respectively), extremely wet as >150%, and average a 90–110%.
In the period 1871–2020, the average annual precipitation in Toruń amounted to 518.2 mm. In the course of the year, the precipitation totals were highest in July (78.2 mm) and lowest in February (25.1 mm). The variability of rainfall from year to year is clear and significant in selected subperiods, but precipitation in Toruń does not indicate a clear and statistically significant trend. This phenomenon is typical for precipitation in Poland. The occurrence of an extremely dry or wet year is determined primarily by the precipitation of the summer season, which on average accounts for about 40% of annual precipitation. In the case of seasons from 2010 onwards, wetter winters are observed. In the case of other seasons, wetter and drier periods can be indicated, but without a clear long-term trend. Using the percentage criterion, extremely warm, dry periods were identified at the end of the 1930s, in the late 1940s to early 1950s, and in the late 1980s to early 1990s. The beginning of the 1940s can be described as extremely cold and humid, as can the late 1970s to early 1980s.
The research was funded by the National Science Centre, Poland; Project No. 2020/37/B/ST10/00710.
Long time radar data series processing using OPERA ODIM
Authors: Méri Ladislav , Jurašek Marián , Okon Ľuboslav , Kaňák Ján
Published: July 2023

We present the results of a feasibility study on the possibility of using the OPERA data information model (ODIM) with HDF5 file format implementation [Michelson et. al. 2021] for reprocessing long-term weather radar data series in the context of a small national meteorological service such as the Slovak Hydrometeorological Institute (SHMU). 
ODIM was developed during the Operational Programme on the Exchange of Weather Radar Information (OPERA) under the umbrella of the European Meteorological Services Network, EIG EUMETNET [Saltikoff et al. 2019] to support the exchange of volume radar data between meteorological services and different radar systems.
Work was performed in 3 consequent steps:
1. Radar archive consolidation
SHMU has been working with radar data since 1965 [Podhorský & Guba 2014], but the level of equipment available didn't allow us to digitally archive such a large amount of data. We were able to extract archived radar from 1998 to the present. Data from earlier periods were archived on analogue media (e.g. paper drawings, photographs) or on special tapes that we cannot read today. More than 50 old data tapes and more than 500 CDs and DVDs have been extracted. The most recent period was stored in the robotic tape library. We will discuss all the problems we encountered during this step.
2. Conversion to ODIM hdf5 files
From the archive we extracted data from 4 different radar systems: MRL-5, EEC DWSR92C, Radtec RDR-250GCDP with Gamic signal processor and Selex Meteor 735 CDP. 5 different converters were prepared. The most interesting was the converter for MRL-5 data. It only stores raw data, radar equation has to be applied, noise figure subtracted. The scan was not clearly defined, volumes store all data from start of measurement to end, sampled in any position of the antenna, and we got uncorrected reflectivity for S- and X-band channel, because MRL-5 was classic non-Doppler radar and clutter has to be filtered in processing.
3. Processing
For processing, we used "home-made" qRad software running on hpc. It is capable of generating any standard product and making a common composite based on 11+ different quality indices. The clutter map was calculated from the previous 2-3 week period. We had to solve problems with temporal and spatial variability of the input data. The scan repetition time had values of 30, 15, 7.5, 10 and 5 min time. The number of radars varied between 0 and 4. We decided to use only those dates when at least 2 radars were available and covered the whole of Slovakia. As a reference product, the composite of CAPPI 3km was chosen, which provides uniform data for all radars over whole Slovakia. Maps of various statistical variables were calculated from CAPPI 3km composites.
Cluster Analysis of Precipitation Records from the Basque Coast
Authors: Barturen Mónica , Maruri Maria de las Mercedes , Orúe Judith
Published: July 2023

The approach of meteorology to students of the degree in Nautical and MaritimecTransport is done at a theoretical level within the subject of Meteorology in the third year, but the awareness and importance of ocean-meteorology in navigation is acquired when the student embarks or carries out his practices in the coastal maritime field. But in general, all maritime-coastal activities require day-to-day ocean-meteorological information for planning, manoeuvres in ports or voyages.The present work focuses on the study of visibility and precipitation and the relationship between them, using coastal observation systems as input data. This work is carried out under an educational cooperation contract between the "University of the Basque Country" and the TECNALIA research centre. The work starts with the exploitation of the raw database from 2 coastal disdrometers and the main objective is to validate the visibility records of the disdrometer with the historical information from the airports.The results obtained from the comparison and analysis of the raw disdrometer data shed light on the disdrometer compartment and leave many avenues open for future work on the coast. This master’s thesis addresses some of these avenues. Given that the minute resolution is difficult to handle in real time, we propose the design of a product that adapts to the needs of the users, using the most raw and valuable information from the disdrometer. Under this premise, the objective is to investigate, through the spatial minute distribution, the different patterns/episodes recorded over two meteorological years.Therefore, the methodology is based on the use of cluster analysis techniques that allow the classification or grouping of records. The resulting groups will be analysed as episodes that aim to efficiently provide the user with an ocean-meteorological pattern in the area, and thus improve safety in navigation and coastal activities in the future.
The Contribution of Urbanization to the Current Temperature Trend in Türkiye
Authors: Türkmen Davut  Enes , Önol Barış
Published: July 2023

The expansion of urban areas significantly modulates the local climate in cities. In this regard, in the last few decades, there has been a non-negligible increase in the urban areas and the urban population of Türkiye. This study aims to assess the impact of increasing urbanization on the current warming trend which is highly dominated by human-induced climate change. The findings of this study are substantial for sustainable urban planning and future climate studies using temperature observation data. The urban-minus-rural (UMR) method, which has been widely used in urban heat island (UHI) studies, is applied to determine the effect of urbanization on temperature change. In the UMR method, in order to detect the urbanization effect more precisely, the meteorological stations should be properly classified into urban stations and rural stations that have been used as reference stations. In previous studies conducted in Türkiye to determine the impact of urbanization on the warming trend, station classification was done with population data. However, population information does not provide direct information about the extent of urban areas around the stations. Thus, the CORINE (Coordination of Information on the Environment) dataset from 1990 to 2018 was used to directly determine land cover information around the stations. Compared to average temperatures and maximum temperatures, minimum temperatures are more sensitive to the urban heat island effect. Therefore, the daily minimum temperature data of the stations in Türkiye between 1980 and 2022 was used as temperature data. The determination of the change in urban areas around the station was done by placing circular buffers on each station. The correlation coefficient between the change in the urban area within the buffer placed over the stations and the temperature trend of the stations was examined with increasing buffer radii. The radius where the urbanization effect is most pronounced was determined to be 8 km. As a result, statistically significant trends were detected in urban stations in the specified period interval; also, these stations showed a large urbanization effect and urbanization contribution, reaching 0.57°C per decade and 85%, respectively.
Projections of wind energy potential in Portugal assessed with CMIP6 simulations
Authors: Claro André , A. Santos João , Andrade Cristina , Carvalho David
Published: July 2023

Wind energy fluxes over Portugal and the nearby Atlantic Ocean were estimated under an IPCC future socioeconomic scenario (IPCC SSP5-8.5) for the 2046–2065 and 2081–2100 periods, using wind speed data from WRF 6 km regional simulations. CMIP6 (Coupled Model Intercomparison Project) global model ensemble simulations were also used to assess future anomalies in the Euro-Atlantic large-scale circulation, through kinetic energy and sea level pressure data. Projections show a winter southward displacement of the mid-latitude jetstream, along with a northward displacement during spring, summer, and autumn, which leads to a summer strengthening of the northern winds along the northwestern Iberian coast. Moreover, offshore the northwest coast of Portugal and in the Serra da Estrela mountain range, a 25% to 50% increase in the summer wind power density (WPD) should occur in 2046–2065, and up to more than 100% in 2081–2100. This is also seen in the CMIP6 global projections. In 2046–2065, the WPD’s daily variability and extreme values should increase offshore northwestern Portugal during winter, spring and summer. During autumn, extreme WPD event intensity should decrease. Furthermore, the WPD’s inter-annual variability should increase offshore the northwest coast, and decrease along the central western and southern coasts.
 
Acknowledgments:
This work was co-funded by FEDER (European Fund for Regional Development), under the project ATLANTIDA – Platform for the monitoring of the North Atlantic Ocean and tools for the sustainable exploitation of the marine resources (NORTE-01-0145-FEDER-000040). This work was also funded by National Funds by FCT - Portuguese Foundation for Science and Technology, under the project UIDB/04033/2020.
How to use the fractions skill score for ensemble forecast verification
Authors: Necker Tobias , Wolfgruber Ludwig , Serafin Stefano , Dorninger Manfred , Weissmann Martin
Published: July 2023

This study evaluates and demonstrates how to apply the Fractions Skill Score (FSS) for probabilistic forecast verification. The FSS is a spatial verification score originally designed for deterministic forecast verification. It is a neighborhood method frequently used to verify intermittent forecast fields, such as precipitation, that suffer from double penalty errors. Although the FSS was not designed for probabilistic verification, it is frequently used for verifying ensemble forecasts. However, as we show, systematic differences can occur depending on how an ensemble-based FSS is computed. 
Our study compares and evaluates four potential approaches for computing an FSS for ensemble forecasts. We study the dependence of these four approaches on different parameters, such as ensemble size, neighborhood size, or the forecast event frequency of occurrence. The dependence on ensemble size is examined using various subsamples of a large ensemble. Our comparison shows that the behavior of the FSS with ensemble size can vary greatly depending on the approach used to compute the score. Our experiments explore unique convective-scale 1000-member ensemble forecasts and precipitation over Germany for a high-impact summer weather period. For verification, we use random independent members as synthetic observation to minimize the effect of systematic errors, such as biases between the model and observation. In addition, we introduce a probabilistic believable scale and study its dependence on ensemble size. This evaluation highlights that a suitable ensemble size depends on the forecast event frequency. Our study can guide researchers who want to apply an FSS for ensemble forecast verification, as our findings provide insights on how to compute and interpret ensemble-based FSS results correctly.
Contribution of Mediterranean Cyclones to the snowfall accumulation over Romania
Authors: Amihăesei Vlad-Alexandru , Raveh-Rubin Shira , Sfîcă Lucian , Cheval Sorin , Dumitrescu Alexandru
Published: July 2023

Snowfall is an important component of the winter climate in Romania, influencing various economic sectors such as transportation, agriculture, and tourism. Previous studies have identified several synoptic patterns that can bring snow in south-eastern Europe, including Mediterranean Cyclones (MCs). However, the contribution of these cyclones to snowfall in Romania has not been thoroughly investigated.
This study aims to quantify the contribution of MCs to snowfall in Romania. Daily snowfall data from ERA5-LAND covering the period 1981-2020 were analyzed, along with the corresponding atmospheric circulation patterns. The MCs trajectory is based on the “best tracks” produced by the 3T initiative of the COST Action, comprising tracks for the 1979-2020 period. This method is based on 10 different cyclone tracks, using an hourly ERA-5 reanalysis data set, at a 0.25 spatial resolution. These 10 tracking methods are combined to obtain a composite track.
The results indicate that, on average, more than 60% of total snowfall in eastern and southern Romania is due to MCs manifestation. Moreover, in some particular years, in most parts of southern Romania, 90% of snow events are due to the Mediterranean cyclones. In the northern and western parts of Romania, the fraction of snowfall due to the MCs is less than 20%. This can be explained by the fact that here the westerly atmospheric circulation can heavily contribute to the total snowfall amount.  The snowfall amount related to the MC varies between 40 and 290 mm. The lowest values are within the plain areas from the west, south, and east of Romania, instead, the highest values are within the mountains, varying between 40 and 290 mm.
The findings suggest that Mediterranean cyclones are an important factor in the climate of Romania, and their contribution to snowfall should be taken into account in forecasting and planning socio-economic activities.
Acknowledgment 
This work was co-funded by the European Social Fund, through Operational Programme Human Capital 2014-2020, project number POCU/993/6/13/153322, project title "Educational and training support for PhD students and young researchers in preparation for insertion into the labor market".
Vilhelm: A Novel AI-based Global Weather Forecasting System for the Prediction of Atmospheric Hazards
Authors: Gabler Marvin Vincent , Wuillaud Jair , Taheri Shahraiyni Hamid , Neupert Daniela , Grigoryev Alexey , Almeida Rodrigo , Galimzhanov Azamat , Hernandez Gabriel Martin , Daubinet Jordan Dane , Ekhtiari Nikoo , Song Roan John , Dudbridge Peter , Tarakci Emrecan
Published: July 2023

Cyclones are known as one of the biggest hazards to life and property. They can lead to a number of different hazards such as storm surges, floods, very high wind speeds, tornadoes and lighting. The combination of these hazards greatly increases the potential for loss of life and damage of properties. California experienced a devastating and deadly "bomb cyclone" on March 21st (2023), causing widespread destruction and claiming at least five lives. Many people remained without electricity until Thursday morning (March 23rd). Whereas it is hard for models to predict the formation and trajectory of bomb cyclones, Jua’s model, Vilhelm, predicted the formation of the cyclone about 40 hours before it hits California. In addition, it was offering a high level of accuracy in predicting the storm's trajectory 24 hours in advance. Furthermore, Vilhelm's predictions regarding the start of cyclone's dissipation on 22nd March proved to be accurate.
During our analysis on the cyclone, we selected wind speed and pressure as suitable indicators to forecast the formation and trajectory of the cyclone. At 00:00 on March 20th, Vilhelm forecast wind speeds at the 850 hPa and 1000 hPa pressure levels that correctly identified the formation, extension and movement of the cyclone that would hit California on March 21st. In addition, the mean sea level pressure forecasts of the Vilhelm model on 20th March (00:00) approved these findings at the atmospheric layers and therefore the physical consistency of the AI based system. 
Given that the Vilhelm model offered an accurate forecast for the formation, extension, dissipation and crucially, the trajectory of the cyclone, there is a strong potential for it to be used as a global “Atmospheric Hazards Warning System”.