bluuebunny/crossref_metadata_2025 huggingface dataset:
Drought monitoring in Croatia using the Standardized Precipitation-Evapotranspiration Index
Authors: Loncar-Petrinjak Ivan , Pasaric Zoran , Cindric Kalin Ksenija
Published: July 2023

Several droughts during the last decade seriously affected large parts of Europe, including Croatia, causing significant economic losses, particularly in the agriculture and energy sectors. Though rainfall is the main driver of drought, high temperatures during summer months may intensify its development with devastating consequences. Such was the case in 2022 when long dry spells were accompanied by several heat waves. In this study, climatological drought monitoring with the Standardized Precipitation-Evapotranspiration index (SPEI) was analysed with the primary aim of finding the best theoretical distribution for fitting the water balance in Croatia before implementing the index in the official operational procedure for drought monitoring. Monthly precipitation amounts and air temperature values were employed at 31 main meteorological stations for the period 1961-2022 and the water balance (defined as a difference between precipitation and potential evapotranspiration) was calculated for different time scales (1 - 24 months). Among five selected distributions, a three-parameter generalized logistic (GLO) distribution was found as the most appropriate one. There is a general agreement between SPEI and SPI time series, both in sign and intensity of droughts. However, a tendency toward higher drought intensity prevailed with the SPEI, particularly in periods with a light to moderate lack of precipitation and high air temperature. Comparison in precipitation and water balance in the two reference climate periods (1961-1990 and 1991-2020) revealed: a consistent trend toward drying conditions from March to August; an increase in the frequency of dry spells; and a tendency toward longer dry spells (for time scales up to 9 months). A comparative analysis of the 2022 drought in Croatia confirmed the ability of SPEI to detect drought earlier than the SPI, also suggesting that a larger area of the country was affected by drought due to high-temperature anomalies.
Relationships between heat waves and soil drought in the Czech Republic
Authors: Zahradníček Pavel , Brázdil Rudolf , Řehoř Jan , Dolák Lukáš , Trnka Miroslav
Published: July 2023

Heat waves represent meteorological phenomena with serious impacts on human society and environment. Coincidence of their increased occurrence and intensity with increased frequency and severity of the summer drought episodes in the Czech Republic, particularly in the last decade of the 2010s and early 2020s calls for the study of their long-term spatiotemporal variability and compound effects. As an example serve the year 2015, when the Czech Republic experienced a record number of hot days and during July and August the soil moisture was very low. Our analysis of these effects and relationships is based on homogenised data of climatological stations of the Czech Hydrometeorological Institute and on soil moisture outputs coming from calculations of the SoilClim water-balance model for the 1961–2022 period. Different methods of statistical analysis are used to find changes in long-term fluctuations, trends, severity and spatial features of heat waves and soil droughts over the territory of the Czech Republic. Anticyclonic, cyclonic and directional circulation types derived from objective classification taken in account flow strength, flow direction and vorticity are used to investigate possible drivers of related changes in both heat waves and soil droughts and their spatiotemporal relationships. It is also tested whether a stronger relationship exists between soil moisture and heat waves represented by at least three consecutive days with a maximum temperature above 30°C or defined by a certain percentile threshold (e.g., 90 or 95%). Results obtained are discussed with respect to their impacts on the occurrence of wildfires and numbers of related fatalities and injures in the Czech Republic as well as in the context of a broader European scale.
The EUPPBench postprocessing benchmark dataset
Authors: Demaeyer Jonathan , Bhend Jonas , Lerch Sebastian , Primo Cristina , Van Schaeybroeck Bert , Atencia Aitor , Ben Bouallègue Zied , Chen Jieyu , Dabernig Markus , Evans Gavin , Faganeli Pucer Jana , Hooper Ben , Horat Nina , Jobst David , Merše Janko , Mlakar Peter , Möller Annette , Mestre Olivier , Taillardat Maxime , Vannitsem Stéphane
Published: July 2023

Statistical postprocessing of forecasts produced by numerical weather prediction systems is an important part of modern weather forecasting systems. Since the beginning of modern data science, numerous postprocessing methods have been proposed, and one of the questions that frequently arises is the relative performance of the methods for a given specific task. However, a comprehensive, community-driven comparison of their relative performance is yet to be established. One of the main reasons for this lack is the difficulty of constructing a common comprehensive dataset that can be used to perform such intercomparison. Here we introduce the first version of the EUPPBench, a dataset of time-aligned medium-range forecasts and observations over Central Europe, with the aim to facilitate and standardize the intercomparison of postprocessing methods. This dataset is publicly available [1], includes station and gridded data based on the ECMWF model forecasts [2]. The initial dataset is the basis of an ongoing project to establish a benchmarking platform for postprocessing of medium-range weather forecasts. We showcase a first benchmark of several methods for the adjustment of near-surface temperature forecasts and outline the future plans for the benchmark project activities. [1] https://github.com/EUPP-benchmark/climetlab-eumetnet-postprocessing-benchmark
[2] Demaeyer, J., Bhend, J., Lerch, S., Primo, C., Van Schaeybroeck, B., Atencia, A., Ben Bouallègue, Z., Chen, J., Dabernig, M., Evans, G., Faganeli Pucer, J., Hooper, B., Horat, N., Jobst, D., Merše, J., Mlakar, P., Möller, A., Mestre, O., Taillardat, M., and Vannitsem, S.: The EUPPBench postprocessing benchmark dataset v1.0, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2022-465, in review, 2023. 
The Heat Health Warning System in Germany – As part of Heat Actions Plans
Authors: Matzarakis Andreas , Muthers Stefan
Published: July 2023

Heat Health Warning System (HHWS) provide information for general public and public health. In Germany, weather Forecast is used to predict heat episodes, which are associated with negative health impacts. Therefore, a heat balance model of the human body and an extracted equivalent temperature (Perceived Temperature) is applied. Thresholds for strong and extreme heat stress based on thermal perception classification are used and build the first approach of the HHWS. Furthermore, the threshold of strong heat stress includes a short term adaptation component and considers the previous thermal stress conditions of the last 30 days. The second step includes nocturnal conditions, based on forecasted minimum air temperature or a simulated maximum indoor temperature for typical houses. The indoor temperature is calculated also based on a urban heat model for cities with a population over 100.000 inhabitants. Both criteria are important for the decision about warnings for the present and next days. Warnings are generated by daily weather forecast automatically and are additionally confirmed or adjusted by a biometeorological forecaster. The warning is valid on county level considering several elevation classes. The heat warning is available as a map on the internet and registered users can receive information by a daily newsletter. A specific smartphone app is also available for general use. The main target groups are the public, nursing homes and ministries of the federal states and other authorities. The HHWS with his regional differentiation of heat stress warnings is also part of the heat health action plans in Germany. HHWS is main part of the Heat action Plans in Germany.
Results of the tram-based measurements from the Hannover urban climate project (2017 to 2020)
Authors: Bauditz Stefanie , Krugmann Gabriele , Tinz Birger , Möller Thomas
Published: July 2023

The current climate change is a great challenge, especially for cities. The already elevated temperature levels rise further, hence, the urban heat island effect is intensified. To adapt adequately, it is essential to understand the climatic conditions of a city and how they might vary within the city. In the context of preventive disaster control, the state of Lower Saxony and the German Meteorological Service (DWD) work closely together. In a joint project, which took place between July 2017 and December 2020, the climate of the city of Hannover was investigated. To obtain a complete picture of the climate in the city, various measurement methods were used.  Here, we want to present the results of the tram measurements. Three regular trams from the Hannover public transport (Üstra) were equipped with measuring sensors. During their regular trips through the city, these trams collected meteorological data, specifically the air temperature on their route. These measurements enabled a comprehensive spatial resolution of meteorological data. For the evaluation, special route sections were selected that were of particular interest from a structural standpoint. These ranged from purely commercial areas to residential areas and even sparsely built green spaces. The differences (spatial temperature anomalies) between the tram data and a reference station located in the surrounding area, were evaluated. It was found that the structural characteristics along the route alone do not always have to be the cause of high or low overheating. The conditions in the immediate neighborhood also play a significant role. For example, a route section located in a green strip experiences strong overheating when the wind blows from the east, where the mostly strong overheated Nordstadt is located. On the other hand, heavily built and sealed areas can benefit from a sparsely built and greener environment when winds come from the appropriate direction.
In summary, the measurement of meteorological variables using trams is a powerful tool for analyzing the microclimate of a city. The high spatial resolution offers the possibility to investigate the climatic conditions of all city areas. This is a great advantage, as it is not always possible to install temporary measurement stations everywhere.
The Basque Impact Weather Catalogue
Authors: Gaztelumendi Santiago , Egaña Joseba , Ruiz Miriam , Iturrioz Eguzkiñe
Published: July 2023

Improving the resilience of our societies against impact weather is a priority today and will increase in importance in the future as a consequence of potential local increase of severe weather and exposure. As a first step in this complex process of impact weather characterization, accurate information from past events must be collected, prepared and maintained with different purposes. In this paper, we present the Basque Country Severe Event Catalogue, a multipurpose tool designed, developed and maintained by Tecnalia and Basque Meteorology Agency (Euskalmet) in order to register detailed information about severe/adverse weather events that affect our territory.
This catalogue is a space where we collect information for characterization and evaluation of extreme weather events. The focus is twofold: the environmental conditions and their associated impact.  In the first case different information related with synoptical and local hydro-meteo-ocean conditions are registered, including date, duration, spatial extension, event typology, hazard type, measurement statistics data and a brief summary. Dealing with impact, various metrics are defined in order to characterize main aspects, including severe weather warning level, economic damages, human fatalities or normal life disruptions.
Different data sources and repositories are used in the Catalogue elaboration, not only from Tecnalia and Euskalmet but also, especially in the side of impact, from emergencies interventions, newspapers, local media webs, Twitter and Spanish Insurance Consortium data.
Unless the amount of available material differs from case to case, a common information structure and minimum content is mandatory for all the registered events, in such a way that qualitative analysis based on extended reports and quantitative analysis based on data registered or estimated metrics are possible for 21st century.
In this work, we focus on the design and structuration of the catalogue, the methodologies used for environmental and impact characterization and the main steps followed for its implementation. We also present some general conclusions from the process and future work planned.
Evaluation of analog-based post-processing with a special focus on strong wind episodes
Authors: Odak Plenkovic Iris , Kozul Ena , Vujec Ivan
Published: July 2023

The error reduction of NWP wind speed forecast is a rather expected effect when an analog-based statistical post-processing method (ABM) is applied. The efficiency of ABM, naturally, directly depends on the exact setup. For instance, the wind direction NWP is proven to be the most important predictor variable in the analog search process, in addition to the wind speed itself. The properly weighted additional predictor variables improve results even further, especially in complex terrain. Additionally, since the post-processing methods can be prone to underestimate the intensity of extreme events, the correction for high wind speed is implemented as a valuable tool, affecting the ABM when the raw NWP forecast exceeds a certain value.
After several upgrades were recently made in the operational DHMZ suite, these upgraded ABM forecasts are thoroughly evaluated, taking into consideration the overall performance. Since wind speed often reaches gale values during the bora and jugo wind episodes in the coastal region of Croatia, the effect on rare event forecasts is also considered, especially in complex terrain prone to high wind speed (e.g., bora wind).
Results show that the error, in general, is larger in complex terrain prone to high-wind speed than in less complex continental areas, and the reduction of error by ABM is thus more pronounced. In addition to improvement for the climatologically more common events, it can also be achieved for rare events in some cases as well. This is especially the case after applying the statistical correction which enlarges the frequency of such forecasts. The large errors occurred mainly due to short-term weakening of the wind speed within the strong wind episode, or because of the time delay of the beginning or the ending of the forecasted strong wind episode.
Multiscale numerical simulations of climate change impact on urban microclimate and human health
Authors: Antoniou Nestoras , Montazeri Hamid , Blocken Bert , Neophytou Marina
Published: July 2023

As a result of climate change, projections show that the increasing urban population will be exposed to higher air temperatures (Hayes et al., 2014; Sheffield and Wood, 2008). In addition, due to climatic changes, the frequency and duration of heatwaves are expected to increase while the Urban Heat Island effect (UHI) is expected to become more severe (Emmanuel and Krüger, 2012; Kovats and Hajat, 2008; Mirzaei and Haghighat, 2010), causing increasing heat-related mortality and morbidity (Garssen et al., 2005; Xu et al., 2012). Meditteranean-type climate regions have been characterized as particularly vulnerable to climate change due to their high exposure to extreme weather phenomena (Diffenbaugh and Giorgi, 2012; Paz et al., 2016). The intensity of heat waves in these regions is expected to increase further, leading to other life-threatening consequences for urban populations in the Mediterranean region  (Legasa et al., 2020; Zittis et al., 2021). Under this context, the detailed investigation of the impact of climate change on the urban microclimate and human health is considered highly important. This study investigates the impact of climate change on urban microclimate and pedestrian thermal comfort through a series of numerical simulations. For this purpose, 3D Computational Fluid Dynamics (CFD) simulations are performed based on the Unsteady Raynolds-Average Navier-Stokes (URANS) equations for urban microclimate in a real compact heterogeneous urban area. The CFD validation is based on high-resolution field and laboratory measurements of the case study area in Nicosia, Cyprus (Antoniou et al., 2019, 2017). Simulations are performed for meteorological conditions based on field measurements performed in 2010, and for predicted meteorological conditions for 2050 derived from downscaled Regional Climate Models (RCMs). The RCM data are derived from the European Coordinate Regional Downscaling Experiment (EURO-CORDEX) database. CFD results are combined with radiation modeling results of the same urban area to calculate pedestrian thermal comfort using the Universal Thermal Comfort Index (UTCI). The results show that by 2050, a 2.3 °C  increase in the maximum air temperature is expected to occur, which can lead to a more than 240% increase in heat-related mortality. In addition, an increase of UTCI levels is also expected, which is more pronounced in the late afternoon hours, reaching up to 4.3 °C increase at 20:00. A significant change in the thermal stress categories is also identified between the 2010 and 2050 scenarios, where “very strong heat stress” conditions (UTCI: 38-46 °C) are expected to prevail for twice as long, increasing from 3.3 to 6.6 hours, and  “extreme heat stress” conditions (UTCI > 46 °C) appear at some locations of the area in 2050.
 
 
Using the Precipitation Attribution Distance for localized verification and in a global domain
Authors: Skok Gregor
Published: July 2023

Precipitation is one of the most important meteorological parameters and is notoriously difficult to measure, predict, and also to verify. Distance measures are one of the five classes of spatial verification metrics that try to address the problems of traditionally used non-spatial methods (which only compare values at collocated grid points). Distance measures provide the results in terms of distance or displacement between the precipitation in the forecast and observation fields. Recently we developed a new distance measure, called the Precipitation Attribution Distance (PAD), that is based on a random nearest-neighbor attribution concept - it works by sequentially attributing randomly selected precipitation in one field to the closest precipitation in the other. Here we tried to adapt the PAD to provide localized verification information and take into account the spherical geometry of the Earth. Namely, most distance measures only provide a single estimate of the distance/displacement of precipitation in the forecasts, representing the whole domain. In the real world, in a large domain encompassing multiple geographical regions with different climatological characteristics, the typical displacement errors will likely differ in each individual region, so identifying localized estimates of errors would be more meaningful. Many spatial verification methods also have a hard time dealing with global domains. It is either hard to use them in such a way to properly account for the spherical geometry of a global domain, or the computation time in spherical geometry increases so much that it makes them difficult to be used. Luckily PAD can be adapted to provide localized verification information and can also be modified for use in a global domain without a significant increase in computation time. We analyzed the behavior of the adapted metric on various idealized and real-world examples, which show that it provides meaningful localized verification results and properly accounts for the spherical geometry of the Earth in a global domain.
Assessment of variability and trends of heavy precipitation in Trentino – South Tyrol (north-eastern Italian Alps) based on rain-gauge records (1956-2020)
Authors: Maines Elena , Crespi Alice , Steger Stefan , Zebisch Marc
Published: July 2023

In recent decades, the Alpine regions have been affected by several heavy precipitation events occasionally associated with storms causing landslides, debris flows, forest damage or flooding with cascading impacts to socio-economic systems. There is scientific evidence that a warming climate is likely to induce changes in the intensity and occurrence of precipitation extremes, even though extracting a long-term changing signal on regional and local scale is still challenging and requires an adequate observation coverage.
Some studies on extreme precipitation observed in the Alpine region exist, but only a few focus more in detail on the Trentino-Alto Adige area (north-eastern Italian Alps). In this context, the intensity and frequency of heavy precipitation, their spatial variability and trends over 1956-2020 are analysed for the region based on an archive of quality-checked daily historical records from more than 60 rain gauges.
The annual and seasonal analyses of maxima and exceedances of the 97th percentile show distinctive spatial patterns in both magnitude and seasonality. Maxima primarily occur during summer in the northern and more alpine part of the region, and during autumn in the south where the influence of the Mediterranean climate is more pronounced. Almost two thirds of the analysed stations reveal an increasing tendency in either the intensity or the frequency of heavy precipitation, especially in the north, even though trends are statistically significant only for a limited number of stations (e.g. less than 10% for annual maxima). The 1956-2020 intense precipitation observations are also scaled with global and regional temperatures and results are compared with previous studies in surrounding countries in order to assess global and regional warming effects on extreme changes. Finally, the extreme value distributions based on the 65-year records and two subsequent subperiods (1961-1990 and 1991-2020) provide a first evaluation of changes in statistical properties and precipitation amounts associated to different return periods. This is also used to characterize the local precipitation intensities during the exceptional event which hit north-eastern Alps in 2018, named storm Vaia, with intense precipitation together with extreme wind speed conditions.
This contribution shows and discusses the main results and provides an outlook towards the assessment of climate drivers of precipitation events in the region, the occurrence of compound extremes and links to subsequent impacts.
The research leading to these results has received funding from Interreg Alpine Space Program 2021-27 under the project number ASP0100101, “How to adapt to changing weather eXtremes and associated compound and cascading RISKs in the context of Climate Change” (X-RISK-CC).
 
Climate variables interpolation by using INLA and the SPDE approach
Authors: Fioravanti Guido , Martino Sara , Cameletti Michela , Toreti Andrea
Published: July 2023

Gridded observational datasets of the main climate variables are essential in climate science. However, common interpolation approaches (e.g., classical kriging-based methods), often lack of a proper propagation and representation of uncertainty. In this study, a Bayesian spatio-temporal regression model based on the Integrated Nested Laplace Approximation (INLA) and the Stochastic Partial Differential Equation (SPDE) is introduced. Although the effective use of INLA and SPDE is documented in several envitonmental studies, their use among climate practitioners is still quite limited. Here, based on high-resolution monthly 2-meter maximum (Tmax) and minimum (Tmin) air temperature, we employ INLA and SPDE to derive gridded monthly temperature climatologies for Italy both for the most recent standard 30-year period (1991–2020) and three previous standard periods (1961-1990, 1971-2000, 1981-2010). Our regression model includes three spatial predictors (elevation, latitude and distance to sea) and a linear time effect accounting for the  temporal trend in the observed monthly temperatures. A Matern field is used to capture the residual spatio-temporal correlation. Because of the large space-time domain of our study, the regression analysis is run separately for each month (January-December) and for each variable (Tmax/Tmin). Despite its simplicity, this approach provides a flexible model to produce accurate continuous gridded surfaces equipped with model-based uncertainties. Through simulation, we generate  a distribution of plausible gridded surfaces of Tmax and Tmin monthly means, which we summarize through measures of central tendency (posterior mean)  and variability (standard deviation). We use the standard deviation maps to investigate how uncertainty affects our estimates of the 1991-2020 monthly climatologies and where, and the 95% credible intervals maps to assess the regions where the  1991-2020 period is significantly warmer than the previous 30-year standard periods.
 
 
Assessing the impact of climate change on grassland ecosystem services using DayCent
Authors: dos Reis Martins Marcio , Ammann Christof , Calanca Pierluigi
Published: July 2023

Grasslands deliver a range of ecosystem services to society that are potentially threatened by climate change. Assessing climate change impacts on grassland ecosystem services is essential for developing adaptation strategies. This is particularly important for a country like Switzerland, in which grasslands represent about two thirds of its agricultural land. Among grassland ecosystem services, fodder production (provisioning) and soil carbon sequestration (regulating) are most vulnerable to drought and other extreme events. Process-based ecosystem models, such as DayCent, are suitable tools for assessing concomitant impacts of climate change on different ecosystem services. DayCent simulates fluxes of C and N among the atmosphere, vegetation, and soil and allows the prediction of the effect of increasing temperature and CO2 levels and decreasing rainfall on herbage growth and soil carbon stocks. We have been using DayCent to simulate the dynamics of herbage growth and soil organic carbon pools with varying degree of stability in managed permanent grasslands in Switzerland. For the present study, we selected an experimental grassland site located at Oensingen, Canton of Solothurn. We calibrated DayCent using inverse modeling (PEST tool) and verified the model performance based on several years of field data. We then applied the model to examine how future shifts in climatic conditions are likely to affect yields and carbon stocks, and what are the associated uncertainties. For this exercise, we developed local climate change scenarios using a stochastic weather generator (LARSWG). After reviewing the results, we discuss how process-based modeling can contribute for development of climate-smart agriculture tools, which can support better definition of agricultural policies and payment systems for grassland ecosystem services.
A Study of the Impact of Climate Change on Hydrological Drought Conditions across the World using CORDEX-CORE Simulations
Authors: García-Valdecasas Ojeda Matilde , Coppola Erika , Di Sante Fabio , Vargas-Heinz Luiza , GÁmiz-Fortis Sonia R.
Published: July 2023

Rivers have been a vital part of the natural system, favoring the development of different countries and their economies. However, part of the river system may undergo significant changes as a result of climate change, with significant implications for water management, agriculture, and aquatic ecosystems.
This study investigates future hydrological drought risks worldwide through an ensemble of regional hydroclimatic projections for different CORDEX domains (i.e., CORDEX-CORE simulations). For this, a river routing model derived from the CETEMPS Hydrological model (CHyM) forced with the CORDEX-CORE total runoff was used to simulate the daily river flow at 0.06º spatial resolution from 1976 to 2099 and under the Representative Concentration Pathway (RCP) 8.5.
For the analysis of hydrological droughts, a block minima approach based on the annual minimum 7-day river flow (7AMF) was selected for the nonfrost season (i.e., the period when the upstream area of a given river point presents a mean temperature above 0 ºC). These values were fitted to a Generalized Extreme Value (GEV) distribution and the minimum flow for different return periods were computed for a reference period and for conditions of 1.5º, 2º, and 3ºC above temperatures in the pre-industrial period. Thus, the purposes of this preliminary study were (1) to evaluate the performance of the CORDEX-CORE hydroclimatic simulations to characterize hydrological droughts around the world by comparing the simulated extreme river flow with observations from the Global Runoff Data Base (GRDB) and (2) to project extreme discharge values in order to analyze the impact of climate change on river drought characteristics.
The findings of this study could provide valuable information for adaptation and mitigation strategies to climate change from a hydrological perspective.
Keywords: Hydrological drought, CORDEX-CORE, CHyM, minimum river flow.
Acknowledgments: This research was financed by the project P20_00035 funded by FEDER/Junta de Andalucía-Consejería de Transformación Económica, Industria, Conocimiento y Universidades, the project “Thematic Center on Mountain Ecosystem & Remote sensing, Deep learning-AIe-Services University of Granada-SierraNevada”(LifeWatch-2019-10-UGR-01), which has been co-funded by the Ministry of Science and Innovation through the FEDER funds from the Spanish Pluriregional Operational Program2014-2020 (POPE), LifeWatch-ERIC action line, and by the project PID2021-126401OB-I00 funded by MCIN/AEI/ 10.13039/501100011033/FEDER  Una manera de hacer Europa.
Analysis of July 2022 persistent and extreme high temperatures episode in the Basque Country
Authors: Egaña Joseba , Palacio Virginia , Arrillaga Jon Ander , Gaztelumendi Santiago
Published: July 2023

In this work we analyse one of the most intense heat episodes ever happened in the Basque Country. This historic event produces numerous absolute record. with the highest maximum and minimum temperatures, as well as the highest maximum and minimum values for a month of July. In addition, numerous fires are produced during this period. A red alarm for extreme high temperatures has been set for the first time (note that colour-coded warnings have been implemented in Euskalmet case in 2009).
The worst is between the 16th and 18th, although the period of high temperatures lasts from the 11th to the 18th. From the 16th to the 18th many stations exceed 40ºC. On the 16th, the highest temperatures are recorded in the south part, specifically at the Zambrana station with 41.7 ºC. On the 17th the intense heat is repeated, with temperatures rising in several areas, especially in the Cantabrian area of Alava. During this day, values above 42 ºC are recorded at several stations and above 40 ºC at a large number of them. Gardea and Saratxo reach 42.9 ºC and Ordunte 42.4 ºC respectively. The maximum temperatures are above 40 ºC in many stations in Alava, including Abetxuko in Vitoria (40.1 ºC). The 18th is another day of suffocating heat. With a prevailing southerly wind, temperatures rise on the Cantabrian slope, especially in Gipuzkoa, and 11 stations reach or exceed 42 ºC. In Gardea, 43.6 ºC is recorded, the highest temperature value recorded during the whole episode. In Arrasate and Saratxo the temperatures are also around 43 ºC, with 42.9 ºC and 42.7 ºC respectively.
Due to the heat, there are numerous incidents. One person dies of heatstroke. According to the Basque Government, health services treat a total of 184 people for conditions related to the high temperatures, 83 of whom are taken to hospital.
In this work, the synoptic and mesoscale factors of this episode are analysed. The information from Basque Country Automatic Weather Station Mesonetwork is reviewed, analysing the spatial-temporal evolution of the temperatures at different locations. Finally we include some conclusions taking into account other previous persistent and extreme temperatures episodes and some impact information.
Data rescue of national and international meteorological observations at Deutscher Wetterdienst
Authors: Möller Thomas , Leiding Tina , Andersson Axel , Imbery Florian , Junghänel Thomas
Published: July 2023

Historic observational data records are an important contribution for climate reconstructions and analysis of past weather events. Particularly in remote and data sparse regions, such as the open ocean, newly rescued data can significantly improve the knowledge about weather and climatic conditions in earlier decades and centuries.
Deutscher Wetterdienst (DWD) holds several collections of original historical weather records from land stations and ships. They comprise not only observations from Germany, but also of the global oceans and land stations in many parts of the world.
All German state-owned meteorological observations beginning with the Prussian Meteorological Institute in 1848 are collected in the main archive of DWD in Offenbach.
DWD’s branch office in Hamburg holds the marine archive starting with the collections of the German Naval Observatory, 'Deutsche Seewarte', which existed from 1868 to 1945. It includes marine data records from ships, as well as land stations in many parts of the world (e.g. from former German colonies) and signal stations situated at the coasts of the North and Baltic Sea.
With the further expansion of the IT infrastructure, high temporal resolution data have increasingly become the focus of climate research in recent years. Thus, the processing of such historical data is also increasingly necessary. The digitization of recording strips from pluviographs, for example, is currently one focal point of the data rescue activities at DWD.
The documentation, digitisation and quality check of the enormous quantity of handwritten journals of all four data archives is still ongoing. The digitised data will be freely accessible to all interested scientists and are also continuously submitted to international data archives, such as ICOADS and ISPD. Through these data sets, the data are also an important input for regional and global reanalyses.
The presentation will give an overview of the historical archives of Deutscher Wetterdienst and will show the recent progress of the digitization efforts and ongoing analysis of the data.
DWD-Crowdsourcing: Are User Reports beneficial for Object-based Nowcasting?
Authors: Spitzer Arne , Kempf Harald , Jerg Matthias , Werner Manuel , Blahak Ulrich
Published: July 2023

Since July 2020 the DWD WarnWetter-App comprises the Crowdsourcing module “User Reports”. This module provides users the functionality to report observations about current weather conditions and severe weather to DWD and other users.
The user reports represent the current meteorological conditions at a certain place at a certain point of time. The Crowdsourcing module provides 10 different meteorological categories (lightning, wind, hail, rain, wet icy conditions, snowfall, snow cover, cloudiness, fog, tornado), each of which contains specific characteristic levels and optionally additional attributes. In addition, the user has the option of setting the location and time of the event manually.
The benefit of the data is that meteorological information at ground level is collected at places where no weather station is located in the immediate vicinity. The dataset is able to complement the existing synoptic station network. Forecasters from DWD already benefit from user-based observations that are available in near real-time.
In recent years, a new nowcasting algorithm has been developed at DWD, called KONRAD3D. The algorithm aims to automatically detect, track, and nowcast convective cells in order to support DWD’s warning management.
KONRAD3D uses three-dimensional radar reflectivity data as main input. In addition, also lightning data and information about hydrometeor types based on polarimetric radar data is regarded. In particular, in the latest version KONRAD3D features the new hail flag - a warning parameter that assesses a cell’s threat of hail. The new parameter rests upon the hydrometeor data and should roughly estimate the expectable near-ground hail size. Other features of KONRAD3D are the gust flag – a warning parameter that estimates the maximum speed of wind gusts - and the heavy rain flag which assesses the potential of heavy rain.
This is where the crowdsourcing data comes into play. Observations from app users are able to confirm expected hail sizes on the ground and provide promptly information about wind gusts and rain intensity. Preliminary results show that KONRAD3D tends to overestimate hail and underestimate gusts and heavy rain. Our analyses will show, in which cases the warning parameter estimates were reasonable and at which point the user reports could complement the real-time operation of KONRAD3D.
The impact of land use scenarios on the water balance in the Thaya river basin
Authors: Ghisi Tomas , Fischer Milan , Bernsteinova Jana , Bohuslav Jakub , Zalud Zdenek , Zeman Evzen , Trnka Miroslav
Published: July 2023

The Thaya river basin is one of the key river basins in the southern part of the Czech Republic. Due to extensive river regulations and partial drainage of the basin area, it belongs to river basins sensitive to climate change impacts. This is supported by significant negative runoff trends over the past 40 years. The main aim of this contribution is to analyze impacts of the hypothetical land use changes on the hydrological processes of the upper Thaya basin. In this study, we used a hydrological Mike SHE model. The physically based and spatially distributed model Mike SHE was calibrated and validated using measured river discharge data in the three hydrological profiles for the period 1991–2020. Selected hypothetical adaptation land use scenarios including the vegetation cover changes were compared to the reference scenario (represents the current land use of the basin) to analyze the impacts of the simulated land use changes on the hydrological processes in the basin. Except the field management changes, the land use scenarios encompassed extreme vegetation changes, where the entire basin in the model was changed to (1) grassland, (2) mixed deciduous-coniferous forest, (3) deciduous forest, or (4) cropland. These extreme land use scenarios were analyzed for several CMIP6 downscaled climate models and different RCP emissions scenarios up to the end of the first half of the 21st century. The results showed that the evapotranspiration is the dominant water loss component for all simulated land use scenarios in the basin. The highest evapotranspiration was modeled for the mixed deciduous-coniferous forest, while the lowest was for the grassland and cropland scenarios. The Mike SHE model also simulated that the total runoff was lowest for both forest scenarios. Results of the study showed the sensitivity of the river basin on the climate change impacts, where a slight increase of the evapotranspiration value in the basin has a significant effect on the total runoff from the basin. This study was conducted within the evaluating and designing nature-based adaptation measures to climate change in the Thaya river basin.
PBL parameterization schemes analysis over the central Amazon basin during GoAmazon 2014/5 experiment
Authors: Fisch Gilberto , Mantovani José Antonio , Aravéquia José Antonio , Carneiro Rayonil Gomes
Published: July 2023

The boundary layer characteristics at Central Amazonia were studied using the WRF model, with a domain of 3 one-way interacting nested grids. The results from the inner domain (1 km) for different PBL schemes (nonlocal (ACM2, MRF, SH, YSU, QNSE-EDMF) and local (BouLac, GBM, MYNN2.5, MYNN3, MYJ, UW)) were analyzed against in situ observations. This validation dataset was made during the GoAmazon 2014/5 experiment. The PBL heights (PBLH) were compared with ceilometer (Vaisala Oy, Finland) measurements installed during the field work. Short-term forecasts (72-h) were conducted (with a 12 h spin-up) for 4 different and typical cases: rainy and dry seasons for a typical (2014) and an ENSO-influenced (2015) years. The statistical analysis was performed separately for daytime and nighttime due to the pronounced diurnal variation, which revealed that the PBLH is better predicted during daytime. The local schemes (MYNN2.5, MYNN3, MYJ) give reasonable estimates for the convective boundary layer and non-local scheme (SH) for stable conditions. The diagnosed PBLH spatial fields for nighttime (02 Local Time – UTC-4 h) and daytime (14 LT) were investigated. The PBLH spatial fields revealed that nonlocal PBL schemes are influenced by the hydrography, while local PBL schemes were not. In general, the local MYNN2.5 and MYNN3 and the nonlocal QNSE-EDMF schemes predicted a deeper PBLH. Nonlocal schemes (ACM2 and MRF) depict the hydrography in their PBLH distribution with higher PBLH over the land (> 1500 m) and lower over the water bodies (< 800 m) during the daytime. The same typical values for nighttime are 100-200 m over the continent and 50-100 m over the water. The values during ENSO (2015) were higher than for the typical year (2014).
Dry Intrusions and Their Role in Extreme Wildfires
Authors: Magaritz Ronen Leehi , Raveh-Rubin Shira
Published: July 2023

A multitude of factors influence the size and intensity of a wildfire and the extensive damage it will cause. Among these are the landscape features, soil moisture and type and amount of vegetation. Atmospheric conditions such as heat waves, ‘correct’ wind speed, wind direction and changes in the wind direction, as well as atmospheric instability are key factors in the spread of the wildfire.
Dry Intrusions are slantwise descending airstreams that descend over 400hPa in 48 hours. They form as part of mid-latitude cyclones bringing to the surface dry upper tropospheric air and may bring to the surface either a cold or warm temperature anomaly. Dry Intrusions are known to destabilize the lower troposphere, lead to stronger winds at the surface and have been found to strengthen the cold front in cases of extreme wildfires in Australia.
In this work we globally analyze the co-occurrence of large wildfires and Dry Intrusions, using a Global Fire Atlas (GFED, Andela et al., 2019) and a calculated Dry Intrusion trajectory database based on ERA5 reanalysis (Hersbach et al., 2020). We find that in fire prone areas of the world there is a strong connection between the most extreme wildfires and the occurrence of Dry Intrusions. We examine this relation in different regions in Europe, Asia, America and Australia, areas in which the frequency of Dry Intrusions vary, and show that the connection is season dependent. Identifying processes that influence the spread of wildfires can improve their current forecast and future predictions in a changing climate.
Thermo-hygrometric characteristics of Local Climate Zones (LCZs) in the primary urban areas of north-eastern Romania investigated through multivariate tools
Authors: Sfica Lucian , Ichim Pavel , Crețu Claudiu-Stefanel , Amihaesei Vlad-Alexandru , Bistricean Petrut-Ionel , Hritac Robert , Irasoc Adrian , Mihaila Dumitru
Published: July 2023

In this research, we outline the main thermo-hygrometric characteristics of local climate zones (LCZs) identified in four of the largest cities in north-eastern Romania (Iași, Bacău, Botoșani, and Suceava), which together have a population of over 1 million inhabitants. The urban structure of these cities could be considered typical for medium size cities in Eastern Europe, being characterized by their recent development, with residential and industrial areas developed intensively in the communist period, followed nowadays by the conversion of decaying industrial areas in commercial units and a new phase of largely unorganized residential expansion.
We used the LCZ Generator to assess local climate zones in these cities, resulting in the identification of eight LCZs, with the largest extension being specific to compact midrise and open midrise, covering approximately 40% of the cities' surface. The accuracy of the LCZ delimitation ranges from 0.80 to 0.90.
We described the thermo-hygrometric features within the identified LCZs using in-situ observations, mobile measurements, and LANDSAT LST products. We used 30 in-situ observation points for air temperature and humidity with hourly temporal resolution to describe the major features of LCZs. We also made two mobile measurements monthly between May 2022 and April 2023 for each city, during clear sky conditions, in the early morning and the first part of the night, in order to spatially cover the diversity of LCZs. The thermo-hygrometric profile of LCZs was completed with LANDSAT LST data analyzed for 1983-2021, enabling a multiannual trend analysis of the two main LCZs in the analyzed cities. 
We grouped the study results by advective and radiative conditions using a Self-Organizing Maps method for atmospheric circulation. We also explored the thermo-hygrometric features of the two main LCZs using EUROCORDEX data for 2025-2100. The main output of this analysis indicates that the magnitude of changes identified in either moderate or extreme climate scenarios overwhelms the differences observed nowadays between the current conditions imposed by each local climate zone.
The results of this study synthesize the progress made in assessing urban climate conditions in the cities of North-Eastern Romania, in the framework of UCLAR project, and are intended to serve as a basis for mitigation policies to be developed by local and regional stakeholders for the sustainable development of these cities in the actual context of climate change. 
Acknowledgement: This work was supported by a grant of the Ministry of Research, Innovation and Digitization, CNCS - UEFISCDI, project number PN-III-P1-1.1-TE-2021-0882, within PNCDI III. 